diff --git a/.gitignore b/.gitignore index ecf150a..af03672 100644 --- a/.gitignore +++ b/.gitignore @@ -13,6 +13,7 @@ env sftp-config.json *.pkl +!classifier.pkl *.sql *.bak data/phenotypes/snorkel/dicts* diff --git a/.gitmodules b/.gitmodules index 098feea..e99f9e6 100644 --- a/.gitmodules +++ b/.gitmodules @@ -3,4 +3,4 @@ url = https://github.com/HazyResearch/snorkel.git [submodule "snorkel-tables"] path = snorkel-tables - url = git@github.com:HazyResearch/snorkel.git + url = git@github.com:kuleshov/snorkel.git diff --git a/README.md b/README.md index 0e9e302..2c8c7c6 100644 --- a/README.md +++ b/README.md @@ -3,17 +3,29 @@ GWASdb GWASdb is a machine reading system for discovering associations between genetic mutations and disease from academic papers. +## Results + +The machine-curated relations are found in `notebooks/results/associations.tsv`. +The five columns are: `pmid`, `rsid`, high-level phenotype, low-level phenotype, p-value. If the latter is `-1`, it means that we were not able to extract the p-value. + +In addition, the following files are important: + +* `notebooks/results/nb-output`: folder containing the output of each system module +* `notebooks/util/phenotype.mapping.annotated.tsv`: manually annotated mapping between GWAS Central and GWASdb phenotypes +* `notebooks/util/phenotype.mapping.gwascat.annotated.tsv`: manually annotated mapping between GWAS Catalog and GWASdb phenotypes +* `notebooks/util/rels.discovered.annotated.txt`: random subset of 100 previously unreported relations with explanations for why they are correct or not. + ## Requirements GWASdb is implemented in Python and requires: -* `lxml`, ElementTree +* `lxml`, `ElementTree` * `numpy` * `sklearn` * `sqlite` * `snorkel` -Check out the Snorkel web page for a list of its requirements. +Check out the [Snorkel repo](https://github.com/kuleshov/snorkel) for a list of its requirements. ## Installation @@ -46,7 +58,7 @@ In addition, we use hand-curated databases such as GWAS Catalog and GWAS Central The first step is to download this data onto your machine. The `data` subfolder contains code for doing this. ``` -cd data +cd data/db # we will store part of the dataset in a sqlite databset make init # this will initialize an empty database @@ -57,7 +69,7 @@ make init # this will initialize an empty database make phenotypes # next, we download the contents of the hand-curated GWAS catalog database -make gwas-catalog # the results will go in the sqlite db (in /tmp/gwas.sql by default) +make gwas-catalog # loads into sqlite db (/tmp/gwas.sql by default); this takes a while # now, let's download from pubmed all the open-access papers mentioned in the GWAS catalog make dl-papers # downloads ~600 papers + their supplementary material! @@ -70,7 +82,7 @@ This process can be automated by just typing `make`. ## Information extraction -We demo our system in a series of Jupyter notebooks in the `notebooks` subfolder. +We demo our system in a series of Jupyter notebooks in the `notebooks` subfolder. Currently, notebooks 1 and 5 are up, and we are cleaning up the others (see `dev` branch). 1. `phenotype-extraction.ipynb` identifies the phenotypes studied in each paper 2. `table-pval-extraction.ipynb` extracts mutation ids and their associated p-values @@ -82,4 +94,4 @@ The result is a second SQLite database containing facts (e.g. mutation/disease r ## Feedback -Please send feedback to [Volodymyr Kuleshov](http://web.stanford.edu/~kuleshov/). \ No newline at end of file +Please send feedback to [Volodymyr Kuleshov](http://web.stanford.edu/~kuleshov/). diff --git a/data/classifiers/classifier.pkl b/data/classifiers/classifier.pkl new file mode 100644 index 0000000..404fe03 --- /dev/null +++ b/data/classifiers/classifier.pkl @@ -0,0 +1,1170981 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.pipeline +Pipeline +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'steps' +p6 +(lp7 +(S'vect' +p8 +g0 +(csklearn.feature_extraction.text +CountVectorizer +p9 +g2 +Ntp10 +Rp11 +(dp12 +S'decode_error' 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' + table_data)\n", + " weak_rsid_filter = len(all_rsid) > 0\n", + " strong_rsid_filter = len(table_rsid) > 0\n", + "\n", + " extracted_filters = [year_filter, weak_rsid_filter, strong_rsid_filter]\n", + "\n", + " return [extracted_text, extracted_filters]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "../data/db/papers/17447842.xml\n", + "../data/db/papers/17658951.xml\n", + "../data/db/papers/17684544.xml\n", + "../data/db/papers/17903292.xml\n", + "../data/db/papers/17903293.xml\n", + "../data/db/papers/17903294.xml\n", + "../data/db/papers/17903295.xml\n", + "../data/db/papers/17903296.xml\n", + "../data/db/papers/17903297.xml\n", + "../data/db/papers/17903298.xml\n", + "../data/db/papers/17903300.xml\n", + "../data/db/papers/17903301.xml\n", + "../data/db/papers/17903302.xml\n", + "../data/db/papers/17903303.xml\n", + 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X_text.append(features[0])\n", + " X_filters.append(features[1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To predict whether a paper is GWAS or not, we use an SVM classifier that has been trained on the extracted text of papers using a bag-of-words model." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "with open('../data/classifiers/classifier.pkl') as f:\n", + " clf = pickle.load(f)\n", + "predicted = clf.predict(X_text)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Also, we filter out any paper published before 2006, because those papers are highly unlikely to be GWAS. (The first GWAS paper was published in 2005.)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "filters = np.asarray(X_filters)\n", + "predicted = np.logical_and(predicted, filters[:,0])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Optionally, we can also filter out papers that do not have any extractable information. The weak filter excludes any papers that don't have an RSID in the extracted text or tables. The strong filter excludes any papers that don't have an RSID in the tables. We use the weak filter as default." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "filter_type = 'weak' # You can change this! The choices are None, 'weak', or 'strong'\n", + "if filter_type == 'weak':\n", + " predicted = np.logical_and(predicted, filters[:,1])\n", + "elif filter_type == 'strong':\n", + " predicted = np.logical_and(predicted, filters[:,2])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Write out the results." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number GWAS predicted: 297 out of 320\n", + "../data/db/papers/17658951.xml - Genome-Wide Association Scan Shows Genetic Variants in the FTO Gene Are Associated with Obesity-Related Traits\n", + "../data/db/papers/17684544.xml - Systematic Association Mapping Identifies NELL1 as a Novel IBD Disease Gene\n", + "../data/db/papers/17903292.xml - A genome-wide association for kidney function and endocrine-related traits in the NHLBI's Framingham Heart Study\n", + "../data/db/papers/17903293.xml - Genome-wide association with select biomarker traits in the Framingham Heart Study\n", + "../data/db/papers/17903294.xml - Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study\n", + "../data/db/papers/17903295.xml - Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study\n", + "../data/db/papers/17903296.xml - Genome-wide association with bone mass and geometry in the Framingham Heart Study\n", + "../data/db/papers/17903297.xml - Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham study\n", + "../data/db/papers/17903298.xml - Genome-wide association with diabetes-related traits in the Framingham Heart Study\n", + "../data/db/papers/17903300.xml - Genome-wide association to body mass index and waist circumference: the Framingham Heart Study 100K project\n", + "../data/db/papers/17903301.xml - Genome-wide association of echocardiographic dimensions, brachial artery endothelial function and treadmill exercise responses in the Framingham Heart Study\n", + "../data/db/papers/17903302.xml - Framingham Heart Study 100K Project: genome-wide associations for blood pressure and arterial stiffness\n", + "../data/db/papers/17903303.xml - Genome-wide association study for subclinical atherosclerosis in major arterial territories in the NHLBI's Framingham Heart Study\n", + "../data/db/papers/17903304.xml - Framingham Heart Study 100K project: genome-wide associations for cardiovascular disease outcomes\n", + "../data/db/papers/17903305.xml - A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study\n", + "../data/db/papers/17903306.xml - Genome-wide association study of electrocardiographic and heart rate variability traits: the Framingham Heart Study\n", + "../data/db/papers/17903307.xml - Framingham Heart Study genome-wide association: results for pulmonary function measures\n", + "../data/db/papers/17997608.xml - The GLUT9 Gene Is Associated with Serum Uric Acid Levels in Sardinia and Chianti Cohorts\n", + "../data/db/papers/18159244.xml - Genome Wide Association (GWA) Study for Early Onset Extreme Obesity Supports the Role of Fat Mass and Obesity Associated Gene (FTO) Variants\n", + "../data/db/papers/18262040.xml - LDL-cholesterol concentrations: a genome-wide association study\n", + "../data/db/papers/18282107.xml - Genome-Wide Association Identifies a Common Variant in the Reelin Gene That Increases the Risk of Schizophrenia Only in Women\n", + "../data/db/papers/18369459.xml - A Genome-Wide Association Study of Psoriasis and Psoriatic Arthritis Identifies New Disease Loci\n", + "../data/db/papers/18455228.xml - Bone mineral density, osteoporosis, and osteoporotic fractures: a genome-wide association study\n", + "../data/db/papers/18464913.xml - A Genome-Wide Association Study Identifies Protein Quantitative Trait Loci (pQTLs)\n", + "../data/db/papers/18483556.xml - A Genome-Wide Association Study Identifies Novel Alleles Associated with Hair Color and Skin Pigmentation\n", + "../data/db/papers/18604267.xml - Novel Association of ABO Histo-Blood Group Antigen with Soluble ICAM-1: Results of a Genome-Wide Association Study of 6,578 Women\n", + "../data/db/papers/18776929.xml - Identification of PLCL1 Gene for Hip Bone Size Variation in Females in a Genome-Wide Association Study\n", + "../data/db/papers/18823527.xml - A genome-wide association study for late-onset Alzheimer's disease using DNA pooling\n", + "../data/db/papers/18840781.xml - Follow-Up Analysis of Genome-Wide Association Data Identifies Novel Loci for Type 1 Diabetes\n", + "../data/db/papers/18846228.xml - Genome-Wide Scan on Total Serum IgE Levels Identifies FCER1A as Novel Susceptibility Locus\n", + "../data/db/papers/18941528.xml - Identification of a Novel Risk Locus for Multiple Sclerosis at 13q31.3 by a Pooled Genome-Wide Scan of 500,000 Single Nucleotide Polymorphisms\n", + "../data/db/papers/19056611.xml - Adiposity-Related Heterogeneity in Patterns of Type 2 Diabetes Susceptibility Observed in Genome-Wide Association Data\n", + "../data/db/papers/19081515.xml - Genetic risk factors for variant Creutzfeldt–Jakob disease: a genome-wide association study\n", + "../data/db/papers/19096518.xml - Novel Association of HK1 with Glycated Hemoglobin in a Non-Diabetic Population: A Genome-Wide Evaluation of 14,618 Participants in the Women's Genome Health Study\n", + "../data/db/papers/19116933.xml - Identification of a novel susceptibility locus for juvenile idiopathic arthritis by genome-wide association analysis\n", + "../data/db/papers/19122664.xml - Ulcerative colitis loci on chromosomes 1p36 and 12q15 identified by genome-wide association study\n", + "../data/db/papers/19132087.xml - A Genome-Wide Association Study Identifies Novel and Functionally Related Susceptibility Loci for Kawasaki Disease\n", + "../data/db/papers/19169254.xml - Genomewide Scan Reveals Association of Psoriasis with IL-23 and NF-κB Pathways\n", + "../data/db/papers/19197348.xml - Genome-Wide Association Studies in an Isolated Founder Population from the Pacific Island of Kosrae\n", + "../data/db/papers/19219042.xml - Genome-wide association study identifies a novel breast cancer susceptibility locus at 6q25.1\n", + "../data/db/papers/19300482.xml - A Genome-Wide Association Study in Chronic Obstructive Pulmonary Disease (COPD): Identification of Two Major Susceptibility Loci\n", + "../data/db/papers/19300499.xml - A Genome-Wide Association Study Confirms VKORC1, CYP2C9, and CYP4F2 as Principal Genetic Determinants of Warfarin Dose\n", + "../data/db/papers/19300500.xml - A Genome-Wide Association Study of Pulmonary Function Measures in the Framingham Heart Study\n", + "../data/db/papers/19304780.xml - Genome-wide scan identifies CDH13 as a novel susceptibility locus contributing to blood pressure determination in two European populations\n", + "../data/db/papers/19305408.xml - Common variants at ten loci influence myocardial repolarization: the QTGEN consortium\n", + "../data/db/papers/19343178.xml - Meta-Analysis of Genome-Wide Scans for Human Adult Stature Identifies Novel Loci and Associations with Measures of Skeletal Frame Size\n", + "../data/db/papers/19359265.xml - A genome-wide association study identifies a novel locus on chromosome 18q12.2 influencing white cell telomere length\n", + "../data/db/papers/19401414.xml - Confirmation of Multiple Risk Loci and Genetic Impacts by a Genome-Wide Association Study of Type 2 Diabetes in the Japanese Population\n", + "../data/db/papers/19412175.xml - Common variations in BARD1 influence susceptibility to high-risk neuroblastoma\n", + "../data/db/papers/19412176.xml - Narcolepsy is strongly associated with the TCR alpha locus\n", + "../data/db/papers/19421330.xml - Genome-Wide Association Study of Young-Onset Hypertension in the Han Chinese Population of Taiwan\n", + "../data/db/papers/19430480.xml - Genome-wide association study and meta-analysis finds over 40 loci affect risk of type 1 diabetes\n", + "../data/db/papers/19430483.xml - Eight blood pressure loci identified by genome-wide association study of 34,433 people of European ancestry\n", + "../data/db/papers/19448621.xml - Genome-wide association studies identify novel loci associated with age at menarche and age at natural menopause\n", + "../data/db/papers/19454037.xml - Genome-wide association study identifies single-nucleotide polymorphism in KCNB1 associated with left ventricular mass in humans: The HyperGEN Study\n", + "../data/db/papers/19503088.xml - REL, a member of the NF-κB family of transcription factors, is a newly defined risk locus for rheumatoid arthritis\n", + "../data/db/papers/19503597.xml - Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations\n", + "../data/db/papers/19557161.xml - Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution\n", + "../data/db/papers/19557197.xml - Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution\n", + "../data/db/papers/19570815.xml - A genome-wide association study of northwestern Europeans involves the C-type natriuretic peptide signaling pathway in the etiology of human height variation\n", + "../data/db/papers/19571809.xml - Common variants on chromosome 6p22.1 are associated with schizophrenia\n", + "../data/db/papers/19578366.xml - Variants in the CDKN2B and RTEL1 regions are associated with high grade glioma susceptibility\n", + "../data/db/papers/19587794.xml - Common Genetic Variation Near the Phospholamban Gene Is Associated with Cardiac Repolarisation: Meta-Analysis of Three Genome-Wide Association Studies\n", + "../data/db/papers/19597492.xml - Variants in ZFHX3 are associated with atrial fibrillation in individuals of European ancestry\n", + "../data/db/papers/19609347.xml - A Genome-Wide Association Study of Hypertension and Blood Pressure in African Americans\n", + "../data/db/papers/19668339.xml - Hippocampal Atrophy as a Quantitative Trait in a Genome-Wide Association Study Identifying Novel Susceptibility Genes for Alzheimer's Disease\n", + "../data/db/papers/19684604.xml - Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia\n", + "../data/db/papers/19714205.xml - Genome-Wide Association Study Implicates Chromosome 9q21.31 as a Susceptibility Locus for Asthma in Mexican Children\n", + "../data/db/papers/19714249.xml - Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males\n", + "../data/db/papers/19734902.xml - Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease, and shows evidence for additional susceptibility genes\n", + "../data/db/papers/19779542.xml - A Genome-Wide Association Analysis Identified a Novel Susceptible Locus for Pathological Myopia at 11q24.1\n", + "../data/db/papers/19798445.xml - Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations\n", + "../data/db/papers/19801982.xml - Twenty bone mineral density loci identified by large-scale meta-analysis of genome-wide association studies\n", + "../data/db/papers/19812673.xml - A GENOME-WIDE LINKAGE AND ASSOCIATION SCAN REVEALS NOVEL LOCI FOR AUTISM\n", + "../data/db/papers/19820699.xml - Common variants in TMPRSS6 are associated with iron status and erythrocyte volume\n", + "../data/db/papers/19862010.xml - Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium\n", + "../data/db/papers/19874204.xml - IL21R and PTH May Underlie Variation of Femoral Neck Bone Mineral Density as Revealed by a Genome-wide Association Study\n", + "../data/db/papers/19915575.xml - Genome-Wide Association Study reveals genetic risk underlying Parkinson’s disease\n", + "../data/db/papers/19966805.xml - The imprinted DLK1-MEG3 gene region on chromosome 14q32.2 alters susceptibility to type 1 diabetes\n", + "../data/db/papers/20011104.xml - A Genome-Wide Association Study Reveals Variants in ARL15 that Influence Adiponectin Levels\n", + "../data/db/papers/20038947.xml - Novel loci for major depression identified by genome-wide association study of STAR*D and meta-analysis of three studies\n", + "../data/db/papers/20041166.xml - Common Genetic Variation and the Control of HIV-1 in Humans\n", + "../data/db/papers/20062060.xml - Genome-wide association study of PR interval\n", + "../data/db/papers/20066028.xml - Modeling of Environmental Effects in Genome-Wide Association Studies Identifies SLC2A2 and HP as Novel Loci Influencing Serum Cholesterol Levels\n", + "../data/db/papers/20072603.xml - Genome-Wide Association Study Identifies ALDH7A1 as a Novel Susceptibility Gene for Osteoporosis\n", + "../data/db/papers/20081856.xml - Meta-analysis of genome-wide association data detects a risk locus for major mood disorders on chromosome 3p21.1\n", + "../data/db/papers/20081858.xml - New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk\n", + "../data/db/papers/20169177.xml - Genome-Wide Association Study in Asian Populations Identifies Variants in ETS1 and WDFY4 Associated with Systemic Lupus Erythematosus\n", + "../data/db/papers/20173747.xml - Common Variants in KCNN3 are Associated with Lone Atrial Fibrillation\n", + "../data/db/papers/20173748.xml - Variants in FAM13A are associated with chronic obstructive pulmonary disease\n", + "../data/db/papers/20174558.xml - A Genome-Wide Association Study Identifies Susceptibility Variants for Type 2 Diabetes in Han Chinese\n", + "../data/db/papers/20190752.xml - Multiple common variants for celiac disease influencing immune gene expression\n", + "../data/db/papers/20195266.xml - Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs\n", + "../data/db/papers/20305777.xml - New Sequence Variants in HLA Class II/III Region Associated with Susceptibility to Knee Osteoarthritis Identified by Genome-Wide Association Study\n", + "../data/db/papers/20339536.xml - Genome-Wide Association of Lipid-Lowering Response to Statins in Combined Study Populations\n", + "../data/db/papers/20364137.xml - Genome-wide association study of intracranial aneurysm identifies three new risk loci\n", + "../data/db/papers/20372150.xml - Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight\n", + "../data/db/papers/20395239.xml - Genome-wide association identifies ATOH7 as a major gene determining human optic disc size\n", + "../data/db/papers/20418485.xml - Genome-wide association study of circulating vitamin D levels\n", + "../data/db/papers/20421936.xml - Two New Loci for Body-Weight Regulation Identified in a Joint Analysis of Genome-Wide Association Studies for Early-Onset Extreme Obesity in French and German Study Groups\n", + "../data/db/papers/20436471.xml - Genome wide association study identifies variants at CSF1, OPTN and TNFRSF11A as genetic risk factors for Paget’s disease of bone\n", + "../data/db/papers/20442857.xml - Genome-Wide Association Study of Lp-PLA2 Activity and Mass in the Framingham Heart Study\n", + "../data/db/papers/20463881.xml - Digital Quantification of Human Eye Color Highlights Genetic Association of Three New Loci\n", + "../data/db/papers/20485516.xml - Common Genetic Variants near the Brittle Cornea Syndrome Locus ZNF469 Influence the Blinding Disease Risk Factor Central Corneal Thickness\n", + "../data/db/papers/20522523.xml - Common genetic variation and susceptibility to partial epilepsies: a genome-wide association study\n", + "../data/db/papers/20526338.xml - Genome-wide meta-analyses identifies 7 loci associated with platelet aggregation in response to agonists\n", + "../data/db/papers/20548944.xml - An Integration of Genome-Wide Association Study and Gene Expression Profiling to Prioritize the Discovery of Novel Susceptibility Loci for Osteoporosis-Related Traits\n", + "../data/db/papers/20548946.xml - A Genome-Wide Association Study of Optic Disc Parameters\n", + "../data/db/papers/20585626.xml - Identification of a Functional Genetic Variant at 16q12.1 for Breast Cancer Risk: Results from the Asia Breast Cancer Consortium\n", + "../data/db/papers/20585627.xml - Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits\n", + "../data/db/papers/20622878.xml - Genome-wide association study identifies variants in the MHC class I, IL10, and IL23R/IL12RB2 regions associated with Behçet's disease\n", + "../data/db/papers/20634892.xml - A Genome-Wide Association Study of Neuroticism in a Population-Based Sample\n", + "../data/db/papers/20639881.xml - Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32\n", + "../data/db/papers/20661308.xml - Genome-Wide Meta-Analysis for Serum Calcium Identifies Significantly Associated SNPs near the Calcium-Sensing Receptor (CASR) Gene\n", + "../data/db/papers/20663923.xml - A genome-wide scan for common alleles affecting risk for autism\n", + "../data/db/papers/20675712.xml - The perception of quinine taste intensity is associated with common genetic variants in a bitter receptor cluster on chromosome 12\n", + "../data/db/papers/20686608.xml - Genome-Wide Association Study of Pancreatic Cancer in Japanese Population\n", + "../data/db/papers/20686651.xml - Association of Variants at UMOD with Chronic Kidney Disease and Kidney Stones—Role of Age and Comorbid Diseases\n", + "../data/db/papers/20694014.xml - Genome-wide association analyses identifies a susceptibility locus for tuberculosis on chromosome 18q11.2\n", + "../data/db/papers/20694148.xml - A Genome-Wide Association Study of the Metabolic Syndrome in Indian Asian Men\n", + "../data/db/papers/20700438.xml - The 5p15.33 Locus Is Associated with Risk of Lung Adenocarcinoma in Never-Smoking Females in Asia\n", + "../data/db/papers/20700443.xml - Genome-Wide Association Studies of Serum Magnesium, Potassium, and Sodium Concentrations Identify Six Loci Influencing Serum Magnesium Levels\n", + "../data/db/papers/20711177.xml - Common genetic variation in the HLA region is associated with late-onset sporadic Parkinson’s disease\n", + "../data/db/papers/20729852.xml - Genome-wide association studies of gastric adenocarcinoma and esophageal squamous cell carcinoma identify a shared susceptibility locus in PLCE1 at 10q23\n", + "../data/db/papers/20801717.xml - Chromosome 9p21 in sporadic amyotrophic lateral sclerosis in the UK and seven other countries: a genome-wide association study\n", + "../data/db/papers/20802479.xml - Genome-wide association study of migraine implicates a common susceptibility variant on 8q22.1\n", + "../data/db/papers/20838585.xml - Longitudinal Genome-Wide Association of Cardiovascular Disease Risk Factors in the Bogalusa Heart Study\n", + "../data/db/papers/20852633.xml - Common variants at 19p13 are associated with susceptibility to ovarian cancer\n", + "../data/db/papers/20858683.xml - Common Variants at 10 Genomic Loci Influence Hemoglobin A1C Levels via Glycemic and Nonglycemic Pathways\n", + "../data/db/papers/20861866.xml - Genome-wide association identifies SKIV2L and MYRIP as protective factors for age-related macular degeneration\n", + "../data/db/papers/20862305.xml - Identification of New Genetic Risk Variants for Type 2 Diabetes\n", + "../data/db/papers/20885792.xml - Dementia Revealed: Novel Chromosome 6 Locus for Late-Onset Alzheimer Disease Provides Genetic Evidence for Folate-Pathway Abnormalities\n", + "../data/db/papers/20921969.xml - Genome-wide association study of antipsychotic induced QTc interval prolongation\n", + "../data/db/papers/20927387.xml - A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record\n", + "../data/db/papers/20932310.xml - Genome-wide association reveals genetic effects on human Aβ42 and τ protein levels in cerebrospinal fluids: a case control study\n", + "../data/db/papers/20935630.xml - A twin study of human obesity\n", + "../data/db/papers/20953186.xml - Common variants at TRAF3IP2 are associated with susceptibility to psoriatic arthritis and psoriasis\n", + "../data/db/papers/20953189.xml - Genome-wide association analysis identifies three psoriasis susceptibility loci\n", + "../data/db/papers/20972438.xml - A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci\n", + "../data/db/papers/20972440.xml - Meta-analysis of three genome-wide association studies identifies susceptibility loci for colorectal cancer at 1q41, 3q26.2, 12q13.13 and 20q13.33\n", + "../data/db/papers/21037568.xml - A genome-wide association study of Hodgkin Lymphoma identifies new susceptibility loci at 2p16.1 (REL), 8q24.21, and 10p14 (GATA3)\n", + "../data/db/papers/21042317.xml - Genome-wide association study of major depressive disorder: new results, meta-analysis, and lessons learned\n", + "../data/db/papers/21044948.xml - Dissection of the genetics of Parkinson's disease identifies an additional association 5′ of SNCA and multiple associated haplotypes at 17q21\n", + "../data/db/papers/21051773.xml - PCSK6 is associated with handedness in individuals with dyslexia\n", + "../data/db/papers/21060860.xml - Common Genetic Variants and Modification of Penetrance of BRCA2-Associated Breast Cancer\n", + "../data/db/papers/21060863.xml - Coronary microvascular dysfunction.\n", + "../data/db/papers/21076409.xml - Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction\n", + "../data/db/papers/21079607.xml - A genome-wide association study of anorexia nervosa\n", + "../data/db/papers/21082022.xml - Genome-Wide Association Study of Blood Pressure Extremes Identifies Variant near UMOD Associated with Hypertension\n", + "../data/db/papers/21124946.xml - Genome-Wide Association Meta-Analysis of Cortical Bone Mineral Density Unravels Allelic Heterogeneity at the RANKL Locus and Potential Pleiotropic Effects on Bone\n", + "../data/db/papers/21124955.xml - Genome-Wide Association Study Identifies Two Novel Regions at 11p15.5-p13 and 1p31 with Major Impact on Acute-Phase Serum Amyloid A\n", + "../data/db/papers/21151130.xml - Genome-wide association study identifies a locus at 7p15.2 associated with endometriosis\n", + "../data/db/papers/21203500.xml - Genomics Meets Glycomics—The First GWAS Study of Human N-Glycome Identifies HNF1α as a Master Regulator of Plasma Protein Fucosylation\n", + "../data/db/papers/21223598.xml - Genome-wide joint SNP and CNV analysis of aortic root diameter in African Americans: the HyperGEN study\n", + "../data/db/papers/21242260.xml - Common variant in 6q26-q27 is associated with distal colon cancer in an Asian population\n", + "../data/db/papers/21244703.xml - Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data\n", + "../data/db/papers/21273288.xml - Genome-wide association analysis and fine mapping of NT-proBNP level provide novel insight into the role of the MTHFR-CLCN6-NPPA-NPPB gene cluster\n", + "../data/db/papers/21278746.xml - Common variants in ZNF365 are associated with both mammographic density and breast cancer risk\n", + "../data/db/papers/21297633.xml - Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47\n", + "../data/db/papers/21298027.xml - A Meta-Analysis of Genome-Wide Association Scans Identifies IL18RAP, PTPN2, TAGAP, and PUS10 As Shared Risk Loci for Crohn's Disease and Celiac Disease\n", + "../data/db/papers/21326860.xml - Identification of Novel Susceptibility Loci for Kawasaki Disease in a Han Chinese Population by a Genome-Wide Association Study\n", + "../data/db/papers/21339755.xml - A non- synonymous polymorphism in galactose mutarotase (GALM) is associated with serotonin transporter binding potential in the human thalamus: Results of a genome-wide association study\n", + "../data/db/papers/21347284.xml - Genome-Wide Association Studies of the PR Interval in African Americans\n", + "../data/db/papers/21364930.xml - Genome-Wide Association Study Identifies Single Nucleotide Polymorphism in DYRK1A Associated with Replication of HIV-1 in Monocyte-Derived Macrophages\n", + "../data/db/papers/21379329.xml - Genome-Wide Association of Familial Late-Onset Alzheimer's Disease Replicates BIN1 and CLU and Nominates CUGBP2 in Interaction with APOE\n", + "../data/db/papers/21383967.xml - Meta-Analysis of Genome-Wide Association Studies in Celiac Disease and Rheumatoid Arthritis Identifies Fourteen Non-HLA Shared Loci\n", + "../data/db/papers/21386085.xml - A Bivariate Genome-Wide Approach to Metabolic Syndrome\n", + "../data/db/papers/21390209.xml - Meta-Analysis for Genome-Wide Association Study Identifies Multiple Variants at the BIN1 Locus Associated with Late-Onset Alzheimer's Disease\n", + "../data/db/papers/21399635.xml - Genome-wide association study identifies 12 new susceptibility loci for primary biliary cirrhosis\n", + "../data/db/papers/21418511.xml - Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited\n", + "../data/db/papers/21423239.xml - A genome-wide association study of attempted suicide\n", + "../data/db/papers/21423719.xml - Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits\n", + "../data/db/papers/21424380.xml - Potential novel candidate polymorphisms identified in genome-wide association study for breast cancer susceptibility\n", + "../data/db/papers/21437268.xml - A Genome-Wide Association Study of Upper Aerodigestive Tract Cancers Conducted within the INHANCE Consortium\n", + "../data/db/papers/21448238.xml - Meta-analysis of genome-wide association for migraine in six population-based European cohorts\n", + "../data/db/papers/21460840.xml - Common variants in ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease\n", + "../data/db/papers/21460841.xml - Common variants in MS4A4/MS4A6E, CD2uAP, CD33, and EPHA1 are associated with late-onset Alzheimer’s disease\n", + "../data/db/papers/21483430.xml - Impact of DISC1 variation on neuroanatomical and neurocognitive phenotypes\n", + "../data/db/papers/21483845.xml - Genome-Wide Association Study Identifies Genetic Loci Associated with Iron Deficiency\n", + "../data/db/papers/21490707.xml - Genome-Wide Meta-Analysis Identifies Regions on 7p21 (AHR) and 15q24 (CYP1A2) As Determinants of Habitual Caffeine Consumption\n", + "../data/db/papers/21490949.xml - Diabetes in Asia.\n", + "../data/db/papers/21502949.xml - Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N=1198) using genome-wide search\n", + "../data/db/papers/21533022.xml - Impact of genetics on low bone mass in adults.\n", + "../data/db/papers/21533024.xml - Genome-Wide Association Analysis of Soluble ICAM-1 Concentration Reveals Novel Associations at the NFKBIK, PNPLA3, RELA, and SH2B3 Loci\n", + "../data/db/papers/21533074.xml - Organochlorines and risk of non-Hodgkin lymphoma.\n", + "../data/db/papers/21533175.xml - Eight Common Genetic Variants Associated with Serum DHEAS Levels Suggest a Key Role in Ageing Mechanisms\n", + "../data/db/papers/21552555.xml - A Genome-Wide Association Study on Obesity and Obesity-Related Traits\n", + "../data/db/papers/21573004.xml - Genome-Wide Association Study of Relative Telomere Length\n", + "../data/db/papers/21573128.xml - Common Variants in a Novel Gene, FONG on Chromosome 2q33.1 Confer Risk of Osteoporosis in Japanese\n", + "../data/db/papers/21602797.xml - Genome-wide association and linkage identify modifier loci of lung disease severity in cystic fibrosis at 11p13 and 20q13.2\n", + "../data/db/papers/21602798.xml - Genome-wide association study of prostate cancer in men of African ancestry identifies a susceptibility locus at 17q21\n", + "../data/db/papers/21627779.xml - The membrane-spanning 4-domains, subfamily A (MS4A) gene cluster contains a common variant associated with Alzheimer's disease\n", + "../data/db/papers/21658281.xml - GWAS for discovery and replication of genetic loci associated with sudden cardiac arrest in patients with coronary artery disease\n", + "../data/db/papers/21665990.xml - Common variants near FRK/COL10A1 and VEGFA are associated with advanced age-related macular degeneration\n", + "../data/db/papers/21685912.xml - Identification of common variants influencing risk of the tauopathy Progressive Supranuclear Palsy\n", + "../data/db/papers/21700879.xml - Novel Locus FER Is Associated With Serum HMW Adiponectin Levels\n", + "../data/db/papers/21708048.xml - Genome wide association study identifies KCNMA1 contributing to human obesity\n", + "../data/db/papers/21729881.xml - Genome-wide association study identifies common variants associated with circulating vitamin E levels\n", + "../data/db/papers/21738478.xml - Identification of Nine Novel Loci Associated with White Blood Cell Subtypes in a Japanese Population\n", + "../data/db/papers/21738479.xml - Genome-Wide Association Study of White Blood Cell Count in 16,388 African Americans: the Continental Origins and Genetic Epidemiology Network (COGENT)\n", + "../data/db/papers/21738487.xml - Web-Based Genome-Wide Association Study Identifies Two Novel Loci and a Substantial Genetic Component for Parkinson's Disease\n", + "../data/db/papers/21738491.xml - Identification of a Sudden Cardiac Death Susceptibility Locus at 2q24.2 through Genome-Wide Association in European Ancestry Individuals\n", + "../data/db/papers/21750679.xml - Genome-Wide Scan Identifies TNIP1, PSORS1C1, and RHOB as Novel Risk Loci for Systemic Sclerosis\n", + "../data/db/papers/21771975.xml - A Genome-Wide Association Study Reveals a Quantitative Trait Locus of Adiponectin on CDH13 That Predicts Cardiometabolic Outcomes\n", + "../data/db/papers/21779176.xml - Genome-Wide Association Study Identifies Novel Restless Legs Syndrome Susceptibility Loci on 2p14 and 16q12.1\n", + "../data/db/papers/21779181.xml - Identification of Novel Genetic Markers Associated with Clinical Phenotypes of Systemic Sclerosis through a Genome-Wide Association Strategy\n", + "../data/db/papers/21779381.xml - Genetic Determinants of Cardiovascular Events among Women with Migraine: A Genome-Wide Association Study\n", + "../data/db/papers/21799836.xml - A Genome-Wide Association Study Confirms Previously Reported Loci for Type 2 Diabetes in Han Chinese\n", + "../data/db/papers/21801394.xml - Genome-wide association study of Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in Europe\n", + "../data/db/papers/21804547.xml - Common variation at 10p12.31 near MLLT10 influences meningioma risk\n", + "../data/db/papers/21804549.xml - Meta-analysis of Genome-wide Association Studies of Asthma In Ethnically Diverse North American Populations\n", + "../data/db/papers/21810271.xml - Combined analysis of three genome-wide association studies on vWF and FVIII plasma levels\n", + "../data/db/papers/21812969.xml - Genome-Wide association study identifies candidate genes for Parkinson's disease in an Ashkenazi Jewish population\n", + "../data/db/papers/21814517.xml - Genome-Wide Association Study Identifies HLA-DP as a Susceptibility Gene for Pediatric Asthma in Asian Populations\n", + "../data/db/papers/21829377.xml - Genetic Loci Associated with Plasma Phospholipid n-3 Fatty Acids: A Meta-Analysis of Genome-Wide Association Studies from the CHARGE Consortium\n", + "../data/db/papers/21829393.xml - Genome-Wide Association Analysis of Autoantibody Positivity in Type 1 Diabetes Cases\n", + "../data/db/papers/21873549.xml - Genome-Wide Association Identifies Nine Common Variants Associated With Fasting Proinsulin Levels and Provides New Insights Into the Pathophysiology of Type 2 Diabetes\n", + "../data/db/papers/21876539.xml - Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM\n", + "../data/db/papers/21878437.xml - Genome-wide association study of circulating retinol levels\n", + "../data/db/papers/21901158.xml - Genome-Wide Detection of Allele Specific Copy Number Variation Associated with Insulin Resistance in African Americans from the HyperGEN Study\n", + "../data/db/papers/21909110.xml - Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure\n", + "../data/db/papers/21909115.xml - Genetic Variants in Novel Pathways Influence Blood Pressure and Cardiovascular Disease Risk\n", + "../data/db/papers/21931564.xml - A Genome-Wide Metabolic QTL Analysis in Europeans Implicates Two Loci Shaped by Recent Positive Selection\n", + "../data/db/papers/21931568.xml - Genome-Wide Association Study Identifies Four Loci Associated with Eruption of Permanent Teeth\n", + "../data/db/papers/21935397.xml - Genome-Wide Population-Based Association Study of Extremely Overweight Young Adults – The GOYA Study\n", + "../data/db/papers/21943158.xml - Genetic variants in LPL, OASL and TOMM40/APOE-C1-C2-C4 genes are associated with multiple cardiovascular-related traits\n", + "../data/db/papers/21946350.xml - Genome-wide association and large scale follow-up identifies 16 new loci influencing lung function\n", + "../data/db/papers/21980299.xml - A Genome-Wide Meta-Analysis of Six Type 1 Diabetes Cohorts Identifies Multiple Associated Loci\n", + "../data/db/papers/21980494.xml - Genetics of Venous Thrombosis: Insights from a New Genome Wide Association Study\n", + "../data/db/papers/21983785.xml - Genome-wide association study identifies a new melanoma susceptibility locus at 1q21.3\n", + "../data/db/papers/21983787.xml - Genome-wide association study identifies three new melanoma susceptibility loci\n", + "../data/db/papers/21998595.xml - Identification, Replication, and Fine-Mapping of Loci Associated with Adult Height in Individuals of African Ancestry\n", + "../data/db/papers/21998597.xml - Genetic Determinants of Serum Testosterone Concentrations in Men\n", + "../data/db/papers/22001756.xml - Genome-wide association study identifies susceptibility loci for Dengue shock syndrome at MICB and PLCE1\n", + "../data/db/papers/22028671.xml - A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol\n", + "../data/db/papers/22085899.xml - UGT1A1 is a major locus influencing bilirubin levels in African Americans\n", + "../data/db/papers/22087292.xml - Bivariate Genome-Wide Association Analyses of Femoral Neck Bone Geometry and Appendicular Lean Mass\n", + "../data/db/papers/22144915.xml - Genome-Wide Meta-Analysis of Five Asian Cohorts Identifies PDGFRA as a Susceptibility Locus for Corneal Astigmatism\n", + "../data/db/papers/22170493.xml - Genome-wide meta-analysis of Psoriatic Arthritis Identifies Susceptibility Locus at REL\n", + "../data/db/papers/22197932.xml - META-ANALYSIS OF GENOME-WIDE ASSOCIATION STUDIES IDENTIFIES THREE NEW RISK LOCI FOR ATOPIC DERMATITIS\n", + "../data/db/papers/22216198.xml - A Genome-Wide Association Study of the Protein C Anticoagulant Pathway\n", + "../data/db/papers/22233651.xml - A Genome-Wide Association Study of Gestational Diabetes Mellitus in Korean Women\n", + "../data/db/papers/22238593.xml - A Genome-Wide Association Search for Type 2 Diabetes Genes in African Americans\n", + "../data/db/papers/22247754.xml - Genome-Wide Association of Implantable Cardioverter-Defibrillator Activation With Life-Threatening Arrhythmias\n", + "../data/db/papers/22267201.xml - Meta-analyses identify 13 novel loci associated with age at menopause and highlights DNA repair and immune pathways\n", + "../data/db/papers/22291604.xml - A Genome-Wide Association Study Identified AFF1 as a Susceptibility Locus for Systemic Lupus Eyrthematosus in Japanese\n", + "../data/db/papers/22291609.xml - A Genome-Wide Association Scan on the Levels of Markers of Inflammation in Sardinians Reveals Associations That Underpin Its Complex Regulation\n", + "../data/db/papers/22306652.xml - Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke\n", + "../data/db/papers/22344219.xml - Meta-analysis identifies common variants associated with body mass index in East Asians\n", + "../data/db/papers/22359512.xml - Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations\n", + "../data/db/papers/22368281.xml - \n", + "../data/db/papers/22383897.xml - Genome-Wide Association Study in East Asians Identifies Novel Susceptibility Loci for Breast Cancer\n", + "../data/db/papers/22384028.xml - A Genome-Wide Linkage and Association Scan Reveals Novel Loci for Hypertension and Blood Pressure Traits\n", + "../data/db/papers/22396660.xml - A Genome-Wide Association Study of Nephrolithiasis in the Japanese Population Identifies Novel Susceptible Loci at 5q35.3, 7p14.3, and 13q14.1\n", + "../data/db/papers/22423221.xml - Platelet activation and atherothrombosis.\n", + "../data/db/papers/22428042.xml - Common Variants in CDKN2B-AS1 Associated with Optic-Nerve Vulnerability of Glaucoma Identified by Genome-Wide Association Studies in Japanese\n", + "../data/db/papers/22430674.xml - Genome-wide haplotype association study identifies the FRMD4A gene as a risk locus for Alzheimer's disease\n", + "../data/db/papers/22438815.xml - Comprehensive Research Synopsis and Systematic Meta-Analyses in Parkinson's Disease Genetics: The PDGene Database\n", + "../data/db/papers/22452962.xml - A genome-wide association study identifies a breast cancer risk variant in ERBB4 at 2q34: results from the Seoul Breast Cancer Study\n", + "../data/db/papers/22470424.xml - A High-Density Genome-Wide Association Screen of Sporadic ALS in US Veterans\n", + "../data/db/papers/22479191.xml - Genome-Wide Association and Functional Follow-Up Reveals New Loci for Kidney Function\n", + "../data/db/papers/22479202.xml - Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals\n", + "../data/db/papers/22479309.xml - Genome-Wide Association Study to Identify Common Variants Associated with Brachial Circumference: A Meta-Analysis of 14 Cohorts\n", + "../data/db/papers/22479419.xml - Genome-Wide Association Study of Treatment Refractory Schizophrenia in Han Chinese\n", + "../data/db/papers/22484627.xml - A genome-wide association meta-analysis identifies new childhood obesity loci\n", + "../data/db/papers/22493691.xml - Novel Associations for Hypothyroidism Include Known Autoimmune Risk Loci\n", + "../data/db/papers/22504421.xml - Common variants at 12q14 and 12q24 are associated with hippocampal volume\n", + "../data/db/papers/22509378.xml - A Genome-Wide Association Study of Female Sexual Dysfunction\n", + "../data/db/papers/22511988.xml - A Genome-Wide Association Study Identifies UGT1A1 as a Regulator of Serum Cell-Free DNA in Young Adults: The Cardiovascular Risk in Young Finns Study\n", + "../data/db/papers/22544364.xml - A genome-wide association study identifies susceptibility loci for Wilms tumor\n", + "../data/db/papers/22558069.xml - Association of Common Variants in TNFRSF13B, TNFSF13, and ANXA3 with Serum Levels of Non-Albumin Protein and Immunoglobulin Isotypes in Japanese\n", + "../data/db/papers/22558097.xml - A Genome-Wide Association Study of Total Bilirubin and Cholelithiasis Risk in Sickle Cell Anemia\n", + "../data/db/papers/22561518.xml - Genome-wide association analyses identify 13 new susceptibility loci for generalized vitiligo\n", + "../data/db/papers/22570617.xml - Common Variants at 9p21 and 8q22 Are Associated with Increased Susceptibility to Optic Nerve Degeneration in Glaucoma\n", + "../data/db/papers/22570627.xml - Common Genetic Determinants of Intraocular Pressure and Primary Open-Angle Glaucoma\n", + "../data/db/papers/22570697.xml - Genome-Wide Association Study of Multiple Sclerosis Confirms a Novel Locus at 5p13.1\n", + "../data/db/papers/22589738.xml - Genome-Wide Association for Abdominal Subcutaneous and Visceral Adipose Reveals a Novel Locus for Visceral Fat in Women\n", + "../data/db/papers/22589742.xml - Genome-Wide Association of Pericardial Fat Identifies a Unique Locus for Ectopic Fat\n", + "../data/db/papers/22675492.xml - Genome-Wide Association Study of Circulating Estradiol, Testosterone, and Sex Hormone-Binding Globulin in Postmenopausal Women\n", + "../data/db/papers/22685421.xml - Genetic Variants on Chromosome 1q41 Influence Ocular Axial Length and High Myopia\n", + "../data/db/papers/22693455.xml - Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases\n", + "../data/db/papers/22693459.xml - Six Novel Susceptibility Loci for Early-Onset Androgenetic Alopecia and Their Unexpected Association with Common Diseases\n", + "../data/db/papers/22719876.xml - Genetic Polymorphisms of the Human PNPLA3 Gene Are Strongly Associated with Severity of Non-Alcoholic Fatty Liver Disease in Japanese\n", + "../data/db/papers/22737229.xml - Genome-Wide Association Study Confirming Association of HLA-DP with Protection against Chronic Hepatitis B and Viral Clearance in Japanese and Korean\n", + "../data/db/papers/22745674.xml - Genome-Wide Association Study in a Lebanese Cohort Confirms PHACTR1 as a Major Determinant of Coronary Artery Stenosis\n", + "../data/db/papers/22760553.xml - Genome-wide pharmacogenomic study of citalopram-induced side effects in STAR*D\n", + "../data/db/papers/22763110.xml - Identification of new susceptibility loci for osteoarthritis (arcOGEN): a genome-wide association study\n", + "../data/db/papers/22792070.xml - Meta-Analysis of Genome-Wide Scans for Total Body BMD in Children and Adults Reveals Allelic Heterogeneity and Age-Specific Effects at the WNT16 Locus\n", + "../data/db/papers/22792071.xml - Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis.\n", + "../data/db/papers/22792082.xml - Genome-Wide Association Analysis in Asthma Subjects Identifies SPATS2L as a Novel Bronchodilator Response Gene\n", + "../data/db/papers/22792221.xml - Common Variants on Chromosome 9p21 Are Associated with Normal Tension Glaucoma\n", + "../data/db/papers/22807686.xml - GWAS Identifies Novel Susceptibility Loci on 6p21.32 and 21q21.3 for Hepatocellular Carcinoma in Chronic Hepatitis B Virus Carriers\n", + "../data/db/papers/22829776.xml - A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation\n", + "../data/db/papers/22832960.xml - A genome-wide meta-analysis of association studies of Cloninger's Temperament Scales\n", + "../data/db/papers/22832961.xml - Genome-wide association study of Alzheimer's disease\n", + "../data/db/papers/22832964.xml - Genome-wide meta-analyses of smoking behaviors in African Americans\n", + "../data/db/papers/22889924.xml - Genome-wide association study of Tourette Syndrome\n" + ] + } + ], + "source": [ + "def get_title(paper):\n", + " with open(paper) as f:\n", + " text = f.read()\n", + " title_regex = re.compile('.+?')\n", + " match = re.search(title_regex, text)\n", + " if match is None:\n", + " return \"\"\n", + " title = match.group(0)[15:-16]\n", + " title = title.replace('', '').replace('', '')\n", + " return title\n", + "\n", + "num_gwas_predicted = np.count_nonzero(predicted)\n", + "print \"number GWAS predicted: {} out of {}\".format(num_gwas_predicted, len(predicted))\n", + "for i, p in enumerate(predicted):\n", + " if p == 1:\n", + " print \"{} - {}\".format(papers[i], get_title(papers[i]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now let's see what happens when we run on a set of 100 random open-access papers. We should expect very few papers to be classified as GWAS, if any." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "filter_type = 'weak' # You can change this again! The choices are None, 'weak', or 'strong'" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number GWAS predicted: 0 out of 88\n" + ] + } + ], + "source": [ + "X_text = []\n", + "X_filters = []\n", + "\n", + "papers = glob.glob('../data/db/non-gwas/*')\n", + "\n", + "for paper in papers:\n", + " features = extract_features(paper)\n", + " X_text.append(features[0])\n", + " X_filters.append(features[1])\n", + " \n", + "with open('../data/classifiers/classifier.pkl') as f:\n", + " clf = pickle.load(f)\n", + "predicted = clf.predict(X_text)\n", + "\n", + "filters = np.asarray(X_filters)\n", + "predicted = np.logical_and(predicted, filters[:,0])\n", + "if filter_type == 'weak':\n", + " predicted = np.logical_and(predicted, filters[:,1])\n", + "elif filter_type == 'strong':\n", + " predicted = np.logical_and(predicted, filters[:,2])\n", + "\n", + "num_gwas_predicted = np.count_nonzero(predicted)\n", + "print \"number GWAS predicted: {} out of {}\".format(num_gwas_predicted, len(predicted))\n", + "for i, p in enumerate(predicted):\n", + " if p == 1:\n", + " print \"{} - {}\".format(papers[i], get_title(papers[i]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We ran the classifier with weak filter on 1.37 million open-access papers, and identified 1431 of them as GWAS. The PMC IDs for these 1431 can be found at /data/db/predicted/weak. You can download those 1431 papers by running the following:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%bash\n", + "cd ../data/db\n", + "make dl-predicted-papers" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The predicted papers will be downloaded in XML format into /data/db/predicted-papers." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/notebooks/phenotype-extraction.ipynb b/notebooks/phenotype-extraction.ipynb index 67c9811..62f6214 100644 --- a/notebooks/phenotype-extraction.ipynb +++ b/notebooks/phenotype-extraction.ipynb @@ -7,67 +7,86 @@ "# Phenotype extraction" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this notebook, we demo the first module of the GWASdb system, which extracts the phenotypes that are studied in each paper.\n", + "\n", + "Before starting, make sure you have downloaded all the datasets: the phenotype ontologies, the GWAS Catalog database, and the open-access GWAS papers." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Preparations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We start by configuring Jupyter and setting up our environment." + ] + }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 1, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], + "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", "\n", "import sys\n", "import cPickle\n", + "import numpy as np\n", + "import sqlalchemy\n", "\n", - "# import snorkel and gwasdb\n", - "sys.path.append('../snorkel')\n", + "# set the paths to snorkel and gwasdb\n", + "sys.path.append('../snorkel-tables')\n", "sys.path.append('../src')\n", "sys.path.append('../src/crawler')\n", "\n", - "# set up paths\n", + "# set up the directory with the input papers\n", "abstract_dir = '../data/db/papers'\n", "\n", "# set up matplotlib\n", "import matplotlib\n", "%matplotlib inline\n", - "matplotlib.rcParams['figure.figsize'] = (12,4)" + "matplotlib.rcParams['figure.figsize'] = (12,4)\n", + "\n", + "# create a Snorkel session\n", + "from snorkel import SnorkelSession\n", + "session = SnorkelSession()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Extract phenotype candidates from papers" + "### Load corpus" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Load corpus" + "Our system will read PubMed papers that have been previously identified as GWAS-related. We load this corpus below" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "from snorkel.parser import XMLDocParser\n", - "from extractor.parser import UnicodeXMLDocParser, GWASXMLAbstractParser\n", + "from extractor.parser import GWASXMLAbstractParser\n", "\n", "xml_parser = GWASXMLAbstractParser(\n", " path=abstract_dir,\n", @@ -79,9 +98,16 @@ " keep_xml_tree=True)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`GWASXMLAbstractParser` is a custom parser that we wrote. For each paper, it extracts the title and either the abstract of the first paragraph (if there is no abstract)." + ] + }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 3, "metadata": { "collapsed": false }, @@ -90,30 +116,43 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 13.5 s, sys: 994 ms, total: 14.5 s\n", - "Wall time: 1min 28s\n" + "CPU times: user 20.9 s, sys: 2.94 s, total: 23.9 s\n", + "Wall time: 3min 16s\n", + "Loaded corpus of 589 documents\n" ] } ], "source": [ - "from snorkel.parser import HTMLParser\n", "from snorkel.parser import SentenceParser\n", "from snorkel.parser import CorpusParser\n", + "from snorkel.models import Corpus\n", "\n", - "sent_parser = SentenceParser()\n", - "html_parser = HTMLParser(path='../data/db/papers/')\n", - "\n", - "corpus_name = 'gwas-text-corpus.pkl'\n", + "# this splits documents into sentences and parses each sentence with Stanford CoreNLP\n", + "sent_parser = SentenceParser(timeout=600000)\n", "\n", "try:\n", - " with open(corpus_name,\"r\") as pkl:\n", - " corpus = cPickle.load(pkl)\n", + " corpus = session.query(Corpus).filter(Corpus.name == 'GWAS Corpus').one()\n", "except:\n", " cp = CorpusParser(xml_parser, sent_parser)\n", - " %time corpus = cp.parse_corpus(name='GWAS Corpus')\n", - " # pickling currently doesn't work...\n", - "# with open(corpus_name,\"w\") as pkl:\n", - "# corpus = cPickle.dump(corpus, pkl)" + " %time corpus = cp.parse_corpus(name='GWAS Corpus', session=session)\n", + " session.add(corpus)\n", + " session.commit()\n", + "\n", + "print 'Loaded corpus of %d documents' % len(corpus)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Candidate extraction" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The first stage is to generate a large set of candidate phenotypes, which may or may not be correct. After that, we will train classifiers to predict which ones are correct." ] }, { @@ -123,45 +162,27 @@ "### Extract candidates" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We first load our phenotype ontologies, which will be used to generate candidates." + ] + }, { "cell_type": "code", - "execution_count": 113, + "execution_count": 4, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 10min 16s, sys: 3.92 s, total: 10min 20s\n", - "Wall time: 10min 22s\n", - "70091 candidates extracted\n" - ] - } - ], + "outputs": [], "source": [ - "from snorkel.candidates import Ngrams\n", - "from snorkel.matchers import DictionaryMatch, Union, RegexMatchSpan\n", - "from snorkel.candidates import EntityExtractor\n", - "from snorkel.utils import slice_into_ngrams\n", - "\n", - "from extractor.util import change_name\n", - "from extractor.matcher import PhenotypeMatcher\n", "from db.kb import KnowledgeBase\n", - "\n", - "def make_ngrams(L, n_max=10, n_min=3, delim=' '):\n", - " for l in L:\n", - " yield l\n", - " tokens = l.strip().split(delim)\n", - " for ngram in slice_into_ngrams(tokens, n_max=n_max, n_min=n_min, delim=delim):\n", - " yield ngram\n", - "\n", - "# Define a candidate space\n", - "ngrams = Ngrams(n_max=7)\n", + "from extractor.util import make_ngrams\n", "\n", "# collect phenotype list\n", "kb = KnowledgeBase()\n", + "\n", "# efo phenotypes\n", "efo_phenotype_list0 = kb.get_phenotype_candidates(source='efo-matching', peek=False) # TODO: remove peaking\n", "efo_phenotype_list = list(make_ngrams(efo_phenotype_list0))\n", @@ -173,51 +194,60 @@ "# mesh chemicals\n", "chem_phenotype_list = kb.get_phenotype_candidates(source='chemical')\n", "# regex matches\n", - "rgx = u'[A-Za-z\\u2013-]+ (disease|trait|phenotype|outcome|response|quantitative trait|measurement|response|side effects)s?'\n", - "\n", - "# Define matchers\n", - "efo_phen_matcher = PhenotypeMatcher(d=efo_phenotype_list, ignore_case=True, mod_fn=change_name)\n", - "snom_phen_matcher = PhenotypeMatcher(d=snomed_phenotype_list, ignore_case=True, mod_fn=change_name)\n", - "mesh_phen_matcher = PhenotypeMatcher(d=mesh_phenotype_list, ignore_case=True, mod_fn=change_name)\n", - "chem_phen_matcher = DictionaryMatch(d=chem_phenotype_list, longest_match_only=True, ignore_case=True)\n", - "regex_phen_matcher = RegexMatchSpan(rgx=rgx)\n", - "# phen_matcher = Union(efo_phen_matcher, mesh_phen_matcher, chem_phen_matcher, regex_phen_matcher)\n", - "phen_matcher = Union(efo_phen_matcher, snom_phen_matcher, mesh_phen_matcher, chem_phen_matcher, regex_phen_matcher)\n", - "\n", - "# Extractor\n", - "phen_extractor = EntityExtractor(ngrams, phen_matcher)\n", - "\n", - "# collect candidates\n", - "%time phen_c = phen_extractor.extract(corpus.get_sentences(), name='all')\n", - "print len(phen_c), 'candidates extracted'" + "rgx = u'[A-Za-z\\u2013-]+ (disease|trait|phenotype|outcome|response|quantitative trait|measurement|response|side effects)s?'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We define matchers and an extractor that generate candaites based on these ontologies." ] }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "def make_ngrams(L, n_max=10, n_min=3, delim=' '):\n", - " for l in L:\n", - " yield l\n", - " tokens = l.strip().split(delim)\n", - " for ngram in slice_into_ngrams(tokens, n_max=n_max, n_min=n_min, delim=delim):\n", - " yield ngram" + "from snorkel.candidates import Ngrams\n", + "from snorkel.matchers import DictionaryMatch, Union, RegexMatchSpan\n", + "from extractor.matcher import PhenotypeMatcher\n", + "from extractor.util import change_name\n", + "\n", + "# Define a candidate space\n", + "ngrams = Ngrams(n_max=7)\n", + "\n", + "# Define a matcher for each ontology\n", + "efo_phen_matcher = PhenotypeMatcher(d=efo_phenotype_list, ignore_case=True, mod_fn=change_name)\n", + "snom_phen_matcher = PhenotypeMatcher(d=snomed_phenotype_list, ignore_case=True, mod_fn=change_name)\n", + "mesh_phen_matcher = PhenotypeMatcher(d=mesh_phenotype_list, ignore_case=True, mod_fn=change_name)\n", + "chem_phen_matcher = DictionaryMatch(d=chem_phenotype_list, longest_match_only=True, ignore_case=True)\n", + "regex_phen_matcher = RegexMatchSpan(rgx=rgx)\n", + "\n", + "# The phenotype matcher is the union of these\n", + "phen_matcher = Union(efo_phen_matcher, snom_phen_matcher, mesh_phen_matcher, chem_phen_matcher, regex_phen_matcher)\n", + "\n", + "# Define the extractor\n", + "from snorkel.candidates import CandidateExtractor\n", + "from snorkel.models import candidate_subclass\n", + "\n", + "Phenotype = candidate_subclass('SnorkelPhenotype', ['phenotype'])\n", + "phen_extractor = CandidateExtractor(Phenotype, ngrams, phen_matcher)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We would like to remove nested candidates (manually, for now)." + "Finally, we extract the candidates." ] }, { "cell_type": "code", - "execution_count": 114, + "execution_count": 6, "metadata": { "collapsed": false }, @@ -226,43 +256,39 @@ "name": "stdout", "output_type": "stream", "text": [ - "18660 candidates dropped, now we have 51431\n" + "6863 sentences loaded\n", + "[========================================] 100%\n", + "CPU times: user 14min 3s, sys: 5.31 s, total: 14min 8s\n", + "Wall time: 14min 21s\n", + "71476 candidates extracted\n" ] } ], "source": [ - "# load existing candidates into a dict\n", - "span_dict = { str(span.context) : list() for span in phen_c }\n", - "for span in phen_c:\n", - " span_dict[str(span.context)].append( (span.char_start, span.char_end) )\n", + "from snorkel.models import CandidateSet\n", "\n", - "def nested(ivl1, ivl2):\n", - " if ivl1 != ivl2 and ivl2[0] <= ivl1[0] <= ivl1[1] <= ivl2[1]:\n", - " return True\n", - " else:\n", - " return False\n", + "try:\n", + " phen_c = session.query(CandidateSet).filter(CandidateSet.name == 'Phenotype Candidates').one()\n", + "except:\n", + " sentences = [s for doc in corpus for s in doc.sentences]\n", + " print '%d sentences loaded' % len(sentences)\n", + " %time phen_c = phen_extractor.extract(sentences, 'Phenotype Candidates', session)\n", + " session.add(phen_c)\n", + " session.commit()\n", "\n", - "new_phen_c = list()\n", - "for span in phen_c:\n", - " span_ivl = span.char_start, span.char_end\n", - " span_name = str(span.context)\n", - " if all([not nested(span_ivl, other_ivl) for other_ivl in span_dict[span_name]]):\n", - " new_phen_c.append(span)\n", - " \n", - "print len(phen_c) - len(new_phen_c), 'candidates dropped, now we have', len(new_phen_c)\n", - "phen_c = new_phen_c" + "print '%d candidates extracted' % len(phen_c)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Create gold-truth set" + "We would like to remove nested candidates as well as obviously wrong candidates." ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 7, "metadata": { "collapsed": false }, @@ -271,59 +297,64 @@ "name": "stdout", "output_type": "stream", "text": [ - "Found 1282 gold mentions, e.g.:\n", - "[('23251661', u'http://www.ebi.ac.uk/efo/EFO_0004749'), ('19587794', u'http://www.ebi.ac.uk/efo/EFO_0004682'), ('24376456', u'http://www.ebi.ac.uk/efo/EFO_0006340'), ('20081858', u'http://www.ebi.ac.uk/efo/EFO_0004501'), ('23776548', u'http://www.ebi.ac.uk/efo/EFO_0004731')]\n", - "1063 535\n" + "64008 candidates dropped, now we have 7468\n" ] } ], "source": [ - "from db.kb import KnowledgeBase\n", - "from nltk.stem import PorterStemmer\n", - "from extractor.util import change_name\n", + "from extractor.candidates import deduplicate, filter_cand\n", "\n", - "kb = KnowledgeBase() # reload\n", - "gold_set_phens = frozenset \\\n", - "([ \n", - " (doc.name, phen.ontology_ref) for doc in corpus.documents \n", - " for phen in kb.phen_by_pmid(doc.name, source='efo')\n", - "])\n", + "# we filter candidates or candidates that don't occur within first 3 sentences\n", + "# TODO: add stopwords: genome, association, population, analysis\n", + "def filter_fn(cand, attrib='phenotype'):\n", + " txt = getattr(cand, attrib).get_span()\n", + " sent_n = getattr(cand, attrib).parent.position\n", + " return False if len(txt) < 5 or sent_n > 2 else True\n", "\n", - "# map phenotype names to their id\n", - "phen2id = \\\n", - "{\n", - " change_name(syn) : phen.ontology_ref for doc in corpus.documents\n", - " \n", - " for phen in kb.phen_by_pmid(doc.name, source='efo')\n", - " for syn in [phen.name] + phen.synonyms.split('|')\n", - "}\n", - "\n", - "# this is the more correct version (code below should be changed to use it)\n", - "# we collect a set of EFOs matching a string; we use this only at the very end for now\n", - "phen2idset = dict()\n", - "for doc in corpus.documents:\n", - " for phen in kb.phen_by_pmid(doc.name, source='efo'):\n", - " synonyms = [phen.name] + phen.synonyms.split('|')\n", - " ngrams = make_ngrams(synonyms)\n", - " for ngram in ngrams:\n", - " syn_name = change_name(ngram)\n", - " if syn_name not in phen2idset: phen2idset[syn_name] = set()\n", - " phen2idset[syn_name].add(phen.id)\n", - "\n", - "id2phen = \\\n", - "{\n", - " phen.ontology_ref : phen for doc in corpus.documents\n", - " for phen in kb.phen_by_pmid(doc.name, source='efo')\n", - "}\n", + "try:\n", + " new_phen_c = session.query(CandidateSet).filter(CandidateSet.name == 'Filtered Phenotype Candidates').one()\n", + "except:\n", + " new_phen_c = CandidateSet(name='Filtered Phenotype Candidates')\n", + " for cand in filter_cand(deduplicate(phen_c), filter_fn=filter_fn):\n", + " new_phen_c.append(cand)\n", + " session.add(new_phen_c)\n", + " session.commit()\n", "\n", - "print 'Found %d gold mentions, e.g.:' % len(gold_set_phens)\n", - "print list(gold_set_phens)[:5]\n", - "print len(phen2id), len(id2phen)" + "print len(phen_c) - len(new_phen_c), 'candidates dropped, now we have', len(new_phen_c)\n", + "phen_c = new_phen_c" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Learning the correctness of our candidates" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we will train machine learning models to identify which phenotype candidates are actually correct." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generating a labeled set of examples" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We first split data into an (unlabeled) training set (since we will use unsupervised risk estimation to train a candidate on it), and a dev/test set." ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 11, "metadata": { "collapsed": false }, @@ -332,443 +363,254 @@ "name": "stdout", "output_type": "stream", "text": [ - "7\n" + "3734.0\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Library/Python/2.7/site-packages/ipykernel/__main__.py:18: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initialized 3734 training and 3734 dev/testing candidates\n" ] } ], "source": [ - "from db import db_session\n", - "from db.schema import *\n", + "try:\n", + " train_c = session.query(CandidateSet).filter(CandidateSet.name == 'Phenotype Training Candidates').one()\n", + " devtest_c = session.query(CandidateSet).filter(CandidateSet.name == 'Phenotype Dev/Test Candidates').one()\n", + "except:\n", + " # delete any previous sets with that name\n", + " session.query(CandidateSet).filter(CandidateSet.name == 'Phenotype Training Candidates').delete()\n", + " session.query(CandidateSet).filter(CandidateSet.name == 'Phenotype Dev/Test Candidates').delete()\n", "\n", - "# paper = db_session.query(Paper).filter(Paper.pubmed_id=='20195266').first()\n", - "# print [ (assoc.phenotype.name, [(p.name, p.source) for p in assoc.phenotype.equivalents]) for assoc in paper.associations ]\n", - "# print first_degree_phens\n", + " frac_test = 0.5\n", "\n", - "from db.kb import KnowledgeBase\n", - "kb = KnowledgeBase() # reload\n", - "print len(kb.phen_by_pmid('20195266', source='efo'))" + " # initialize the new sets\n", + " train_c = CandidateSet(name='Phenotype Training Candidates')\n", + " devtest_c = CandidateSet(name='Phenotype Dev/Test Candidates')\n", + "\n", + " # choose a random subset for the labeled set\n", + " n_test = len(phen_c) * frac_test\n", + " test_idx = set(np.random.choice(len(phen_c), size=(n_test,), replace=False))\n", + "\n", + " # add to the sets\n", + " for i, c in enumerate(phen_c):\n", + " if i in test_idx:\n", + " devtest_c.append(c)\n", + " else:\n", + " train_c.append(c)\n", + "\n", + " # save the results\n", + " session.add(train_c)\n", + " session.add(devtest_c)\n", + " session.commit()\n", + "\n", + "print 'Initialized %d training and %d dev/testing candidates' % (len(train_c), len(devtest_c))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Statistics" + "We will come back to this split later on." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "First, we need to understand whether the extraction or the classification approach will be better." + "### Labeling functions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Number of phenotypes per paper" + "Following the data programming approach, we define set of labeling functions. We will learn their accuracy via unsupervised learning and use them for classifying candidates." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Number of EFO phenotypes per paper" + "First, we need to preload data form our phenotype dictionaries, and we also define common stopwords that we will try to filter out." ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "docid2efo = \\\n", - "{\n", - " doc.name : [ phen.name for phen in kb.phen_by_pmid(doc.name, source='efo') ] for doc in corpus.documents\n", - "}" + "import re, string\n", + "from nltk.stem import PorterStemmer\n", + "from db.kb import KnowledgeBase\n", + "punctuation = set(string.punctuation)\n", + "stemmer = PorterStemmer()\n", + "\n", + "# load set of dictionary phenotypes\n", + "kb = KnowledgeBase()\n", + "phenotype_list = kb.get_phenotype_candidates() # TODO: load disease names from NCBI\n", + "phenotype_list = [phenotype for phenotype in phenotype_list]\n", + "phenotype_set = set(phenotype_list)\n", + "\n", + "# load stopwords\n", + "with open('../data/phenotypes/snorkel/dicts/manual_stopwords.txt') as f:\n", + " stopwords = {line.strip() for line in f}\n", + "stopwords.update(['analysis', 'age', 'drug', 'community', 'detect', 'activity', 'genome',\n", + " 'genetic', 'phenotype', 'response', 'population', 'parameter', 'diagnosis',\n", + " 'level', 'survival', 'maternal', 'paternal', 'clinical', 'joint', 'related',\n", + " 'status', 'risk', 'protein', 'association', 'signal', 'pathway', 'genotype', 'scale',\n", + " 'human', 'family', 'heart', 'general', 'chromosome', 'susceptibility', 'select', \n", + " 'medical', 'system', 'trait', 'suggest', 'confirm', 'subclinical', 'receptor', \n", + " 'class', 'adult', 'affecting', 'increase'])\n", + "from nltk.corpus import stopwords as nltk_stopwords\n", + "stopwords.update(nltk_stopwords.words('english'))\n", + "stopwords = {stemmer.stem(word) for word in stopwords}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Number of GWAS catalog (i.e. aggregate) phenotypes per paper" + "We also define a few helpers." ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 13, "metadata": { - "collapsed": false + "collapsed": true }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GWAS catalog phenotype numbers per paper: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14, 14, 14, 14, 14, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 16, 16, 16, 16, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 19, 20, 20, 20, 20, 21, 21, 21, 21, 21, 21, 22, 22, 22, 23, 23, 23, 24, 24, 24, 25, 25, 26, 26, 27, 28, 28, 28, 29, 29, 30, 30, 30, 31, 31, 31, 31, 32, 33, 33, 34, 34, 34, 34, 34, 35, 35, 35, 35, 36, 36, 37, 37, 38, 38, 38, 39, 39, 39, 40, 40, 41, 41, 42, 42, 47, 48, 48, 49, 50, 50, 50, 53, 56, 59, 60, 62, 69, 73, 74, 87, 89, 98, 151, 163, 166, 166, 168, 181, 199, 219, 241, 245, 299, 699, 949]\n" - ] - } - ], + "outputs": [], "source": [ - "docid2efo = \\\n", - "{\n", - " doc.name : [ phen.name for phen in kb.phen_by_pmid(doc.name, source='gwas_catalog') ] for doc in corpus.documents\n", - "}\n", - "print 'GWAS catalog phenotype numbers per paper:', sorted([len(v) for d, v in docid2efo.items()])" + "def get_phenotype(entity, stem=False):\n", + " phenotype = entity.get_span()\n", + " if stem: phenotype = stemmer.stem(phenotype)\n", + " return phenotype.lower()\n", + "\n", + "def stem_list(L):\n", + " return [stemmer.stem(l.lower()) for l in L]\n", + "\n", + "def span(c):\n", + " return c if isinstance(c, TemporarySpan) else c[-1]\n", + "\n", + "def has_stopwords(m):\n", + " txt = span(m).get_span()\n", + " txt = ''.join(ch for ch in txt if ch not in punctuation)\n", + " words = txt.lower().split()\n", + " return True if all(word in stopwords for word in words) or \\\n", + " all(stemmer.stem(word) in stopwords for word in words) or \\\n", + " all(change_name(word) in stopwords for word in words) else False\n", + " \n", + "# candidate_by_sent = dict()\n", + "# for c in phen_c:\n", + "# if has_stopwords(c): continue\n", + "# context_id = c[0].parent.document.name, c[0].parent.sentence.position\n", + "# if context_id not in candidate_by_sent:\n", + "# candidate_by_sent[context_id] = [999]\n", + "# candidate_by_sent[context_id].append(c) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Candidate recall statistics" + "Now we define the functions themselves." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Over EFO phenotypes" + "We start with functions that are indicative of the mention being true." ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 59, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Statistics over EFO phenotypes:\n", - "# of gold annotations\t= 1282\n", - "# of candidates\t\t= 27861\n", - "Candidate recall\t= 0.534\n", - "Candidate precision\t= 0.025\n" - ] - } - ], + "outputs": [], "source": [ - "from extractor.util import gold_phen_stats\n", - "gold_phen_stats(phen_c, gold_set_phens, phen2id)" + "from snorkel.annotations import LabelManager\n", + "from snorkel.lf_helpers import *\n", + "\n", + "label_manager = LabelManager()\n", + "\n", + "# positive LFs\n", + "def LF_first_sentence(m):\n", + " return +15 if span(m).parent.position == 0 and not has_stopwords(m) else 0\n", + "def LF_from_regex(m):\n", + " if span(m).parent.position == 0 and not regex_phen_matcher._f(span(m)) and not LF_bad_words(m): return +5\n", + " else: return 0\n", + "def LF_with_acronym(m):\n", + " post_txt = ''.join(right_text(m, attr='words', window=5))\n", + " return +1 if re.search(r'\\([A-Z]{2,4}\\)', post_txt) else 0\n", + "def LF_many_words(m):\n", + " return +1 if len(span(m).get_span().split()) >= 3 else 0\n", + "def LF_start_of_sentence(m):\n", + " return +1 if m[0].get_word_start() <= 5 and not has_stopwords(m) and not LF_no_nouns(m) else 0\n", + "def LF_first_mention_in_sentence(m):\n", + " context_id = m[0].parent.document.name, m[0].parent.sentence.position\n", + " other_pos = [c.get_word_start() for c in candidate_by_sent[context_id]]\n", + " return +1 if m.get_word_start() == min(other_pos) else 0\n", + "\n", + "LFs_pos = [LF_first_sentence, LF_with_acronym, LF_from_regex, LF_many_words, LF_start_of_sentence]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Why is the recall low?" + "Next, we also define functions that are indicative of the mention being spurious." ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 57, "metadata": { - "collapsed": false + "collapsed": true }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "597\n", - "24204828\n", - "homa-ir http://www.ebi.ac.uk/efo/EFO_0004501\n", - "homa-b http://www.ebi.ac.uk/efo/EFO_0004469\n", - "fasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466\n", - "fasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466\n", - "fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "Genome-wide contribution of genotype by environment interaction to variation of diabetes-related traits.\n", - "Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits. While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P -nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P -nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P -nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits.\n", - "\n", - "23209189\n", - "type ii diabetes mellitus http://www.ebi.ac.uk/efo/EFO_0001360\n", - "type ii diabetes mellitus http://www.ebi.ac.uk/efo/EFO_0001360\n", - "diabetes mellitus type 02|non-insulin dependent diabetes mellitus|stable diabetes mellitus|diabetes mellitus\n", - "Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21.\n", - "Genome-Wide Association Study for Type 2 Diabetes in Indians Identifies a New Susceptibility Locus at 2q21. Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes–associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 Ă— 10 â’9 ). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 Ă— 10 â’12 ) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD ; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated ( P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.\n", - "\n", - "23535730\n", - "ovarian carcinoma http://www.ebi.ac.uk/efo/EFO_0001075\n", - "ovarian carcinoma http://www.ebi.ac.uk/efo/EFO_0001075\n", - "neoplasms\n", - "GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer.\n", - "GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer. Genome wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC) with another two loci being close to genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the United Kingdom. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. Follow-up genotyping was carried out in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 previously near genome-wide significance and identified three novel loci associated with risk; two loci associated with all EOC subtypes, at 8q21 (rs11782652, P=5.5Ă—10 -9 ) and 10p12 (rs1243180; P=1.8Ă—10 -8 ), and another locus specific to the serous subtype at 17q12 (rs757210; P=8.1Ă—10 -10 ). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility that implicates CHMP4C in the pathogenesis of ovarian cancer.\n", - "\n", - "22044751\n", - "renal sinus adipose tissue measurement http://www.ebi.ac.uk/efo/EFO_0004864\n", - "renal sinus adipose tissue measurement http://www.ebi.ac.uk/efo/EFO_0004864\n", - "\n", - "Heritability and genome-wide association analysis of renal sinus fat accumulation in the Framingham Heart Study.\n", - "Heritability and genome-wide association analysis of renal sinus fat accumulation in the Framingham Heart Study. Ectopic fat accumulation in the renal sinus is associated with chronic kidney disease and hypertension. The genetic contributions to renal sinus fat accumulation in humans have not been well characterized. The present analysis consists of participants from the Framingham Offspring and Third Generation who underwent computed tomography; renal sinus fat and visceral adipose tissue (VAT) were quantified. Renal sinus fat was natural log transformed and sex- and cohort-specific residuals were created, adjusted for (1) age, (2) age and body mass index (BMI), and (3) age and VAT. Residuals were pooled and used to calculate heritability using variance-components analysis in SOLAR. A genome-wide association study (GWAS) for renal sinus fat was performed using an additive model with approximately 2.5 million imputed single nucleotide polymorphisms (SNPs). Finally, we identified the associations of renal sinus fat in our GWAS results with validated SNPs for renal function (n = 16), BMI (n = 32), and waist-to-hip ratio (WHR, n = 14), and applied a multi-SNP genetic risk score method to determine if the SNPs for each renal and obesity trait were in aggregate associated with renal sinus fat. The heritability of renal sinus fat was 39% (p < 0.0001); results were not materially different after adjustment for BMI (39%) or VAT (40%). No SNPs reached genome-wide significance in our GWAS. In our candidate gene analysis, we observed nominal, direction consistent associations with renal sinus fat for one SNP associated with renal function (p = 0.01), two associated with BMI (p < 0.03), and two associated with WHR (p < 0.03); however, none remained significant after accounting for multiple testing. Finally, we observed that in aggregate, the 32 SNPs associated with BMI were nominally associated with renal sinus fat (multi-SNP genetic risk score p = 0.03). Renal sinus fat is a heritable trait, even after accounting for generalized and abdominal adiposity. This provides support for further research into the genetic determinants of renal sinus fat. While our study was underpowered to detect genome-wide significant loci, our candidate gene BMI risk score results suggest that variability in renal sinus fat may be associated with SNPs previously known to be associated with generalized adiposity.\n", - "\n", - "20932310\n", - "beta-amyloid 1-42 measurement http://www.ebi.ac.uk/efo/EFO_0004670\n", - "t-tau measurement http://www.ebi.ac.uk/efo/EFO_0004760\n", - "p-tau measurement http://www.ebi.ac.uk/efo/EFO_0004763\n", - "beta-amyloid 1-42 measurement http://www.ebi.ac.uk/efo/EFO_0004670\n", - "csf a1-42 levels|csf ab1-42 levels|amyloid-beta 1-42 measurement\n", - "Genome-wide association reveals genetic effects on human Aβ42 and τ protein levels in cerebrospinal fluids: a case control study.\n", - "Genome-wide association reveals genetic effects on human Aβ 42 and Ď„ protein levels in cerebrospinal fluids: a case control study. Alzheimer's disease (AD) is common and highly heritable with many genes and gene variants associated with AD in one or more studies, including APOE ε2/ε3/ε4. However, the genetic backgrounds for normal cognition, mild cognitive impairment (MCI) and AD in terms of changes in cerebrospinal fluid (CSF) levels of Aβ 1-42 , T-tau, and P-tau 181P , have not been clearly delineated. We carried out a genome-wide association study (GWAS) in order to better define the genetic backgrounds to these three states in relation to CSF levels. Subjects were participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). The GWAS dataset consisted of 818 participants (mainly Caucasian) genotyped using the Illumina Human Genome 610 Quad BeadChips. This sample included 410 subjects (119 Normal, 115 MCI and 176 AD) with measurements of CSF Aβ 1-42 , T-tau, and P-tau 181P Levels. We used PLINK to find genetic associations with the three CSF biomarker levels. Association of each of the 498,205 SNPs was tested using additive, dominant, and general association models while considering APOE genotype and age. Finally, an effort was made to better identify relevant biochemical pathways for associated genes using the ALIGATOR software. We found that there were some associations with APOE genotype although CSF levels were about the same for each subject group; CSF Aβ 1-42 levels decreased with APOE gene dose for each subject group. T-tau levels tended to be higher among AD cases than among normal subjects. From adjusted result using APOE genotype and age as covariates, no SNP was associated with CSF levels among AD subjects. CYP19A1 'aromatase' (rs2899472), NCAM2 , and multiple SNPs located on chromosome 10 near the ARL5B gene demonstrated the strongest associations with Aβ 1-42 in normal subjects. Two genes found to be near the top SNPs, CYP19A1 (rs2899472, p = 1.90 Ă— 10 -7 ) and NCAM2 (rs1022442, p = 2.75 Ă— 10 -7 ) have been reported as genetic factors related to the progression of AD from previous studies. In AD subjects, APOE ε2/ε3 and ε2/ε4 genotypes were associated with elevated T-tau levels and ε4/ε4 genotype was associated with elevated T-tau and P-tau 181P levels. Pathway analysis detected several biological pathways implicated in Normal with CSF β-amyloid peptide (Aβ 1-42 ). Our genome-wide association analysis identified several SNPs as important factors for CSF biomarker. We also provide new evidence for additional candidate genetic risk factors from pathway analysis that can be tested in further studies.\n", - "\n", - "22792070\n", - "bone density http://www.ebi.ac.uk/efo/EFO_0003923\n", - "bone density http://www.ebi.ac.uk/efo/EFO_0003923\n", - "density\n", - "Meta-analysis of genome-wide scans for total body BMD in children and adults reveals allelic heterogeneity and age-specific effects at the WNT16 locus.\n", - "Meta-Analysis of Genome-Wide Scans for Total Body BMD in Children and Adults Reveals Allelic Heterogeneity and Age-Specific Effects at the WNT16 Locus WNT16 Influences Bone Mineral Density, Cortical Bone Thickness, Bone Strength, and Osteoporotic Fracture Risk. To identify genetic loci influencing bone accrual, we performed a genome-wide association scan for total-body bone mineral density (TB-BMD) variation in 2,660 children of different ethnicities. We discovered variants in 7q31.31 associated with BMD measurements, with the lowest P = 4.1Ă—10 â’11 observed for rs917727 with minor allele frequency of 0.37. We sought replication for all SNPs located ±500 kb from rs917727 in 11,052 additional individuals from five independent studies including children and adults, together with de novo genotyping of rs3801387 (in perfect linkage disequilibrium (LD) with rs917727) in 1,014 mothers of children from the discovery cohort. The top signal mapping in the surroundings of WNT16 was replicated across studies with a meta-analysis P = 2.6Ă—10 â’31 and an effect size explaining between 0.6%–1.8% of TB-BMD variance. Conditional analyses on this signal revealed a secondary signal for total body BMD (P = 1.42Ă—10 â’10 ) for rs4609139 and mapping to C7orf58 . We also examined the genomic region for association with skull BMD to test if the associations were independent of skeletal loading. We identified two signals influencing skull BMD variation, including rs917727 (P = 1.9Ă—10 â’16 ) and rs7801723 (P = 8.9Ă—10 â’28 ), also mapping to C7orf58 ( r 2  = 0.50 with rs4609139). Wnt16 knockout (KO) mice with reduced total body BMD and gene expression profiles in human bone biopsies support a role of C7orf58 and WNT16 on the BMD phenotypes observed at the human population level. In summary, we detected two independent signals influencing total body and skull BMD variation in children and adults, thus demonstrating the presence of allelic heterogeneity at the WNT16 locus. One of the skull BMD signals mapping to C7orf58 is mostly driven by children, suggesting temporal determination on peak bone mass acquisition. Our life-course approach postulates that these genetic effects influencing peak bone mass accrual may impact the risk of osteoporosis later in life. Genetic investigations on bone mineral density (BMD) variation in children allow the identification of factors determining peak bone mass and their influence on developing osteoporosis later in life. We ran a genome-wide association study (GWAS) for total body BMD based on 2,660 children of different ethnic backgrounds, followed by replication in an additional 12,066 individuals comprising children, young adults, and elderly populations. Our GWAS meta-analysis identified two independent signals in the 7q31.31 locus, arising from SNPs in the vicinity of WNT16 , FAM3C , and C7orf58 . These variants were also associated with skull BMD, a skeletal trait with much less environmental influence for which one of the signals displayed age-specific effects. Integration of functional studies in a Wnt16 knockout mouse model and gene expression profiles in human bone tissue provided additional evidence that WNT16 and C7orf58 underlie the described associations. All together our findings demonstrate the relevance of these factors for bone biology, the attainment of peak bone mass, and their likely impact on bone fragility later in life.\n", - "\n", - "23834954\n", - "post-operative sensory disturbance http://www.ebi.ac.uk/efo/EFO_0005324\n", - "post-operative sensory disturbance http://www.ebi.ac.uk/efo/EFO_0005324\n", - "\n", - "Genome-wide association study of sensory disturbances in the inferior alveolar nerve after bilateral sagittal split ramus osteotomy.\n", - "Genome-wide association study of sensory disturbances in the inferior alveolar nerve after bilateral sagittal split ramus osteotomy. Bilateral sagittal split ramus osteotomy (BSSRO) is a common orthognatic surgical procedure. Sensory disturbances in the inferior alveolar nerve, including hypoesthesia and dysesthesia, are frequently observed after BSSRO, even without distinct nerve injury. The mechanisms that underlie individual differences in the vulnerability to sensory disturbances have not yet been elucidated. The present study investigated the relationships between genetic polymorphisms and the vulnerability to sensory disturbances after BSSRO in a genome-wide association study (GWAS). A total of 304 and 303 patients who underwent BSSRO were included in the analyses of hypoesthesia and dysesthesia, respectively. Hypoesthesia was evaluated using the tactile test 1 week after surgery. Dysesthesia was evaluated by interview 4 weeks after surgery. Whole-genome genotyping was conducted using Illumina BeadChips including approximately 300,000 polymorphism markers. Hypoesthesia and dysesthesia occurred in 51 (16.8%) and 149 (49.2%) subjects, respectively. Significant associations were not observed between the clinical data (i.e., age, sex, body weight, body height, loss of blood volume, migration length of bone fragments, nerve exposure, duration of anesthesia, and duration of surgery) and the frequencies of hypoesthesia and dysesthesia. Significant associations were found between hypoesthesia and the rs502281 polymorphism (recessive model: combined χ 2 = 24.72, nominal P = 6.633 Ă— 10 -7 ), between hypoesthesia and the rs2063640 polymorphism (recessive model: combined χ 2 = 23.07, nominal P = 1.563 Ă— 10 -6 ), and between dysesthesia and the nonsynonymous rs2677879 polymorphism (trend model: combined χ 2 = 16.56, nominal P = 4.722 Ă— 10 -5 ; dominant model: combined χ 2 = 16.31, nominal P = 5.369 Ă— 10 -5 ). The rs502281 and rs2063640 polymorphisms were located in the flanking region of the ARID1B and ZPLD1 genes on chromosomes 6 and 3, whose official names are “AT rich interactive domain 1B (SWI1-like)” and “zona pellucida-like domain containing 1”, respectively. The rs2677879 polymorphism is located in the METTL4 gene on chromosome 18, whose official name is “methyltransferase like 4”. The GWAS of sensory disturbances after BSSRO revealed associations between genetic polymorphisms located in the flanking region of the ARID1B and ZPLD1 genes and hypoesthesia and between a nonsynonymous genetic polymorphism in the METTL4 gene and dysesthesia.\n", - "\n", - "22792071\n", - "cortical thickness http://www.ebi.ac.uk/efo/EFO_0004840\n", - "bone density http://www.ebi.ac.uk/efo/EFO_0003923\n", - "bone density http://www.ebi.ac.uk/efo/EFO_0003923\n", - "density\n", - "WNT16 influences bone mineral density, cortical bone thickness, bone strength, and osteoporotic fracture risk.\n", - "WNT16 Influences Bone Mineral Density, Cortical Bone Thickness, Bone Strength, and Osteoporotic Fracture Risk. We aimed to identify genetic variants associated with cortical bone thickness (CBT) and bone mineral density (BMD) by performing two separate genome-wide association study (GWAS) meta-analyses for CBT in 3 cohorts comprising 5,878 European subjects and for BMD in 5 cohorts comprising 5,672 individuals. We then assessed selected single-nucleotide polymorphisms (SNPs) for osteoporotic fracture in 2,023 cases and 3,740 controls. Association with CBT and forearm BMD was tested for âĽ2.5 million SNPs in each cohort separately, and results were meta-analyzed using fixed effect meta-analysis. We identified a missense SNP (Thr>Ile; rs2707466) located in the WNT16 gene (7q31), associated with CBT (effect size of â’0.11 standard deviations [SD] per C allele, P = 6.2Ă—10 â’9 ). This SNP, as well as another nonsynonymous SNP rs2908004 (Gly>Arg), also had genome-wide significant association with forearm BMD (â’0.14 SD per C allele, P = 2.3Ă—10 â’12 , and â’0.16 SD per G allele, P = 1.2Ă—10 â’15 , respectively). Four genome-wide significant SNPs arising from BMD meta-analysis were tested for association with forearm fracture. SNP rs7776725 in FAM3C , a gene adjacent to WNT16 , was associated with a genome-wide significant increased risk of forearm fracture (OR = 1.33, P = 7.3Ă—10 â’9 ), with genome-wide suggestive signals from the two missense variants in WNT16 (rs2908004: OR = 1.22, P = 4.9Ă—10 â’6 and rs2707466: OR = 1.22, P = 7.2Ă—10 â’6 ). We next generated a homozygous mouse with targeted disruption of Wnt16 . Female Wnt16 â’/â’ mice had 27% (P<0.001) thinner cortical bones at the femur midshaft, and bone strength measures were reduced between 43%–61% (6.5Ă—10 â’13 0.8) with rs6978712. Thus, in the aspect of decision-making in adherence behavior, the association between medication adherence and three loci proximal to the GCC1 gene seems worthy of further research. However, to overcome a few limitations in this study, defining the standardized phenotype criteria for self-reported adherence should be performed before replicating association studies.\n", - "\n", - "17903297\n", - "neuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926\n", - "volumetric brain mri http://www.ebi.ac.uk/efo/EFO_0004868\n", - "neuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926\n", - "test\n", - "Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham Study.\n", - "Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham study. Brain magnetic resonance imaging (MRI) and cognitive tests can identify heritable endophenotypes associated with an increased risk of developing stroke, dementia and Alzheimer's disease (AD). We conducted a genome-wide association (GWA) and linkage analysis exploring the genetic basis of these endophenotypes in a community-based sample. A total of 705 stroke- and dementia-free Framingham participants (age 62 +9 yrs, 50% male) who underwent volumetric brain MRI and cognitive testing (1999–2002) were genotyped. We used linear models adjusting for first degree relationships via generalized estimating equations (GEE) and family based association tests (FBAT) in additive models to relate qualifying single nucleotide polymorphisms (SNPs, 70,987 autosomal on Affymetrix 100K Human Gene Chip with minor allele frequency ≥ 0.10, genotypic call rate ≥ 0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001) to multivariable-adjusted residuals of 9 MRI measures including total cerebral brain (TCBV), lobar, ventricular and white matter hyperintensity (WMH) volumes, and 6 cognitive factors/tests assessing verbal and visuospatial memory, visual scanning and motor speed, reading, abstract reasoning and naming. We determined multipoint identity-by-descent utilizing 10,592 informative SNPs and 613 short tandem repeats and used variance component analyses to compute LOD scores. The strongest gene-phenotype association in FBAT analyses was between SORL1 (rs1131497; p = 3.2 Ă— 10 -6 ) and abstract reasoning, and in GEE analyses between CDH4 (rs1970546; p = 3.7 Ă— 10 -8 ) and TCBV. SORL1 plays a role in amyloid precursor protein processing and has been associated with the risk of AD. Among the 50 strongest associations (25 each by GEE and FBAT) were other biologically interesting genes. Polymorphisms within 28 of 163 candidate genes for stroke, AD and memory impairment were associated with the endophenotypes studied at p < 0.001. We confirmed our previously reported linkage of WMH on chromosome 4 and describe linkage of reading performance to a marker on chromosome 18 (GATA11A06), previously linked to dyslexia (LOD scores = 2.2 and 5.1). Our results suggest that genes associated with clinical neurological disease also have detectable effects on subclinical phenotypes. These hypothesis generating data illustrate the use of an unbiased approach to discover novel pathways that may be involved in brain aging, and could be used to replicate observations made in other studies.\n", - "\n", - "20675712\n", - "sensory perception of bitter taste http://purl.obolibrary.org/obo/GO_0050913\n", - "sensory perception of bitter taste http://purl.obolibrary.org/obo/GO_0050913\n", - "bitter taste sensitivity|bitter taste perception\n", - "The perception of quinine taste intensity is associated with common genetic variants in a bitter receptor cluster on chromosome 12.\n", - "The perception of quinine taste intensity is associated with common genetic variants in a bitter receptor cluster on chromosome 12. The perceived taste intensities of quinine HCl, caffeine, sucrose octaacetate (SOA) and propylthiouracil (PROP) solutions were examined in 1457 twins and their siblings. Previous heritability modeling of these bitter stimuli indicated a common genetic factor for quinine, caffeine and SOA (22–28%), as well as separate specific genetic factors for PROP (72%) and quinine (15%). To identify the genes involved, we performed a genome-wide association study with the same sample as the modeling analysis, genotyped for approximately 610 000 single-nucleotide polymorphisms (SNPs). For caffeine and SOA, no SNP association reached a genome-wide statistical criterion. For PROP, the peak association was within TAS2R38 ( rs713598 , A49P, P = 1.6 Ă— 10 â’104 ), which accounted for 45.9% of the trait variance. For quinine, the peak association was centered in a region that contains bitter receptor as well as salivary protein genes and explained 5.8% of the trait variance ( TAS2R19 , rs10772420 , R299C, P = 1.8 Ă— 10 â’15 ). We confirmed this association in a replication sample of twins of similar ancestry ( P = 0.00001). The specific genetic factor for the perceived intensity of PROP was identified as the gene previously implicated in this trait ( TAS2R38 ). For quinine, one or more bitter receptor or salivary proline-rich protein genes on chromosome 12 have alleles which affect its perception but tight linkage among very similar genes precludes the identification of a single causal genetic variant.\n", - "\n", - "22479191\n", - "cystatin c measurement http://www.ebi.ac.uk/efo/EFO_0004617\n", - "chronic kidney disease http://www.ebi.ac.uk/efo/EFO_0003884\n", - "serum creatinine measurement http://www.ebi.ac.uk/efo/EFO_0004518\n", - "cystatin c measurement http://www.ebi.ac.uk/efo/EFO_0004617\n", - "\n", - "Genome-wide association and functional follow-up reveals new loci for kidney function.\n", - "Genome-Wide Association and Functional Follow-Up Reveals New Loci for Kidney Function. Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2 , DDX1 , SLC47A1 , CDK12 , CASP9 , and INO80 . Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD. Chronic kidney disease (CKD) is an important public health problem with a hereditary component. We performed a new genome-wide association study in up to 130,600 European ancestry individuals to identify genes that may influence kidney function, specifically genes that may influence kidney function differently depending on sex, age, hypertension, and diabetes status of individuals. We uncovered 6 new loci associated with estimated glomerular filtration rate (eGFR), the primary measure of renal function, in or near MPPED2 , DDX1 , SLC47A1 , CDK12 , CASP9 , and INO80 . CDK12 effect was stronger in younger and absent in older individuals. MPPED2 , DDX1 , SLC47A1 , and CDK12 loci were associated with eGFR in African ancestry samples as well, highlighting the cross-ethnicity validity of our findings. Using the zebrafish model, we performed morpholino knockdown of mpped2 and casp9 in zebrafish embryos and revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. These results further our understanding of the pathogenesis of CKD and provide insights into potential novel mechanisms of disease.\n", - "\n", - "20038947\n", - "unipolar depression http://www.ebi.ac.uk/efo/EFO_0003761\n", - "unipolar depression http://www.ebi.ac.uk/efo/EFO_0003761\n", - "melancholia\n", - "Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies.\n", - "Novel loci for major depression identified by genome-wide association study of STAR*D and meta-analysis of three studies. We report a genome-wide association study (GWAS) of major depressive disorder (MDD) in 1,221 cases from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study and 1,636 screened controls. No genome-wide evidence for association was detected. We also carried out a meta-analysis of three European-ancestry MDD GWAS datasets: STAR*D, Genetics of Recurrent Early-Onset Depression (GenRED) and the publicly-available Genetic Association Information Network MDD dataset (GAIN-MDD). These datasets, totaling 3,957 cases and 3,428 controls, were genotyped using four different platforms (Affymetrix 6.0, 5.0 and 500K, and Perlegen). For each of 2.4 million HapMap II SNPs, using genotyped data where available and imputed data otherwise, single-SNP association tests were carried out in each sample with correction for ancestry-informative principal components. The strongest evidence for association in the meta-analysis was observed for intronic SNPs in ATP6V1B2 (P = 6.78 Ă— 10 â’7 ), SP4 ( P = 7.68 Ă— 10 â’7 ) and GRM7 ( P = 1.11 Ă— 10 â’6 ). Additional exploratory analyses were carried out for a narrower phenotype (recurrent MDD with onset before age 31, N = 2,191 cases), and separately for males and females. Several of the best findings were supported primarily by evidence from narrow cases or from either males or females. Based on previous biological evidence, we consider GRM7 a strong MDD candidate gene. Larger samples will be required to determine whether any common SNPs are significantly associated with MDD.\n", - "\n", - "24564958\n", - "social communication impairment http://www.ebi.ac.uk/efo/EFO_0005427\n", - "social communication impairment http://www.ebi.ac.uk/efo/EFO_0005427\n", - "\n", - "Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence.\n", - "Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence. Social-communication abilities are heritable traits, and their impairments overlap with the autism continuum. To characterise the genetic architecture of social-communication difficulties developmentally and identify genetic links with the autistic dimension, we conducted a genome-wide screen of social-communication problems at multiple time-points during childhood and adolescence. Social-communication difficulties were ascertained at ages 8, 11, 14 and 17 years in a UK population-based birth cohort (Avon Longitudinal Study of Parents and Children; N  ≤ 5,628) using mother-reported Social Communication Disorder Checklist scores. Genome-wide Complex Trait Analysis (GCTA) was conducted for all phenotypes. The time-points with the highest GCTA heritability were subsequently analysed for single SNP association genome-wide. Type I error in the presence of measurement relatedness and the likelihood of observing SNP signals near known autism susceptibility loci (co-location) were assessed via large-scale, genome-wide permutations. Association signals ( P  ≤ 10 â’5 ) were also followed up in Autism Genetic Resource Exchange pedigrees ( N  = 793) and the Autism Case Control cohort ( N cases / N controls  = 1,204/6,491). GCTA heritability was strongest in childhood ( h 2 (8 years)  = 0.24) and especially in later adolescence ( h 2 (17 years)  = 0.45), with a marked drop during early to middle adolescence ( h 2 (11 years)  = 0.16 and h 2 (14 years)  = 0.08). Genome-wide screens at ages 8 and 17 years identified for the latter time-point evidence for association at 3p22.2 near SCN11A (rs4453791, P  = 9.3 × 10 â’9 ; genome-wide empirical P  = 0.011) and suggestive evidence at 20p12.3 at PLCB1 (rs3761168, P  = 7.9 × 10 â’8 ; genome-wide empirical P  = 0.085). None of these signals contributed to risk for autism. However, the co-location of population-based signals and autism susceptibility loci harbouring rare mutations, such as PLCB1 , is unlikely to be due to chance (genome-wide empirical P co-location  = 0.007). Our findings suggest that measurable common genetic effects for social-communication difficulties vary developmentally and that these changes may affect detectable overlaps with the autism spectrum.\n", - "\n", - "25085501\n", - "seasonal allergic rhinitis http://www.ebi.ac.uk/efo/EFO_0003956\n", - "asthma http://www.ebi.ac.uk/efo/EFO_0000270\n", - "allergic rhinitis http://www.ebi.ac.uk/efo/EFO_0005854\n", - "allergic rhinitis http://www.ebi.ac.uk/efo/EFO_0005854\n", - "\n", - "Integrated Genome-wide Association, Coexpression Network, and Expression Single Nucleotide Polymorphism Analysis Identifies Novel Pathway in Allergic Rhinitis.\n", - "Integrated genome-wide association, coexpression network, and expression single nucleotide polymorphism analysis identifies novel pathway in allergic rhinitis. Allergic rhinitis is a common disease whose genetic basis is incompletely explained. We report an integrated genomic analysis of allergic rhinitis. We performed genome wide association studies (GWAS) of allergic rhinitis in 5633 ethnically diverse North American subjects. Next, we profiled gene expression in disease-relevant tissue (peripheral blood CD4+ lymphocytes) collected from subjects who had been genotyped. We then integrated the GWAS and gene expression data using expression single nucleotide (eSNP), coexpression network, and pathway approaches to identify the biologic relevance of our GWAS. GWAS revealed ethnicity-specific findings, with 4 genome-wide significant loci among Latinos and 1 genome-wide significant locus in the GWAS meta-analysis across ethnic groups. To identify biologic context for these results, we constructed a coexpression network to define modules of genes with similar patterns of CD4+ gene expression (coexpression modules) that could serve as constructs of broader gene expression. 6 of the 22 GWAS loci with P-value ≤ 1x10 â’6 tagged one particular coexpression module (4.0-fold enrichment, P-value 0.0029), and this module also had the greatest enrichment (3.4-fold enrichment, P-value 2.6 × 10 â’24 ) for allergic rhinitis-associated eSNPs (genetic variants associated with both gene expression and allergic rhinitis). The integrated GWAS, coexpression network, and eSNP results therefore supported this coexpression module as an allergic rhinitis module. Pathway analysis revealed that the module was enriched for mitochondrial pathways (8.6-fold enrichment, P-value 4.5 × 10 â’72 ). Our results highlight mitochondrial pathways as a target for further investigation of allergic rhinitis mechanism and treatment. Our integrated approach can be applied to provide biologic context for GWAS of other diseases.\n", - "\n", - "21483430\n", - "neuroimaging measurement http://www.ebi.ac.uk/efo/EFO_0004346\n", - "south texas assessment of neurocognition http://www.ebi.ac.uk/efo/EFO_0004785\n", - "south texas assessment of neurocognition http://www.ebi.ac.uk/efo/EFO_0004785\n", - "\n", - "Impact of DISC1 variation on neuroanatomical and neurocognitive phenotypes.\n", - "Impact of DISC1 variation on neuroanatomical and neurocognitive phenotypes. Although DISC1 has been implicated in many psychiatric disorders, including schizophrenia, bipolar disorder, schizoaffective disorder and major depression, its biological role in these disorders is unclear. To better understand this gene and its role in psychiatric disease, we conducted transcriptional profiling and genome-wide association analysis in 1 232 pedigreed Mexican American individuals for whom we have neuroanatomic images, neurocognitive assessments and neuropsychiatric diagnoses. SOLAR was used to determine heritability, identify gene expression patterns and perform association analyses on 188 quantitative brain-related phenotypes. We found that the DISC1 transcript is highly heritable (h 2 =0.50; p=1.97 Ă— 10 â’22 ), and that gene expression is strongly cis -regulated ( cis -LOD=3.89) but is also influenced by trans -effects. We identified several DISC1 polymorphisms that were associated with cortical gray-matter thickness within the parietal, temporal and frontal lobes. Associated regions affiliated with memory included the entorhinal cortex (rs821639, p=4.11 Ă— 10 â’5 ; rs2356606, p=4.71 Ă— 10 â’4 ), cingulate cortex (rs16856322, p=2.88 Ă— 10 â’4 ) and parahippocampal gyrus (rs821639, p=4.95 Ă— 10 â’4 ); those affiliated with executive and other cognitive processing included the transverse temporal gyrus (rs9661837, p=5.21 Ă— 10 â’4 ; rs17773946, p=6.23 Ă— 10 â’4 ), anterior cingulate cortex (rs2487453, p=; 4.79 Ă— 10 â’4 ; rs3738401, p= 5.43 Ă— 10 â’4 ) and medial orbitofrontal cortex (rs9661837; p=7.40 Ă— 10 â’4 ). Cognitive measures of working memory (rs2793094, p=3.38 Ă— 10 â’4 ), as well as lifetime history of depression (rs4658966, p=4.33 Ă— 10 â’4 ; rs12137417, p=4.93 Ă— 10 â’4 ) and panic (rs12137417, p=7.41 Ă— 10 â’4 ) were associated with DISC1 sequence variation. DISC1 has well-defined genetic regulation and clearly influences important phenotypes related to psychiatric disease.\n", - "\n", - "21076409\n", - "qrs duration http://www.ebi.ac.uk/efo/EFO_0005055\n", - "heart function measurement http://www.ebi.ac.uk/efo/EFO_0004311\n", - "heart function measurement http://www.ebi.ac.uk/efo/EFO_0004311\n", - "heart function tests|cardiac function tests\n", - "Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction.\n", - "Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction. QRS interval on the electrocardiogram reflects ventricular depolarization and conduction time, and is a risk factor for mortality, sudden death, and heart failure. We performed a genome-wide association meta-analysis in 40,407 European-descent individuals from 14 studies, with further genotyping in 7170 additional Europeans, and identified 22 loci associated with QRS duration ( P < 5 Ă— 10 â’8 ). These loci map in or near genes in pathways with established roles in ventricular conduction such as sodium channels, transcription factors, and calcium-handling proteins, but also point to novel biologic processes, such as kinase inhibitors and genes related to tumorigenesis. We demonstrate that SCN10A , a gene at our most significant locus, is expressed in the mouse ventricular conduction system, and treatment with a selective SCN10A blocker prolongs QRS duration. These findings extend our current knowledge of ventricular depolarization and conduction.\n", - "\n", - "21829393\n", - "autoantibody measurement http://www.ebi.ac.uk/efo/EFO_0004866\n", - "type i diabetes mellitus http://www.ebi.ac.uk/efo/EFO_0001359\n", - "type i diabetes mellitus http://www.ebi.ac.uk/efo/EFO_0001359\n", - "iddm|diabetes mellitus\n", - "Genome-wide association analysis of autoantibody positivity in type 1 diabetes cases.\n", - "Genome-Wide Association Analysis of Autoantibody Positivity in Type 1 Diabetes Cases. The genetic basis of autoantibody production is largely unknown outside of associations located in the major histocompatibility complex (MHC) human leukocyte antigen (HLA) region. The aim of this study is the discovery of new genetic associations with autoantibody positivity using genome-wide association scan single nucleotide polymorphism (SNP) data in type 1 diabetes (T1D) patients with autoantibody measurements. We measured two anti-islet autoantibodies, glutamate decarboxylase (GADA, n = 2,506), insulinoma-associated antigen 2 (IA-2A, n = 2,498), antibodies to the autoimmune thyroid (Graves') disease (AITD) autoantigen thyroid peroxidase (TPOA, n = 8,300), and antibodies against gastric parietal cells (PCA, n = 4,328) that are associated with autoimmune gastritis. Two loci passed a stringent genome-wide significance level ( p <10 â’10 ): 1q23/ FCRL3 with IA-2A and 9q34/ ABO with PCA. Eleven of 52 non-MHC T1D loci showed evidence of association with at least one autoantibody at a false discovery rate of 16%: 16p11/ IL27 -IA-2A, 2q24/ IFIH1 -IA-2A and PCA, 2q32/ STAT4 -TPOA, 10p15/ IL2RA -GADA, 6q15/ BACH2 -TPOA, 21q22/ UBASH3A -TPOA, 1p13/ PTPN22 -TPOA, 2q33/ CTLA4 -TPOA, 4q27/ IL2 /TPOA, 15q14/ RASGRP1 /TPOA, and 12q24/ SH2B3 -GADA and TPOA. Analysis of the TPOA-associated loci in 2,477 cases with Graves' disease identified two new AITD loci ( BACH2 and UBASH3A ). Autoantibodies are important markers for autoimmune diseases such as type 1 diabetes and Graves' disease. However, little is known about the genetic factors that control their production. To improve our understanding of this genetic basis, we measured four autoantibodies in a collection of up to 8,300 type 1 diabetes cases plasma samples. We combined these measurements with genome-wide genotype data to conduct four independent genome-wide association studies. Two loci showed unequivocal evidence of autoantibody association: the FCRL3 locus and the ABO blood group locus. Variants in the FCRL3 gene have been previously associated with autoimmune diseases, but such associations have not been reported for ABO blood group genotypes. In addition, we found extensive overlap between type 1 diabetes and autoantibody loci, and these findings provide new information about the role of these risk variants. Lastly, we hypothesized that loci associated with thyroid autoantibodies are strong candidates for association with thyroid autoimmune disorders. We confirmed this hypothesis by genotyping these variants in an independent cohort of Graves' disease cases, and we found evidence for two new Graves' disease loci.\n", - "\n", - "24204295\n", - "narcolepsy with cataplexy http://www.ebi.ac.uk/efo/EFO_0000614\n", - "age at onset http://www.ebi.ac.uk/efo/EFO_0004847\n", - "narcolepsy with cataplexy http://www.ebi.ac.uk/efo/EFO_0000614\n", - "gelineau's syndrome|narcolepsy nos|paroxysmal sleep|gelineaus syndrome|syndrome\n", - "Genome wide analysis of narcolepsy in China implicates novel immune loci and reveals changes in association prior to versus after the 2009 H1N1 influenza pandemic.\n", - "Genome Wide Analysis of Narcolepsy in China Implicates Novel Immune Loci and Reveals Changes in Association Prior to Versus After the 2009 H1N1 Influenza Pandemic. Previous studies in narcolepsy, an autoimmune disorder affecting hypocretin (orexin) neurons and recently associated with H1N1 influenza, have demonstrated significant associations with five loci. Using a well-characterized Chinese cohort, we refined known associations in TRA@ and P2RY11-DNMT1 and identified new associations in the TCR beta (TRB@; rs9648789 max P = 3.7Ă—10 â’9 OR 0.77), ZNF365 (rs10995245 max P = 1.2Ă—10 â’11 OR 1.23), and IL10RB-IFNAR1 loci (rs2252931 max P = 2.2Ă—10 â’9 OR 0.75). Variants in the Human Leukocyte Antigen (HLA)- DQ region were associated with age of onset (rs7744020 P = 7.9Ă—10 â’9 beta â’1.9 years) and varied significantly among cases with onset after the 2009 H1N1 influenza pandemic compared to previous years (rs9271117 P = 7.8Ă—10 â’10 OR 0.57). These reflected an association of DQB1*03:01 with earlier onset and decreased DQB1*06:02 homozygosity following 2009. Our results illustrate how genetic association can change in the presence of new environmental challenges and suggest that the monitoring of genetic architecture over time may help reveal the appearance of novel triggers for autoimmune diseases. Narcolepsy-hypocretin deficiency results from a highly specific autoimmune attack on hypocretin cells. Recent studies have established antigen presentation by specific class II proteins encoded by (HLA DQB1*06:02 and DQA1*01:02) to the cognate T cell receptor as the main disease pathway, with a role for H1N1 influenza in the triggering process. Here, we have used a large and well-characterized cohort of Chinese narcolepsy cases to examine genetic architecture not observed in European samples. We confirmed previously implicated susceptibility genes (T cell receptor alpha, P2RY11), and identify new loci (ZNF365, IL10RB-IFNAR1), most notably, variants at the beta chain of the T cell receptor. We found that one HLA variant, (DQB1*03:01), is associated with dramatically earlier disease onset (nearly 2 years). We also identified differences in HLA haplotype frequencies among cases with onset following the 2009 H1N1 influenza pandemic as compared to before the outbreak, with fewer HLA DQB1*06:02 homozygotes. This may be the first demonstration of such an effect, and suggests that the study of changes in GWAS signals over time could help identify environmental factors in other autoimmune diseases.\n", - "\n", - "21383967\n", - "immune system disease http://www.ebi.ac.uk/efo/EFO_0000540\n", - "immune system disease http://www.ebi.ac.uk/efo/EFO_0000540\n", - "[x]disorder involving the immune mechanism\n", - "Meta-analysis of genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci.\n", - "Meta-Analysis of Genome-Wide Association Studies in Celiac Disease and Rheumatoid Arthritis Identifies Fourteen Non-HLA Shared Loci. Epidemiology and candidate gene studies indicate a shared genetic basis for celiac disease (CD) and rheumatoid arthritis (RA), but the extent of this sharing has not been systematically explored. Previous studies demonstrate that 6 of the established non-HLA CD and RA risk loci (out of 26 loci for each disease) are shared between both diseases. We hypothesized that there are additional shared risk alleles and that combining genome-wide association study (GWAS) data from each disease would increase power to identify these shared risk alleles. We performed a meta-analysis of two published GWAS on CD (4,533 cases and 10,750 controls) and RA (5,539 cases and 17,231 controls). After genotyping the top associated SNPs in 2,169 CD cases and 2,255 controls, and 2,845 RA cases and 4,944 controls, 8 additional SNPs demonstrated P <5Ă—10 â’8 in a combined analysis of all 50,266 samples, including four SNPs that have not been previously confirmed in either disease: rs10892279 near the DDX6 gene ( P combined  = 1.2Ă—10 â’12 ), rs864537 near CD247 ( P combined  = 2.2Ă—10 â’11 ), rs2298428 near UBE2L3 ( P combined  = 2.5Ă—10 â’10 ), and rs11203203 near UBASH3A ( P combined  = 1.1Ă—10 â’8 ). We also confirmed that 4 gene loci previously established in either CD or RA are associated with the other autoimmune disease at combined P <5Ă—10 â’8 ( SH2B3 , 8q24 , STAT4 , and TRAF1-C5 ). From the 14 shared gene loci, 7 SNPs showed a genome-wide significant effect on expression of one or more transcripts in the linkage disequilibrium (LD) block around the SNP. These associations implicate antigen presentation and T-cell activation as a shared mechanism of disease pathogenesis and underscore the utility of cross-disease meta-analysis for identification of genetic risk factors with pleiotropic effects between two clinically distinct diseases. Celiac disease (CD) and rheumatoid arthritis (RA) are two autoimmune diseases characterized by distinct clinical features but increased co-occurrence in families and individuals. Genome-wide association studies (GWAS) performed in CD and RA have identified the HLA region and 26 non-HLA genetic risk loci in each disease. Of the 26 CD and 26 RA risk loci, previous studies have shown that six are shared between the two diseases. In this study we aimed to identify additional shared risk alleles and, in doing so, gain more insight into shared disease pathogenesis. We first empirically investigated the distribution of putative risk alleles from GWAS across both diseases (after removing known risk loci for both diseases). We found that CD risk alleles are non-randomly distributed in the RA GWAS (and vice versa), indicating that CD risk alleles have an increased prior probability of being associated with RA (and vice versa). Next, we performed a GWAS meta-analysis to search for shared risk alleles by combing the RA and CD GWAS, performing both directional and opposite allelic effect analyses, followed by replication testing in independent case-control datasets in both diseases. In addition to the already established six non-HLA shared risk loci, we observed statistically robust associations at eight SNPs, thereby increasing the number of shared non-HLA risk loci to fourteen. Finally, we used gene expression studies and pathway analysis tools to identify the plausible candidate genes in the fourteen associated loci. We observed remarkable overrepresentation of T-cell signaling molecules among the shared genes.\n", - "\n", - "21998595\n", - "body height http://www.ebi.ac.uk/efo/EFO_0004339\n", - "anthropometry http://www.ebi.ac.uk/efo/EFO_0004302\n", - "anthropometry http://www.ebi.ac.uk/efo/EFO_0004302\n", - "anthropometric traits\n", - "Identification, replication, and fine-mapping of Loci associated with adult height in individuals of african ancestry.\n", - "Identification, Replication, and Fine-Mapping of Loci Associated with Adult Height in Individuals of African Ancestry. Adult height is a classic polygenic trait of high heritability ( h 2 âĽ0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain âĽ10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P  = 3.4Ă—10 â’12 and 2p14-rs4315565, P  = 1.2Ă—10 â’8 ). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry ( P  = 1.7Ă—10 â’4 for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs ( P <0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits. Adult height is an ideal phenotype to improve our understanding of the genetic architecture of complex diseases and traits: it is easily measured and usually available in large cohorts, relatively stable, and mostly influenced by genetics (narrow-sense heritability of height h 2 âĽ0.8). Genome-wide association (GWA) studies in individuals of European ancestry have identified >180 single nucleotide polymorphisms (SNPs) associated with height. In the current study, we continued to use height as a model polygenic trait and explored the genetic influence in populations of African ancestry through a meta-analysis of GWA height results from 20,809 individuals of African descent. We identified two novel height loci not previously found in Europeans. We also replicated the European height signals, suggesting that many of the genetic variants that are associated with height are shared between individuals of European and African descent. Finally, in fine-mapping the European height loci in African-ancestry individuals, we found SNPs more likely to be associated with the expression of nearby genes than the SNPs originally found in Europeans. Thus, our results support the utility of performing genetic studies in non-European populations to gain insights into complex human diseases and traits.\n", - "\n", - "25742292\n", - "female fertility http://www.ebi.ac.uk/efo/EFO_0006918\n", - "fertility measurement http://www.ebi.ac.uk/efo/EFO_0006923\n", - "female fertility http://www.ebi.ac.uk/efo/EFO_0006918\n", - "\n", - "Genome-wide association study of parity in bangladeshi women.\n", - "Genome-Wide Association Study of Parity in Bangladeshi Women. Human fertility is a complex trait determined by gene-environment interactions in which genetic factors represent a significant component. To better understand inter-individual variability in fertility, we performed one of the first genome-wide association studies (GWAS) of common fertility phenotypes, lifetime number of pregnancies and number of children in a developing country population. The fertility phenotype data and DNA samples were obtained at baseline recruitment from individuals participating in a large prospective cohort study in Bangladesh. GWAS analyses of fertility phenotypes were conducted among 1,686 married women. One SNP on chromosome 4 was non-significantly associated with number of children at P <10 -7 and number of pregnancies at P <10 -6 . This SNP is located in a region without a gene within 1 Mb. One SNP on chromosome 6 was non-significantly associated with extreme number of children at P <10 -6 . The closest gene to this SNP is HDGFL1 , a hepatoma-derived growth factor. When we excluded hormonal contraceptive users, a SNP on chromosome 5 was non-significantly associated at P <10 -5 for number of children and number of pregnancies. This SNP is located near C5orf64 , an open reading frame, and ZSWIM6 , a zinc ion binding gene. We also estimated the heritability of these phenotypes from our genotype data using GCTA (Genome-wide Complex Trait Analysis) for number of children (h g 2 = 0.149, SE = 0.24, p-value = 0.265) and number of pregnancies (h g 2 = 0.007, SE = 0.22, p-value = 0.487). Our genome-wide association study and heritability estimates of number of pregnancies and number of children in Bangladesh did not confer strong evidence of common variants for parity variation. However, our results suggest that future studies may want to consider the role of 3 notable SNPs in their analysis.\n", - "\n", - "20174558\n", - "type ii diabetes mellitus http://www.ebi.ac.uk/efo/EFO_0001360\n", - "type ii diabetes mellitus http://www.ebi.ac.uk/efo/EFO_0001360\n", - "diabetes mellitus type 02|non-insulin dependent diabetes mellitus|stable diabetes mellitus|diabetes mellitus\n", - "A genome-wide association study identifies susceptibility variants for type 2 diabetes in Han Chinese.\n", - "A Genome-Wide Association Study Identifies Susceptibility Variants for Type 2 Diabetes in Han Chinese. To investigate the underlying mechanisms of T2D pathogenesis, we looked for diabetes susceptibility genes that increase the risk of type 2 diabetes (T2D) in a Han Chinese population. A two-stage genome-wide association (GWA) study was conducted, in which 995 patients and 894 controls were genotyped using the Illumina HumanHap550-Duo BeadChip for the first genome scan stage. This was further replicated in 1,803 patients and 1,473 controls in stage 2. We found two loci not previously associated with diabetes susceptibility in and around the genes protein tyrosine phosphatase receptor type D ( PTPRD ) ( P  = 8.54Ă—10 â’10 ; odds ratio [OR] = 1.57; 95% confidence interval [CI] = 1.36–1.82), and serine racemase ( SRR ) ( P  = 3.06Ă—10 â’9 ; OR = 1.28; 95% CI = 1.18–1.39). We also confirmed that variants in KCNQ1 were associated with T2D risk, with the strongest signal at rs2237895 ( P  = 9.65Ă—10 â’10 ; OR = 1.29, 95% CI = 1.19–1.40). By identifying two novel genetic susceptibility loci in a Han Chinese population and confirming the involvement of KCNQ1 , which was previously reported to be associated with T2D in Japanese and European descent populations, our results may lead to a better understanding of differences in the molecular pathogenesis of T2D among various populations. Type 2 diabetes (T2D) is a complex disease that involves many genes and environmental factors. Genome-wide and candidate-gene association studies have thus far identified at least 19 regions containing genes that may confer a risk for T2D. However, most of these studies were conducted with patients of European descent. We studied Chinese patients with T2D and identified two genes, PTPRD and SRR, that were not previously known to be involved in diabetes and are involved in biological pathways different from those implicated in T2D by previous association reports. PTPRD is a protein tyrosine phosphatase and may affect insulin signaling on its target cells. SRR encodes a serine racemase that synthesizes D-serine from L-serine. Both D-serine (coagonist) and the neurotransmitter glutamate bind to NMDA receptors and trigger excitatory neurotransmission in the brain. Glutamate signaling also regulates insulin and glucagon secretion in pancreatic islets. Thus, SRR and D-serine, in addition to regulating insulin and glucagon secretion, may play a role in the etiology of T2D. Our study suggests that, in different patient populations, different genes may confer risks for diabetes. Our findings may lead to a better understanding of the molecular pathogenesis of T2D.\n", - "\n", - "20169177\n", - "rheumatoid arthritis http://www.ebi.ac.uk/efo/EFO_0000685\n", - "systemic lupus erythematosus http://www.ebi.ac.uk/efo/EFO_0002690\n", - "rheumatoid arthritis http://www.ebi.ac.uk/efo/EFO_0000685\n", - "proliferative arthritis|rheumatoid arthritis (disorder)|arthritis\n", - "Genome-wide association study in Asian populations identifies variants in ETS1 and WDFY4 associated with systemic lupus erythematosus.\n", - "Genome-Wide Association Study in Asian Populations Identifies Variants in ETS1 and WDFY4 Associated with Systemic Lupus Erythematosus. Systemic lupus erythematosus is a complex and potentially fatal autoimmune disease, characterized by autoantibody production and multi-organ damage. By a genome-wide association study (320 patients and 1,500 controls) and subsequent replication altogether involving a total of 3,300 Asian SLE patients from Hong Kong, Mainland China, and Thailand, as well as 4,200 ethnically and geographically matched controls, genetic variants in ETS1 and WDFY4 were found to be associated with SLE ( ETS1 : rs1128334, P  = 2.33Ă—10 â’11 , OR = 1.29; WDFY4 : rs7097397, P  = 8.15Ă—10 â’12 , OR = 1.30). ETS1 encodes for a transcription factor known to be involved in a wide range of immune functions, including Th17 cell development and terminal differentiation of B lymphocytes. SNP rs1128334 is located in the 3′-UTR of ETS1 , and allelic expression analysis from peripheral blood mononuclear cells showed significantly lower expression level from the risk allele. WDFY4 is a conserved protein with unknown function, but is predominantly expressed in primary and secondary immune tissues, and rs7097397 in WDFY4 changes an arginine residue to glutamine (R1816Q) in this protein. Our study also confirmed association of the HLA locus, STAT4 , TNFSF4 , BLK , BANK1 , IRF5 , and TNFAIP3 with SLE in Asians. These new genetic findings may help us to gain a better understanding of the disease and the functions of the genes involved. In this study, we first conducted a genome-wide association study in a Hong Kong Chinese population, followed by replication in three other cohorts from Mainland China and a cohort from Thailand, which totaled 3,300 Asian patients and 4,200 ethnically and geographically matched controls. We identified novel variants in ETS1 and WDFY4 associated with SLE with genome-wide significance and confirmed the association of HLA locus, STAT4 , BLK , IRF5 , BANK1 , TNFSF , and IRF5 with the disease. ETS1 encodes a critical transcription factor involved in Th17 and B cell development. Allelic expression study showed a significantly lower expression of ETS1 from the risk allele, which provided functional support to the genetic findings. WDFY4 is a huge protein with unknown function but is predominantly expressed in primary and secondary immune tissues, and a nonsynonymous SNP in this gene was found to be highly associated with SLE susceptibility. Our findings shed new light on the function of these genes as well as the mechanism of this devastating disease.\n", - "\n", - "22911880\n", - "mental or behavioural disorder http://www.ebi.ac.uk/efo/EFO_0000677\n", - "eating disorder http://www.ebi.ac.uk/efo/EFO_0005203\n", - "mental or behavioural disorder http://www.ebi.ac.uk/efo/EFO_0000677\n", - "disorders\n", - "Genome-wide association analysis of eating disorder-related symptoms, behaviors, and personality traits.\n", - "Genome-Wide Association Analysis of Eating Disorder-Related Symptoms, Behaviors, and Personality Traits. Eating disorders (EDs) are common, complex psychiatric disorders thought to be caused by both genetic and environmental factors. They share many symptoms, behaviors, and personality traits, which may have overlapping heritability. The aim of the present study is to perform a genome-wide association scan (GWAS) of six ED phenotypes comprising three symptom traits from the Eating Disorders Inventory 2 [Drive for Thinness (DT), Body Dissatisfaction (BD), and Bulimia], Weight Fluctuation symptom, Breakfast Skipping behavior and Childhood Obsessive-Compulsive Personality Disorder trait (CHIRP). Investigated traits were derived from standardized self-report questionnaires completed by the TwinsUK population-based cohort. We tested 283,744 directly typed SNPs across six phenotypes of interest in the TwinsUK discovery dataset and followed-up signals from various strata using a two-stage replication strategy in two independent cohorts of European ancestry. We meta-analyzed a total of 2,698 individuals for DT, 2,680 for BD, 2,789 (821 cases/1,968 controls) for Bulimia, 1,360 (633 cases/727 controls) for Childhood Obsessive-Compulsive Personality Disorder trait, 2,773 (761 cases/2,012 controls) for Breakfast Skipping, and 2,967 (798 cases/2,169 controls) for Weight Fluctuation symptom. In this GWAS analysis of six ED-related phenotypes, we detected association of eight genetic variants with P < 10 â’5 . Genetic variants that showed suggestive evidence of association were previously associated with several psychiatric disorders and ED-related phenotypes. Our study indicates that larger-scale collaborative studies will be needed to achieve the necessary power to detect loci underlying ED-related traits. © 2012 Wiley Periodicals, Inc.\n", - "\n", - "25226531\n", - "infant expressive language ability http://www.ebi.ac.uk/efo/EFO_0006316\n", - "infant expressive language ability http://www.ebi.ac.uk/efo/EFO_0006316\n", - "\n", - "Common variation near ROBO2 is associated with expressive vocabulary in infancy.\n", - "Common variation near ROBO2 is associated with expressive vocabulary in infancy. Twin studies suggest that expressive vocabulary at ~24 months is modestly heritable. However, the genes influencing this early linguistic phenotype are unknown. Here we conduct a genome-wide screen and follow-up study of expressive vocabulary in toddlers of European descent from up to four studies of the EArly Genetics and Lifecourse Epidemiology consortium, analysing an early (15–18 months, â€one-word stage’, N Total =8,889) and a later (24–30 months, â€two-word stage’, N Total =10,819) phase of language acquisition. For the early phase, one single-nucleotide polymorphism (rs7642482) at 3p12.3 near ROBO2 , encoding a conserved axon-binding receptor, reaches the genome-wide significance level ( P =1.3 Ă— 10 â’8 ) in the combined sample. This association links language-related common genetic variation in the general population to a potential autism susceptibility locus and a linkage region for dyslexia, speech-sound disorder and reading. The contribution of common genetic influences is, although modest, supported by genome-wide complex trait analysis (meta-GCTA h 2 15–18-months =0.13, meta-GCTA h 2 24–30-months =0.14) and in concordance with additional twin analysis (5,733 pairs of European descent, h 2 24-months =0.20). The genetic basis of expressive vocabulary in children around 2 years old is poorly understood. Here, the authors show that a genetic variant near the ROBO2 gene is associated with early language acquisition in the general population and highlight a potential genetic link between language-related common genetic variation and a linkage region for dyslexia, speech-sound disorder and reading.\n", - "\n", - "20861866\n", - "glaucoma http://www.ebi.ac.uk/efo/EFO_0000516\n", - "age-related macular degeneration http://www.ebi.ac.uk/efo/EFO_0001365\n", - "glaucoma http://www.ebi.ac.uk/efo/EFO_0000516\n", - "glaucoma associated with other ocular disorders|other specified glaucoma nos|glaucoma nec|glaucoma nos|other specified glaucoma nos (disorder)|glaucoma (disorder)|glaucoma associated with other ocular disorders (disorder)|glaucoma\n", - "Genome-wide association identifies SKIV2L and MYRIP as protective factors for age-related macular degeneration.\n", - "Genome-wide association identifies SKIV2L and MYRIP as protective factors for age-related macular degeneration. Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly in the developed world. We conducted a genome-wide association study in a series of families enriched for AMD and completed a meta-analysis of this new data with results from reanalysis of an existing study of a late-stage case/control cohort. We tested the top findings for replication in 1 896 cases and 1 866 controls and identified two novel genetic protective factors for AMD. In addition to the CFH (p=2.3Ă—10 â’64 ) and ARMS2 (p=1.2Ă—10 â’60 ) loci, we observed a protective effect at rs429608, an intronic SNP in SKIV2L (p=5.3Ă—10 â’15 ), a gene near the C2/BF locus, that indicates the protective effect may be mediated by variants other than the C2/BF variants previously studied. Haplotype analysis at this locus identified three protective haplotypes defined by the rs429608 protective allele. We also identified a new potentially protective effect at rs2679798 in MYRIP (p=2.9Ă—10 â’4 ), a gene involved in retinal pigment epithelium melanosome trafficking. Interestingly, MYRIP was initially identified in the family-based scan and was confirmed in the case-control set. From these efforts, we report the identification of two novel protective factors for AMD and confirm the previously known associations at CFH , ARMS2 and C3 .\n", - "\n" - ] - } - ], + "outputs": [], "source": [ - "from extractor.util import gold_phen_recall\n", - "kb = KnowledgeBase()\n", - "id2doc = {doc.name : doc for doc in corpus.documents}\n", - "gold_dict_phen = { doc_id : set() for doc_id, phen_id in gold_set_phens }\n", - "for doc_id, phen_id in gold_set_phens:\n", - " gold_dict_phen[doc_id].add(phen_id)\n", + "# negative LFs\n", + "def LF_bad_words(m):\n", + " bad_words = ['disease', 'single', 'map', 'genetic variation', '( p <']\n", + " return -100 if any(span(m).get_span().lower().startswith(b) for b in bad_words) else 0\n", + "def LF_short(m):\n", + " txt = span(m).get_attrib_span('words', 3)\n", + " return -50 if len(txt) < 5 else 0\n", + "def LF_no_nouns(m):\n", + " return -10 if not any(t.startswith('NN') for t in span(m).get_attrib_tokens('pos_tags')) else 0\n", + "def LF_not_first_sentences(m):\n", + " return -1 if span(m).parent.position > 1 else 0\n", + "def LF_stopwords(m):\n", + " return -50 if has_stopwords(m) else 0\n", "\n", - "phen_not_found = list(gold_phen_recall(phen_c, gold_set_phens, phen2id))\n", - "print len(phen_not_found)\n", - "for doc_id, phen_id in phen_not_found[:100]:\n", - " if len(gold_dict_phen[doc_id]) > 3: continue\n", - " print doc_id\n", - " for phen_id2 in gold_dict_phen[doc_id]:\n", - " print id2phen[phen_id2].name, phen_id2\n", - "# print gold_dict_phen[doc_id]\n", - " print id2phen[phen_id].name, id2phen[phen_id].ontology_ref\n", - " print id2phen[phen_id].synonyms \n", - " print kb.title_by_pmid(doc_id)\n", - " print ' '.join(s.text for s in id2doc[doc_id].sentences)\n", - " print" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Over aggregate phenotypes" + "LFs_neg = [LF_bad_words, LF_short, LF_no_nouns, LF_not_first_sentences, LF_stopwords]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We say that a mention for an aggregate phenotype is correct, if it corresponds to the name of the GWC phenotype or to the phenotype of any equivalent EFO phenotype." + "Finally, we combine both functions and use them to label our training set." ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 60, "metadata": { "collapsed": false }, @@ -777,603 +619,169 @@ "name": "stdout", "output_type": "stream", "text": [ - "Found 1282 gold mentions, e.g.:\n", - "[('23251661', u'http://www.ebi.ac.uk/efo/EFO_0004749'), ('19587794', u'http://www.ebi.ac.uk/efo/EFO_0004682'), ('24376456', u'http://www.ebi.ac.uk/efo/EFO_0006340'), ('20081858', u'http://www.ebi.ac.uk/efo/EFO_0004501'), ('23776548', u'http://www.ebi.ac.uk/efo/EFO_0004731')]\n", - "1063 535\n", - "Statistics over EFO phenotypes:\n", - "# of gold annotations\t= 9747\n", - "# of candidates\t\t= 27861\n", - "# of correct candidates\t= 9017\n", - "Candidate recall\t= 0.925\n", - "Candidate precision\t= 0.324\n" + "10\n", + "CPU times: user 228 ms, sys: 10.5 ms, total: 239 ms\n", + "Wall time: 240 ms\n" ] } ], "source": [ - "from db.kb import KnowledgeBase\n", - "from nltk.stem import PorterStemmer\n", - "from extractor.util import change_name\n", - "\n", - "kb = KnowledgeBase() # reload\n", - "gold_set_agg_phens = frozenset \\\n", - "([ \n", - " (doc.name, phen.id) for doc in corpus.documents \n", - " for phen in kb.phen_by_pmid(doc.name, source='gwas_catalog')\n", - "])\n", - "\n", - "# map phenotype names to their id (EFO syn -> GWC id)\n", - "agg_phen2id = dict()\n", - "for doc in corpus.documents:\n", - " for phen in kb.phen_by_pmid(doc.name, source='gwas_catalog'):\n", - " for eq_phen in phen.equivalents:\n", - " for syn in [phen.name] + [eq_phen.name] + eq_phen.synonyms.split('|'):\n", - " syn_name = change_name(syn)\n", - " if syn_name not in agg_phen2id: agg_phen2id[syn_name] = set()\n", - " agg_phen2id[syn_name].add(phen.id)\n", - "\n", - "# map ids to phenotypes (GWC id -> GWC phen obj) \n", - "agg_id2phen = \\\n", - "{\n", - " phen.id : phen for doc in corpus.documents\n", - " for phen in kb.phen_by_pmid(doc.name, source='gwas_catalog')\n", - "}\n", - "\n", - "print 'Found %d gold mentions, e.g.:' % len(gold_set_phens)\n", - "print list(gold_set_phens)[:5]\n", - "print len(phen2id), len(id2phen)\n", + "LFs = LFs_pos + LFs_neg\n", "\n", - "from extractor.util import gold_phen_stats, gold_agg_phen_stats\n", - "gold_agg_phen_stats(phen_c, gold_set_agg_phens, agg_phen2id)" + "try:\n", + " %time L_train = label_manager.load(session, train_c, 'Phenotype LF Labels')\n", + "except sqlalchemy.orm.exc.NoResultFound:\n", + " %time L_train = label_manager.create(session, train_c, 'Phenotype LF Labels', f=LFs)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Why is the recall low?" + "The table below displays some statistics about our labeling functions." ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 61, "metadata": { "collapsed": false }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "1003\n", - "22383897\n", - "breast cancer 25571\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer 25572\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer 25573\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer\n", - "Genome-Wide Association Study in East Asians Identifies Novel Susceptibility Loci for Breast Cancer. Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. We aimed to discover novel genetic susceptibility loci for breast cancer. We conducted a four-stage genome-wide association study (GWAS) in 19,091 cases and 20,606 controls of East-Asian descent including Chinese, Korean, and Japanese women. After analyzing 690,947 SNPs in 2,918 cases and 2,324 controls, we evaluated 5,365 SNPs for replication in 3,972 cases and 3,852 controls. Ninety-four SNPs were further evaluated in 5,203 cases and 5,138 controls, and finally the top 22 SNPs were investigated in up to 17,423 additional subjects (7,489 cases and 9,934 controls). SNP rs9485372, near the TGF-β activated kinase ( TAB2 ) gene in chromosome 6q25.1, showed a consistent association with breast cancer risk across all four stages, with a P -value of 3.8Ă—10 â’12 in the combined analysis of all samples. Adjusted odds ratios (95% confidence intervals) were 0.89 (0.85–0.94) and 0.80 (0.75–0.86) for the A/G and A/A genotypes, respectively, compared with the genotype G/G. SNP rs9383951 ( P  = 1.9Ă—10 â’6 from the combined analysis of all samples), located in intron 5 of the ESR1 gene, and SNP rs7107217 ( P  = 4.6Ă—10 â’7 ), located at 11q24.3, also showed a consistent association in each of the four stages. This study provides strong evidence for a novel breast cancer susceptibility locus represented by rs9485372, near the TAB2 gene (6q25.1), and identifies two possible susceptibility loci located in the ESR1 gene and 11q24.3, respectively. Breast cancer is one of the most common malignancies among women worldwide. Genetic factors play an important role in the etiology of breast cancer. To identify common genetic susceptibility alleles for breast cancer, we performed a four-stage genome-wide association study in 19,091 cases and 20,606 controls among East-Asian women. Single nucleotide polymorphism (SNP) rs9485372, near the TGF-beta activated kinase 1 ( TAB2 ) gene at chromosome 6q25.1, was associated with breast cancer risk ( P  = 3.8Ă—10 â’12 ). SNPs rs9383951, located in intron 5 of the estrogen receptor 1 ( ESR1 ) gene, and rs7107217, located at 11q24.3, were also consistently associated with breast cancer risk in all four stages with a combined P of 1.9Ă—10 â’6 and 4.6Ă—10 â’7 , respectively. This study provides strong evidence for a novel breast cancer susceptibility locus represented by rs9485372, near the TAB2 gene (6q25.1), and identifies two possible susceptibility loci located in the ESR1 gene and 11q24.3, respectively.\n", - "\n", - "19578366\n", - "glioma (high-grade) 20856\n", - "\tcentral nervous system cancer http://www.ebi.ac.uk/efo/EFO_0000326 cns cancer|malignant central nervous system neoplasm|malignant tumor of cns|cancer of cns|malignant tumor of central nervous system|malignant cns neoplasms|malignant neoplasm of cns|malignant tumor of the central nervous system|malignant cns tumor|malignant central nervous system tumor|malignant neoplasm of the cns|malignant neoplasm of the central nervous system|malignant cns neoplasm|central nervous system neoplasms\n", - "glioma (high-grade) 20857\n", - "\tcentral nervous system cancer http://www.ebi.ac.uk/efo/EFO_0000326 cns cancer|malignant central nervous system neoplasm|malignant tumor of cns|cancer of cns|malignant tumor of central nervous system|malignant cns neoplasms|malignant neoplasm of cns|malignant tumor of the central nervous system|malignant cns tumor|malignant central nervous system tumor|malignant neoplasm of the cns|malignant neoplasm of the central nervous system|malignant cns neoplasm|central nervous system neoplasms\n", - "glioma (high-grade) 20855\n", - "\tcentral nervous system cancer http://www.ebi.ac.uk/efo/EFO_0000326 cns cancer|malignant central nervous system neoplasm|malignant tumor of cns|cancer of cns|malignant tumor of central nervous system|malignant cns neoplasms|malignant neoplasm of cns|malignant tumor of the central nervous system|malignant cns tumor|malignant central nervous system tumor|malignant neoplasm of the cns|malignant neoplasm of the central nervous system|malignant cns neoplasm|central nervous system neoplasms\n", - "glioma (high-grade)\n", - "Variants in the CDKN2B and RTEL1 regions are associated with high grade glioma susceptibility. The causes of glioblastoma and other devastating gliomas remain obscure 1 , 2 . To discover new candidate genes that might influence glioma susceptibility, we conducted a principal component 3 adjusted genome wide association study (GWAS) of 275,895 autosomal variants among 692 adult high grade glioma patients (622 from the San Francisco Adult Glioma Study (AGS) and 70 from the Cancer Genome Atlas (TCGA) 4 versus 3992 controls (602 from AGS and 3390 from Illumina iControlDB (iControls)). For replication, we then analyzed the 13 SNPs with p<10 â’6 using completely independent data from 176 high grade glioma patients versus 174 controls from the Mayo Clinic. Rs1412829 in chromosome 9p21 (near CDKN2B ) had discovery p-value 3.4*10 â’8 , replication p-value 0.0038, and combined p-value 1.85*10 â’10 . Rs6010620 intronic to RTEL1 had discovery p-value 1.5*10 â’7 , replication p-value 0.00035, and combined p-value 3.40*10 â’9 . For both SNPs, the direction of association was the same in discovery and replication phases.\n", - "\n", - "19412176\n", - "narcolepsy 20551\n", - "\tnarcolepsy with cataplexy http://www.ebi.ac.uk/efo/EFO_0000614 gelineau's syndrome|narcolepsy nos|paroxysmal sleep|gelineaus syndrome|syndrome\n", - "narcolepsy\n", - "Narcolepsy is strongly associated with the TCR alpha locus. Narcolepsy-cataplexy, characterized by sleepiness and rapid onset into REM sleep, affects 1 in 2,000 individuals 1 , 2 . Narcolepsy was first shown to be tightly associated with HLA-DR2 3 , and later sublocalized to DQB1*0602 4 . Following studies in dogs 5 and mice 6 , a 95% loss of hypocretin-producing cells in human postmortem hypothalami was reported 7 , 8 , Using Genome Wide Association (GWA) in Caucasians with replication in three ethnic groups, we found association with polymorphisms in the T-Cell receptor alpha ( TCRA ) locus, with highest significance at rs1154155 (average allelic odds ratio 1.69, genotype odds ratios 1.94 and 2.55, p<10 â’21 , 1830 cases, 2164 controls). This is the first documented genetic involvement of the TCRA locus, the major receptor for HLA-peptide presentation, in any disease. It is still unclear how specific HLA alleles confer susceptibility to over 100 HLA-associated disorders 9 , thus narcolepsy will provide new insights on how HLA-TCR interactions contribute to organ specific autoimmune targeting.\n", - "\n", - "23001122\n", - "breast cancer (male) 21123\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer (male) 21124\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer (male) 21125\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer (male)\n", - "Genome-wide association study identifies a novel variant in RAD51B associated with male breast cancer risk. We conducted a genome-wide association study of male breast cancer using 823 cases and 2,795 controls of European ancestry with validation in independent sample sets totalling 438 cases and 474 controls. A novel variant in RAD51B (14q24.1) was significantly associated with male breast cancer risk ( P = 3.02 Ă—10 â’13 , odds ratio (OR) = 1.57). TOX3 (16q12.1) was also a susceptibility locus ( P = 3.87 Ă—10 â’15 , OR = 1.50).\n", - "\n", - "23183491\n", - "opioid sensitivity 21902\n", - "\tresponse to opiate http://purl.obolibrary.org/obo/GO_0014072 response to isoquinoline alkaloid\n", - "opioid sensitivity\n", - "Genome-wide association study identifies a potent locus associated with human opioid sensitivity. Opioids, such as morphine and fentanyl, are widely used as effective analgesics for the treatment of acute and chronic pain. In addition, the opioid system has a key role in the rewarding effects of morphine, ethanol, cocaine and various other drugs. Although opioid sensitivity is well known to vary widely among individual subjects, several candidate genetic polymorphisms reported so far are not sufficient for fully understanding the wide range of interindividual differences in human opioid sensitivity. By conducting a multistage genome-wide association study (GWAS) in healthy subjects, we found that genetic polymorphisms within a linkage disequilibrium block that spans 2q33.3–2q34 were strongly associated with the requirements for postoperative opioid analgesics after painful cosmetic surgery. The C allele of the best candidate single-nucleotide polymorphism (SNP), rs2952768, was associated with more analgesic requirements, and consistent results were obtained in patients who underwent abdominal surgery. In addition, carriers of the C allele in this SNP exhibited less vulnerability to severe drug dependence in patients with methamphetamine dependence, alcohol dependence, and eating disorders and a lower â€Reward Dependence' score on a personality questionnaire in healthy subjects. Furthermore, the C/C genotype of this SNP was significantly associated with the elevated expression of a neighboring gene, CREB1 . These results show that SNPs in this locus are the most potent genetic factors associated with human opioid sensitivity known to date, affecting both the efficacy of opioid analgesics and liability to severe substance dependence. Our findings provide valuable information for the personalized treatment of pain and drug dependence.\n", - "\n", - "22383897\n", - "breast cancer 25571\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer 25572\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer 25573\n", - "\tbreast carcinoma http://www.ebi.ac.uk/efo/EFO_0000305 breast neoplasms|neoplasm\n", - "breast cancer\n", - "Genome-Wide Association Study in East Asians Identifies Novel Susceptibility Loci for Breast Cancer. Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. We aimed to discover novel genetic susceptibility loci for breast cancer. We conducted a four-stage genome-wide association study (GWAS) in 19,091 cases and 20,606 controls of East-Asian descent including Chinese, Korean, and Japanese women. After analyzing 690,947 SNPs in 2,918 cases and 2,324 controls, we evaluated 5,365 SNPs for replication in 3,972 cases and 3,852 controls. Ninety-four SNPs were further evaluated in 5,203 cases and 5,138 controls, and finally the top 22 SNPs were investigated in up to 17,423 additional subjects (7,489 cases and 9,934 controls). SNP rs9485372, near the TGF-β activated kinase ( TAB2 ) gene in chromosome 6q25.1, showed a consistent association with breast cancer risk across all four stages, with a P -value of 3.8Ă—10 â’12 in the combined analysis of all samples. Adjusted odds ratios (95% confidence intervals) were 0.89 (0.85–0.94) and 0.80 (0.75–0.86) for the A/G and A/A genotypes, respectively, compared with the genotype G/G. SNP rs9383951 ( P  = 1.9Ă—10 â’6 from the combined analysis of all samples), located in intron 5 of the ESR1 gene, and SNP rs7107217 ( P  = 4.6Ă—10 â’7 ), located at 11q24.3, also showed a consistent association in each of the four stages. This study provides strong evidence for a novel breast cancer susceptibility locus represented by rs9485372, near the TAB2 gene (6q25.1), and identifies two possible susceptibility loci located in the ESR1 gene and 11q24.3, respectively. Breast cancer is one of the most common malignancies among women worldwide. Genetic factors play an important role in the etiology of breast cancer. To identify common genetic susceptibility alleles for breast cancer, we performed a four-stage genome-wide association study in 19,091 cases and 20,606 controls among East-Asian women. Single nucleotide polymorphism (SNP) rs9485372, near the TGF-beta activated kinase 1 ( TAB2 ) gene at chromosome 6q25.1, was associated with breast cancer risk ( P  = 3.8Ă—10 â’12 ). SNPs rs9383951, located in intron 5 of the estrogen receptor 1 ( ESR1 ) gene, and rs7107217, located at 11q24.3, were also consistently associated with breast cancer risk in all four stages with a combined P of 1.9Ă—10 â’6 and 4.6Ă—10 â’7 , respectively. This study provides strong evidence for a novel breast cancer susceptibility locus represented by rs9485372, near the TAB2 gene (6q25.1), and identifies two possible susceptibility loci located in the ESR1 gene and 11q24.3, respectively.\n", - "\n" - ] + "data": { + "text/html": [ + "
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conflictscoveragejoverlaps
LF_first_sentence 0.212908 1.992501 0 1.992501
LF_with_acronym 0.022764 0.035083 1 0.027584
LF_from_regex 0.827531 1.375201 2 1.375201
LF_many_words 0.029727 0.115426 3 0.086770
LF_start_of_sentence 0.015801 0.113283 4 0.069363
LF_bad_words 0.562400 1.794322 5 1.794322
LF_short 0.000000 0.000000 6 0.000000
LF_no_nouns 1.387252 5.982860 7 5.982860
LF_not_first_sentences 0.041510 0.326727 8 0.249330
LF_stopwords 8.583289 23.018211 9 23.018211
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10 rows Ă— 4 columns

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" + ], + "text/plain": [ + " conflicts coverage j overlaps\n", + "LF_first_sentence 0.212908 1.992501 0 1.992501\n", + "LF_with_acronym 0.022764 0.035083 1 0.027584\n", + "LF_from_regex 0.827531 1.375201 2 1.375201\n", + "LF_many_words 0.029727 0.115426 3 0.086770\n", + "LF_start_of_sentence 0.015801 0.113283 4 0.069363\n", + "LF_bad_words 0.562400 1.794322 5 1.794322\n", + "LF_short 0.000000 0.000000 6 0.000000\n", + "LF_no_nouns 1.387252 5.982860 7 5.982860\n", + "LF_not_first_sentences 0.041510 0.326727 8 0.249330\n", + "LF_stopwords 8.583289 23.018211 9 23.018211\n", + "\n", + "[10 rows x 4 columns]" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "from extractor.util import gold_agg_phen_recall\n", - "kb = KnowledgeBase()\n", - "id2doc = {doc.name : doc for doc in corpus.documents}\n", - "gold_agg_dict_phen = { doc_id : set() for doc_id, phen_id in gold_set_agg_phens }\n", - "for doc_id, phen_id in gold_set_agg_phens:\n", - " gold_agg_dict_phen[doc_id].add(phen_id)\n", - "\n", - "# this contains (doc_id, gwc_id) pairs from gold_set_agg_phens that haven't been found\n", - "phen_not_found = list(gold_agg_phen_recall(phen_c, gold_set_agg_phens, agg_phen2id))\n", - "print len(phen_not_found)\n", - "for doc_id, phen_id in phen_not_found[:100]:\n", - " if len(gold_agg_dict_phen[doc_id]) > 3: continue # skip if >3 gwc_phen_ids in doc\n", - " print doc_id\n", - " for phen_id2 in gold_agg_dict_phen[doc_id]: # iterate over gwc_id's in doc\n", - " print agg_id2phen[phen_id2].name, phen_id2 # print its name and id\n", - " for eq_phen in agg_id2phen[phen_id2].equivalents: # loop over equivalent phens\n", - " print '\\t', eq_phen.name, eq_phen.ontology_ref, eq_phen.synonyms # print name, ref, synonyms\n", - " print agg_id2phen[phen_id].name # print the one that we haven't found\n", - " print ' '.join(s.text for s in id2doc[doc_id].sentences)\n", - " print" + "L_train.lf_stats()" ] }, { - "cell_type": "code", - "execution_count": 85, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[u'Genome-wide', u'association', u'study', u'identifies', u'multiple', u'susceptibility', u'loci', u'for', u'pulmonary', u'fibrosis', u'.']\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "print id2doc[doc_id].sentences[0].words" + "### Training machine learning models" ] }, { - "cell_type": "code", - "execution_count": 89, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Sentence(Document('23583980', Corpus (GWAS Corpus)), 0, u'Genome-wide association study identifies multiple susceptibility loci for pulmonary fibrosis.')\n", - "Genome-wide association study identifies multiple susceptibility loci\n", - "Genome-wide association study identifies multiple susceptibility loci genom wide associ studi identifi multipl suscept loci\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "association study identifies multiple susceptibility loci for\n", - "association study identifies multiple susceptibility loci for associ studi identifi multipl suscept loci for\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "study identifies multiple susceptibility loci for pulmonary\n", - "study identifies multiple susceptibility loci for pulmonary studi identifi multipl suscept loci for pulmonari\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "identifies multiple susceptibility loci for pulmonary fibrosis\n", - "identifies multiple susceptibility loci for pulmonary fibrosis identifi multipl suscept loci for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "multiple susceptibility loci for pulmonary fibrosis.\n", - "multiple susceptibility loci for pulmonary fibrosis. multipl suscept loci for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "Genome-wide association study identifies multiple susceptibility\n", - "Genome-wide association study identifies multiple susceptibility genom wide associ studi identifi multipl suscept\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "association study identifies multiple susceptibility loci\n", - "association study identifies multiple susceptibility loci associ studi identifi multipl suscept loci\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "study identifies multiple susceptibility loci for\n", - "study identifies multiple susceptibility loci for studi identifi multipl suscept loci for\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "identifies multiple susceptibility loci for pulmonary\n", - "identifies multiple susceptibility loci for pulmonary identifi multipl suscept loci for pulmonari\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "multiple susceptibility loci for pulmonary fibrosis\n", - "multiple susceptibility loci for pulmonary fibrosis multipl suscept loci for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "susceptibility loci for pulmonary fibrosis.\n", - "susceptibility loci for pulmonary fibrosis. suscept loci for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "Genome-wide association study identifies multiple\n", - "Genome-wide association study identifies multiple genom wide associ studi identifi multipl\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "association study identifies multiple susceptibility\n", - "association study identifies multiple susceptibility associ studi identifi multipl suscept\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "study identifies multiple susceptibility loci\n", - "study identifies multiple susceptibility loci studi identifi multipl suscept loci\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "identifies multiple susceptibility loci for\n", - "identifies multiple susceptibility loci for identifi multipl suscept loci for\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "multiple susceptibility loci for pulmonary\n", - "multiple susceptibility loci for pulmonary multipl suscept loci for pulmonari\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "susceptibility loci for pulmonary fibrosis\n", - "susceptibility loci for pulmonary fibrosis suscept loci for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "loci for pulmonary fibrosis.\n", - "loci for pulmonary fibrosis. loci for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "Genome-wide association study identifies\n", - "Genome-wide association study identifies genom wide associ studi identifi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "association study identifies multiple\n", - "association study identifies multiple associ studi identifi multipl\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "study identifies multiple susceptibility\n", - "study identifies multiple susceptibility studi identifi multipl suscept\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "identifies multiple susceptibility loci\n", - "identifies multiple susceptibility loci identifi multipl suscept loci\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "multiple susceptibility loci for\n", - "multiple susceptibility loci for multipl suscept loci for\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "susceptibility loci for pulmonary\n", - "susceptibility loci for pulmonary suscept loci for pulmonari\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "loci for pulmonary fibrosis\n", - "loci for pulmonary fibrosis loci for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "for pulmonary fibrosis.\n", - "for pulmonary fibrosis. for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "Genome-wide association study\n", - "Genome-wide association study genom wide associ studi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "association study identifies\n", - "association study identifies associ studi identifi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "study identifies multiple\n", - "study identifies multiple studi identifi multipl\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "identifies multiple susceptibility\n", - "identifies multiple susceptibility identifi multipl suscept\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "multiple susceptibility loci\n", - "multiple susceptibility loci multipl suscept loci\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "susceptibility loci for\n", - "susceptibility loci for suscept loci for\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "loci for pulmonary\n", - "loci for pulmonary loci for pulmonari\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "for pulmonary fibrosis\n", - "for pulmonary fibrosis for pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "pulmonary fibrosis.\n", - "pulmonary fibrosis. pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "Genome-wide association\n", - "Genome-wide association genom wide associ\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "association study\n", - "association study associ studi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "study identifies\n", - "study identifies studi identifi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "identifies multiple\n", - "identifies multiple identifi multipl\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "multiple susceptibility\n", - "multiple susceptibility multipl suscept\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "susceptibility loci\n", - "susceptibility loci suscept loci\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "loci for\n", - "loci for loci for\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "for pulmonary\n", - "for pulmonary for pulmonari\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "pulmonary fibrosis\n", - "pulmonary fibrosis pulmonari fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "fibrosis.\n", - "fibrosis. fibrosi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "Genome-wide\n", - "Genome-wide genom wide\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "association\n", - "association associ\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "study\n", - "study studi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "identifies\n", - "identifies identifi\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "multiple\n", - "multiple multipl\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "susceptibility\n", - "susceptibility suscept\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "loci\n", - "loci loci\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "for\n", - "for for\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "pulmonary\n", - "pulmonary pulmonari\n", - "... False False False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - "fibrosis\n", - "fibrosis fibrosi\n", - "... True True False False False\n", - "None\n", - "23583980 None\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n", - ".\n", - ". \n", - "... False False True False True\n", - "http://www.ebi.ac.uk/efo/EFO_0006918\n", - "23583980 http://www.ebi.ac.uk/efo/EFO_0006918\n", - "set([u'http://www.ebi.ac.uk/efo/EFO_0004244'])\n", - "\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "# FOR DEBUGGING WHY SPANS ARENT MATCHED\n", - "from extractor.util import change_name\n", + "So far, we have defined a set of noisy labeling functions that are indicative of each mention being true or false. Next, we use data programming to train a noise-aware generative model that can estimate the accuracies of these labeling functions from data in an unsupervised manner.\n", "\n", - "doc_id = '23583980'\n", - "ngrams = Ngrams(n_max=7)\n", - "print id2doc[doc_id].sentences[0]\n", - "for span in ngrams.apply(id2doc[doc_id].sentences[0]):\n", - " print span.get_span()\n", - " if phen_matcher._f(span): \n", - " phen_name = span.get_span()\n", - " print phen_name, change_name(phen_name)\n", - " print '...', phen_name == 'fibrosis', phen_name in phenotype_list, change_name(phen_name) in phenotype_list, phen_name in efo_phen_matcher.d, change_name(phen_name) in efo_phen_matcher.d\n", - " phen_id = phen2id.get(change_name(phen_name), None)\n", - " print phen_id\n", - " if not phen_id or phen_id not in gold_dict_phen[span.context.document.name]:\n", - " print span.context.document.name, phen_id\n", - " print gold_dict_phen[span.context.document.name]\n", - " \n", - " print" + "The resulting model can be used to provide a learning signal for a second discriminative model (as described in the data programming paper), or it can be used to make predictions directly. Here, we will follow the latter approach." ] }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 62, "metadata": { "collapsed": false }, @@ -1382,55 +790,72 @@ "name": "stdout", "output_type": "stream", "text": [ - "[u'cd8_alpha-negative plasmactyoid dendritic cell', u'alpha-hydro-omega-hydroxypoly(oxyethylene)', u'ajmalan-17alpha', u'(-)-(s)-alpha-ethyl-2-oxo-1-pyrrolidineacetamide', u'alpha-l-fucosidase deficiency', u'branched chain alpha-ketoacid dehydrogenase complex deficiency', u'tumor necrosis factor-alpha', u'primary alpha-dystroglycanopathy', u'alpha-thalassemia - x-linked intellectual disability syndrome', u' alpha-beta intraepithelial t cell', u'alpha-n-acetylgalactosaminidase deficiency', u'(3alpha', u'cd8-alpha-beta-positive', u'l-alpha-acetamido-beta-mercaptopropionic acid', u'fc-epsilon rialpha-high basophil progenitor cell', u'cd8_alpha-positive cd11b-negative dendritic cell', u'alpha globulin measurement', u'hyperphenylalaninemia due to pterin-4-alpha-carbinolamine dehydratase deficiency', u'alpha-tocopherol metabolic process', u'(22s)-5alpha-campestane-3beta', u'(s)-(+)-alpha-amino-4-carboxy-2-methylbenzeneacetic', u't-b+ scid due to il-7ralpha deficiency', u'cd8alpha-negative thymic conventional dendritic cell', u'alpha-b crystallin-related late-onset distal myopathy', u'mature alpha-beta t cell', u'hemorrhagic disease due to alpha-1-antitrypsin pittsburgh mutation', u'alpha mating type (yeast)', u'alpha-phthalimidoglutarimide', u'dl-alpha-tocopherol', u'(s)-alpha-methyl-4-carboxyphenylglycine', u'interleukin-2 receptor alpha chain deficiency', u'3-(alpha-phenyl-beta-acetylethyl)-4-hydroxycoumarin', u'immature cd8_alpha-positive cd11b-negative dendritic cell', u'3-carboxamido-4-hydroxy-alpha-((1-methyl-3-phenylpropylamino)methyl)benzyl alcohol', u'pyruvate dehydrogenase e1-alpha deficiency', u'familial hypoalphalipoproteinemia', u'qualitative or quantitative defects of alpha-actin', u'alpha-methyl-p-tyrosine', u'17alpha-ethynylestradiol', u'mating_type_alpha', u'congenital adrenal hyperplasia due to 17-alpha-hydroxylase deficiency', u'hereditary persistence of alpha-fetoprotein', u'hereditary renal amyloidosis due to fibrinogen a alpha-chain variant', u'3-(alpha-acetonyl-p-nitrobenzyl)-4-hydroxycoumarin', u'analphalipoproteinemia', u'(s)-alpha-methyl-4-(2-methylpropyl)benzeneacetic acid', u'alpha-naphthaleneacetic acid', u'(s)-6-methoxy-alpha-methyl-2-naphthaleneacetic acid', u'7alpha-{9-[(4', u'alpha-adrenergic receptor blockaders', u'(alphae)-2-[[6-(2-cyanophenoxy)-4-pyrimidinyl]oxy]-alpha-(methoxymethylene) benzeneacetic acid methyl ester', u'(5alpha', u'3-(alpha-acetonyl-4-nitrobenzyl)-4-hydroxycoumarin', u'alpha granule disease', u'alpha cell', u'7 alpha-hydroxy-4-cholesten-3-one 12-alpha-hydroxylase', u' cd8_alpha-negative', u'tumor necrosis factor-alpha measurement', u'alpha-adrenergic agonist', u'streptomyces griseus subsp. alpha', u'qualitative or quantitative defects of integrin alpha-7', u'immature alpha-beta t cell', u'hereditary amyloid nephropathy due to fibrinogen a alpha-chain variant', u'n-(alpha', u'alpha-thalassemia major', u'mating type alpha', u'17alpha-methyl-delta(4)-androsten-17beta-ol-3-one', u'n-[(1s)-1-(dihydroxyboranyl)-3-methylbutyl]-n(alpha)-(pyrazin-2-ylcarbonyl)-d-phenylalaninamide', u'1-(o-chloro-alpha', u'alpha-1', u'17alpha-estradiol', u'cd8_alpha-positive plasmactyoid dendritic cell', u'n-acetyl-alpha-glucosaminidase deficiency', u' alpha-beta cytokine secreting effector t cell', u'alpha-butylene', u'3-(alpha-p-nitrophenyl-beta-acetylethyl)-4-hydroxycoumarin', u'[2r-(2alpha', u'gamma-diisopropylamino-alpha-phenyl-alpha-(2-pyridyl)butyramide', u'tcr-alpha-beta+ t-cell deficiency', u'immature cd8_alpha-negative cd11b-positive dendritic cell', u'l-alpha-methyltyrosine', u'17alpha-ethynylestra-1', u'qualitative or quantitative defects of protein involved in o-glycosylation of alpha-dystroglycan', u'secondary alpha-dystroglycanopathy', u'interferon alpha', u'alphavirus infections', u'(rs)-4-hydroxy-alpha(1)-({[6-(4-phenylbutoxy)hexyl]amino}methyl)-1', u'4-alpha-hydroxyphenylpyruvate hydroxylase deficiency', u'alpha dense granule deficiency', u'alpha peak frequency measurement', u'l-histidylglycyl-l-alpha-glutamylglycyl-l-threonyl-l-phenylalanyl-l-threonyl-l-seryl-l-alpha-aspartyl-l-leucyl-l-seryl-l-lysyl-l-glutaminyl-l-methionyl-l-alpha-glutamyl-l-alpha-glutamyl-l-alpha-glutamyl-l-alanyl-l-valyl-l-arginyl-l-leucyl-l-phenylalanyl-l-isoleucyl-l-alpha-glutamyl-l-tryptophyl-l-leucyl-l-lysyl-l-asparaginylglycylglycyl-l-prolyl-l-seryl-l-serylglycyl-l-alanyl-l-prolyl-l-prolyl-l-prolyl-l-serinamide', u'qualitative or quantitative defects of alpha-sarcoglycan', u'lysosomal alpha-d-mannosidase deficiency', u'heparan-alpha-glucosaminide n-acetyltransferase deficiency', u'alpha-1-antitrypsin deficiency (disorder)', u'alpha-thalassemia - myelodysplastic syndrome', u'alpha-methyl-acetoacetyl-coa thiolase deficiency', u'mature cd8_alpha-negative cd11b-negative dendritic cell', u'cd8alpha-positive thymic conventional dendritic cell', u'platelet alpha-granule deficiency', u'alpha-ketopropionaldehyde', u'alpha-methyldopa', u'familial amyloid nephropathy due to fibrinogen a alpha-chain variant', u'(s)-(-)-alpha-ethyl-2-oxo-1-pyrrolidineacetamide', u'hypoalphalipoproteinemia', u'17(alpha)-methyl-delta(4)-androsten-17(beta)-ol-3-one', u'3-(alpha-(p-nitrophenol)-beta-acetylethyl)-4-hydroxycoumarin', u'alpha-adrenergic antagonists', u'mature cd8_alpha-negative cd11b-positive dendritic cell', u'alpha-methyltyrosine', u'(24r)-5alpha-ergostan-3beta-ol', u'4-androstene-17alpha-methyl-17beta-ol-3-one', u'alpha-methyl-beta-(3', u' alpha-beta cytotoxic t cell', u'disorder of peroxisomal alpha-', u'congenital disorder of glycosylation due to steroid 5alpha-reductase type 3 deficiency', u'(2s-(2alpha', u'oxysterol 7-alpha-hydroxylase deficiency', u'immature cd8_alpha-negative cd11b-negative dendritic cell', u'serum alpha-1-antitrypsin measurement', u\"3-(alpha-(4'-nitrophenyl)-beta-acetylethyl)-4-hydroxycoumarin\", u'alpha lipoprotein cholesterol', u'alpha-thalassemia and related diseases', u'adult-onset alpha-n-acetylgalactosaminidase deficiency', u'qualitative or quantitative defects of alphab-cristallin', u'alpha-thalassemia - intellectual disability syndrome linked to chromosome 16', u'(2alpha', u'pregnenolone 16alpha-carbonitrile', u'mature cd8_alpha-positive cd11b-negative dendritic cell', u'congenital muscular alpha-dystroglycanopathy with brain and eye anomalies', u'5alpha-dihydrotestosterone', u'1-dehydro-16alpha-methyl-9alpha-fluorohydrocortisone', u'alpha-thalassemia hydrops fetalis', u'bleeding diathesis due to integrin alpha2-beta1 deficiency', u'bilirubin ixalpha', u'alpha-1-antichymotrypsin deficiency', u'obsolete_alpha-1-antitrypsin deficiency', u'alpha thalassemia - retardation syndrome', u'(-)-alpha-methyl-l-tyrosine', u'congenital muscular dystrophy with integrin alpha-7 deficiency', u'interferon alpha measurement', u'familial hyperalphalipoproteinemia', u'alpha-l-iduronidase deficiency', u'alpha-1-antitrypsin def', u'cd8_alpha-low langerhans cell', u'alpha-amino-gamma-methylmercaptobutyric acid', u'fc-epsilon rialpha-low mast cell progenitor', u'soluble interleukin-2 receptor subunit alpha measurement', u'l-seryl-l-tyrosyl-l-seryl-l-methionyl-l-alpha-glutamyl-l-histidyl-l-phenylalanyl-l-arginyl-l-tryptophylglycyl-l-lysyl-l-prolyl-l-valylglycyl-l-lysyl-l-lysyl-l-arginyl-l-arginyl-l-prolyl-l-valyl-l-lysyl-l-valyl-l-tyrosyl-l-prolyl-l-alpha-aspartylglycyl-l-alanyl-l-alpha-glutamyl-l-alpha-aspartyl-l-alpha-glutamyl-l-seryl-l-alanyl-l-alpha-glutamyl-l-alanyl-l-phenylalanyl-l-prolyl-l-leucyl-l-alpha-glutamyl-l-phenylalanine', u'cd8-alpha-alpha-positive', u'cah due to 17-alpha-hydroxylase deficiency', u' alpha-beta regulatory t cell', u'immature cd8_alpha-low langerhans cell', u'susceptibility to respiratory infections associated with cd8alpha chain mutation', u'sterol 12 alpha hydroxylase', u'tcr-alpha-beta-positive t-cell deficiency', u'alpha-n-acetylgalactosaminidase deficiency type 2', u'alpha-crystallinopathy', u'alpha wave measurement', u'primary qualitative or quantitative defects of alpha-dystroglycan', u'steroid 12-alpha-hydroxylase', u'(s)-alpha-ethyl-2-oxo-1-pyrrolidineacetamide', u'hypercholesterolemia due to cholesterol 7alpha-hydroxylase deficiency', u'alpha macroglobulin measurement', u' alpha-beta thymocyte', u'(alphas)-n', u'alpha-thalassemia', u'17alpha-ethinyl estradiol', u'congenital deficiency in alpha-fetoprotein', u'alpha-beta t cell', u'alpha-tocopherol metabolism', u'alpha-(p-chlorophenoxy)isobutyric acid', u'alpha-methyl-l-p-tyrosine', u'alpha-naphthyl n-methylcarbamate', u'alpha-methyl-acyl-coa racemase deficiency', u'qualitative or quantitative defects of alpha-dystroglycan', u'lysine alpha-ketoglutarate reductase deficiency', u'alpha-amanitin', u'alpha-methyl-l-dopa', u'7-amino-9alpha-methoxymitosane', u'alpha-thalassemia-related diseases', u'alpha delta granule deficiency', u'(+-)-n-methyl-3-phenyl-3-((alpha', u'hyperalphalipoproteinemia', u'alpha-d-glucose', u'17alpha-methyltestosterone', u'1-dehydro-6alpha-methylhydrocortisone', u't-b+ severe combined immunodeficiency due to il-7ralpha deficiency', u'xy disorder of sex development due to 5-alpha-reductase 2 deficiency', u'alpha-n-acetylgalactosaminidase deficiency type 1', u'alpha-n-acetylgalactosaminidase deficiency type 3', u'alpha-naphthyl isothiocyanate', u'6-(p-hydroxy-alpha-aminophenylacetamido)penicillanic acid', u'alpha-dystroglycanopathy', u'l-alpha-pyrrolidinecarboxylic acid', u\"(5'alpha)-2-bromo-12'-hydroxy-5'-isobutyl-2'-isopropyl-3'\", u'delta(1)-6alpha-methylhydrocortisone', u'17alpha-methyl-3-oxo-4-androsten-17beta-ol', u'alpha-adrenergic blockers', u'vgamma5-positive cd8alpha alpha positive gamma-delta intraepithelial t cell', u'17beta-hydroxy-5alpha-androstan-3-one', u'(s)-(+)-alpha-methyl-4-carboxyphenylglycine', u'fibrinogen a alpha-chain amyloidosis', u'tnf-alpha; tumor necrosis factor', u'alpha-sarcoglycanopathy', u'alpha-p-chlorophenoxyisobutyryl ethyl ester', u'alpha-(4-chlorophenoxy)-alpha-methylpropionic acid', u'alpha-aminoadipic aciduria', u' alpha-beta t cell', u'alpha-galactosidase a deficiency', u'alphavirus infectious disease', u'streptomyces griseus subsp. alpha (ciferri 1927) pridham 1970 (approved lists 1980)', u'6alpha-methylprednisolone', u'(+)-alpha-tocopherol', u'alpha-(2-(diisopropylamino)ethyl)-alpha-phenyl-2-pyridineacetamide', u'alpha', u'alpha-methyl-l-tyrosine', u'homozygous alpha0-thalassemia', u'mature cd8_alpha-low langerhans cell', u'alpha-thalassemia intermedia', u'alpha-beta intraepithelial t cell', u'cd8-alpha alpha positive', u'alpha-adrenoceptor antagonists', u'alpha-mannosidosis', u'(e)-(+-)-beta-((4-chlorophenyl)methylene)-alpha-(1', u'alpha-ketoglutarate dehydrogenase deficiency', u'(s)-(alpha)-methyl-4-carboxyphenylglycine', u'alpha-kainic acid', u'5alpha-campestan-3beta-ol', u'alpha-tocopherol', u'familial renal amyloidosis due to fibrinogen a alpha-chain variant', u'interferon alpha 2a', u'(s)-alpha-methyltyrosine', u'(+)-(s)-6-methoxy-alpha-methyl-2-naphthaleneacetic acid', u'(s)-alpha-amino-5-fluoro-3', u'alpha-methylguanidino acetic acid', u'congenital alpha2 antiplasmin deficiency', u'cd8_alpha-negative cd11b-negative dendritic cell', u'alpha 1-antitrypsin deficiency', u'1-alpha-hydroxylase deficiency', u'alpha-methyl-para-tyrosine', u'pancreatic alpha cell', u'alpha-adrenergic blocker', u'alpha-butene', u' alpha-beta memory t cell', u'(+)-alpha-methyl-4-carboxyphenylglycine', u'alpha-amino-beta-phenylpropionic acid', u'alpha-adrenergic antagonist', u'alpha-lipoprotein cholesterol', u'cytochrome p450 subfamily viiib (sterol 12-alpha-hydroxylase) polypeptide 1', u'alpha-1-antitrypsin deficiency', u'congenital muscular dystrophy due to laminin alpha2 deficiency', u'alpha storage pool deficiency', u'vgamma5-negative cd8alpha alpha positive gamma-delta intraepithelial t cell', u'limb-girdle muscular dystrophy due to alpha-sarcoglycan deficiency', u'pyruvate dehydrogenase complex e1 component subunit alpha deficiency']\n", - "[u'alpha chain defici', u'due to cholesterol 7alpha hydroxylas defici', u'dehydrogenas e1 alpha defici', u'4 alpha hydroxyphenylpyruv hydroxylas defici', u'alphaviru infecti diseas', u'hereditari amyloid nephropathi due to fibrinogen a alpha chain', u'alpha 2 6 2 cyanophenoxi 4 pyrimidinyloxi alpha methoxymethylen benzeneacet acid', u'disord of sex develop due to 5 alpha reductas 2 defici', u'protein involv in o glycosyl of alpha dystroglycan', u'congenit muscular alpha dystroglycanopathi with brain and', u'adren hyperplasia due to 17 alpha hydroxylas', u'amyloid nephropathi due to fibrinogen a alpha chain variant', u'matur cd8alpha neg cd11b neg dendrit cell', u'alpha thalassemia hydrop fetali', u'to alpha sarcoglycan defici', u'to respiratori infect associ with cd8alpha chain mutat', u'or quantit defect of protein involv in o glycosyl of alpha dystroglycan', u'alpha beta intraepitheli t', u'alpha thalassemia myelodysplast', u'sterol 12 alpha hydroxylas', u'p450 subfamili viiib sterol 12 alpha hydroxylas polypeptid 1', u'alpha b crystallin relat late onset distal', u'or quantit defect of integrin alpha 7', u'congenit alpha2 antiplasmin', u'diathesi due to integrin alpha2 beta1 defici', u'to laminin alpha2', u'interleukin 2 receptor alpha chain defici', u'to cholesterol 7alpha hydroxylas defici', u'congenit muscular alpha dystroglycanopathi with brain and eye', u'alpha amino gamma methylmercaptobutyr acid', u'famili hypoalphalipoproteinemia', u'serum alpha 1 antitrypsin', u'glycosyl due to steroid 5alpha reductas', u'fibrinogen a alpha chain', u'fc epsilon rialpha low mast', u'due to pterin 4 alpha carbinolamin dehydratas defici', u'amyloidosi due to fibrinogen a alpha chain variant', u'5alpha reductas type 3 defici', u'alpha adrenerg antagonist', u'of integrin alpha 7', u'cd8alpha neg thymic convent dendrit cell', u'tcr alpha beta t cell defici', u'streptomyc griseu subsp alpha ciferri 1927 pridham 1970', u'12 alpha hydroxylas polypeptid 1', u'due to steroid 5alpha reductas type', u'with cd8alpha chain mutat', u'quantit defect of protein involv in o glycosyl of alpha dystroglycan', u'associ with cd8alpha', u'due to steroid 5alpha reductas type 3 defici', u'immatur cd8alpha neg cd11b posit', u'matur alpha beta t cell', u'or quantit defect of alpha dystroglycan', u'vgamma5 neg cd8alpha alpha posit gamma delta intraepitheli t', u's alpha ethyl 2 oxo 1 pyrrolidineacetamid', u'alpha storag pool defici', u'cd8alpha neg plasmactyoid dendrit cell', u'combin immunodefici due to il 7ralpha defici', u'alpha thalassemia intellectu disabl syndrom link', u'cd8alpha neg cd11b neg dendrit', u'to steroid 5alpha reductas', u'bleed diathesi due to integrin alpha2 beta1', u'homozyg alpha0 thalassemia', u'matur cd8alpha posit cd11b neg dendrit cell', u'alpha methyl 4 carboxyphenylglycin', u'rs 4 hydroxi alpha1 6 4 phenylbutoxyhexylaminomethyl 1', u'qualit or quantit defect of alpha sarcoglycan', u'alpha beta t cell', u'xy disord of sex develop due to 5 alpha reductas', u'alpha dystroglycanopathi with brain', u'alpha thalassemia and relat', u'famili renal amyloidosi due to fibrinogen a alpha chain variant', u'alpha thalassemia', u'alpha 1 antitrypsin pittsburgh mutat', u'quantit defect of alpha dystroglycan', u'due to alpha 1 antitrypsin', u'cd8alpha posit thymic convent dendrit cell', u'respiratori infect associ with cd8alpha', u'diseas due to alpha 1 antitrypsin pittsburgh', u'quantit defect of alphab cristallin', u'immunodefici due to il 7ralpha defici', u'or quantit defect of alpha actin', u'suscept to respiratori infect associ with cd8alpha', u'cd8alpha alpha posit gamma delta', u'immatur cd8alpha neg cd11b neg dendrit cell', u'dehydrogenas complex e1 compon subunit alpha defici', u'immatur cd8alpha neg cd11b neg dendrit', u'renal amyloidosi due to fibrinogen a alpha chain', u'3 carboxamido 4 hydroxi alpha 1 methyl 3 phenylpropylaminomethylbenzyl alcohol', u'pterin 4 alpha carbinolamin dehydratas defici', u'of protein involv in o glycosyl of alpha dystroglycan', u'l histidylglycyl l alpha glutamylglycyl l threonyl l phenylalanyl l threonyl l seryl l alpha aspartyl l leucyl l seryl l lysyl l glutaminyl l methionyl l alpha glutamyl l alpha glutamyl l alpha glutamyl l alanyl l valyl l arginyl l leucyl l phenylalanyl l isoleucyl l alpha glutamyl l tryptophyl l leucyl l lysyl l asparaginylglycylglycyl l prolyl l seryl l serylglycyl l alanyl l prolyl l prolyl l prolyl l serinamid', u'matur cd8alpha low langerhan cell', u'3 alpha acetonyl 4 nitrobenzyl 4 hydroxycoumarin', u'diseas due to alpha 1 antitrypsin pittsburgh mutat', u'alpha methyl l p tyrosin', u't b scid due to il 7ralpha defici', u'diathesi due to integrin alpha2 beta1', u'tnf alpha tumor necrosi', u'alpha posit gamma delta intraepitheli t', u'sex develop due to 5 alpha reductas 2', u'12 alpha hydroxylas', u'muscular dystrophi with integrin alpha 7', u'disord of glycosyl due to steroid 5alpha reductas', u'due to alpha 1 antitrypsin pittsburgh', u'oxysterol 7 alpha hydroxylas defici', u'of peroxisom alpha', u'alpha ketoacid dehydrogenas complex defici', u'due to integrin alpha2 beta1 defici', u't b sever combin immunodefici due to il 7ralpha', u'alpha galactosidas a defici', u'alpha ketoglutar dehydrogenas defici', u'alpha naphthaleneacet acid', u'hypoalphalipoproteinemia', u'famili amyloid nephropathi due to fibrinogen a alpha chain', u'ciferri 1927 griseu subsp alpha', u'or quantit defect of alpha sarcoglycan', u'alpha delta granul defici', u'lysin alpha ketoglutar reductas', u'alpha 2 diisopropylaminoethyl alpha phenyl 2 pyridineacetamid', u's alpha methyltyrosin', u'to 5 alpha reductas 2', u'griseu subsp alpha ciferri 1927 pridham 1970 approv', u'quantit defect of integrin alpha 7', u'congenit muscular alpha dystroglycanopathi with brain and eye anomali', u'alpha mate type', u'chain alpha ketoacid dehydrogenas complex defici', u'alpha dystroglycanopathi with brain and eye', u'hypercholesterolemia due to cholesterol 7alpha hydroxylas', u'alpha methyl l dopa', u'alpha crystallinopathi', u'a alpha chain variant', u'glycosyl due to steroid 5alpha reductas type', u'disord of glycosyl due to steroid 5alpha reductas type 3', u'griseu subsp alpha ciferri', u'chain alpha ketoacid dehydrogenas complex', u'22 5alpha campestan 3beta', u'vgamma5 neg cd8alpha alpha posit gamma delta intraepitheli t cell', u's alpha methyl 4 2 methylpropylbenzeneacet acid', u'e beta 4 chlorophenylmethylen alpha 1', u'complex e1 compon subunit alpha defici', u'due to 5 alpha reductas 2', u'receptor alpha chain', u'alpha thalassemia x link', u'respiratori infect associ with cd8alpha chain mutat', u's 6 methoxi alpha methyl 2 naphthaleneacet acid', u'cd8alpha neg cd11b posit dendrit', u'to cholesterol 7alpha hydroxylas', u'alpha beta cytotox t', u'l alpha pyrrolidinecarboxyl acid', u'to 17 alpha hydroxylas defici', u'subfamili viiib sterol 12 alpha hydroxylas polypeptid 1', u'alpha beta memori t cell', u'hyperplasia due to 17 alpha hydroxylas', u'limb girdl muscular dystrophi due to alpha sarcoglycan defici', u'matur cd8alpha low langerhan', u'1 dehydro 16alpha methyl 9alpha fluorohydrocortison', u'congenit muscular alpha dystroglycanopathi with', u'ciferri 1927 alpha', u'or quantit defect of alphab cristallin', u'subfamili viiib sterol 12 alpha hydroxylas polypeptid', u'griseu subsp alpha ciferri 1927 pridham 1970 approv list', u'sex develop due to 5 alpha reductas', u'branch chain alpha ketoacid dehydrogenas complex', u'cd8alpha chain mutat', u'cd8alpha neg plasmactyoid dendrit', u'solubl interleukin 2 receptor subunit alpha', u'integrin alpha 7 defici', u't b scid due to il 7ralpha', u'matingtypealpha', u'alpha p chlorophenoxyisobutyryl ethyl ester', u'dystrophi with integrin alpha 7 defici', u'6alpha methylprednisolon', u'3 alpha p nitrophenol beta acetylethyl 4 hydroxycoumarin', u'defici in alpha fetoprotein', u'muscular alpha dystroglycanopathi with brain and', u'alpha storag pool', u'cd8 alpha beta posit', u'alpha naphthyl n methylcarbam', u'secondari alpha dystroglycanopathi', u'amyloidosi due to fibrinogen a alpha chain', u'alpha mannosidosi', u'approv list 1980 subsp alpha ciferri 1927 pridham 1970', u'alpha aminoadip aciduria', u'alpha beta cytokin secret effector t', u'approv list 1980 alpha ciferri 1927 pridham 1970', u'2s 2alpha', u'congenit adren hyperplasia due to 17 alpha hydroxylas', u'17beta hydroxi 5alpha androstan 3 one', u'tnf alpha tumor necrosi factor', u'alpha thalassemia intellectu disabl syndrom link to chromosom 16', u'streptomyc griseu subsp alpha ciferri', u'xy disord of sex develop due to 5 alpha reductas 2 defici', u'congenit adren hyperplasia due to 17 alpha hydroxylas defici', u'alpha adrenoceptor antagonist', u'alpha ciferri 1927 pridham 1970', u'sterol 12 alpha', u'alpha thalassemia and relat diseas', u'2r 2alpha', u'alpha adrenerg blocker', u'alpha wave', u'alpha 1 antitrypsin defici', u'alpha methyl l tyrosin', u'to laminin alpha2 defici', u'due to 17 alpha hydroxylas', u'lysin alpha ketoglutar reductas defici', u'griseu subsp alpha', u'gamma diisopropylamino alpha phenyl alpha 2 pyridylbutyramid', u'dystrophi due to laminin alpha2 defici', u'of sex develop due to 5 alpha reductas', u'alpha sarcoglycanopathi', u'nephropathi due to fibrinogen a alpha chain variant', u'alpha ketoacid dehydrogenas complex', u'5alpha 2 bromo 12 hydroxi 5 isobutyl 2 isopropyl 3', u'alpha n acetylgalactosaminidas defici type 2', u'alpha n acetylgalactosaminidas defici type 3', u'alpha n acetylgalactosaminidas defici type 1', u'hemorrhag diseas due to alpha 1 antitrypsin', u'immunodefici due to il 7ralpha', u'hyperalphalipoproteinemia', u'defect of protein involv in o glycosyl of alpha dystroglycan', u'primari qualit or quantit defect of alpha dystroglycan', u'scid due to il 7ralpha', u'alpha thalassemia intellectu disabl', u'muscular dystrophi due to laminin alpha2', u'due to 17 alpha hydroxylas defici', u'renal amyloidosi due to fibrinogen a alpha chain variant', u'subsp alpha ciferri 1927 pridham', u'sterol 12 alpha hydroxylas viiib', u'vgamma5 posit cd8alpha alpha posit gamma delta intraepitheli', u'dl alpha tocopherol', u'branch chain alpha ketoacid dehydrogenas complex defici', u'cd8alpha posit thymic convent dendrit', u'with integrin alpha 7', u'sterol 12 alpha hydroxylas subfamili viiib', u'5alpha', u'o glycosyl of alpha dystroglycan', u'3 alpha p nitrophenyl beta acetylethyl 4 hydroxycoumarin', u'necrosi factor alpha', u'alpha dens granul defici', u'interleukin 2 receptor subunit alpha', u'alpha posit gamma delta intraepitheli t cell', u'alpha thalassemia x link intellectu disabl syndrom', u'alpha p chlorophenoxyisobutyr acid', u'associ with cd8alpha chain mutat', u'alpha beta intraepitheli t cell', u'alpha b crystallin relat late onset distal myopathi', u'24r 5alpha ergostan 3beta ol', u'muscular dystrophi due to laminin alpha2 defici', u'qualit or quantit defect of integrin alpha 7', u'qualit or quantit defect of alphab cristallin', u'alpha', u'infect associ with cd8alpha', u'defect of alphab cristallin', u'alpha thalassemia intellectu disabl syndrom link to', u'of sex develop due to 5 alpha reductas 2 defici', u'muscular alpha dystroglycanopathi with brain and eye anomali', u'fc epsilon rialpha high basophil progenitor cell', u'sever combin immunodefici due to il 7ralpha defici', u'scid due to il 7ralpha defici', u'pyruv dehydrogenas complex e1 compon subunit alpha defici', u'alpha delta granul', u'cah due to 17 alpha hydroxylas', u'alpha methyl acetoacetyl coa thiolas defici', u'alpha butylen', u'alpha tocopherol metabol process', u'to alpha 1 antitrypsin pittsburgh', u'alpha ketoglutar reductas defici', u'with integrin alpha 7 defici', u'5alpha campestan 3beta ol', u'vgamma5 neg cd8alpha alpha posit gamma delta intraepitheli', u'cd8alpha neg cd11b posit dendrit cell', u'interferon alpha 2a', u'in o glycosyl of alpha dystroglycan', u'hemorrhag diseas due to alpha 1 antitrypsin pittsburgh', u'vgamma5 neg cd8alpha alpha', u'immatur cd8alpha low langerhan', u'immatur alpha beta t', u'alpha beta thymocyt', u'to integrin alpha2 beta1', u'pancreat alpha cell', u'7alpha 9 4', u'alpha methyltyrosin', u'due to steroid 5alpha reductas type 3', u'alpha 2 6 2 cyanophenoxi 4 pyrimidinyloxi alpha methoxymethylen benzeneacet acid methyl', u'17alpha ethynylestradiol', u'laminin alpha2 defici', u'vgamma5 posit cd8alpha alpha posit', u'6 p hydroxi alpha aminophenylacetamidopenicillan acid', u'alpha posit gamma delta', u'immatur cd8alpha neg cd11b neg', u'vgamma5 posit cd8alpha alpha posit gamma delta intraepitheli t cell', u'muscular dystrophi due to alpha sarcoglycan', u'alpha dystroglycanopathi', u'sterol 12 alpha hydroxylas polypeptid 1', u'integrin alpha2 beta1 defici', u'dehydrogenas complex e1 compon subunit alpha', u'17alpha methyl delta4 androsten 17beta ol 3 one', u'alpha hydro omega hydroxypolyoxyethylen', u'immatur cd8alpha posit cd11b neg', u'compon subunit alpha', u'alpha macroglobulin', u'vgamma5 posit cd8alpha alpha', u'immatur alpha beta t cell', u'muscular dystrophi due to alpha sarcoglycan defici', u'a alpha chain amyloidosi', u'rialpha high basophil progenitor', u'alpha beta cytokin secret effector', u'interferon alpha', u'alpha n acetylgalactosaminidas defici', u'sterol 12 alpha hydroxylas p450 subfamili viiib', u'hyperphenylalaninemia due to pterin 4 alpha carbinolamin dehydratas defici', u'disord of peroxisom alpha', u'alpha thalassemia retard', u'hyperplasia due to 17 alpha hydroxylas defici', u'hereditari persist of alpha fetoprotein', u'alpha l iduronidas defici', u'to steroid 5alpha reductas type 3', u'compon subunit alpha defici', u'immatur cd8alpha neg cd11b posit dendrit cell', u'alpha globulin', u'matur cd8alpha neg cd11b neg', u'alpha adrenerg agonist', u'sterol 12 alpha hydroxylas cytochrom p450 subfamili viiib', u'griseu subsp alpha ciferri 1927 pridham', u'due to laminin alpha2', u'immatur cd8alpha posit cd11b neg dendrit cell', u'alpha thalassemia relat diseas', u'17alpha estradiol', u'suscept to respiratori infect associ with cd8alpha chain', u'cytochrom p450 subfamili viiib sterol 12 alpha hydroxylas polypeptid 1', u'famili amyloid nephropathi due to fibrinogen a alpha chain variant', u'alpha ciferri 1927 pridham', u'alpha dystroglycanopathi with brain and', u'alpha b crystallin relat late onset', u'alpha thalassemia intellectu', u'quantit defect of alpha actin', u'analphalipoproteinemia', u'streptomyc griseu subsp alpha', u'develop due to 5 alpha reductas 2 defici', u'congenit disord of glycosyl due to steroid 5alpha reductas type', u'limb girdl muscular dystrophi due to alpha sarcoglycan', u'rialpha low mast cell', u'to pterin 4 alpha carbinolamin dehydratas', u'vgamma5 posit cd8alpha alpha posit gamma delta', u'alpha adrenerg receptor blockad', u'l alpha acetamido beta mercaptopropion acid', u'streptomyc griseu subsp alpha ciferri 1927 pridham 1970 approv', u'cd8alpha posit cd11b neg dendrit', u'alpha cell', u'alpha amino beta phenylpropion acid', u'cd8alpha posit thymic convent', u'cd8alpha alpha posit gamma delta intraepitheli t cell', u'qualit or quantit defect of protein involv in o glycosyl of alpha dystroglycan', u'immatur cd8alpha neg cd11b posit dendrit', u'infect associ with cd8alpha chain', u'1 o chloro alpha', u'alpha methyl beta 3', u'alpha beta cytokin secret', u'alpha beta regulatori t cell', u'subsp alpha ciferri 1927 pridham 1970', u'defect of alpha dystroglycan', u'interleukin 2 receptor alpha', u'subunit alpha defici', u'tcr alpha beta posit t cell defici', u'fc epsilon rialpha high basophil progenitor', u'cah due to 17 alpha hydroxylas defici', u'disord alpha 1 antitrypsin defici', u'to respiratori infect associ with cd8alpha', u'disord of glycosyl due to steroid 5alpha reductas type 3 defici', u'cd8alpha low langerhan cell', u'alpha ciferri 1927 pridham 1970 approv list', u'steroid 5alpha reductas type 3', u'alpha thalassemia myelodysplast syndrom', u'fibrinogen a alpha chain variant', u'muscular alpha dystroglycanopathi with brain', u'4 androsten 17alpha methyl 17beta ol 3 one', u'rialpha high basophil progenitor cell', u'amyloid nephropathi due to fibrinogen a alpha chain', u'dystrophi with integrin alpha 7', u'to pterin 4 alpha carbinolamin dehydratas defici', u'nephropathi due to fibrinogen a alpha chain', u'congenit alpha2 antiplasmin defici', u'due to alpha 1 antitrypsin pittsburgh mutat', u'due to 5 alpha reductas', u'cd8alpha neg thymic convent dendrit', u'2alpha', u'alpha beta regulatori t', u'involv in o glycosyl of alpha dystroglycan', u'3alpha', u'to integrin alpha2 beta1 defici', u'to steroid 5alpha reductas type 3 defici', u'quantit defect of alpha sarcoglycan', u's alpha methyl 4 carboxyphenylglycin', u'to il 7ralpha defici', u'alpha thalassemia intellectu disabl syndrom', u'n methyl 3 phenyl 3 alpha', u'congenit muscular alpha dystroglycanopathi with brain', u'hereditari renal amyloidosi due to fibrinogen a alpha chain', u'to 5 alpha reductas 2 defici', u'7 amino 9alpha methoxymitosan', u'congenit defici in alpha fetoprotein', u'alpha d glucos', u'3 alpha 4 nitrophenyl beta acetylethyl 4 hydroxycoumarin', u'alpha ciferri 1927 pridham 1970 approv', u'immatur cd8alpha low langerhan cell', u'ajmalan 17alpha', u's alpha amino 5 fluoro 3', u'pyruv dehydrogenas e1 alpha defici', u'famili renal amyloidosi due to fibrinogen a alpha chain', u'muscular dystrophi with integrin alpha 7 defici', u'alpha methyl acyl coa racemas defici', u'heparan alpha glucosaminid n acetyltransferas defici', u'l alpha methyltyrosin', u'alpha ketopropionaldehyd', u'due to steroid 5alpha reductas', u'adult onset alpha n acetylgalactosaminidas defici', u'bleed diathesi due to integrin alpha2 beta1 defici', u'receptor alpha chain defici', u'3 alpha phenyl beta acetylethyl 4 hydroxycoumarin', u'of glycosyl due to steroid 5alpha reductas type 3 defici', u'qualit or quantit defect of alpha actin', u'cd8alpha neg cd11b neg dendrit cell', u'qualit or quantit defect of alpha dystroglycan', u'alpha 1 antitrypsin def', u'e1 compon subunit alpha defici', u'alpha n acetylgalactosaminidas defici type', u'cd8alpha alpha posit', u'alpha lipoprotein cholesterol', u'associ with cd8alpha chain', u'with cd8alpha chain', u'receptor subunit alpha', u'cd8alpha posit plasmactyoid dendrit', u'defect of alpha sarcoglycan', u'of sex develop due to 5 alpha reductas 2', u'5 alpha reductas 2 defici', u'to steroid 5alpha reductas type', u'matur cd8alpha neg cd11b posit dendrit', u'cd8alpha posit cd11b neg dendrit cell', u'dystrophi due to laminin alpha2', u'subsp alpha ciferri 1927 pridham 1970 approv list', u'alpha methyl para tyrosin', u'alphaviru infect', u'alpha beta cytokin secret effector t cell', u'defect of alpha actin', u'alpha beta cytotox t cell', u'matur alpha beta t', u'17alpha methyl 3 oxo 4 androsten 17beta ol', u'matur cd8alpha neg cd11b neg dendrit', u'bilirubin ixalpha', u'obsoletealpha 1 antitrypsin defici', u'due to laminin alpha2 defici', u'due to integrin alpha2 beta1', u'alpha 1 antichymotrypsin defici', u'chain alpha ketoacid dehydrogenas', u'immatur cd8alpha posit cd11b neg dendrit', u'persist of alpha fetoprotein', u'vgamma5 posit cd8alpha alpha posit gamma delta intraepitheli t', u'alpha methylguanidino acet acid', u'adren hyperplasia due to 17 alpha hydroxylas defici', u'muscular alpha dystroglycanopathi with brain and eye', u'griseu subsp alpha ciferri 1927 pridham 1970', u't b sever combin immunodefici due to il 7ralpha defici', u'17alpha ethinyl estradiol', u'glycosyl due to steroid 5alpha reductas type 3 defici', u's alpha amino 4 carboxi 2 methylbenzeneacet', u'alpha 4 chlorophenoxi alpha methylpropion acid', u'alpha buten', u'fc epsilon rialpha low mast cell progenitor', u'complex e1 compon subunit alpha', u'due to 5 alpha reductas 2 defici', u'steroid 12 alpha hydroxylas', u'alpha thalassemia intellectu disabl syndrom link to chromosom', u'combin immunodefici due to il 7ralpha', u'sterol 12 alpha hydroxylas polypeptid', u'17alpha methyltestosteron', u'disord of sex develop due to 5 alpha reductas 2', u'cd8alpha alpha posit gamma delta intraepitheli', u'ciferri 1927 streptomyc griseu subsp alpha', u'lysosom alpha d mannosidas defici', u'dystrophi due to alpha sarcoglycan defici', u'due to alpha sarcoglycan defici', u'subsp alpha ciferri', u'alpha methyl p tyrosin', u'famili hyperalphalipoproteinemia', u'alpha 2 6 2 cyanophenoxi 4 pyrimidinyloxi alpha methoxymethylen benzeneacet acid methyl ester', u'infect associ with cd8alpha chain mutat', u'alpha amanitin', u'hereditari renal amyloidosi due to fibrinogen a alpha chain variant', u'branch chain alpha ketoacid dehydrogenas', u'cholesterol 7alpha hydroxylas defici', u'to alpha 1 antitrypsin pittsburgh mutat', u'due to alpha sarcoglycan', u'disord of glycosyl due to steroid 5alpha reductas type', u'alpha2 antiplasmin defici', u'of glycosyl due to steroid 5alpha reductas type 3', u'due to fibrinogen a alpha chain variant', u'alpha posit gamma delta intraepitheli', u'to fibrinogen a alpha chain', u'ciferri 1927 subsp alpha', u'steroid 5alpha reductas type 3 defici', u'1 alpha hydroxylas defici', u'fc epsilon rialpha high basophil', u'alpha l fucosidas defici', u'xy disord of sex develop due to 5 alpha reductas 2', u'dystrophi due to alpha sarcoglycan', u'glycosyl due to steroid 5alpha reductas type 3', u'mate type alpha', u'alpha peak frequenc', u'of glycosyl due to steroid 5alpha reductas', u'alpha thalassemia retard syndrom', u'pregnenolon 16alpha carbonitril', u'hyperphenylalaninemia due to pterin 4 alpha carbinolamin dehydratas', u'subsp alpha ciferri 1927 pridham 1970 approv', u'congenit muscular dystrophi with integrin alpha 7 defici', u'of glycosyl due to steroid 5alpha reductas type', u'n alpha', u'alpha thalassemia x link intellectu', u'platelet alpha granul defici', u'alpha 1', u'alpha n', u'n acetyl alpha glucosaminidas defici', u'tumor necrosi factor alpha', u'cd8 alpha alpha posit', u'alpha naphthyl isothiocyan', u'cytochrom p450 subfamili viiib sterol 12 alpha hydroxylas polypeptid', u'congenit disord of glycosyl due to steroid 5alpha reductas', u'matur cd8alpha posit cd11b neg', u'n 1s 1 dihydroxyboranyl 3 methylbutyl nalpha pyrazin 2 ylcarbonyl d phenylalaninamid', u'vgamma5 neg cd8alpha alpha posit gamma delta', u'l seryl l tyrosyl l seryl l methionyl l alpha glutamyl l histidyl l phenylalanyl l arginyl l tryptophylglycyl l lysyl l prolyl l valylglycyl l lysyl l lysyl l arginyl l arginyl l prolyl l valyl l lysyl l valyl l tyrosyl l prolyl l alpha aspartylglycyl l alanyl l alpha glutamyl l alpha aspartyl l alpha glutamyl l seryl l alanyl l alpha glutamyl l alanyl l phenylalanyl l prolyl l leucyl l alpha glutamyl l phenylalanin', u'alpha tocopherol', u'e1 compon subunit alpha', u'due to fibrinogen a alpha chain', u'due to il 7ralpha', u'pyruv dehydrogenas e1 alpha', u'steroid 5alpha reductas type', u'cd8alpha neg', u'matur cd8alpha posit cd11b neg dendrit', u'congenit muscular dystrophi with integrin alpha 7', u'alpha phthalimidoglutarimid', u'fc epsilon rialpha low mast cell', u'primari alpha dystroglycanopathi', u'vgamma5 neg cd8alpha alpha posit', u'alpha kainic acid', u'7 alpha hydroxi 4 cholesten 3 one 12 alpha hydroxylas', u'delta1 6alpha methylhydrocortison', u'congenit muscular dystrophi due to laminin alpha2 defici', u'defect of integrin alpha 7', u'suscept to respiratori infect associ with cd8alpha chain mutat', u'3 alpha acetonyl p nitrobenzyl 4 hydroxycoumarin', u'17alpha ethynylestra 1', u'yeast alpha mate type', u'alpha thalassemia intermedia', u'1 dehydro 6alpha methylhydrocortison', u'subunit alpha', u'alpha dens granul', u'alpha tocopherol metabol', u'due to pterin 4 alpha carbinolamin dehydratas', u'viiib sterol 12 alpha hydroxylas polypeptid 1', u'develop due to 5 alpha reductas', u'cd8alpha neg thymic convent', u'to respiratori infect associ with cd8alpha chain', u'develop due to 5 alpha reductas 2', u'diseas due to alpha 1 antitrypsin', u'sex develop due to 5 alpha reductas 2 defici', u'alpha thalassemia x link intellectu disabl', u'5alpha reductas type 3', u'to fibrinogen a alpha chain variant', u'matur cd8alpha neg cd11b posit', u'hereditari amyloid nephropathi due to fibrinogen a alpha chain variant', u'sever combin immunodefici due to il 7ralpha', u'due to cholesterol 7alpha hydroxylas', u'alpha methyldopa', u'disord of sex develop due to 5 alpha reductas', u'rialpha low mast cell progenitor', u'hemorrhag diseas due to alpha 1 antitrypsin pittsburgh mutat', u'alpha beta memori t', u'congenit muscular dystrophi due to laminin alpha2', u'branch chain alpha ketoacid', u'approv list 1980 streptomyc griseu subsp alpha ciferri 1927 pridham 1970', u'alpha granul diseas', u'congenit disord of glycosyl due to steroid 5alpha reductas type 3', u'respiratori infect associ with cd8alpha chain', u'streptomyc griseu subsp alpha ciferri 1927 pridham 1970 approv list', u'due to pterin 4 alpha carbinolamin', u'cd8alpha posit plasmactyoid dendrit cell', u'cd8alpha alpha posit gamma delta intraepitheli t', u'congenit disord of glycosyl due to steroid 5alpha reductas type 3 defici', u'due to il 7ralpha defici', u'pyruv dehydrogenas complex e1 compon subunit alpha', u'hypercholesterolemia due to cholesterol 7alpha hydroxylas defici', u'matur cd8alpha neg cd11b posit dendrit cell', u'streptomyc griseu subsp alpha ciferri 1927 pridham', u'hyperphenylalaninemia due to pterin 4 alpha carbinolamin', u'interleukin 2 receptor alpha chain', u'muscular alpha dystroglycanopathi with', u'congenit muscular alpha dystroglycanopathi', u'p450 subfamili viiib sterol 12 alpha hydroxylas polypeptid', u'approv list 1980 griseu subsp alpha ciferri 1927 pridham 1970', u'viiib sterol 12 alpha hydroxylas polypeptid', u'5alpha dihydrotestosteron', u'alpha dystroglycanopathi with brain and eye anomali', u'fibrinogen a alpha chain amyloidosi']\n" + "================================================================================\n", + "Training marginals (!= 0.5):\t3734\n", + "Features:\t\t\t10\n", + "================================================================================\n", + "Begin training for rate=0.01, mu=1e-06\n", + "\tLearning epoch = 0\tGradient mag. = 5.702781\n", + "\tLearning epoch = 250\tGradient mag. = 1.591952\n", + "\tLearning epoch = 500\tGradient mag. = 0.797498\n", + "\tLearning epoch = 750\tGradient mag. = 0.545646\n", + "\tLearning epoch = 1000\tGradient mag. = 0.401758\n", + "\tLearning epoch = 1250\tGradient mag. = 0.310199\n", + "\tLearning epoch = 1500\tGradient mag. = 0.249711\n", + "\tLearning epoch = 1750\tGradient mag. = 0.207701\n", + "\tLearning epoch = 2000\tGradient mag. = 0.176717\n", + "\tLearning epoch = 2250\tGradient mag. = 0.152529\n", + "\tLearning epoch = 2500\tGradient mag. = 0.132795\n", + "\tLearning epoch = 2750\tGradient mag. = 0.116204\n", + "\tLearning epoch = 3000\tGradient mag. = 0.101995\n", + "\tLearning epoch = 3250\tGradient mag. = 0.089694\n", + "\tLearning epoch = 3500\tGradient mag. = 0.078980\n", + "\tLearning epoch = 3750\tGradient mag. = 0.069617\n", + "\tLearning epoch = 4000\tGradient mag. = 0.061422\n", + "\tLearning epoch = 4250\tGradient mag. = 0.054243\n", + "\tLearning epoch = 4500\tGradient mag. = 0.047955\n", + "\tLearning epoch = 4750\tGradient mag. = 0.042450\n", + "\tLearning epoch = 5000\tGradient mag. = 0.037632\n", + "\tLearning epoch = 5250\tGradient mag. = 0.033421\n", + "\tLearning epoch = 5500\tGradient mag. = 0.029745\n", + "\tLearning epoch = 5750\tGradient mag. = 0.026542\n", + "\tLearning epoch = 6000\tGradient mag. = 0.023755\n", + "\tLearning epoch = 6250\tGradient mag. = 0.021338\n", + "\tLearning epoch = 6500\tGradient mag. = 0.019246\n", + "\tLearning epoch = 6750\tGradient mag. = 0.017442\n", + "\tLearning epoch = 7000\tGradient mag. = 0.015893\n", + "\tLearning epoch = 7250\tGradient mag. = 0.014568\n", + "\tLearning epoch = 7500\tGradient mag. = 0.013439\n", + "\tLearning epoch = 7750\tGradient mag. = 0.012481\n", + "\tLearning epoch = 8000\tGradient mag. = 0.011674\n", + "\tLearning epoch = 8250\tGradient mag. = 0.010995\n", + "\tLearning epoch = 8500\tGradient mag. = 0.010426\n", + "\tLearning epoch = 8750\tGradient mag. = 0.009952\n", + "\tLearning epoch = 9000\tGradient mag. = 0.009557\n", + "\tLearning epoch = 9250\tGradient mag. = 0.009228\n", + "\tLearning epoch = 9500\tGradient mag. = 0.008954\n", + "\tLearning epoch = 9750\tGradient mag. = 0.008726\n", + "Final gradient magnitude for rate=0.01, mu=1e-06: 0.009\n" ] } ], "source": [ - "print [ph for ph in efo_phenotype_list0 if 'alpha' in ph]\n", - "print [ph for ph in efo_phen_matcher.d if 'alpha' in ph]" + "from snorkel.learning import NaiveBayes\n", + "\n", + "gen_model = NaiveBayes()\n", + "gen_model.train(L_train, n_iter=10000, rate=1e-2)" ] }, { - "cell_type": "code", - "execution_count": 83, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "'NoneType' object has no attribute 'split'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mphenotype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mphenotype_names\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mphenotype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0msynonyms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msyn\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msyn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mphenotype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msynonyms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'|'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 12\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mquery_word\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msynonyms\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mquery_word\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mphenotype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mphenotype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mphenotype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0montology_ref\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'split'" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "query_word = 'trait in'\n", - "from db import db_session\n", - "from db.schema import *\n", - "\n", - "phenotypes = db_session.query(Phenotype).filter(Phenotype.source=='snomed').all()\n", - "# phenotypes == kb.get_phenotype_candidates_cheating()\n", - "phenotype_names = set()\n", - "for phenotype in phenotypes:\n", - " if phenotype.name:\n", - " phenotype_names.add((phenotype.name))\n", - " synonyms = [(syn) for syn in phenotype.synonyms.split('|')]\n", - " if query_word in synonyms or query_word == phenotype.name:\n", - " print phenotype.name, phenotype.ontology_ref\n", - " phenotype_names.update(synonyms)" + "The numbers below give an estimate of the weights learned for each feature. As you can see, several features have been substantially reweighted (while some others have remained mostly unchanged)." ] }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 63, "metadata": { "collapsed": false }, @@ -1438,2258 +863,436 @@ { "data": { "text/plain": [ - "[(u'borderline personality disorder', u'borderlin person')]" + "array([ 2.1160965 , 0.82758228, -0.38315466, 0.97169885, 1.09790897,\n", + " 9.93726566, 0.98503744, 9.99651539, 1.8207841 , 9.99909417])" ] }, - "execution_count": 91, + "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# print len(phenotype_names)\n", - "[(word, change_name(word)) for word in snomed_phenotype_list if change_name(word) == change_name('borderline personality')]" + "gen_model.w" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Look at results on the test set (optional)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Extraction performance" + "We can adjust the above classifier (e.g. the labelling functions, the hyper-parameters) and assess the results on the dev/test set. This section shows how this can be done." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "First, extract some features for each candidate mention." + "We will label a small number of dev/test candidates." ] }, { "cell_type": "code", - "execution_count": 115, + "execution_count": 20, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Building feature index...\n", - "Extracting features...\n", - "0/642099\n", - "5000/642099\n", - "10000/642099\n", - "15000/642099\n", - "20000/642099\n", - "25000/642099\n", - "30000/642099\n", - "35000/642099\n", - "40000/642099\n", - "45000/642099\n", - "50000/642099\n", - "55000/642099\n", - "60000/642099\n", - "65000/642099\n", - "70000/642099\n", - "75000/642099\n", - "80000/642099\n", - "85000/642099\n", - "90000/642099\n", - "95000/642099\n", - "100000/642099\n", - "105000/642099\n", - "110000/642099\n", - "115000/642099\n", - "120000/642099\n", - "125000/642099\n", - "130000/642099\n", - "135000/642099\n", - "140000/642099\n", - "145000/642099\n", - "150000/642099\n", - "155000/642099\n", - "160000/642099\n", - "165000/642099\n", - "170000/642099\n", - "175000/642099\n", - "180000/642099\n", - "185000/642099\n", - "190000/642099\n", - "195000/642099\n", - "200000/642099\n", - "205000/642099\n", - "210000/642099\n", - "215000/642099\n", - "220000/642099\n", - "225000/642099\n", - "230000/642099\n", - "235000/642099\n", - "240000/642099\n", - "245000/642099\n", - "250000/642099\n", - "255000/642099\n", - "260000/642099\n", - "265000/642099\n", - "270000/642099\n", - "275000/642099\n", - "280000/642099\n", - "285000/642099\n", - "290000/642099\n", - "295000/642099\n", - "300000/642099\n", - "305000/642099\n", - "310000/642099\n", - "315000/642099\n", - "320000/642099\n", - "325000/642099\n", - "330000/642099\n", - "335000/642099\n", - "340000/642099\n", - "345000/642099\n", - "350000/642099\n", - "355000/642099\n", - "360000/642099\n", - "365000/642099\n", - "370000/642099\n", - "375000/642099\n", - "380000/642099\n", - "385000/642099\n", - "390000/642099\n", - "395000/642099\n", - "400000/642099\n", - "405000/642099\n", - "410000/642099\n", - "415000/642099\n", - "420000/642099\n", - "425000/642099\n", - "430000/642099\n", - "435000/642099\n", - "440000/642099\n", - "445000/642099\n", - "450000/642099\n", - "455000/642099\n", - "460000/642099\n", - "465000/642099\n", - "470000/642099\n", - "475000/642099\n", - "480000/642099\n", - "485000/642099\n", - "490000/642099\n", - "495000/642099\n", - "500000/642099\n", - "505000/642099\n", - "510000/642099\n", - "515000/642099\n", - "520000/642099\n", - "525000/642099\n", - "530000/642099\n", - "535000/642099\n", - "540000/642099\n", - "545000/642099\n", - "550000/642099\n", - "555000/642099\n", - "560000/642099\n", - "565000/642099\n", - "570000/642099\n", - "575000/642099\n", - "580000/642099\n", - "585000/642099\n", - "590000/642099\n", - "595000/642099\n", - "600000/642099\n", - "605000/642099\n", - "610000/642099\n", - "615000/642099\n", - "620000/642099\n", - "625000/642099\n", - "630000/642099\n", - "635000/642099\n", - "640000/642099\n", - "Example features: [u'DDLIB_WORD_SEQ_[Crohn Disease]', u'DDLIB_LEMMA_SEQ_[crohn disease]', u'DDLIB_POS_SEQ_[NN NN]', u'DDLIB_DEP_SEQ_[compound compound]', u'DDLIB_W_LEFT_1_[novel]', u'DDLIB_W_LEFT_POS_1_[JJ]', u'DDLIB_W_LEFT_2_[. novel]', u'DDLIB_W_LEFT_POS_2_[. JJ]', u'DDLIB_W_LEFT_3_[ptger4 . novel]', u'DDLIB_W_LEFT_POS_3_[NN . JJ]']\n" - ] - } - ], + "outputs": [], "source": [ - "import cPickle \n", - "from snorkel.features import NgramFeaturizer\n", - "\n", - "# pkl_f = 'phenotype_feats.pkl'\n", - "# try:\n", - "# with open(pkl_f, 'rb') as f:\n", - "# featurizer = cPickle.load(f)\n", - "# except:\n", - "featurizer = NgramFeaturizer()\n", - "featurizer.fit_transform(phen_c)\n", + "n_labeled = 300 # number of candidates to label\n", "\n", - "print 'Example features:', [f for f in featurizer.get_features_by_candidate(phen_c[0])[:10]]" + "random_idx = np.random.choice(len(devtest_c), size=(n_labeled,), replace=False)\n", + "labeled_c = CandidateSet(name='Phenotype Labeled Candidates')\n", + "for i in random_idx:\n", + " labeled_c.append(devtest_c[i])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We may use the Snorkel viewer to label a set of examples." ] }, { "cell_type": "code", - "execution_count": 116, + "execution_count": 21, "metadata": { "collapsed": false }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Defined 2675 positive and 48756 negative gold mentions\n" - ] - } - ], - "source": [ - "# classify candidates as correct or not\n", - "\n", - "# doc_id -> set of correct gwc_ids\n", - "gold_agg_dict_phen = { doc_id : set() for doc_id, phen_id in gold_set_agg_phens }\n", - "for doc_id, phen_id in gold_set_agg_phens:\n", - " gold_agg_dict_phen[doc_id].add(phen_id)\n", - "\n", - "def c2uid(candidate):\n", - " return candidate.context.document.name, candidate.context.position, candidate.char_start, candidate.char_end\n", - " \n", - "gt_dict_pos = dict()\n", - "gt_dict_neg = dict()\n", - "for candidate in phen_c:\n", - " doc_id = candidate.context.document.name\n", - " agg_ids = agg_phen2id.get(change_name(candidate.get_span()), set())\n", - " uid = c2uid(candidate)\n", - " if agg_ids & gold_agg_dict_phen[doc_id]:\n", - " gt_dict_pos[uid] = +1\n", - " else:\n", - " gt_dict_neg[uid] = -1\n", - "\n", - "gt_dict = dict(gt_dict_pos.items() + gt_dict_neg.items())\n", - "print 'Defined %d positive and %d negative gold mentions' % (len(gt_dict_pos), len(gt_dict_neg))" + "data": { + "application/javascript": [ + "require.undef('viewer');\n", + "\n", + "// NOTE: all elements should be selected using this.$el.find to avoid collisions with other Viewers\n", + "\n", + "define('viewer', [\"jupyter-js-widgets\"], function(widgets) {\n", + " var ViewerView = widgets.DOMWidgetView.extend({\n", + " render: function() {\n", + " this.cids = this.model.get('cids');\n", + " this.nPages = this.cids.length;\n", + " this.pid = 0;\n", + " this.cxid = 0;\n", + " this.cid = 0;\n", + "\n", + " // Insert the html payload\n", + " this.$el.append(this.model.get('html'));\n", + "\n", + " // Initialize all labels from previous sessions\n", + " this.labels = this.deserializeDict(this.model.get('_labels_serialized'));\n", + " for (var i=0; i < this.nPages; i++) {\n", + " this.pid = i;\n", + " for (var j=0; j < this.cids[i].length; j++) {\n", + " this.cxid = j;\n", + " for (var k=0; k < this.cids[i][j].length; k++) {\n", + " this.cid = k;\n", + " if (this.cids[i][j][k] in this.labels) {\n", + " this.markCurrentCandidate(false);\n", + " }\n", + " }\n", + " }\n", + " }\n", + " this.pid = 0;\n", + " this.cxid = 0;\n", + " this.cid = 0;\n", + "\n", + " // Enable button functionality for navigation\n", + " var that = this;\n", + " this.$el.find(\"#next-cand\").click(function() {\n", + " that.switchCandidate(1);\n", + " });\n", + " this.$el.find(\"#prev-cand\").click(function() {\n", + " that.switchCandidate(-1);\n", + " });\n", + " this.$el.find(\"#next-context\").click(function() {\n", + " that.switchContext(1);\n", + " });\n", + " this.$el.find(\"#prev-context\").click(function() {\n", + " that.switchContext(-1);\n", + " });\n", + " this.$el.find(\"#next-page\").click(function() {\n", + " that.switchPage(1);\n", + " });\n", + " this.$el.find(\"#prev-page\").click(function() {\n", + " that.switchPage(-1);\n", + " });\n", + " this.$el.find(\"#label-true\").click(function() {\n", + " that.labelCandidate(true, true);\n", + " });\n", + " this.$el.find(\"#label-false\").click(function() {\n", + " that.labelCandidate(false, true);\n", + " });\n", + "\n", + " // Arrow key functionality\n", + " this.$el.keydown(function(e) {\n", + " switch(e.which) {\n", + " case 74: // j\n", + " that.switchCandidate(-1);\n", + " break;\n", + "\n", + " case 73: // i\n", + " that.switchPage(-1);\n", + " break;\n", + "\n", + " case 76: // l\n", + " that.switchCandidate(1);\n", + " break;\n", + "\n", + " case 75: // k\n", + " that.switchPage(1);\n", + " break;\n", + "\n", + " case 84: // t\n", + " that.labelCandidate(true, true);\n", + " break;\n", + "\n", + " case 70: // f\n", + " that.labelCandidate(false, true);\n", + " break;\n", + " }\n", + " });\n", + "\n", + " // Show the first page and highlight the first candidate\n", + " this.$el.find(\"#viewer-page-0\").show();\n", + " this.switchCandidate(0);\n", + " },\n", + "\n", + " // Get candidate selector for currently selected candidate, escaping id properly\n", + " getCandidate: function() {\n", + " return this.$el.find(\".\"+this.cids[this.pid][this.cxid][this.cid]);\n", + " }, \n", + "\n", + " // Color the candidate correctly according to registered label, as well as set highlighting\n", + " markCurrentCandidate: function(highlight) {\n", + " var cid = this.cids[this.pid][this.cxid][this.cid];\n", + " var tags = this.$el.find(\".\"+cid);\n", + "\n", + " // Clear color classes\n", + " tags.removeClass(\"candidate-h\");\n", + " tags.removeClass(\"true-candidate\");\n", + " tags.removeClass(\"true-candidate-h\");\n", + " tags.removeClass(\"false-candidate\");\n", + " tags.removeClass(\"false-candidate-h\");\n", + " tags.removeClass(\"highlighted\");\n", + "\n", + " if (highlight) {\n", + " if (cid in this.labels) {\n", + " tags.addClass(String(this.labels[cid]) + \"-candidate-h\");\n", + " } else {\n", + " tags.addClass(\"candidate-h\");\n", + " }\n", + " \n", + " // If un-highlighting, leave with first non-null coloring\n", + " } else {\n", + " var that = this;\n", + " tags.each(function() {\n", + " var cids = $(this).attr('class').split(/\\s+/).map(function(item) {\n", + " return parseInt(item);\n", + " });\n", + " cids.sort();\n", + " for (var i in cids) {\n", + " if (cids[i] in that.labels) {\n", + " var label = that.labels[cids[i]];\n", + " $(this).addClass(String(label) + \"-candidate\");\n", + " $(this).removeClass(String(!label) + \"-candidate\");\n", + " break;\n", + " }\n", + " }\n", + " });\n", + " }\n", + "\n", + " // Extra highlighting css\n", + " if (highlight) {\n", + " tags.addClass(\"highlighted\");\n", + " }\n", + "\n", + " // Classes for showing direction of relation\n", + " if (highlight) {\n", + " this.$el.find(\".\"+cid+\"-0\").addClass(\"left-candidate\");\n", + " this.$el.find(\".\"+cid+\"-1\").addClass(\"right-candidate\");\n", + " } else {\n", + " this.$el.find(\".\"+cid+\"-0\").removeClass(\"left-candidate\");\n", + " this.$el.find(\".\"+cid+\"-1\").removeClass(\"right-candidate\");\n", + " }\n", + " },\n", + "\n", + " // Cycle through candidates and highlight, by increment inc\n", + " switchCandidate: function(inc) {\n", + " var N = this.cids[this.pid].length\n", + " var M = this.cids[this.pid][this.cxid].length;\n", + " if (N == 0 || M == 0) { return false; }\n", + "\n", + " // Clear highlighting from previous candidate\n", + " if (inc != 0) {\n", + " this.markCurrentCandidate(false);\n", + "\n", + " // Increment the cid counter\n", + "\n", + " // Move to next context\n", + " if (this.cid + inc >= M) {\n", + " while (this.cid + inc >= M) {\n", + " \n", + " // At last context on page, halt\n", + " if (this.cxid == N - 1) {\n", + " this.cid = M - 1;\n", + " inc = 0;\n", + " break;\n", + " \n", + " // Increment to next context\n", + " } else {\n", + " inc -= M - this.cid;\n", + " this.cxid += 1;\n", + " M = this.cids[this.pid][this.cxid].length;\n", + " this.cid = 0;\n", + " }\n", + " }\n", + "\n", + " // Move to previous context\n", + " } else if (this.cid + inc < 0) {\n", + " while (this.cid + inc < 0) {\n", + " \n", + " // At first context on page, halt\n", + " if (this.cxid == 0) {\n", + " this.cid = 0;\n", + " inc = 0;\n", + " break;\n", + " \n", + " // Increment to previous context\n", + " } else {\n", + " inc += this.cid + 1;\n", + " this.cxid -= 1;\n", + " M = this.cids[this.pid][this.cxid].length;\n", + " this.cid = M - 1;\n", + " }\n", + " }\n", + " }\n", + "\n", + " // Move within current context\n", + " this.cid += inc;\n", + " }\n", + " this.markCurrentCandidate(true);\n", + "\n", + " // Push this new cid to the model\n", + " this.model.set('_selected_cid', this.cids[this.pid][this.cxid][this.cid]);\n", + " this.touch();\n", + " },\n", + "\n", + " // Switch through contexts\n", + " switchContext: function(inc) {\n", + " this.markCurrentCandidate(false);\n", + "\n", + " // Iterate context on this page\n", + " var M = this.cids[this.pid].length;\n", + " if (this.cxid + inc < 0) {\n", + " this.cxid = 0;\n", + " } else if (this.cxid + inc >= M) {\n", + " this.cxid = M - 1;\n", + " } else {\n", + " this.cxid += inc;\n", + " }\n", + "\n", + " // Reset cid and set to first candidate\n", + " this.cid = 0;\n", + " this.switchCandidate(0);\n", + " },\n", + "\n", + " // Switch through pages\n", + " switchPage: function(inc) {\n", + " this.markCurrentCandidate(false);\n", + " this.$el.find(\".viewer-page\").hide();\n", + " if (this.pid + inc < 0) {\n", + " this.pid = 0;\n", + " } else if (this.pid + inc > this.nPages - 1) {\n", + " this.pid = this.nPages - 1;\n", + " } else {\n", + " this.pid += inc;\n", + " }\n", + " this.$el.find(\"#viewer-page-\"+this.pid).show();\n", + "\n", + " // Show pagination\n", + " this.$el.find(\"#page\").html(this.pid);\n", + "\n", + " // Reset cid and set to first candidate\n", + " this.cid = 0;\n", + " this.cxid = 0;\n", + " this.switchCandidate(0);\n", + " },\n", + "\n", + " // Label currently-selected candidate\n", + " labelCandidate: function(label, highlighted) {\n", + " var c = this.getCandidate();\n", + " var cid = this.cids[this.pid][this.cxid][this.cid];\n", + " var cl = String(label) + \"-candidate\";\n", + " var clh = String(label) + \"-candidate-h\";\n", + " var cln = String(!label) + \"-candidate\";\n", + " var clnh = String(!label) + \"-candidate-h\";\n", + "\n", + " // Toggle label highlighting\n", + " if (c.hasClass(cl) || c.hasClass(clh)) {\n", + " c.removeClass(cl);\n", + " c.removeClass(clh);\n", + " if (highlighted) {\n", + " c.addClass(\"candidate-h\");\n", + " }\n", + " this.labels[cid] = null;\n", + " this.send({event: 'delete_label', cid: cid});\n", + " } else {\n", + " c.removeClass(cln);\n", + " c.removeClass(clnh);\n", + " if (highlighted) {\n", + " c.addClass(clh);\n", + " } else {\n", + " c.addClass(cl);\n", + " }\n", + " this.labels[cid] = label;\n", + " this.send({event: 'set_label', cid: cid, value: label});\n", + " }\n", + "\n", + " // Set the label and pass back to the model\n", + " this.model.set('_labels_serialized', this.serializeDict(this.labels));\n", + " this.touch();\n", + " },\n", + "\n", + " // Serialization of hash maps, because traitlets Dict doesn't seem to work...\n", + " serializeDict: function(d) {\n", + " var s = [];\n", + " for (var key in d) {\n", + " s.push(key+\"~~\"+d[key]);\n", + " }\n", + " return s.join();\n", + " },\n", + "\n", + " // Deserialization of hash maps\n", + " deserializeDict: function(s) {\n", + " var d = {};\n", + " var entries = s.split(/,/);\n", + " var kv;\n", + " for (var i in entries) {\n", + " kv = entries[i].split(/~~/);\n", + " if (kv[1] == \"true\") {\n", + " d[kv[0]] = true;\n", + " } else if (kv[1] == \"false\") {\n", + " d[kv[0]] = false;\n", + " }\n", + " }\n", + " return d;\n", + " },\n", + " });\n", + "\n", + " return {\n", + " ViewerView: ViewerView\n", + " };\n", + "});\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from snorkel.viewer import SentenceNgramViewer\n", + "sv = SentenceNgramViewer(labeled_c, session, annotator_name=\"Snorkel Phenotype Annotations\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This will display the viewer." ] }, { "cell_type": "code", - "execution_count": 117, + "execution_count": 69, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17447842\n", - "crohn's disease 19827\n", - "\tcrohn's disease http://www.ebi.ac.uk/efo/EFO_0000384 gastritis associated with crohn's disease|ileitis\n", - "crohn's disease 19333\n", - "\tcrohn's disease http://www.ebi.ac.uk/efo/EFO_0000384 gastritis associated with crohn's disease|ileitis\n", - "crohn's disease 19486\n", - "\tcrohn's disease http://www.ebi.ac.uk/efo/EFO_0000384 gastritis associated with crohn's disease|ileitis\n", - "Novel Crohn Disease Locus Identified by Genome-Wide Association Maps to a Gene Desert on 5p13.1 and Modulates Expression of PTGER4. To identify novel susceptibility loci for Crohn disease (CD), we undertook a genome-wide association study with more than 300,000 SNPs characterized in 547 patients and 928 controls. We found three chromosome regions that provided evidence of disease association with p -values between 10 â’6 and 10 â’9 . Two of these ( IL23R on Chromosome 1 and CARD15 on Chromosome 16) correspond to genes previously reported to be associated with CD. In addition, a 250-kb region of Chromosome 5p13.1 was found to contain multiple markers with strongly suggestive evidence of disease association (including four markers with p < 10 â’7 ). We replicated the results for 5p13.1 by studying 1,266 additional CD patients, 559 additional controls, and 428 trios. Significant evidence of association ( p < 4 Ă— 10 â’4 ) was found in case/control comparisons with the replication data, while associated alleles were over-transmitted to affected offspring ( p < 0.05), thus confirming that the 5p13.1 locus contributes to CD susceptibility. The CD-associated 250-kb region was saturated with 111 SNP markers. Haplotype analysis supports a complex locus architecture with multiple variants contributing to disease susceptibility. The novel 5p13.1 CD locus is contained within a 1.25-Mb gene desert. We present evidence that disease-associated alleles correlate with quantitative expression levels of the prostaglandin receptor EP4, PTGER4, the gene that resides closest to the associated region. Our results identify a major new susceptibility locus for CD, and suggest that genetic variants associated with disease risk at this locus could modulate cis -acting regulatory elements of PTGER4 . Individual susceptibility to many common diseases is determined by a combination of environmental and genetic factors. Identifying these genetic risk factors is one of the most important objectives of modern medical genetics, as it paves the way towards personalized medicine and drug target identification. Recent advances in SNP genotyping technology allows systematic association scanning of the entire genome for the detection of novel susceptibility loci. We herein apply this approach to Crohn disease, which afflicts an estimated 0.15% of the people in the developed world and identify a novel susceptibility locus on Chromosome 5. A unique feature of the novel 5p13.1 locus is that it coincides with a 1.25-Mb gene desert. We present evidence that genetic variants at this locus influence the expression levels of the closest gene, PTGER4, located 270 kb away, in the direction of the centromere. PTGER4 encodes the prostaglandin receptor EP4 and is a strong candidate susceptibility gene for Crohn disease as PTGER4 knock-out mice have increased susceptibility to colitis.\n", - "1 Crohn Disease | crohn's disease http://www.ebi.ac.uk/efo/EFO_0000384\n", - "-1 to a\n", - "-1 Association\n", - "-1 Maps | mean arterial pressure http://www.ebi.ac.uk/efo/EFO_0006340\n", - "-1 and\n", - "-1 of\n", - "-1 Crohn disease (CD),\n", - "-1 a\n", - "-1 association\n", - "-1 in\n", - "-1 and\n", - "-1 disease association with\n", - "-1 of disease\n", - "-1 p -\n", - "-1 -values\n", - "-1 chromosome\n", - "-1 and\n", - "-1 associated with\n", - "-1 of\n", - "-1 Chromosome\n", - "-1 and\n", - "-1 Chromosome\n", - "-1 , a\n", - "-1 of Chromosome\n", - "-1 of disease\n", - "-1 disease association\n", - "-1 In\n", - "-1 was\n", - "-1 suggestive\n", - "-1 p\n", - "-1 , and\n", - "-1 of\n", - "-1 association\n", - "-1 p\n", - "-1 Ă—\n", - "-1 was\n", - "-1 in\n", - "-1 associated\n", - "-1 affected\n", - "-1 p\n", - "-1 confirming\n", - "-1 was\n", - "-1 to disease\n", - "-1 analysis\n", - "-1 a\n", - "-1 a\n", - "-1 levels of the\n", - "-1 prostaglandin receptor\n", - "-1 disease-associated\n", - "-1 associated\n", - "-1 associated with disease\n", - "-1 a major\n", - "-1 , and\n", - "-1 suggest\n", - "-1 genetic\n", - "-1 at\n", - "-1 of\n", - "-1 common diseases\n", - "-1 a\n", - "-1 of\n", - "-1 and\n", - "-1 genetic\n", - "-1 risk factors\n", - "-1 of the\n", - "-1 genetics,\n", - "-1 , as\n", - "-1 genetic\n", - "-1 of\n", - "-1 medical\n", - "-1 personalized | personality http://www.ebi.ac.uk/efo/EFO_0003947\n", - "-1 and\n", - "-1 drug | response to drug http://purl.obolibrary.org/obo/GO_0042493\n", - "-1 of the\n", - "-1 in\n", - "-1 genotyping\n", - "-1 association\n", - "-1 genome\n", - "-1 detection\n", - "-1 of\n", - "1 Crohn disease, | crohn's disease http://www.ebi.ac.uk/efo/EFO_0000384\n", - "-1 of the\n", - "-1 Chromosome 5\n", - "-1 an\n", - "-1 in\n", - "-1 developed\n", - "-1 and\n", - "-1 a\n", - "-1 of the\n", - "-1 A\n", - "-1 a\n", - "-1 levels of the\n", - "-1 , in\n", - "-1 of the\n", - "-1 genetic\n", - "-1 at\n", - "-1 prostaglandin receptor\n", - "1 Crohn disease | crohn's disease http://www.ebi.ac.uk/efo/EFO_0000384\n", - "-1 disease as\n", - "-1 and\n", - "-1 a\n", - "-1 increased\n", - "-1 colitis\n", - "\n", - "17658951\n", - "obesity-related traits 19256\n", - "\tadiponectin measurement http://www.ebi.ac.uk/efo/EFO_0004502 adiponectin levels\n", - "\thoma-ir http://www.ebi.ac.uk/efo/EFO_0004501 homeostasis model assessment insulin resistance\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tthyroid stimulating hormone measurement http://www.ebi.ac.uk/efo/EFO_0004748 thyrotropin measurement|thyroid stimulating hormone level|thyroid stimulating hormone levels\n", - "\tprotein measurement http://www.ebi.ac.uk/efo/EFO_0004747 protein levels\n", - "\tblood urea nitrogen measurement http://www.ebi.ac.uk/efo/EFO_0004741 \n", - "\tlean body mass http://www.ebi.ac.uk/efo/EFO_0004995 \n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\taspartate aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004736 aspartate transaminase measurement\n", - "\thormone measurement http://www.ebi.ac.uk/efo/EFO_0004730 \n", - "\tfat body mass http://www.ebi.ac.uk/efo/EFO_0005409 total body fat measurement\n", - "\tadipose tissue measurement http://www.ebi.ac.uk/efo/EFO_0004764 \n", - "\ticam-1 measurement http://www.ebi.ac.uk/efo/EFO_0004520 soluble icam1 measurement|soluble intercellular adhesion molecule-1|sicam-1\n", - "\ttriglyceride measurement http://www.ebi.ac.uk/efo/EFO_0004530 triglyceride levels\n", - "\twaist circumference http://www.ebi.ac.uk/efo/EFO_0004342 \n", - "\tbody mass index http://www.ebi.ac.uk/efo/EFO_0004340 quetelet's index|bmi\n", - "\tobesity http://www.ebi.ac.uk/efo/EFO_0001073 overweight and obesity|obesity (disorder)|obese|obesity nos|obese (finding)|adiposity|adiposis|obesity [ambiguous]|obesity\n", - "\tbirth weight http://www.ebi.ac.uk/efo/EFO_0004344 birthweight\n", - "\twaist-hip ratio http://www.ebi.ac.uk/efo/EFO_0004343 \n", - "\theart rate http://www.ebi.ac.uk/efo/EFO_0004326 pulse rate|cardiac chronotropy\n", - "\tbody height http://www.ebi.ac.uk/efo/EFO_0004339 height\n", - "\tbody weight http://www.ebi.ac.uk/efo/EFO_0004338 weight\n", - "\thomocysteine measurement http://www.ebi.ac.uk/efo/EFO_0004578 homocysteine levels\n", - "\ttotal cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004574 cholesterol\n", - "\tccl5 measurement http://www.ebi.ac.uk/efo/EFO_0005117 regulated on activation\n", - "\tigfbp-1 measurement http://www.ebi.ac.uk/efo/EFO_0005118 \n", - "\tantioxidant measurement http://www.ebi.ac.uk/efo/EFO_0005119 \n", - "\thead circumference http://www.ebi.ac.uk/efo/EFO_0005114 \n", - "\tmetabolic rate measurement http://www.ebi.ac.uk/efo/EFO_0005115 \n", - "\turinary metabolite measurement http://www.ebi.ac.uk/efo/EFO_0005116 \n", - "\tfatty acid measurement http://www.ebi.ac.uk/efo/EFO_0005110 \n", - "\tfolic acid measurement http://www.ebi.ac.uk/efo/EFO_0005111 folate measurement|vitamin b9 measurement\n", - "\tgestational age http://www.ebi.ac.uk/efo/EFO_0005112 \n", - "\tbody composition measurement http://www.ebi.ac.uk/efo/EFO_0005106 \n", - "\tarm span http://www.ebi.ac.uk/efo/EFO_0005108 \n", - "\tenergy expenditure http://www.ebi.ac.uk/efo/EFO_0005109 \n", - "\tamino acid measurement http://www.ebi.ac.uk/efo/EFO_0005134 \n", - "\tc-peptide measurement http://www.ebi.ac.uk/efo/EFO_0005187 \n", - "\tccl11 measurement http://www.ebi.ac.uk/efo/EFO_0005188 \n", - "\trespiratory quotient http://www.ebi.ac.uk/efo/EFO_0005189 \n", - "\turinary nitrogen measurement http://www.ebi.ac.uk/efo/EFO_0005190 \n", - "\twaist height ratio http://www.ebi.ac.uk/efo/EFO_0005191 \n", - "\ttestosterone measurement http://www.ebi.ac.uk/efo/EFO_0004908 testosterone levels|testosterone level\n", - "\tinterleukin-6 measurement http://www.ebi.ac.uk/efo/EFO_0004810 il-6 levels|il-6 level|il-6 measurement\n", - "\ttransforming growth factor beta measurement http://www.ebi.ac.uk/efo/EFO_0004818 \n", - "\tigf-1 measurement http://www.ebi.ac.uk/efo/EFO_0004627 insulin-like growth factor 1 levels\n", - "\tigfbp-3 measurement http://www.ebi.ac.uk/efo/EFO_0004626 insulin-like growth factor binding protein 3 levels\n", - "\tvitamin b12 measurement http://www.ebi.ac.uk/efo/EFO_0004620 vitamin b12 levels\n", - "\tsleep measurement http://www.ebi.ac.uk/efo/EFO_0004870 \n", - "\thigh density lipoprotein cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004612 hdl measurement\n", - "\tlow density lipoprotein cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004611 ldl measurement\n", - "\tmaximal oxygen uptake measurement http://www.ebi.ac.uk/efo/EFO_0004887 maximal oxygen consumption|peak oxygen uptake|maximal oxygen uptake|maximal aerobic capacity|vo2 max\n", - "\tcortisol secretion measurement http://www.ebi.ac.uk/efo/EFO_0004642 \n", - "\tfasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466 fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "\tinsulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471 insulin sensitivity test\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "\testradiol measurement http://www.ebi.ac.uk/efo/EFO_0004697 oestrogen level|oestrogen levels|estradiol levels\n", - "\tsystolic blood pressure http://www.ebi.ac.uk/efo/EFO_0006335 sysbp|systolic pressure\n", - "\tdiastolic blood pressure http://www.ebi.ac.uk/efo/EFO_0006336 diastolic pressure|diabp\n", - "\tleptin measurement http://www.ebi.ac.uk/efo/EFO_0005000 \n", - "\thip circumference http://www.ebi.ac.uk/efo/EFO_0005093 \n", - "\tenergy intake http://www.ebi.ac.uk/efo/EFO_0003939 caloric intake\n", - "\tphysical activity http://www.ebi.ac.uk/efo/EFO_0003940 motor activity|activities\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "obesity-related traits 19254\n", - "\tadiponectin measurement http://www.ebi.ac.uk/efo/EFO_0004502 adiponectin levels\n", - "\thoma-ir http://www.ebi.ac.uk/efo/EFO_0004501 homeostasis model assessment insulin resistance\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tthyroid stimulating hormone measurement http://www.ebi.ac.uk/efo/EFO_0004748 thyrotropin measurement|thyroid stimulating hormone level|thyroid stimulating hormone levels\n", - "\tprotein measurement http://www.ebi.ac.uk/efo/EFO_0004747 protein levels\n", - "\tblood urea nitrogen measurement http://www.ebi.ac.uk/efo/EFO_0004741 \n", - "\tlean body mass http://www.ebi.ac.uk/efo/EFO_0004995 \n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\taspartate aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004736 aspartate transaminase measurement\n", - "\thormone measurement http://www.ebi.ac.uk/efo/EFO_0004730 \n", - "\tfat body mass http://www.ebi.ac.uk/efo/EFO_0005409 total body fat measurement\n", - "\tadipose tissue measurement http://www.ebi.ac.uk/efo/EFO_0004764 \n", - "\ticam-1 measurement http://www.ebi.ac.uk/efo/EFO_0004520 soluble icam1 measurement|soluble intercellular adhesion molecule-1|sicam-1\n", - "\ttriglyceride measurement http://www.ebi.ac.uk/efo/EFO_0004530 triglyceride levels\n", - "\twaist circumference http://www.ebi.ac.uk/efo/EFO_0004342 \n", - "\tbody mass index http://www.ebi.ac.uk/efo/EFO_0004340 quetelet's index|bmi\n", - "\tobesity http://www.ebi.ac.uk/efo/EFO_0001073 overweight and obesity|obesity (disorder)|obese|obesity nos|obese (finding)|adiposity|adiposis|obesity [ambiguous]|obesity\n", - "\tbirth weight http://www.ebi.ac.uk/efo/EFO_0004344 birthweight\n", - "\twaist-hip ratio http://www.ebi.ac.uk/efo/EFO_0004343 \n", - "\theart rate http://www.ebi.ac.uk/efo/EFO_0004326 pulse rate|cardiac chronotropy\n", - "\tbody height http://www.ebi.ac.uk/efo/EFO_0004339 height\n", - "\tbody weight http://www.ebi.ac.uk/efo/EFO_0004338 weight\n", - "\thomocysteine measurement http://www.ebi.ac.uk/efo/EFO_0004578 homocysteine levels\n", - "\ttotal cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004574 cholesterol\n", - "\tccl5 measurement http://www.ebi.ac.uk/efo/EFO_0005117 regulated on activation\n", - "\tigfbp-1 measurement http://www.ebi.ac.uk/efo/EFO_0005118 \n", - "\tantioxidant measurement http://www.ebi.ac.uk/efo/EFO_0005119 \n", - "\thead circumference http://www.ebi.ac.uk/efo/EFO_0005114 \n", - "\tmetabolic rate measurement http://www.ebi.ac.uk/efo/EFO_0005115 \n", - "\turinary metabolite measurement http://www.ebi.ac.uk/efo/EFO_0005116 \n", - "\tfatty acid measurement http://www.ebi.ac.uk/efo/EFO_0005110 \n", - "\tfolic acid measurement http://www.ebi.ac.uk/efo/EFO_0005111 folate measurement|vitamin b9 measurement\n", - "\tgestational age http://www.ebi.ac.uk/efo/EFO_0005112 \n", - "\tbody composition measurement http://www.ebi.ac.uk/efo/EFO_0005106 \n", - "\tarm span http://www.ebi.ac.uk/efo/EFO_0005108 \n", - "\tenergy expenditure http://www.ebi.ac.uk/efo/EFO_0005109 \n", - "\tamino acid measurement http://www.ebi.ac.uk/efo/EFO_0005134 \n", - "\tc-peptide measurement http://www.ebi.ac.uk/efo/EFO_0005187 \n", - "\tccl11 measurement http://www.ebi.ac.uk/efo/EFO_0005188 \n", - "\trespiratory quotient http://www.ebi.ac.uk/efo/EFO_0005189 \n", - "\turinary nitrogen measurement http://www.ebi.ac.uk/efo/EFO_0005190 \n", - "\twaist height ratio http://www.ebi.ac.uk/efo/EFO_0005191 \n", - "\ttestosterone measurement http://www.ebi.ac.uk/efo/EFO_0004908 testosterone levels|testosterone level\n", - "\tinterleukin-6 measurement http://www.ebi.ac.uk/efo/EFO_0004810 il-6 levels|il-6 level|il-6 measurement\n", - "\ttransforming growth factor beta measurement http://www.ebi.ac.uk/efo/EFO_0004818 \n", - "\tigf-1 measurement http://www.ebi.ac.uk/efo/EFO_0004627 insulin-like growth factor 1 levels\n", - "\tigfbp-3 measurement http://www.ebi.ac.uk/efo/EFO_0004626 insulin-like growth factor binding protein 3 levels\n", - "\tvitamin b12 measurement http://www.ebi.ac.uk/efo/EFO_0004620 vitamin b12 levels\n", - "\tsleep measurement http://www.ebi.ac.uk/efo/EFO_0004870 \n", - "\thigh density lipoprotein cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004612 hdl measurement\n", - "\tlow density lipoprotein cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004611 ldl measurement\n", - "\tmaximal oxygen uptake measurement http://www.ebi.ac.uk/efo/EFO_0004887 maximal oxygen consumption|peak oxygen uptake|maximal oxygen uptake|maximal aerobic capacity|vo2 max\n", - "\tcortisol secretion measurement http://www.ebi.ac.uk/efo/EFO_0004642 \n", - "\tfasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466 fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "\tinsulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471 insulin sensitivity test\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "\testradiol measurement http://www.ebi.ac.uk/efo/EFO_0004697 oestrogen level|oestrogen levels|estradiol levels\n", - "\tsystolic blood pressure http://www.ebi.ac.uk/efo/EFO_0006335 sysbp|systolic pressure\n", - "\tdiastolic blood pressure http://www.ebi.ac.uk/efo/EFO_0006336 diastolic pressure|diabp\n", - "\tleptin measurement http://www.ebi.ac.uk/efo/EFO_0005000 \n", - "\thip circumference http://www.ebi.ac.uk/efo/EFO_0005093 \n", - "\tenergy intake http://www.ebi.ac.uk/efo/EFO_0003939 caloric intake\n", - "\tphysical activity http://www.ebi.ac.uk/efo/EFO_0003940 motor activity|activities\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "obesity-related traits 19255\n", - "\tadiponectin measurement http://www.ebi.ac.uk/efo/EFO_0004502 adiponectin levels\n", - "\thoma-ir http://www.ebi.ac.uk/efo/EFO_0004501 homeostasis model assessment insulin resistance\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tthyroid stimulating hormone measurement http://www.ebi.ac.uk/efo/EFO_0004748 thyrotropin measurement|thyroid stimulating hormone level|thyroid stimulating hormone levels\n", - "\tprotein measurement http://www.ebi.ac.uk/efo/EFO_0004747 protein levels\n", - "\tblood urea nitrogen measurement http://www.ebi.ac.uk/efo/EFO_0004741 \n", - "\tlean body mass http://www.ebi.ac.uk/efo/EFO_0004995 \n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\taspartate aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004736 aspartate transaminase measurement\n", - "\thormone measurement http://www.ebi.ac.uk/efo/EFO_0004730 \n", - "\tfat body mass http://www.ebi.ac.uk/efo/EFO_0005409 total body fat measurement\n", - "\tadipose tissue measurement http://www.ebi.ac.uk/efo/EFO_0004764 \n", - "\ticam-1 measurement http://www.ebi.ac.uk/efo/EFO_0004520 soluble icam1 measurement|soluble intercellular adhesion molecule-1|sicam-1\n", - "\ttriglyceride measurement http://www.ebi.ac.uk/efo/EFO_0004530 triglyceride levels\n", - "\twaist circumference http://www.ebi.ac.uk/efo/EFO_0004342 \n", - "\tbody mass index http://www.ebi.ac.uk/efo/EFO_0004340 quetelet's index|bmi\n", - "\tobesity http://www.ebi.ac.uk/efo/EFO_0001073 overweight and obesity|obesity (disorder)|obese|obesity nos|obese (finding)|adiposity|adiposis|obesity [ambiguous]|obesity\n", - "\tbirth weight http://www.ebi.ac.uk/efo/EFO_0004344 birthweight\n", - "\twaist-hip ratio http://www.ebi.ac.uk/efo/EFO_0004343 \n", - "\theart rate http://www.ebi.ac.uk/efo/EFO_0004326 pulse rate|cardiac chronotropy\n", - "\tbody height http://www.ebi.ac.uk/efo/EFO_0004339 height\n", - "\tbody weight http://www.ebi.ac.uk/efo/EFO_0004338 weight\n", - "\thomocysteine measurement http://www.ebi.ac.uk/efo/EFO_0004578 homocysteine levels\n", - "\ttotal cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004574 cholesterol\n", - "\tccl5 measurement http://www.ebi.ac.uk/efo/EFO_0005117 regulated on activation\n", - "\tigfbp-1 measurement http://www.ebi.ac.uk/efo/EFO_0005118 \n", - "\tantioxidant measurement http://www.ebi.ac.uk/efo/EFO_0005119 \n", - "\thead circumference http://www.ebi.ac.uk/efo/EFO_0005114 \n", - "\tmetabolic rate measurement http://www.ebi.ac.uk/efo/EFO_0005115 \n", - "\turinary metabolite measurement http://www.ebi.ac.uk/efo/EFO_0005116 \n", - "\tfatty acid measurement http://www.ebi.ac.uk/efo/EFO_0005110 \n", - "\tfolic acid measurement http://www.ebi.ac.uk/efo/EFO_0005111 folate measurement|vitamin b9 measurement\n", - "\tgestational age http://www.ebi.ac.uk/efo/EFO_0005112 \n", - "\tbody composition measurement http://www.ebi.ac.uk/efo/EFO_0005106 \n", - "\tarm span http://www.ebi.ac.uk/efo/EFO_0005108 \n", - "\tenergy expenditure http://www.ebi.ac.uk/efo/EFO_0005109 \n", - "\tamino acid measurement http://www.ebi.ac.uk/efo/EFO_0005134 \n", - "\tc-peptide measurement http://www.ebi.ac.uk/efo/EFO_0005187 \n", - "\tccl11 measurement http://www.ebi.ac.uk/efo/EFO_0005188 \n", - "\trespiratory quotient http://www.ebi.ac.uk/efo/EFO_0005189 \n", - "\turinary nitrogen measurement http://www.ebi.ac.uk/efo/EFO_0005190 \n", - "\twaist height ratio http://www.ebi.ac.uk/efo/EFO_0005191 \n", - "\ttestosterone measurement http://www.ebi.ac.uk/efo/EFO_0004908 testosterone levels|testosterone level\n", - "\tinterleukin-6 measurement http://www.ebi.ac.uk/efo/EFO_0004810 il-6 levels|il-6 level|il-6 measurement\n", - "\ttransforming growth factor beta measurement http://www.ebi.ac.uk/efo/EFO_0004818 \n", - "\tigf-1 measurement http://www.ebi.ac.uk/efo/EFO_0004627 insulin-like growth factor 1 levels\n", - "\tigfbp-3 measurement http://www.ebi.ac.uk/efo/EFO_0004626 insulin-like growth factor binding protein 3 levels\n", - "\tvitamin b12 measurement http://www.ebi.ac.uk/efo/EFO_0004620 vitamin b12 levels\n", - "\tsleep measurement http://www.ebi.ac.uk/efo/EFO_0004870 \n", - "\thigh density lipoprotein cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004612 hdl measurement\n", - "\tlow density lipoprotein cholesterol measurement http://www.ebi.ac.uk/efo/EFO_0004611 ldl measurement\n", - "\tmaximal oxygen uptake measurement http://www.ebi.ac.uk/efo/EFO_0004887 maximal oxygen consumption|peak oxygen uptake|maximal oxygen uptake|maximal aerobic capacity|vo2 max\n", - "\tcortisol secretion measurement http://www.ebi.ac.uk/efo/EFO_0004642 \n", - "\tfasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466 fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "\tinsulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471 insulin sensitivity test\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "\testradiol measurement http://www.ebi.ac.uk/efo/EFO_0004697 oestrogen level|oestrogen levels|estradiol levels\n", - "\tsystolic blood pressure http://www.ebi.ac.uk/efo/EFO_0006335 sysbp|systolic pressure\n", - "\tdiastolic blood pressure http://www.ebi.ac.uk/efo/EFO_0006336 diastolic pressure|diabp\n", - "\tleptin measurement http://www.ebi.ac.uk/efo/EFO_0005000 \n", - "\thip circumference http://www.ebi.ac.uk/efo/EFO_0005093 \n", - "\tenergy intake http://www.ebi.ac.uk/efo/EFO_0003939 caloric intake\n", - "\tphysical activity http://www.ebi.ac.uk/efo/EFO_0003940 motor activity|activities\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "Genome-Wide Association Scan Shows Genetic Variants in the FTO Gene Are Associated with Obesity-Related Traits. The obesity epidemic is responsible for a substantial economic burden in developed countries and is a major risk factor for type 2 diabetes and cardiovascular disease. The disease is the result not only of several environmental risk factors, but also of genetic predisposition. To take advantage of recent advances in gene-mapping technology, we executed a genome-wide association scan to identify genetic variants associated with obesity-related quantitative traits in the genetically isolated population of Sardinia. Initial analysis suggested that several SNPs in the FTO and PFKP genes were associated with increased BMI, hip circumference, and weight. Within the FTO gene, rs9930506 showed the strongest association with BMI ( p = 8.6 Ă—10 â’ 7 ), hip circumference ( p = 3.4 Ă— 10 â’ 8 ), and weight ( p = 9.1 Ă— 10 â’ 7 ). In Sardinia, homozygotes for the rare “G” allele of this SNP (minor allele frequency = 0.46) were 1.3 BMI units heavier than homozygotes for the common “A” allele. Within the PFKP gene, rs6602024 showed very strong association with BMI ( p = 4.9 Ă— 10 â’ 6 ). Homozygotes for the rare “A” allele of this SNP (minor allele frequency = 0.12) were 1.8 BMI units heavier than homozygotes for the common “G” allele. To replicate our findings, we genotyped these two SNPs in the GenNet study. In European Americans ( N = 1,496) and in Hispanic Americans ( N = 839), we replicated significant association between rs9930506 in the FTO gene and BMI ( p -value for meta-analysis of European American and Hispanic American follow-up samples, p = 0.001), weight ( p = 0.001), and hip circumference ( p = 0.0005). We did not replicate association between rs6602024 and obesity-related traits in the GenNet sample, although we found that in European Americans, Hispanic Americans, and African Americans, homozygotes for the rare “A” allele were, on average, 1.0–3.0 BMI units heavier than homozygotes for the more common “G” allele. In summary, we have completed a whole genome–association scan for three obesity-related quantitative traits and report that common genetic variants in the FTO gene are associated with substantial changes in BMI, hip circumference, and body weight. These changes could have a significant impact on the risk of obesity-related morbidity in the general population. Although twin and family studies have clearly shown that genes play a role in obesity, it has proven quite difficult to identify the specific genetic variants involved. Here, we take advantage of recent technical and methodological advances to examine the role of common genetic variants on several obesity-related traits. By examining >4,000 Sardinians, we show that a specific genetic variant, rs9930506, and other nearby variants on human Chromosome 16 are associated with body mass index, hip circumference, and total body weight. The variants overlap FTO, a gene with poorly understood function. Further studies of the region may implicate new biological pathways affecting susceptibility to obesity. We also show that the association is not restricted to Sardinia but is also seen in independent samples of European Americans and Hispanic Americans. This finding is particularly important because obesity is associated with increased risk of cardiovascular disease and diabetes.\n", - "-1 Associated with\n", - "-1 Obesity-Related Traits\n", - "-1 Association\n", - "-1 Genetic\n", - "-1 in\n", - "-1 major risk factor\n", - "-1 type 2 diabetes\n", - "-1 a major\n", - "-1 cardiovascular disease | cardiovascular disease http://www.ebi.ac.uk/efo/EFO_0000319\n", - "1 obesity | obesity http://www.ebi.ac.uk/efo/EFO_0001073\n", - "-1 epidemic\n", - "-1 a\n", - "-1 in\n", - "-1 developed\n", - "-1 and\n", - "-1 and\n", - "-1 risk factors,\n", - "-1 The disease\n", - "-1 , but\n", - "-1 of genetic\n", - "-1 not\n", - "-1 of\n", - "-1 several\n", - "-1 obesity-related quantitative traits\n", - "-1 associated with\n", - "-1 of\n", - "-1 in\n", - "-1 a\n", - "-1 association\n", - "-1 genetic\n", - "-1 in\n", - "-1 genetically\n", - "-1 population\n", - "-1 of\n", - "1 , hip circumference | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "1 hip circumference, | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "-1 associated with\n", - "1 BMI, | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 , and\n", - "-1 analysis\n", - "-1 suggested\n", - "-1 several\n", - "-1 in\n", - "-1 and\n", - "-1 increased\n", - "1 weight | body weight http://www.ebi.ac.uk/efo/EFO_0004338\n", - "1 ), hip circumference ( | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "-1 association with\n", - "-1 , and\n", - "1 BMI | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 p\n", - "-1 Ă—\n", - "-1 p\n", - "-1 Ă—\n", - "1 weight | body weight http://www.ebi.ac.uk/efo/EFO_0004338\n", - "-1 p\n", - "-1 Ă—\n", - "-1 In\n", - "-1 of\n", - "1 BMI | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 A\n", - "-1 association with\n", - "1 BMI | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 p\n", - "-1 Ă—\n", - "-1 A\n", - "-1 of\n", - "1 BMI | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 findings,\n", - "-1 genotyped\n", - "-1 in\n", - "1 ), weight ( | body weight http://www.ebi.ac.uk/efo/EFO_0004338\n", - "-1 p -\n", - "-1 -value\n", - "-1 , p\n", - "-1 , and\n", - "1 hip circumference | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "-1 In\n", - "-1 N\n", - "-1 and\n", - "-1 in\n", - "-1 N\n", - "-1 association\n", - "-1 in\n", - "-1 and\n", - "1 BMI | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 of\n", - "-1 and\n", - "-1 follow-up\n", - "-1 p\n", - "-1 p\n", - "-1 obesity-related traits\n", - "-1 , and\n", - "-1 not\n", - "-1 association\n", - "-1 and\n", - "-1 in\n", - "-1 in\n", - "-1 A\n", - "1 BMI | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 obesity-related quantitative traits\n", - "1 , hip circumference | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "1 hip circumference, | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "-1 associated with\n", - "1 BMI, | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "-1 , and\n", - "1 body weight | body weight http://www.ebi.ac.uk/efo/EFO_0004338\n", - "-1 In\n", - "-1 a\n", - "-1 genome\n", - "-1 association\n", - "-1 and\n", - "-1 genetic\n", - "-1 in\n", - "-1 changes\n", - "-1 in\n", - "-1 changes\n", - "-1 a\n", - "-1 of\n", - "-1 in\n", - "-1 general\n", - "-1 population\n", - "1 obesity, | obesity http://www.ebi.ac.uk/efo/EFO_0001073\n", - "-1 and\n", - "-1 family\n", - "-1 play\n", - "-1 a\n", - "-1 in\n", - "-1 genetic\n", - "-1 obesity-related traits\n", - "-1 of\n", - "-1 and\n", - "-1 of\n", - "-1 genetic\n", - "-1 several\n", - "1 body mass index, | body mass index http://www.ebi.ac.uk/efo/EFO_0004340\n", - "1 , hip circumference | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "1 hip circumference, | hip circumference http://www.ebi.ac.uk/efo/EFO_0005093\n", - "-1 , and\n", - "-1 associated with\n", - "-1 , and\n", - "1 body weight | body weight http://www.ebi.ac.uk/efo/EFO_0004338\n", - "-1 a\n", - "-1 genetic\n", - "-1 human\n", - "-1 Chromosome\n", - "-1 , a\n", - "-1 of the\n", - "-1 biological\n", - "-1 affecting\n", - "1 obesity | obesity http://www.ebi.ac.uk/efo/EFO_0001073\n", - "-1 association\n", - "-1 not\n", - "-1 but\n", - "-1 in\n", - "-1 independent\n", - "-1 of\n", - "-1 and\n", - "-1 with increased risk of\n", - "-1 of cardiovascular disease\n", - "-1 associated with\n", - "-1 disease and\n", - "-1 finding\n", - "1 obesity | obesity http://www.ebi.ac.uk/efo/EFO_0001073\n", - "-1 diabetes\n", - "\n", - "17684544\n", - "crohn's disease 19532\n", - "\tcrohn's disease http://www.ebi.ac.uk/efo/EFO_0000384 gastritis associated with crohn's disease|ileitis\n", - "crohn's disease 19845\n", - "\tcrohn's disease http://www.ebi.ac.uk/efo/EFO_0000384 gastritis associated with crohn's disease|ileitis\n", - "crohn's disease 19846\n", - "\tcrohn's disease http://www.ebi.ac.uk/efo/EFO_0000384 gastritis associated with crohn's disease|ileitis\n", - "Systematic Association Mapping Identifies NELL1 as a Novel IBD Disease Gene. Crohn disease (CD), a sub-entity of inflammatory bowel disease (IBD), is a complex polygenic disorder. Although recent studies have successfully identified CD-associated genetic variants, these susceptibility loci explain only a fraction of the heritability of the disease. Here, we report on a multi-stage genome-wide scan of 393 German CD cases and 399 controls. Among the 116,161 single-nucleotide polymorphisms tested, an association with the known CD susceptibility gene NOD2 , the 5q31 haplotype, and the recently reported CD locus at 5p13.1 was confirmed. In addition, SNP rs1793004 in the gene encoding nel-like 1 precursor ( NELL1, chromosome 11p15.1 ) showed a consistent disease-association in independent German population- and family-based samples (942 cases, 1082 controls, 375 trios). Subsequent fine mapping and replication in an independent sample of 454 French/Canadian CD trios supported the authenticity of the NELL1 association. Further confirmation in a large German ulcerative colitis (UC) sample indicated that NELL1 is a ubiquitous IBD susceptibility locus (combined p<10 â’6 ; OR = 1.66, 95% CI: 1.30–2.11). The novel 5p13.1 locus was also replicated in the French/Canadian sample and in an independent UK CD patient panel (453 cases, 521 controls, combined p<10 â’6 for SNP rs1992660). Several associations were replicated in at least one independent sample, point to an involvement of ITGB6 (upstream), GRM8 (downstream), OR5V1 (downstream), PPP3R2 (downstream), NM_152575 (upstream) and HNF4G (intron).\n", - "-1 as a\n", - "-1 IBD Disease\n", - "-1 Association\n", - "-1 Mapping | mean arterial pressure http://www.ebi.ac.uk/efo/EFO_0006340\n", - "-1 inflammatory bowel disease (IBD),\n", - "-1 Crohn disease (CD),\n", - "-1 , a\n", - "-1 of\n", - "-1 a\n", - "-1 of the disease\n", - "-1 of the\n", - "-1 genetic\n", - "-1 a\n", - "-1 a\n", - "-1 of\n", - "-1 and\n", - "-1 , an\n", - "-1 association with\n", - "-1 , and\n", - "-1 at\n", - "-1 was\n", - "-1 confirmed\n", - "-1 , chromosome\n", - "-1 population-\n", - "-1 - and\n", - "-1 In\n", - "-1 in\n", - "-1 a\n", - "-1 disease-association\n", - "-1 in\n", - "-1 independent\n", - "-1 of the\n", - "-1 mapping | mean arterial pressure http://www.ebi.ac.uk/efo/EFO_0006340\n", - "-1 and\n", - "-1 in\n", - "-1 an\n", - "-1 independent\n", - "-1 of\n", - "-1 association\n", - "-1 ulcerative colitis (UC)\n", - "-1 confirmation\n", - "-1 in\n", - "-1 a\n", - "-1 indicated | ankle brachial index http://www.ebi.ac.uk/efo/EFO_0003912\n", - "-1 a\n", - "-1 IBD\n", - "-1 p\n", - "-1 was\n", - "-1 in\n", - "-1 and\n", - "-1 in\n", - "-1 an\n", - "-1 independent\n", - "-1 p\n", - "-1 Several\n", - "-1 associations\n", - "-1 in\n", - "-1 at\n", - "-1 independent\n", - "-1 an\n", - "-1 of\n", - "-1 and\n", - "\n", - "17903292\n", - "cystatin c 19169\n", - "\tcystatin c measurement http://www.ebi.ac.uk/efo/EFO_0004617 \n", - "thyroid stimulating hormone 19170\n", - "\tthyroid stimulating hormone measurement http://www.ebi.ac.uk/efo/EFO_0004748 thyrotropin measurement|thyroid stimulating hormone level|thyroid stimulating hormone levels\n", - "\tthyroid function http://www.ebi.ac.uk/efo/EFO_0004296 \n", - "thyroid stimulating hormone 19171\n", - "\tthyroid stimulating hormone measurement http://www.ebi.ac.uk/efo/EFO_0004748 thyrotropin measurement|thyroid stimulating hormone level|thyroid stimulating hormone levels\n", - "\tthyroid function http://www.ebi.ac.uk/efo/EFO_0004296 \n", - "thyroid stimulating hormone 19172\n", - "\tthyroid stimulating hormone measurement http://www.ebi.ac.uk/efo/EFO_0004748 thyrotropin measurement|thyroid stimulating hormone level|thyroid stimulating hormone levels\n", - "\tthyroid function http://www.ebi.ac.uk/efo/EFO_0004296 \n", - "urinary albumin excretion 19173\n", - "\talbuminuria http://www.ebi.ac.uk/efo/EFO_0004285 urinary albumin excretion\n", - "urinary albumin excretion 19626\n", - "\talbuminuria http://www.ebi.ac.uk/efo/EFO_0004285 urinary albumin excretion\n", - "A genome-wide association for kidney function and endocrine-related traits in the NHLBI's Framingham Heart Study. Glomerular filtration rate (GFR) and urinary albumin excretion (UAE) are markers of kidney function that are known to be heritable. Many endocrine conditions have strong familial components. We tested for association between the Affymetrix GeneChip Human Mapping 100K single nucleotide polymorphism (SNP) set and measures of kidney function and endocrine traits. Genotype information on the Affymetrix GeneChip Human Mapping 100K SNP set was available on 1345 participants. Serum creatinine and cystatin-C (cysC; n = 981) were measured at the seventh examination cycle (1998–2001); GFR (n = 1010) was estimated via the Modification of Diet in Renal Disease (MDRD) equation; UAE was measured on spot urine samples during the sixth examination cycle (1995–1998) and was indexed to urinary creatinine (n = 822). Thyroid stimulating hormone (TSH) was measured at the third and fourth examination cycles (1981–1984; 1984–1987) and mean value of the measurements were used (n = 810). Age-sex-adjusted and multivariable-adjusted residuals for these measurements were used in association with genotype data using generalized estimating equations (GEE) and family-based association tests (FBAT) models. We presented the results for association tests using additive allele model. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg Equilibrium p-value ≥ 0.001, and call rates of at least 80%. The top SNPs associated with these traits using the GEE method were rs2839235 with GFR (p-value 1.6*10 -05 ), rs1158167 with cysC (p-value 8.5*10 -09 ), rs1712790 with UAE (p-value 1.9*10 -06 ), and rs6977660 with TSH (p-value 3.7*10 -06 ), respectively. The top SNPs associated with these traits using the FBAT method were rs6434804 with GFR(p-value 2.4*10 -5 ), rs563754 with cysC (p-value 4.7*10 -5 ), rs1243400 with UAE (p-value 4.8*10 -6 ), and rs4128956 with TSH (p-value 3.6*10 -5 ), respectively. Detailed association test results can be found at . Four SNPs in or near the CST 3 gene were highly associated with cysC levels (p-value 8.5*10 -09 to 0.007). Kidney function traits and TSH are associated with SNPs on the Affymetrix GeneChip Human Mapping 100K SNP set. These data will serve as a valuable resource for replication as more SNPs associated with kidney function and endocrine traits are identified.\n", - "-1 endocrine-related traits\n", - "-1 A\n", - "-1 association\n", - "-1 kidney\n", - "-1 and\n", - "-1 in\n", - "-1 's\n", - "-1 Heart\n", - "-1 Glomerular filtration rate | glomerular filtration rate http://www.ebi.ac.uk/efo/EFO_0005208\n", - "1 urinary albumin excretion | albuminuria http://www.ebi.ac.uk/efo/EFO_0004285\n", - "-1 of kidney\n", - "-1 GFR | glomerular filtration rate http://www.ebi.ac.uk/efo/EFO_0005208\n", - "-1 and\n", - "-1 endocrine\n", - "-1 familial\n", - "-1 of kidney\n", - "-1 endocrine traits\n", - "-1 association\n", - "-1 Human\n", - "-1 Mapping | mean arterial pressure http://www.ebi.ac.uk/efo/EFO_0006340\n", - "-1 single | herpes zoster http://www.ebi.ac.uk/efo/EFO_0006510\n", - "-1 and\n", - "-1 and\n", - "-1 Genotype\n", - "-1 Human\n", - "-1 Mapping | mean arterial pressure http://www.ebi.ac.uk/efo/EFO_0006340\n", - "-1 was\n", - "-1 Serum creatinine | serum creatinine measurement http://www.ebi.ac.uk/efo/EFO_0004518\n", - "-1 Renal Disease\n", - "-1 and\n", - "1 cystatin-C | cystatin c measurement http://www.ebi.ac.uk/efo/EFO_0004617\n", - "-1 n\n", - "-1 at\n", - "-1 GFR | glomerular filtration rate http://www.ebi.ac.uk/efo/EFO_0005208\n", - "-1 n\n", - "-1 was\n", - "-1 of\n", - "-1 in\n", - "-1 was\n", - "-1 spot\n", - "-1 urine\n", - "-1 sixth\n", - "-1 and\n", - "-1 was\n", - "-1 creatinine | serum creatinine measurement http://www.ebi.ac.uk/efo/EFO_0004518\n", - "-1 n\n", - "1 Thyroid stimulating hormone | thyroid stimulating hormone measurement http://www.ebi.ac.uk/efo/EFO_0004748\n", - "-1 of the\n", - "-1 the measurements\n", - "-1 TSH\n", - "-1 was\n", - "-1 at\n", - "-1 and\n", - "-1 fourth\n", - "-1 and\n", - "-1 value\n", - "-1 n\n", - "-1 these measurements\n", - "-1 association with\n", - "-1 and\n", - "-1 in\n", - "-1 genotype\n", - "-1 generalized\n", - "-1 and\n", - "-1 association\n", - "-1 tests\n", - "-1 association\n", - "-1 tests\n", - "-1 associations with\n", - "-1 , and\n", - "-1 of\n", - "-1 at\n", - "-1 rates\n", - "-1 of\n", - "-1 at\n", - "-1 associated with\n", - "-1 these traits\n", - "-1 , and\n", - "-1 GFR | glomerular filtration rate http://www.ebi.ac.uk/efo/EFO_0005208\n", - "-1 TSH\n", - "-1 associated with\n", - "-1 these traits\n", - "-1 , and\n", - "-1 GFR | glomerular filtration rate http://www.ebi.ac.uk/efo/EFO_0005208\n", - "-1 -5\n", - "-1 -5\n", - "-1 TSH\n", - "-1 -5\n", - "-1 association test\n", - "-1 at\n", - "-1 associated with\n", - "-1 in\n", - "-1 near\n", - "-1 Kidney function traits\n", - "-1 associated with\n", - "-1 and\n", - "-1 TSH\n", - "-1 Human\n", - "-1 Mapping | mean arterial pressure http://www.ebi.ac.uk/efo/EFO_0006340\n", - "-1 as a\n", - "-1 associated with\n", - "-1 endocrine traits\n", - "-1 will\n", - "-1 as\n", - "-1 kidney\n", - "-1 and\n", - "\n", - "17903293\n", - "select biomarker traits 19638\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19633\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19161\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19627\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19628\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19629\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19630\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19631\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19632\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19160\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19634\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19635\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19636\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19157\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19158\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19159\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19640\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19641\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19642\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19639\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "select biomarker traits 19637\n", - "\tccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749 monocyte chemotactic protein-1 measurement|chemokine ccl2 level|monocyte chemoattractant protein-1 measurement|chemokine ccl2 levels|monocyte chemotactic protein-1 levels|monocyte chemotactic protein-1 level\n", - "\tserum alanine aminotransferase measurement http://www.ebi.ac.uk/efo/EFO_0004735 alanine transaminase measurement|alanine aminotransferase measurement\n", - "\tatrial natriuretic factor measurement http://www.ebi.ac.uk/efo/EFO_0004789 \n", - "\tcd40 ligand measurement http://www.ebi.ac.uk/efo/EFO_0004790 cd154 ligand measurement\n", - "\talkaline phosphatase measurement http://www.ebi.ac.uk/efo/EFO_0004533 ap\n", - "\tbilirubin measurement http://www.ebi.ac.uk/efo/EFO_0004570 bilirubin levels\n", - "\tvitamin d measurement http://www.ebi.ac.uk/efo/EFO_0004631 \n", - "\tvitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618 phylloquinone measurement\n", - "\ttumor necrosis factor-alpha measurement http://www.ebi.ac.uk/efo/EFO_0004684 \n", - "\tc-reactive protein measurement http://www.ebi.ac.uk/efo/EFO_0004458 c-reactive protein level\n", - "Genome-wide association with select biomarker traits in the Framingham Heart Study. Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 ± 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507–1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency ≥ 10%, call rate ≥ 80% and Hardy-Weinberg equilibrium p ≥ 0.001. With GEE , 58 SNPs had p < 10 -6 : the top SNPs were rs2494250 (p = 1.00*10 -14 ) and rs4128725 (p = 3.68*10 -12 ) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10 -8 ) and rs2808629 (p = 3.19*10 -8 ) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT , 11 SNPs had p < 10 -6 : the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10 -8 , and rs2494250, p = 3.55*10 -8 ), and also included B-type natriuretic peptide (rs437021, p = 1.01*10 -6 ) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10 -6 ). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at . The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.\n", - "-1 association with\n", - "-1 biomarker traits\n", - "-1 select\n", - "-1 in\n", - "-1 Heart\n", - "-1 into disease\n", - "-1 , diagnosis\n", - "-1 diagnosis,\n", - "-1 , and\n", - "-1 Systemic\n", - "-1 biomarkers\n", - "-1 heritable phenotypes\n", - "-1 systemic\n", - "-1 biomarker\n", - "-1 association\n", - "-1 genetic\n", - "-1 biomarker\n", - "-1 current\n", - "-1 knowledge\n", - "-1 of\n", - "-1 physiological\n", - "-1 relations\n", - "-1 natriuretic peptides\n", - "-1 liver function\n", - "-1 association\n", - "-1 of\n", - "-1 single | herpes zoster http://www.ebi.ac.uk/efo/EFO_0006510\n", - "-1 systemic\n", - "-1 biomarker\n", - "-1 in\n", - "-1 biological\n", - "-1 stress | exercise test http://www.ebi.ac.uk/efo/EFO_0004328\n", - "-1 and\n", - "-1 vitamins\n", - "-1 of the\n", - "-1 both phenotype\n", - "-1 per phenotype\n", - "-1 Related\n", - "-1 n\n", - "-1 age | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "-1 and\n", - "-1 genotype\n", - "-1 n\n", - "-1 , Family\n", - "-1 Generalized\n", - "-1 Association\n", - "-1 Tests\n", - "-1 and\n", - "-1 relate\n", - "-1 biomarker\n", - "-1 n\n", - "-1 rate\n", - "-1 and\n", - "-1 p\n", - "-1 C-reactive protein (CRP)\n", - "1 monocyte chemoattractant protein-1 | ccl2 measurement http://www.ebi.ac.uk/efo/EFO_0004749\n", - "-1 , and\n", - "-1 p\n", - "-1 p\n", - "-1 and\n", - "-1 p\n", - "-1 p\n", - "-1 and\n", - "-1 p\n", - "-1 over\n", - "-1 B-type natriuretic peptide\n", - "-1 , p\n", - "-1 , and\n", - "-1 , p\n", - "-1 , and\n", - "-1 , p\n", - "1 Vitamin K | vitamin k measurement http://www.ebi.ac.uk/efo/EFO_0004618\n", - "-1 , p\n", - "-1 p\n", - "-1 and\n", - "-1 osteocalcin\n", - "-1 of the\n", - "-1 , chromosome\n", - "-1 , chromosome\n", - "-1 and\n", - "-1 of\n", - "-1 and\n", - "-1 associations with\n", - "-1 at\n", - "-1 p\n", - "-1 and\n", - "-1 in\n", - "-1 disequilibrium\n", - "-1 and\n", - "-1 at\n", - "-1 a\n", - "-1 genetic\n", - "-1 systemic\n", - "-1 biomarker\n", - "-1 associations\n", - "-1 will\n", - "-1 in\n", - "\n", - "17903294\n", - "hemostatic factors and hematological phenotypes 19584\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19585\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19586\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19587\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19588\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19589\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19590\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19591\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "factor vii 19233\n", - "\tfactor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619 \n", - "factor vii 19234\n", - "\tfactor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619 \n", - "hemostatic factors and hematological phenotypes 19235\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19236\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "factor vii 19431\n", - "\tfactor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619 \n", - "factor vii 19575\n", - "\tfactor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619 \n", - "hemostatic factors and hematological phenotypes 19576\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19577\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19578\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19579\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19580\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19581\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19582\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "hemostatic factors and hematological phenotypes 19583\n", - "\thematological measurement http://www.ebi.ac.uk/efo/EFO_0004503 \n", - "\themoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509 hb|haemoglobin measurement|hemoglobin count\n", - "\tplatelet aggregation http://purl.obolibrary.org/obo/GO_0070527 \n", - "\terythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305 erythrocyte number|red blood cell count|rbc\n", - "\tblood viscosity http://www.ebi.ac.uk/efo/EFO_0004301 \n", - "\tplasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792 \n", - "\ttissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791 \n", - "\tmean corpuscular hemoglobin http://www.ebi.ac.uk/efo/EFO_0004527 mch|mean corpuscular haemoglobin\n", - "\tprotein c measurement http://www.ebi.ac.uk/efo/EFO_0004633 coagulation factor xiv\n", - "\tprotein s measurement http://www.ebi.ac.uk/efo/EFO_0004637 \n", - "Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study. Increased circulating levels of hemostatic factors as well as anemia have been associated with increased risk of cardiovascular disease (CVD). Known associations between hemostatic factors and sequence variants at genes encoding these factors explain only a small proportion of total phenotypic variation. We sought to confirm known putative loci and identify novel loci that may influence either trait in genome-wide association and linkage analyses using the Affymetrix GeneChip 100K single nucleotide polymorphism (SNP) set. Plasma levels of circulating hemostatic factors (fibrinogen, factor VII, plasminogen activator inhibitor-1, von Willebrand factor, tissue plasminogen activator, D-dimer) and hematological phenotypes (platelet aggregation, viscosity, hemoglobin, red blood cell count, mean corpuscular volume, mean corpuscular hemoglobin concentration) were obtained in approximately 1000 Framingham Heart Study (FHS) participants from 310 families. Population-based association analyses using the generalized estimating equations (GEE), family-based association test (FBAT), and multipoint variance components linkage analyses were performed on the multivariable adjusted residuals of hemostatic and hematological phenotypes. In association analysis, the lowest GEE p-value for hemostatic factors was p = 4.5*10 -16 for factor VII at SNP rs561241, a variant located near the F7 gene and in complete linkage disequilibrium (LD) (r 2 = 1) with the Arg353Gln F7 SNP previously shown to account for 9% of total phenotypic variance. The lowest GEE p-value for hematological phenotypes was 7*10 -8 at SNP rs2412522 on chromosome 4 for mean corpuscular hemoglobin concentration. We presented top 25 most significant GEE results with p-values in the range of 10 -6 to 10 -5 for hemostatic or hematological phenotypes. In relating 100K SNPs to known candidate genes, we identified two SNPs (rs1582055, rs4897475) in erythrocyte membrane protein band 4.1-like 2 ( EPB41L2 ) associated with hematological phenotypes (GEE p < 10 -3 ). In linkage analyses, the highest linkage LOD score for hemostatic factors was 3.3 for factor VII on chromosome 10 around 15 Mb, and for hematological phenotypes, LOD 3.4 for hemoglobin on chromosome 4 around 55 Mb. All GEE and FBAT association and variance components linkage results can be found at Using genome-wide association methodology, we have successfully identified a SNP in complete LD with a sequence variant previously shown to be strongly associated with factor VII, providing proof of principle for this approach. Further study of additional strongly associated SNPs and linked regions may identify novel variants that influence the inter-individual variability in hemostatic factors and hematological phenotypes.\n", - "-1 hematological phenotypes\n", - "-1 association\n", - "-1 and\n", - "-1 of\n", - "-1 and\n", - "-1 in\n", - "-1 Heart\n", - "-1 cardiovascular disease (CVD)\n", - "-1 with increased risk of\n", - "-1 of cardiovascular disease\n", - "-1 levels of\n", - "-1 associated with\n", - "-1 Increased\n", - "-1 as\n", - "-1 as\n", - "-1 anemia | anemia http://www.ebi.ac.uk/efo/EFO_0004272\n", - "-1 associations\n", - "-1 and\n", - "-1 at\n", - "-1 a\n", - "-1 small\n", - "-1 of\n", - "-1 phenotypic\n", - "-1 either trait\n", - "-1 trait in\n", - "-1 confirm\n", - "-1 and\n", - "-1 association\n", - "-1 and\n", - "-1 single | herpes zoster http://www.ebi.ac.uk/efo/EFO_0006510\n", - "1 , red blood cell count | erythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305\n", - "1 red blood cell count, | erythrocyte count http://www.ebi.ac.uk/efo/EFO_0004305\n", - "-1 , mean corpuscular hemoglobin concentration | mean corpuscular hemoglobin concentration http://www.ebi.ac.uk/efo/EFO_0004528\n", - "1 , plasminogen activator inhibitor-1 | plasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792\n", - "1 plasminogen activator inhibitor-1, | plasminogen activator inhibitor 1 measurement http://www.ebi.ac.uk/efo/EFO_0004792\n", - "-1 , von Willebrand factor | von willebrand factor measurement http://www.ebi.ac.uk/efo/EFO_0004629\n", - "-1 von Willebrand factor, | von willebrand factor measurement http://www.ebi.ac.uk/efo/EFO_0004629\n", - "1 , tissue plasminogen activator | tissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791\n", - "1 tissue plasminogen activator, | tissue plasminogen activator measurement http://www.ebi.ac.uk/efo/EFO_0004791\n", - "-1 , mean corpuscular volume | mean corpuscular volume http://www.ebi.ac.uk/efo/EFO_0004526\n", - "-1 mean corpuscular volume, | mean corpuscular volume http://www.ebi.ac.uk/efo/EFO_0004526\n", - "-1 corpuscular volume, mean | mean corpuscular volume http://www.ebi.ac.uk/efo/EFO_0004526\n", - "-1 volume, mean corpuscular | mean corpuscular volume http://www.ebi.ac.uk/efo/EFO_0004526\n", - "1 , factor VII | factor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619\n", - "1 factor VII, | factor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619\n", - "-1 factor, tissue\n", - "1 platelet aggregation, | platelet aggregation http://purl.obolibrary.org/obo/GO_0070527\n", - "-1 levels of\n", - "-1 fibrinogen, | fibrinogen measurement http://www.ebi.ac.uk/efo/EFO_0004623\n", - "-1 , D-dimer\n", - "-1 hematological phenotypes\n", - "-1 , viscosity\n", - "-1 viscosity,\n", - "1 , hemoglobin | hemoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509\n", - "1 hemoglobin, | hemoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509\n", - "-1 and\n", - "-1 in\n", - "-1 Heart\n", - "-1 FHS\n", - "-1 families\n", - "-1 association test\n", - "-1 , and\n", - "-1 hematological phenotypes\n", - "-1 association\n", - "-1 generalized\n", - "-1 adjusted\n", - "-1 of\n", - "-1 and\n", - "-1 analysis,\n", - "1 factor VII | factor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619\n", - "-1 , a\n", - "-1 In\n", - "-1 association\n", - "-1 was\n", - "-1 p\n", - "-1 at\n", - "-1 near\n", - "-1 and\n", - "-1 in\n", - "-1 disequilibrium\n", - "-1 LD\n", - "-1 of\n", - "-1 phenotypic\n", - "-1 mean corpuscular hemoglobin concentration | mean corpuscular hemoglobin concentration http://www.ebi.ac.uk/efo/EFO_0004528\n", - "-1 hematological phenotypes\n", - "-1 chromosome 4\n", - "-1 was\n", - "-1 at\n", - "-1 hematological phenotypes\n", - "-1 in\n", - "-1 of\n", - "-1 -5\n", - "-1 associated with\n", - "-1 hematological phenotypes\n", - "-1 In\n", - "-1 relating\n", - "-1 in\n", - "-1 erythrocyte | erythrocyte measurement http://www.ebi.ac.uk/efo/EFO_0005047\n", - "-1 protein | protein measurement http://www.ebi.ac.uk/efo/EFO_0004747\n", - "-1 p\n", - "1 factor VII | factor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619\n", - "-1 , and\n", - "-1 hematological phenotypes\n", - "-1 phenotypes,\n", - "-1 chromosome 4\n", - "-1 In\n", - "-1 was\n", - "-1 chromosome\n", - "1 hemoglobin | hemoglobin measurement http://www.ebi.ac.uk/efo/EFO_0004509\n", - "1 factor VII, | factor vii measurement http://www.ebi.ac.uk/efo/EFO_0004619\n", - "-1 associated with\n", - "-1 All\n", - "-1 and\n", - "-1 association\n", - "-1 and\n", - "-1 at\n", - "-1 association\n", - "-1 a\n", - "-1 in\n", - "-1 LD\n", - "-1 a\n", - "-1 of\n", - "-1 hematological phenotypes\n", - "-1 of\n", - "-1 associated\n", - "-1 and\n", - "-1 in\n", - "-1 and\n", - "\n", - "17903295\n", - "aging traits 19811\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19812\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19813\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19814\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19815\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19816\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19817\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "morbidity-free survival 19818\n", - "\tdisease free survival http://www.ebi.ac.uk/efo/EFO_0000409 disease-free survival|morbidity-free survival\n", - "morbidity-free survival 19819\n", - "\tdisease free survival http://www.ebi.ac.uk/efo/EFO_0000409 disease-free survival|morbidity-free survival\n", - "morbidity-free survival 19820\n", - "\tdisease free survival http://www.ebi.ac.uk/efo/EFO_0000409 disease-free survival|morbidity-free survival\n", - "morbidity-free survival 19189\n", - "\tdisease free survival http://www.ebi.ac.uk/efo/EFO_0000409 disease-free survival|morbidity-free survival\n", - "morbidity-free survival 19190\n", - "\tdisease free survival http://www.ebi.ac.uk/efo/EFO_0000409 disease-free survival|morbidity-free survival\n", - "aging traits 19191\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19192\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "aging traits 19193\n", - "\tage at menopause http://www.ebi.ac.uk/efo/EFO_0004704 \n", - "\texercise test http://www.ebi.ac.uk/efo/EFO_0004328 stress test\n", - "\taging http://purl.obolibrary.org/obo/GO_0007568 senescence|aging\n", - "\tage at death http://www.ebi.ac.uk/efo/EFO_0005056 \n", - "Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study. Family studies and heritability estimates provide evidence for a genetic contribution to variation in the human life span. We conducted a genome wide association study (Affymetrix 100K SNP GeneChip) for longevity-related traits in a community-based sample. We report on 5 longevity and aging traits in up to 1345 Framingham Study participants from 330 families. Multivariable-adjusted residuals were computed using appropriate models (Cox proportional hazards, logistic, or linear regression) and the residuals from these models were used to test for association with qualifying SNPs (70, 987 autosomal SNPs with genotypic call rate ≥80%, minor allele frequency ≥10%, Hardy-Weinberg test p ≥ 0.001). In family-based association test (FBAT) models, 8 SNPs in two regions approximately 500 kb apart on chromosome 1 (physical positions 73,091,610 and 73, 527,652) were associated with age at death (p-value < 10 -5 ). The two sets of SNPs were in high linkage disequilibrium (minimum r 2 = 0.58). The top 30 SNPs for generalized estimating equation (GEE) tests of association with age at death included rs10507486 (p = 0.0001) and rs4943794 (p = 0.0002), SNPs intronic to FOXO1A , a gene implicated in lifespan extension in animal models. FBAT models identified 7 SNPs and GEE models identified 9 SNPs associated with both age at death and morbidity-free survival at age 65 including rs2374983 near PON1 . In the analysis of selected candidate genes, SNP associations (FBAT or GEE p-value < 0.01) were identified for age at death in or near the following genes: FOXO1A, GAPDH, KL, LEPR, PON1, PSEN1, SOD2, and WRN . Top ranked SNP associations in the GEE model for age at natural menopause included rs6910534 (p = 0.00003) near FOXO3a and rs3751591 (p = 0.00006) in CYP19A1 . Results of all longevity phenotype-genotype associations for all autosomal SNPs are web posted at . Longevity and aging traits are associated with SNPs on the Affymetrix 100K GeneChip. None of the associations achieved genome-wide significance. These data generate hypotheses and serve as a resource for replication as more genes and biologic pathways are proposed as contributing to longevity and healthy aging.\n", - "-1 age-related phenotypes\n", - "-1 Genetic\n", - "-1 of\n", - "-1 longevity | longevity http://www.ebi.ac.uk/efo/EFO_0004300\n", - "-1 and\n", - "-1 selected\n", - "-1 a\n", - "-1 association\n", - "-1 in\n", - "-1 Family\n", - "-1 and\n", - "-1 a\n", - "-1 genetic\n", - "-1 in\n", - "-1 human\n", - "-1 longevity-related traits\n", - "-1 conducted\n", - "-1 a\n", - "-1 genome\n", - "-1 association\n", - "-1 in\n", - "-1 a\n", - "-1 aging traits\n", - "-1 5\n", - "-1 longevity | longevity http://www.ebi.ac.uk/efo/EFO_0004300\n", - "-1 and\n", - "-1 in\n", - "-1 families\n", - "-1 association with\n", - "-1 test p\n", - "-1 and\n", - "-1 genotypic\n", - "-1 rate\n", - "-1 associated with age at\n", - "1 age at death | sudden cardiac arrest http://www.ebi.ac.uk/efo/EFO_0004278\n", - "-1 association test\n", - "-1 In\n", - "-1 in\n", - "-1 chromosome\n", - "-1 and\n", - "-1 -5\n", - "-1 of\n", - "-1 in\n", - "-1 high\n", - "-1 disequilibrium\n", - "-1 association with age at\n", - "1 age at death | sudden cardiac arrest http://www.ebi.ac.uk/efo/EFO_0004278\n", - "-1 , a\n", - "-1 generalized\n", - "-1 tests\n", - "-1 of\n", - "-1 p\n", - "-1 and\n", - "-1 p\n", - "-1 in\n", - "-1 in\n", - "-1 animal\n", - "1 age at death | sudden cardiac arrest http://www.ebi.ac.uk/efo/EFO_0004278\n", - "-1 associated with\n", - "1 morbidity-free survival | disease free survival http://www.ebi.ac.uk/efo/EFO_0000409\n", - "-1 and\n", - "-1 and\n", - "-1 at\n", - "1 age | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "-1 near\n", - "1 age at death | sudden cardiac arrest http://www.ebi.ac.uk/efo/EFO_0004278\n", - "-1 , and\n", - "-1 In\n", - "-1 analysis\n", - "-1 of\n", - "-1 selected\n", - "-1 associations\n", - "-1 in\n", - "-1 near\n", - "-1 associations\n", - "-1 in\n", - "1 age | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "-1 at\n", - "1 menopause | age at menopause http://www.ebi.ac.uk/efo/EFO_0004704\n", - "-1 p\n", - "-1 near\n", - "-1 and\n", - "-1 p\n", - "-1 in\n", - "-1 CYP19A1\n", - "-1 of\n", - "-1 all\n", - "-1 longevity | longevity http://www.ebi.ac.uk/efo/EFO_0004300\n", - "-1 associations\n", - "-1 all\n", - "-1 at\n", - "-1 aging traits\n", - "-1 associated with\n", - "-1 Longevity | longevity http://www.ebi.ac.uk/efo/EFO_0004300\n", - "-1 and\n", - "-1 of the\n", - "-1 associations\n", - "-1 as a\n", - "-1 generate\n", - "-1 and\n", - "-1 as\n", - "-1 and\n", - "-1 biologic\n", - "-1 as\n", - "-1 longevity | longevity http://www.ebi.ac.uk/efo/EFO_0004300\n", - "-1 and\n", - "1 aging | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "\n", - "17903296\n", - "bone mineral density 19843\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "bone mineral density 19844\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "hip geometry 19598\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19599\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19600\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19601\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19602\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19603\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19604\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19605\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19606\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19607\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19608\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19609\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "bone mineral density 19610\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "bone mineral density 19611\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "bone mineral density 19612\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "bone mineral density 19613\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "bone mineral density 19614\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "bone mineral density 19174\n", - "\tbone density http://www.ebi.ac.uk/efo/EFO_0003923 density\n", - "hip geometry 19175\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19176\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19177\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "hip geometry 19178\n", - "\thip geometry http://www.ebi.ac.uk/efo/EFO_0004685 \n", - "Genome-wide association with bone mass and geometry in the Framingham Heart Study. Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms. We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study (FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density (BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation (GEE) and family-based association tests (FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates ≥80%, HWE p ≥ 0.001, and MAF ≥10% in up to 1141 phenotyped individuals (495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers. Heritability estimates for all bone phenotypes were 30–66%. LOD scores ≥3.0 were found on chromosomes 15 (1.5 LOD confidence interval: 51,336,679–58,934,236 bp) and 22 (35,890,398–48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 Ă— 10 -6 and 2.5 Ă— 10 -5 , respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits (including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association (FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR ; rs1884052 and rs3778099 in ESR1 ; rs4988300 in LRP5 ; rs2189480 in VDR ; rs2075555 in COLIA1 ; rs10519297 and rs2008691 in CYP19 , as well as SNPs in PPARG (rs10510418 and rs2938392) and ANKH (rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at . The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.\n", - "-1 association with bone\n", - "-1 mass\n", - "-1 and\n", - "-1 in\n", - "-1 Heart\n", - "-1 is characterized by\n", - "-1 heritable traits\n", - "-1 Osteoporosis | osteoporosis http://www.ebi.ac.uk/efo/EFO_0003882\n", - "-1 low\n", - "-1 bone\n", - "-1 mass\n", - "-1 and\n", - "-1 bone\n", - "-1 these traits\n", - "-1 no\n", - "-1 association\n", - "-1 and\n", - "-1 genotyping\n", - "-1 primary quantitative traits\n", - "1 bone mineral density\n", - "-1 of the hip\n", - "-1 associations with\n", - "-1 , and\n", - "-1 in\n", - "-1 Heart\n", - "-1 FHS\n", - "-1 genetic\n", - "-1 BMD\n", - "-1 indices | ankle brachial index http://www.ebi.ac.uk/efo/EFO_0003912\n", - "-1 test associations with\n", - "-1 trait values,\n", - "-1 residual trait\n", - "-1 generalized\n", - "-1 and\n", - "-1 association\n", - "-1 tests\n", - "-1 sex\n", - "-1 as\n", - "-1 as\n", - "-1 sexes\n", - "-1 , and\n", - "-1 genotypic\n", - "-1 rates\n", - "-1 p\n", - "-1 in\n", - "-1 phenotyped\n", - "-1 and\n", - "-1 age | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "-1 analysis\n", - "-1 was\n", - "-1 bone phenotypes\n", - "-1 all\n", - "-1 chromosomes\n", - "-1 and\n", - "-1 primary phenotypes\n", - "-1 associations with\n", - "-1 in\n", - "-1 at\n", - "-1 p\n", - "-1 and\n", - "-1 associations\n", - "-1 in\n", - "-1 at\n", - "-1 p\n", - "-1 -5 ,\n", - "-1 and\n", - "-1 all\n", - "-1 Ă—\n", - "-1 and\n", - "-1 Ă—\n", - "-1 Of the\n", - "-1 BMD traits\n", - "-1 , and\n", - "-1 of\n", - "-1 associated\n", - "-1 in\n", - "-1 near\n", - "-1 not\n", - "-1 osteoporosis | osteoporosis http://www.ebi.ac.uk/efo/EFO_0003882\n", - "-1 geometric traits\n", - "-1 associations\n", - "-1 BMD\n", - "-1 and\n", - "-1 bone\n", - "-1 osteoporosis, | osteoporosis http://www.ebi.ac.uk/efo/EFO_0003882\n", - "-1 , as\n", - "-1 association\n", - "-1 p\n", - "-1 was\n", - "-1 several\n", - "-1 in\n", - "-1 as\n", - "-1 in\n", - "-1 and\n", - "-1 in\n", - "-1 in\n", - "-1 in\n", - "-1 in\n", - "-1 and\n", - "-1 in\n", - "-1 as\n", - "-1 in\n", - "-1 and\n", - "-1 and\n", - "-1 and\n", - "-1 All\n", - "-1 and\n", - "-1 as\n", - "-1 an\n", - "-1 at\n", - "-1 FHS\n", - "-1 offers\n", - "-1 an\n", - "-1 and\n", - "-1 suggested\n", - "-1 osteoporosis | osteoporosis http://www.ebi.ac.uk/efo/EFO_0003882\n", - "\n", - "17903297\n", - "volumetric brain mri 19552\n", - "\tvolumetric brain mri http://www.ebi.ac.uk/efo/EFO_0004868 \n", - "volumetric brain mri 19553\n", - "\tvolumetric brain mri http://www.ebi.ac.uk/efo/EFO_0004868 \n", - "volumetric brain mri 19554\n", - "\tvolumetric brain mri http://www.ebi.ac.uk/efo/EFO_0004868 \n", - "cognitive test performance 19555\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19556\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19557\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19558\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19559\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19560\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19561\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19562\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19563\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19564\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19218\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19219\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19220\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "cognitive test performance 19221\n", - "\tneuropsychological test http://www.ebi.ac.uk/efo/EFO_0003926 test\n", - "volumetric brain mri 19222\n", - "\tvolumetric brain mri http://www.ebi.ac.uk/efo/EFO_0004868 \n", - "volumetric brain mri 19551\n", - "\tvolumetric brain mri http://www.ebi.ac.uk/efo/EFO_0004868 \n", - "Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham study. Brain magnetic resonance imaging (MRI) and cognitive tests can identify heritable endophenotypes associated with an increased risk of developing stroke, dementia and Alzheimer's disease (AD). We conducted a genome-wide association (GWA) and linkage analysis exploring the genetic basis of these endophenotypes in a community-based sample. A total of 705 stroke- and dementia-free Framingham participants (age 62 +9 yrs, 50% male) who underwent volumetric brain MRI and cognitive testing (1999–2002) were genotyped. We used linear models adjusting for first degree relationships via generalized estimating equations (GEE) and family based association tests (FBAT) in additive models to relate qualifying single nucleotide polymorphisms (SNPs, 70,987 autosomal on Affymetrix 100K Human Gene Chip with minor allele frequency ≥ 0.10, genotypic call rate ≥ 0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001) to multivariable-adjusted residuals of 9 MRI measures including total cerebral brain (TCBV), lobar, ventricular and white matter hyperintensity (WMH) volumes, and 6 cognitive factors/tests assessing verbal and visuospatial memory, visual scanning and motor speed, reading, abstract reasoning and naming. We determined multipoint identity-by-descent utilizing 10,592 informative SNPs and 613 short tandem repeats and used variance component analyses to compute LOD scores. The strongest gene-phenotype association in FBAT analyses was between SORL1 (rs1131497; p = 3.2 Ă— 10 -6 ) and abstract reasoning, and in GEE analyses between CDH4 (rs1970546; p = 3.7 Ă— 10 -8 ) and TCBV. SORL1 plays a role in amyloid precursor protein processing and has been associated with the risk of AD. Among the 50 strongest associations (25 each by GEE and FBAT) were other biologically interesting genes. Polymorphisms within 28 of 163 candidate genes for stroke, AD and memory impairment were associated with the endophenotypes studied at p < 0.001. We confirmed our previously reported linkage of WMH on chromosome 4 and describe linkage of reading performance to a marker on chromosome 18 (GATA11A06), previously linked to dyslexia (LOD scores = 2.2 and 5.1). Our results suggest that genes associated with clinical neurological disease also have detectable effects on subclinical phenotypes. These hypothesis generating data illustrate the use of an unbiased approach to discover novel pathways that may be involved in brain aging, and could be used to replicate observations made in other studies.\n", - "-1 of brain\n", - "-1 cognitive test\n", - "-1 Genetic\n", - "-1 aging | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "-1 and\n", - "-1 a\n", - "-1 association\n", - "-1 and\n", - "-1 analysis\n", - "-1 in\n", - "-1 Alzheimer's disease (AD)\n", - "-1 increased risk of developing\n", - "-1 associated with an\n", - "-1 cognitive tests\n", - "-1 stroke, | stroke http://www.ebi.ac.uk/efo/EFO_0000712\n", - "-1 , dementia | alzheimers disease http://www.ebi.ac.uk/efo/EFO_0000249\n", - "-1 Brain | brain measurement http://www.ebi.ac.uk/efo/EFO_0004464\n", - "-1 resonance\n", - "-1 and\n", - "-1 endophenotypes\n", - "-1 and\n", - "-1 conducted\n", - "-1 a\n", - "-1 association\n", - "-1 and\n", - "-1 analysis\n", - "-1 genetic\n", - "-1 of\n", - "-1 endophenotypes\n", - "-1 in\n", - "-1 a\n", - "1 volumetric brain MRI | volumetric brain mri http://www.ebi.ac.uk/efo/EFO_0004868\n", - "-1 stroke- | stroke http://www.ebi.ac.uk/efo/EFO_0000712\n", - "-1 - and\n", - "-1 A\n", - "-1 of\n", - "-1 age | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "-1 and\n", - "-1 cognitive\n", - "-1 genotyped\n", - "-1 and white matter\n", - "-1 white matter hyperintensity\n", - "-1 , genotypic\n", - "-1 , and\n", - "-1 , and\n", - "-1 memory,\n", - "-1 , reading | reading http://www.ebi.ac.uk/efo/EFO_0005229\n", - "-1 reading, | reading http://www.ebi.ac.uk/efo/EFO_0005229\n", - "-1 adjusting\n", - "-1 generalized\n", - "-1 and\n", - "-1 family\n", - "-1 association\n", - "-1 tests\n", - "-1 in\n", - "-1 relate\n", - "-1 single | herpes zoster http://www.ebi.ac.uk/efo/EFO_0006510\n", - "-1 Human\n", - "-1 rate\n", - "-1 of\n", - "-1 cerebral\n", - "-1 brain | brain measurement http://www.ebi.ac.uk/efo/EFO_0004464\n", - "-1 cognitive\n", - "-1 and\n", - "-1 and\n", - "-1 reasoning\n", - "-1 and\n", - "-1 and\n", - "-1 short\n", - "-1 and\n", - "-1 reasoning,\n", - "-1 , and\n", - "-1 association\n", - "-1 in\n", - "-1 was\n", - "-1 p\n", - "-1 Ă—\n", - "-1 and\n", - "-1 in\n", - "-1 p\n", - "-1 Ă—\n", - "-1 and\n", - "-1 associated with\n", - "-1 plays\n", - "-1 a\n", - "-1 in\n", - "-1 protein | protein measurement http://www.ebi.ac.uk/efo/EFO_0004747\n", - "-1 and\n", - "-1 of\n", - "-1 AD\n", - "-1 associations\n", - "-1 and\n", - "-1 biologically\n", - "-1 stroke, | stroke http://www.ebi.ac.uk/efo/EFO_0000712\n", - "-1 , AD\n", - "-1 memory impairment\n", - "-1 associated with\n", - "-1 of\n", - "-1 and\n", - "-1 endophenotypes\n", - "-1 at\n", - "-1 p\n", - "-1 chromosome 4\n", - "-1 to a\n", - "-1 chromosome 18\n", - "-1 confirmed\n", - "-1 of\n", - "-1 and\n", - "-1 of\n", - "-1 reading | reading http://www.ebi.ac.uk/efo/EFO_0005229\n", - "-1 dyslexia | dyslexia http://www.ebi.ac.uk/efo/EFO_0005424\n", - "-1 and\n", - "-1 associated with\n", - "-1 neurological disease\n", - "-1 subclinical phenotypes\n", - "-1 suggest\n", - "-1 clinical\n", - "-1 detectable\n", - "-1 aging, | aging http://purl.obolibrary.org/obo/GO_0007568\n", - "-1 , and\n", - "-1 generating\n", - "-1 of\n", - "-1 an\n", - "-1 in\n", - "-1 brain | brain measurement http://www.ebi.ac.uk/efo/EFO_0004464\n", - "-1 in\n", - "\n", - "17903298\n", - "diabetes related insulin traits 19592\n", - "\ta1c measurement http://www.ebi.ac.uk/efo/EFO_0004541 hba1c levels|glycosylated haemoglobin a level|glycosylated hemoglobin a level|glycated hemoglobin levels\n", - "\tfasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466 fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "\tinsulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471 insulin sensitivity test\n", - "\tinsulin resistance http://www.ebi.ac.uk/efo/EFO_0002614 drug resistance to insulin (disorder)\n", - "diabetes related insulin traits 19593\n", - "\ta1c measurement http://www.ebi.ac.uk/efo/EFO_0004541 hba1c levels|glycosylated haemoglobin a level|glycosylated hemoglobin a level|glycated hemoglobin levels\n", - "\tfasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466 fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "\tinsulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471 insulin sensitivity test\n", - "\tinsulin resistance http://www.ebi.ac.uk/efo/EFO_0002614 drug resistance to insulin (disorder)\n", - "fasting plasma glucose 19594\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "fasting plasma glucose 19595\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "fasting plasma glucose 19596\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "fasting plasma glucose 19597\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "diabetes related insulin traits 19194\n", - "\ta1c measurement http://www.ebi.ac.uk/efo/EFO_0004541 hba1c levels|glycosylated haemoglobin a level|glycosylated hemoglobin a level|glycated hemoglobin levels\n", - "\tfasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466 fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "\tinsulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471 insulin sensitivity test\n", - "\tinsulin resistance http://www.ebi.ac.uk/efo/EFO_0002614 drug resistance to insulin (disorder)\n", - "diabetes related insulin traits 19195\n", - "\ta1c measurement http://www.ebi.ac.uk/efo/EFO_0004541 hba1c levels|glycosylated haemoglobin a level|glycosylated hemoglobin a level|glycated hemoglobin levels\n", - "\tfasting blood insulin measurement http://www.ebi.ac.uk/efo/EFO_0004466 fasting blood insulin|fasting blood insulin level|fasting insulin-related traits\n", - "\tinsulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471 insulin sensitivity test\n", - "\tinsulin resistance http://www.ebi.ac.uk/efo/EFO_0002614 drug resistance to insulin (disorder)\n", - "fasting plasma glucose 19196\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "fasting plasma glucose 19197\n", - "\tfasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465 fasting glucose-related traits|fasting blood glucose level|fasting plasma glucose\n", - "diabetes (incident) 19198\n", - "\tdiabetes mellitus http://www.ebi.ac.uk/efo/EFO_0000400 dm - diabetes mellitus|diabetes mellitus\n", - "Genome-wide association with diabetes-related traits in the Framingham Heart Study. Susceptibility to type 2 diabetes may be conferred by genetic variants having modest effects on risk. Genome-wide fixed marker arrays offer a novel approach to detect these variants. We used the Affymetrix 100K SNP array in 1,087 Framingham Offspring Study family members to examine genetic associations with three diabetes-related quantitative glucose traits (fasting plasma glucose (FPG), hemoglobin A1c, 28-yr time-averaged FPG (tFPG)), three insulin traits (fasting insulin, HOMA-insulin resistance, and 0–120 min insulin sensitivity index); and with risk for diabetes. We used additive generalized estimating equations (GEE) and family-based association test (FBAT) models to test associations of SNP genotypes with sex-age-age 2 -adjusted residual trait values, and Cox survival models to test incident diabetes. We found 415 SNPs associated (at p < 0.001) with at least one of the six quantitative traits in GEE, 242 in FBAT (18 overlapped with GEE for 639 non-overlapping SNPs), and 128 associated with incident diabetes (31 overlapped with the 639) giving 736 non-overlapping SNPs. Of these 736 SNPs, 439 were within 60 kb of a known gene. Additionally, 53 SNPs (of which 42 had r 2 < 0.80 with each other) had p < 0.01 for incident diabetes AND (all 3 glucose traits OR all 3 insulin traits, OR 2 glucose traits and 2 insulin traits); of these, 36 overlapped with the 736 other SNPs. Of 100K SNPs, one (rs7100927) was in moderate LD (r 2 = 0.50) with TCF7L2 (rs7903146), and was associated with risk of diabetes (Cox p-value 0.007, additive hazard ratio for diabetes = 1.56) and with tFPG (GEE p-value 0.03). There were no common (MAF > 1%) 100K SNPs in LD (r 2 > 0.05) with ABCC8 A1369S (rs757110), KCNJ11 E23K (rs5219), or SNPs in CAPN10 or HNFa . PPARG P12A (rs1801282) was not significantly associated with diabetes or related traits. Framingham 100K SNP data is a resource for association tests of known and novel genes with diabetes and related traits posted at . Framingham 100K data replicate the TCF7L2 association with diabetes.\n", - "-1 association with\n", - "-1 diabetes-related traits\n", - "-1 in\n", - "-1 Heart\n", - "-1 type 2 diabetes\n", - "-1 genetic\n", - "-1 offer\n", - "-1 a\n", - "-1 detect\n", - "1 fasting plasma glucose | fasting blood glucose measurement http://www.ebi.ac.uk/efo/EFO_0004465\n", - "-1 , hemoglobin A1c\n", - "-1 hemoglobin A1c,\n", - "-1 associations with\n", - "-1 quantitative glucose\n", - "-1 glucose traits\n", - "-1 insulin traits\n", - "-1 insulin, | insulin measurement http://www.ebi.ac.uk/efo/EFO_0004467\n", - "-1 resistance,\n", - "-1 , and\n", - "1 insulin sensitivity | insulin sensitivity measurement http://www.ebi.ac.uk/efo/EFO_0004471\n", - "-1 in\n", - "-1 family\n", - "-1 genetic\n", - "-1 fasting\n", - "-1 and\n", - "-1 diabetes\n", - "-1 trait values,\n", - "-1 association test\n", - "-1 test associations\n", - "-1 -adjusted\n", - "-1 residual trait\n", - "-1 , and\n", - "-1 generalized\n", - "-1 and\n", - "-1 of\n", - "-1 genotypes\n", - "-1 survival | survival time http://www.ebi.ac.uk/efo/EFO_0000714\n", - "-1 diabetes\n", - "-1 six quantitative traits\n", - "-1 of the\n", - "-1 , and\n", - "-1 associated with\n", - "-1 associated\n", - "-1 at\n", - "-1 p\n", - "-1 at\n", - "-1 in\n", - "-1 in\n", - "-1 diabetes\n", - "-1 Of\n", - "-1 of\n", - "-1 a\n", - "-1 glucose traits\n", - "-1 insulin traits\n", - "-1 traits,\n", - "-1 glucose traits\n", - "-1 insulin traits\n", - "-1 of\n", - "-1 p\n", - "-1 diabetes\n", - "-1 AND\n", - "-1 all\n", - "-1 all\n", - "-1 and\n", - "-1 of\n", - "-1 , and\n", - "-1 associated with\n", - "-1 Of\n", - "-1 was\n", - "-1 in\n", - "-1 moderate\n", - "-1 LD\n", - "-1 was\n", - "-1 of\n", - "-1 diabetes\n", - "-1 ratio\n", - "-1 diabetes\n", - "-1 and\n", - "-1 no\n", - "-1 in\n", - "-1 LD\n", - "-1 in\n", - "-1 associated with diabetes\n", - "-1 related traits\n", - "-1 was\n", - "-1 not\n", - "-1 and related traits\n", - "-1 a\n", - "-1 association\n", - "-1 tests\n", - "-1 of\n", - "-1 and\n", - "-1 diabetes\n", - "-1 at\n", - "-1 association with diabetes\n", - "\n" - ] - } - ], + "outputs": [], "source": [ - "# let's look at a few examples\n", - "for doc in corpus.documents[:10]:\n", - " doc_id = doc.name\n", - " print doc.name\n", - " for phen_id2 in gold_agg_dict_phen[doc_id]: # iterate over gwc_id's in doc\n", - " print agg_id2phen[phen_id2].name, phen_id2 # print its name and id\n", - " for eq_phen in agg_id2phen[phen_id2].equivalents: # loop over equivalent phens\n", - " print '\\t', eq_phen.name, eq_phen.ontology_ref, eq_phen.synonyms # print name, ref, synonyms\n", - " print ' '.join(s.text for s in id2doc[doc_id].sentences)\n", - " for candidate in phen_c:\n", - " if candidate.context.document != doc: continue\n", - "# print gt_dict[candidate.uid], candidate.get_span(), [agg_id2phen[phen_id].name for phen_id in phen2id.get(change_name(candidate.get_span()),set())]\n", - " print gt_dict[c2uid(candidate)], candidate.get_span(), \n", - " phen_id = phen2id.get(change_name(candidate.get_span()), None)\n", - " if phen_id: print '|', id2phen[phen_id].name, id2phen[phen_id].ontology_ref,\n", - " print\n", - " print" + "sv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Create training set" + "We can compare these labels against the predictions of our classifier." ] }, { "cell_type": "code", - "execution_count": 118, + "execution_count": 70, "metadata": { "collapsed": false }, @@ -3698,137 +1301,72 @@ "name": "stdout", "output_type": "stream", "text": [ - "Training set size: 25716\n", - "Gold set size: 25715\n", - "Positive labels in training set: 1286\n", - "Negative labels in training set: 24430\n", - "Positive labels in gold set: 1389\n", - "Negative labels in gold set: 24326\n" + "CPU times: user 150 ms, sys: 29.2 ms, total: 179 ms\n", + "Wall time: 318 ms\n", + "Generating annotations for 300 candidates...\n", + "[========================================] 100%\n", + "Loading sparse Label matrix...\n", + "CPU times: user 6.15 s, sys: 298 ms, total: 6.45 s\n", + "Wall time: 7.44 s\n" ] } ], "source": [ - "import numpy as np\n", + "from snorkel.annotations import LabelManager\n", "\n", - "# Split into train and test set\n", - "candidates = phen_c\n", - "training_candidates = []\n", - "gold_candidates = []\n", - "gold_labels = []\n", - "n_half = len(candidates)/2\n", - "for c in candidates[:n_half]:\n", - " uid = c2uid(c)\n", - " if uid in gt_dict:\n", - " gold_candidates.append(c)\n", - " gold_labels.append(gt_dict[uid])\n", - " else:\n", - " training_candidates.append(c)\n", - "training_candidates.extend(candidates[n_half:])\n", - "gold_labels = np.array(gold_labels)\n", - "print \"Training set size: %s\" % len(training_candidates)\n", - "print \"Gold set size: %s\" % len(gold_candidates)\n", - "print \"Positive labels in training set: %s\" % len([c for c in training_candidates if gt_dict.get(c2uid(c),0)==1])\n", - "print \"Negative labels in training set: %s\" % len([c for c in training_candidates if gt_dict.get(c2uid(c),0)==-1])\n", - "print \"Positive labels in gold set: %s\" % len([c for c in gold_candidates if gt_dict[c2uid(c)]==1])\n", - "print \"Negative labels in gold set: %s\" % len([c for c in gold_candidates if gt_dict[c2uid(c)]==-1])" + "label_manager = LabelManager()\n", + "\n", + "%time Y_test = label_manager.load(session, labeled_c, 'Snorkel Phenotype Annotations')\n", + "%time L_test = label_manager.create(session, labeled_c, 'Phenotype LF Test Labels', f=LFs)\n", + "# session.commit()" ] }, { "cell_type": "code", - "execution_count": 140, + "execution_count": 72, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "from nltk.stem import PorterStemmer\n", - "import re\n", - "import string\n", - "punctuation = set(string.punctuation)\n", - "stemmer = PorterStemmer()\n", - "\n", - "# load set of dictionary phenotypes\n", - "kb = KnowledgeBase()\n", - "phenotype_list = kb.get_phenotype_candidates() # TODO: load disease names from NCBI\n", - "phenotype_list = [phenotype for phenotype in phenotype_list]\n", - "phenotype_set = set(phenotype_list)\n", - "\n", - "# load stopwords\n", - "with open('../data/phenotypes/snorkel/dicts/manual_stopwords.txt') as f:\n", - " stopwords = {line.strip() for line in f}\n", - "stopwords.update(['analysis', 'age', 'drug', 'community', 'detect', 'activity', 'genome',\n", - " 'genetic', 'phenotype', 'response', 'population', 'parameter', 'diagnosis',\n", - " 'level', 'survival', 'maternal', 'paternal', 'clinical', 'joint', 'related',\n", - " 'status', 'risk', 'protein', 'association', 'signal', 'pathway', 'genotype', 'scale',\n", - " 'human', 'family', 'heart', 'general', 'chromosome', 'susceptibility', 'select', \n", - " 'medical', 'system', 'trait', 'suggest', 'confirm', 'subclinical', 'receptor', \n", - " 'class', 'adult', 'affecting', 'increase'])\n", - "from nltk.corpus import stopwords as nltk_stopwords\n", - "stopwords.update(nltk_stopwords.words('english'))\n", - "stopwords = {stemmer.stem(word) for word in stopwords}\n", - "\n", - "# small helpers\n", - "def get_phenotype(entity, stem=False):\n", - " phenotype = entity.get_span()\n", - " if stem: phenotype = stemmer.stem(phenotype)\n", - " return phenotype.lower()\n", - "\n", - "def stem_list(L):\n", - " return [stemmer.stem(l.lower()) for l in L]\n", - "\n", - "def LF_gt(m):\n", - " return gt_dict.get(m.uid, 0) if m in training_candidates else 0\n", - "\n", - "# positive LFs\n", - "def LF_first_sentence(m):\n", - " return +10 if m.context.position == 0 else 0\n", - "def LF_from_regex(m):\n", - " if m.context.position == 0 and not regex_phen_matcher._f(m) and not LF_bad_words(m): return +5\n", - " else: return 0\n", - "def LF_with_acronym(m):\n", - " post_txt = ''.join(m.post_window('words',d=5))\n", - " return +1 if re.search(r'\\([A-Z]{2,4}\\)', post_txt) else 0\n", - "def LF_many_words(m):\n", - " return +1 if len(m.get_span().split()) >= 3 else 0\n", - "def LF_start_of_sentence(m):\n", - " return +1 if m.get_word_start() <= 3 else 0\n", - "\n", - "LFs_pos = [LF_first_sentence, LF_with_acronym, LF_from_regex, LF_many_words]\n", - "\n", - "# negative LFs\n", - "def LF_bad_words(m):\n", - " bad_words = ['disease', 'single', 'map', 'genetic variation', '( p <']\n", - " return -100 if any(m.get_span().lower().startswith(b) for b in bad_words) else 0\n", - "def LF_short(m):\n", - " txt = m.get_attrib_span('words', 3)\n", - " return -50 if len(txt) < 5 else 0\n", - "def LF_no_nouns(m):\n", - " return -10 if not any(t.startswith('NN') for t in m.get_attrib_tokens('poses')) else 0\n", - "def LF_pvalue(m):\n", - " txt = m.get_span().lower()\n", - " return -100 if 'p <' in txt or 'p =' in txt else 0\n", - "def LF_not_true_phen(m):\n", - " indicator_ngrams = ['factor for']\n", - " return -1 if any(ngram in m.pre_ngrams() for ngram in indicator_ngrams) else 0\n", - "def LF_not_first_sentences(m):\n", - " return -1 if m.context.position > 1 else 0\n", - "def LF_stopwords(m):\n", - " txt = m.get_span()\n", - " txt = ''.join(ch for ch in txt if ch not in punctuation)\n", - " words = txt.lower().split()\n", - " return -10 if all(word in stopwords for word in words) or \\\n", - " all(stemmer.stem(word) in stopwords for word in words) or \\\n", - " all(change_name(word) in stopwords for word in words) else 0\n", - "\n", - "\n", - "LFs_neg = [LF_bad_words, LF_short, LF_no_nouns, LF_pvalue, LF_not_true_phen, LF_not_first_sentences, LF_stopwords]\n", + "gen_model.score(L_test, Y_test, labeled_c)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Classify all the papers" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now have a classifier that can score phenotype mentions in the text. Let's apply this classifier to assign a phenotype to each of our papers." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Analyze / Visualize" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "If a mention occurs in the title, its probably correct, we can take it.\n", "\n", - "LFs = LFs_pos + LFs_neg" + "Question: what papers did not have any disease mentions in the title?" ] }, { "cell_type": "code", - "execution_count": 141, + "execution_count": 64, "metadata": { "collapsed": false }, @@ -3837,206 +1375,56 @@ "name": "stdout", "output_type": "stream", "text": [ - "Applying LFs...\n", - "Featurizing...\n", - "Building feature index...\n", - "Extracting features...\n", - "0/353330\n", - "5000/353330\n", - "10000/353330\n", - "15000/353330\n", - "20000/353330\n", - "25000/353330\n", - "30000/353330\n", - "35000/353330\n", - "40000/353330\n", - "45000/353330\n", - "50000/353330\n", - "55000/353330\n", - "60000/353330\n", - "65000/353330\n", - "70000/353330\n", - "75000/353330\n", - "80000/353330\n", - "85000/353330\n", - "90000/353330\n", - "95000/353330\n", - "100000/353330\n", - "105000/353330\n", - "110000/353330\n", - "115000/353330\n", - "120000/353330\n", - "125000/353330\n", - "130000/353330\n", - "135000/353330\n", - "140000/353330\n", - "145000/353330\n", - "150000/353330\n", - "155000/353330\n", - "160000/353330\n", - "165000/353330\n", - "170000/353330\n", - "175000/353330\n", - "180000/353330\n", - "185000/353330\n", - "190000/353330\n", - "195000/353330\n", - "200000/353330\n", - "205000/353330\n", - "210000/353330\n", - "215000/353330\n", - "220000/353330\n", - "225000/353330\n", - "230000/353330\n", - "235000/353330\n", - "240000/353330\n", - "245000/353330\n", - "250000/353330\n", - "255000/353330\n", - "260000/353330\n", - "265000/353330\n", - "270000/353330\n", - "275000/353330\n", - "280000/353330\n", - "285000/353330\n", - "290000/353330\n", - "295000/353330\n", - "300000/353330\n", - "305000/353330\n", - "310000/353330\n", - "315000/353330\n", - "320000/353330\n", - "325000/353330\n", - "330000/353330\n", - "335000/353330\n", - "340000/353330\n", - "345000/353330\n", - "350000/353330\n", - "============================================================\n", - "LF Summary Statistics: 11 LFs applied to 25716 candidates\n", - "------------------------------------------------------------\n", - "Coverage (candidates w/ > 0 labels):\t\t95.76%\n", - "Overlap (candidates w/ > 1 labels):\t\t86.51%\n", - "Conflict (candidates w/ conflicting labels):\t9.13%\n", - "============================================================\n" + "Generating annotations for 7468 candidates...\n", + "[========================================] 100%\n", + "Loading sparse Label matrix...\n", + "CPU times: user 1min 34s, sys: 534 ms, total: 1min 35s\n", + "Wall time: 1min 35s\n" ] } ], "source": [ - "from snorkel.snorkel import TrainingSet\n", - "from snorkel.features import NgramFeaturizer\n", + "from snorkel.annotations import LabelManager\n", "\n", - "training_set = TrainingSet(training_candidates, LFs, featurizer=NgramFeaturizer())" + "label_manager = LabelManager()\n", + "\n", + "# delete existing labels\n", + "session.rollback()\n", + "session.query(AnnotationKeySet).filter(AnnotationKeySet.name == 'Phenotype LF All Labels').delete()\n", + "%time L_all = label_manager.create(session, phen_c, 'Phenotype LF All Labels', f=LFs)" ] }, { - "cell_type": "code", - "execution_count": 142, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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conflictscoveragejoverlaps
LF_first_sentence 0.484523 0.666122 0 0.666122
LF_with_acronym 0.017188 0.023021 1 0.020610
LF_from_regex 0.238956 0.323923 2 0.323923
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LF_bad_words 0.194431 0.913828 4 0.913828
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" - ], - "text/plain": [ - " conflicts coverage j overlaps\n", - "LF_first_sentence 0.484523 0.666122 0 0.666122\n", - "LF_with_acronym 0.017188 0.023021 1 0.020610\n", - "LF_from_regex 0.238956 0.323923 2 0.323923\n", - "LF_many_words 0.028815 0.040675 3 0.036786\n", - "LF_bad_words 0.194431 0.913828 4 0.913828\n", - "\n", - "[5 rows x 4 columns]" - ] - }, - "execution_count": 142, - "metadata": {}, - "output_type": "execute_result" - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "lf_stats = training_set.lf_stats()\n", - "lf_stats[:5]" + "Let's now visualize what we found." ] }, { "cell_type": "code", - "execution_count": 143, + "execution_count": 67, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ - "from snorkel.snorkel import Learner, PipelinedLearner\n", - "import snorkel.learning\n", - "from snorkel.learning import LogReg\n", - "\n", - "learner = Learner(training_set, model=snorkel.learning.LogReg())\n", + "scores = gen_model.odds(L_all)\n", + "score_dict = { doc.name : list() for doc in corpus.documents }\n", + "for s, c in zip(scores, phen_c):\n", + " score_dict[c[0].parent.document.name].append((s,c))\n", "\n", - "# Splitting into CV and test set\n", - "n_half = len(gold_candidates)/2\n", - "test_candidates = gold_candidates[:n_half]\n", - "test_labels = gold_labels[:n_half]\n", - "cv_candidates = gold_candidates[n_half:]\n", - "cv_labels = gold_labels[n_half:]" + "results = dict()\n", + "for pmid, preds in score_dict.items():\n", + " if preds: \n", + " best_c = sorted(preds, reverse=True)[0][1]\n", + " results[best_c[0].parent.document.name] = best_c\n", + " " ] }, { "cell_type": "code", - "execution_count": 144, + "execution_count": 75, "metadata": { "collapsed": false }, @@ -4045,2710 +1433,53 @@ "name": "stdout", "output_type": "stream", "text": [ - "============================================================\n", - "Testing mu = 1.00e-05, lf_w0 = 1.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-05\n", - "\tLearning epoch = 0\tGradient mag. = 2.926988\n", - "\tLearning epoch = 250\tGradient mag. = 1.497813\n", - "\tLearning epoch = 500\tGradient mag. = 0.976698\n", - "\tLearning epoch = 750\tGradient mag. = 0.695397\n", - "Final gradient magnitude for rate=0.01, mu=1e-05: 0.544\n", - "Applying LFs...\n", - "Featurizing...\n", - "============================================================\n", - "Testing mu = 1.00e-05, lf_w0 = 2.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-05\n", - "\tLearning epoch = 0\tGradient mag. = 2.594038\n", - "\tLearning epoch = 250\tGradient mag. = 1.203560\n", - "\tLearning epoch = 500\tGradient mag. = 0.733687\n", - "\tLearning epoch = 750\tGradient mag. = 0.542583\n", - "Final gradient magnitude for rate=0.01, mu=1e-05: 0.625\n", - "============================================================\n", - "Testing mu = 1.00e-07, lf_w0 = 1.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-07\n", - "\tLearning epoch = 0\tGradient mag. = 2.926988\n", - "\tLearning epoch = 250\tGradient mag. = 1.497798\n", - "\tLearning epoch = 500\tGradient mag. = 0.976675\n", - "\tLearning epoch = 750\tGradient mag. = 0.695372\n", - "Final gradient magnitude for rate=0.01, mu=1e-07: 0.544\n", - "============================================================\n", - "Testing mu = 1.00e-07, lf_w0 = 2.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-07\n", - "\tLearning epoch = 0\tGradient mag. = 2.594038\n", - "\tLearning epoch = 250\tGradient mag. = 1.203542\n", - "\tLearning epoch = 500\tGradient mag. = 0.733660\n", - "\tLearning epoch = 750\tGradient mag. = 0.542519\n", - "Final gradient magnitude for rate=0.01, mu=1e-07: 0.625\n" + "Document 23401653 A genome-wide association study for corneal curvature identifies the platelet-derived growth factor receptor α gene as a quantitative trait locus for eye size in white Europeans.\n", + "SnorkelPhenotype(Span(\"a quantitative trait\", parent=5231, chars=[123,142], words=[16,18])) [15, 0, 0, 1, 0, 0, 0, 0, 0, 0]\n", + "[(32.713146397913356, SnorkelPhenotype(Span(\"a quantitative trait\", parent=5231, chars=[123,142], words=[16,18]))), (30.92358318810064, SnorkelPhenotype(Span(\"corneal\", parent=5231, chars=[36,42], words=[5,5]))), (30.797373076203804, SnorkelPhenotype(Span(\"platelet-derived growth factor\", parent=5231, chars=[69,98], words=[9,11]))), (29.825674221961485, SnorkelPhenotype(Span(\"eye size\", parent=5231, chars=[154,161], words=[21,22]))), (29.825674221961485, SnorkelPhenotype(Span(\"size in\", parent=5231, chars=[158,164], words=[22,23])))]\n", + "\n", + "Document 22423221 A meta-analysis and genome-wide association study of platelet count and mean platelet volume in african americans.\n", + "SnorkelPhenotype(Span(\"Mean Platelet Volume\", parent=4056, chars=[72,91], words=[10,12])) [15, 0, 5, 1, 0, 0, 0, 0, 0, 0]\n", + "[(30.797373076203804, SnorkelPhenotype(Span(\"Mean Platelet Volume\", parent=4056, chars=[72,91], words=[10,12]))), (29.825674221961485, SnorkelPhenotype(Span(\"Platelet Count\", parent=4056, chars=[53,66], words=[7,8]))), (1.0979089661391537, SnorkelPhenotype(Span(\"platelet count\", parent=4057, chars=[41,54], words=[5,6]))), (0.97169885424231905, SnorkelPhenotype(Span(\"mean platelet volume\", parent=4057, chars=[60,79], words=[8,10]))), (-1.8207841004818972, SnorkelPhenotype(Span(\"platelet count\", parent=4058, chars=[158,171], words=[25,26])))]\n", + "\n", + "Document 17903292 A genome-wide association for kidney function and endocrine-related traits in the NHLBI's Framingham Heart Study.\n", + "SnorkelPhenotype(Span(\"endocrine-related traits\", parent=640, chars=[50,73], words=[7,8])) [15, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n", + "[(31.741447543671036, SnorkelPhenotype(Span(\"endocrine-related traits\", parent=640, chars=[50,73], words=[7,8]))), (30.92358318810064, SnorkelPhenotype(Span(\"kidney\", parent=640, chars=[30,35], words=[4,4]))), (2.0696078203814725, SnorkelPhenotype(Span(\"Glomerular filtration rate\", parent=641, chars=[0,25], words=[0,2]))), (1.7992811302869307, SnorkelPhenotype(Span(\"urinary albumin excretion\", parent=641, chars=[37,61], words=[7,9]))), (0.82758227604461165, SnorkelPhenotype(Span(\"of kidney\", parent=641, chars=[81,89], words=[15,16])))]\n", + "\n", + "Document 23532257 Genome-wide association study in a Chinese population identifies a susceptibility locus for type 2 diabetes at 7q32 near PAX4.\n", + "SnorkelPhenotype(Span(\"type 2 diabetes\", parent=5394, chars=[92,106], words=[12,14])) [15, 0, 5, 1, 0, 0, 0, 0, 0, 0]\n", + "[(30.797373076203804, SnorkelPhenotype(Span(\"type 2 diabetes\", parent=5394, chars=[92,106], words=[12,14]))), (2.0696078203814725, SnorkelPhenotype(Span(\"type 2 diabetes\", parent=5395, chars=[37,51], words=[5,7]))), (-0.84908524623957815, SnorkelPhenotype(Span(\"type 2 diabetes\", parent=5396, chars=[123,137], words=[20,22]))), (-499.95470848020221, SnorkelPhenotype(Span(\"populations\", parent=5395, chars=[86,96], words=[13,13]))), (-501.7754925806841, SnorkelPhenotype(Span(\"population\", parent=5396, chars=[65,74], words=[11,11])))]\n", + "\n", + "Document 20663923 A genome-wide scan for common alleles affecting risk for autism.\n", + "SnorkelPhenotype(Span(\"autism\", parent=2141, chars=[57,62], words=[9,9])) [15, 0, 5, 0, 0, 0, 0, 0, 0, 0]\n", + "[(29.825674221961485, SnorkelPhenotype(Span(\"autism\", parent=2141, chars=[57,62], words=[9,9]))), (2.0696078203814725, SnorkelPhenotype(Span(\"autism spectrum disorders\", parent=2142, chars=[9,33], words=[1,3]))), (-1.8207841004818972, SnorkelPhenotype(Span(\"Autism\", parent=2143, chars=[39,44], words=[7,7]))), (-101.78593800949686, SnorkelPhenotype(Span(\"rigorously\", parent=2143, chars=[93,102], words=[16,16]))), (-501.7754925806841, SnorkelPhenotype(Span(\"association with\", parent=2143, chars=[215,230], words=[34,35])))]\n", + "\n" ] } ], "source": [ - "from snorkel.learning_utils import GridSearch\n", + "for d in corpus.documents[:5]:\n", + " print d, kb.paper_by_pmid(d.name).title\n", + " print unicode(results.get(d.name, None)), [LF(results.get(d.name)) for LF in LFs]\n", + " try:\n", + " print sorted(score_dict[d.name], reverse=True)[:5]\n", + " except UnicodeEncodeError:\n", + " print 'Unicode error'\n", + " print" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false + }, + "source": [ "\n", - "gs = GridSearch(learner, ['mu', 'lf_w0'], [[1e-5, 1e-7],[1.0,2.0]])\n", - "gs_stats = gs.fit(cv_candidates, cv_labels)" + "### Save results" ] }, { "cell_type": "code", - "execution_count": 145, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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mulf_w0Prec.Rec.F1
0 0.00001 1 0.401734 0.199713 0.266795
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" - ], - "text/plain": [ - " mu lf_w0 Prec. Rec. F1\n", - "0 0.00001 1 0.401734 0.199713 0.266795\n", - "1 0.00001 2 0.401734 0.199713 0.266795\n", - "2 0.00000 1 0.401734 0.199713 0.266795\n", - "3 0.00000 2 0.401734 0.199713 0.266795\n", - "\n", - "[4 rows x 5 columns]" - ] - }, - "execution_count": 145, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "gs_stats" - ] - }, - { - "cell_type": "code", - "execution_count": 146, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Applying LFs...\n", - "Featurizing...\n", - "========================================\n", - "Test set size:\t12857\n", - "----------------------------------------\n", - "Precision:\t0.391691394659\n", - "Recall:\t\t0.205928237129\n", - "F1 Score:\t0.269938650307\n", - "----------------------------------------\n", - "TP: 132 | FP: 205 | TN: 11779 | FN: 509\n", - "========================================\n" - ] - } - ], - "source": [ - "learner.test_wmv(test_candidates, test_labels)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Save and analyze the results" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Analyze / Visualize" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "If a mention occurs in the title, its probably correct, we can take it.\n", - "\n", - "Question: what papers did not have any disease mentions in the title?" - ] - }, - { - "cell_type": "code", - "execution_count": 147, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Applying LFs...\n", - "Featurizing...\n", - "34\n", - "23935956 Genome wide association analysis of a founder population identified TAF3 as a gene for MCHC in humans.\n", - "22359512 Genome-wide association study identifies novel loci associated with circulating phospho- and sphingolipid concentrations.\n", - "23056639 A genome-wide association study of circulating galectin-3.\n", - "22044751 Heritability and genome-wide association analysis of renal sinus fat accumulation in the Framingham Heart Study.\n", - "23776548 Genetic loci for retinal arteriolar microcirculation.\n", - "24489884 Genome-wide association study of proneness to anger.\n", - "22205951 Genome-wide association study in bipolar patients stratified by co-morbidity.\n", - "21935397 Genome-wide population-based association study of extremely overweight young adults--the GOYA study.\n", - "24847357 Genome wide association study of SNP-, gene-, and pathway-based approaches to identify genes influencing susceptibility to Staphylococcus aureus infections.\n", - "25226531 Common variation near ROBO2 is associated with expressive vocabulary in infancy.\n", - "21878437 Genome-wide association study of circulating retinol levels.\n", - "21418511 Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited.\n", - "25056061 Biological insights from 108 schizophrenia-associated genetic loci.\n", - "20442857 Genome-wide association study of Lp-PLA(2) activity and mass in the Framingham Heart Study.\n", - "19587794 Common genetic variation near the phospholamban gene is associated with cardiac repolarisation: meta-analysis of three genome-wide association studies.\n", - "25729143 Genome-wide association study identifies three novel genetic markers associated with elite endurance performance.\n", - "21533175 Eight common genetic variants associated with serum DHEAS levels suggest a key role in ageing mechanisms.\n", - "23636237 Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.\n", - "19197348 Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae.\n", - "24625756 Genetic determinants influencing human serum metabolome among African Americans.\n", - "22832960 A genome-wide meta-analysis of association studies of Cloninger's Temperament Scales.\n", - "21502949 Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N=1198) using genome-wide search.\n", - "21844884 Genome-wide meta-analysis identifies variants associated with platinating agent susceptibility across populations\n", - "22470424 A high-density genome-wide association screen of sporadic ALS in US veterans.\n", - "20921969 Genome-wide association study of antipsychotic-induced QTc interval prolongation.\n", - "21931564 A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection.\n", - "21060863 Four novel Loci (19q13, 6q24, 12q24, and 5q14) influence the microcirculation in vivo.\n", - "24068947 Common variants in left/right asymmetry genes and pathways are associated with relative hand skill.\n", - "21876539 Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM.\n", - "19305408 Common variants at ten loci influence QT interval duration in the QTGEN Study.\n", - "25241763 Meta-analysis of genome-wide association studies identifies novel loci that influence cupping and the glaucomatous process.\n", - "24871463 GWAS identifies novel SLE susceptibility genes and explains the association of the HLA region.\n", - "21810271 Combined analysis of three genome-wide association studies on vWF and FVIII plasma levels.\n", - "24800985 Genome-wide association study of maternal and inherited loci for conotruncal heart defects.\n" - ] - } - ], - "source": [ - "preds = learner.predict_wmv(phen_c)\n", - "results = [c for p, c in zip(preds, phen_c) if p > 0 and c.context.position == 0]\n", - "doc_set = {c.context.document.name for c in results}\n", - "missing_docs = {doc.name for doc in corpus.documents} - doc_set\n", - "docs = sorted(list(missing_docs))\n", - "print len(docs)\n", - "for d in missing_docs:\n", - " print d, kb.paper_by_pmid(d).title" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's not visualize what we found." - ] - }, - { - "cell_type": "code", - "execution_count": 148, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Applying LFs...\n", - "Featurizing...\n" - ] - } - ], - "source": [ - "scores = learner.score_wmv(phen_c)\n", - "score_dict = { doc.name : list() for doc in corpus.documents }\n", - "for s, c in zip(scores, phen_c):\n", - " score_dict[c.context.document.name].append((s,c))\n", - "\n", - "results = dict()\n", - "for pmid, preds in score_dict.items():\n", - " if preds: \n", - " best_c = sorted(preds, reverse=True)[0][1]\n", - " results[best_c.context.document.name] = best_c\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 149, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Document('17447842', Corpus (GWAS Corpus)) Novel Crohn disease locus identified by genome-wide association maps to a gene desert on 5p13.1 and modulates expression of PTGER4.\n", - "Span(\"Crohn Disease\", context=None, chars=[6,18], words=[1,2]) 0\n", - "[(8.4683739780796756, Span(\"Crohn Disease\", context=None, chars=[6,18], words=[1,2])), (1.9897015784049445, Span(\"Crohn disease (CD),\", context=None, chars=[42,60], words=[6,11])), (-0.23047794690884227, Span(\"associated with disease\", context=None, chars=[96,118], words=[16,18])), (-1.225371353759513, Span(\"to disease\", context=None, chars=[93,102], words=[11,12])), (-1.225371353759513, Span(\"-values\", context=None, chars=[88,94], words=[13,14]))]\n", - "\n", - "Document('17658951', Corpus (GWAS Corpus)) Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits.\n", - "Span(\"Obesity-Related Traits\", context=None, chars=[90,111], words=[13,14]) 0\n", - "[(8.4683739780796756, Span(\"Obesity-Related Traits\", context=None, chars=[90,111], words=[13,14])), (0.99489340685067074, Span(\"major risk factor\", context=None, chars=[102,118], words=[16,18])), (0.0, Span(\"obesity\", context=None, chars=[4,10], words=[1,1])), (-0.0055719707282433362, Span(\"type 2 diabetes\", context=None, chars=[124,138], words=[20,22])), (-0.23047794690884227, Span(\", hip circumference\", context=None, chars=[109,127], words=[17,19]))]\n", - "\n", - "Document('17684544', Corpus (GWAS Corpus)) Systematic association mapping identifies NELL1 as a novel IBD disease gene.\n", - "Span(\"IBD Disease\", context=None, chars=[61,71], words=[8,9]) 0\n", - "[(8.4683739780796756, Span(\"IBD Disease\", context=None, chars=[61,71], words=[8,9])), (1.9897015784049445, Span(\"Crohn disease (CD),\", context=None, chars=[0,18], words=[0,5])), (1.9897015784049445, Span(\"inflammatory bowel disease (IBD),\", context=None, chars=[36,68], words=[9,15])), (0.76433022464543154, Span(\"ulcerative colitis (UC)\", context=None, chars=[39,61], words=[6,10])), (-0.23047794690884227, Span(\"of the disease\", context=None, chars=[155,168], words=[20,22]))]\n", - "\n", - "Document('17903292', Corpus (GWAS Corpus)) A genome-wide association for kidney function and endocrine-related traits in the NHLBI's Framingham Heart Study.\n", - "Span(\"kidney\", context=None, chars=[30,35], words=[4,4]) 0\n", - "[(13.078313166568094, Span(\"kidney\", context=None, chars=[30,35], words=[4,4])), (8.4683739780796756, Span(\"endocrine-related traits\", context=None, chars=[50,73], words=[7,8])), (1.9897015784049445, Span(\"urinary albumin excretion\", context=None, chars=[37,61], words=[7,9])), (1.9897015784049445, Span(\"Glomerular filtration rate\", context=None, chars=[0,25], words=[0,2])), (0.76433022464543154, Span(\"Thyroid stimulating hormone\", context=None, chars=[0,26], words=[0,2]))]\n", - "\n", - "Document('17903293', Corpus (GWAS Corpus)) Genome-wide association with select biomarker traits in the Framingham Heart Study.\n", - "Span(\"biomarker traits\", context=None, chars=[36,51], words=[4,5]) 0\n", - "[(8.4683739780796756, Span(\"biomarker traits\", context=None, chars=[36,51], words=[4,5])), (0.76433022464543154, Span(\"C-reactive protein (CRP)\", context=None, chars=[231,254], words=[63,67])), (0.0, Span(\"into disease\", context=None, chars=[37,48], words=[4,5])), (0.0, Span(\"biomarkers\", context=None, chars=[9,18], words=[1,1])), (-0.23047794690884227, Span(\"B-type natriuretic peptide\", context=None, chars=[153,178], words=[43,45]))]\n", - "\n", - "Document('17903294', Corpus (GWAS Corpus)) Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study.\n", - "Span(\"hematological phenotypes\", context=None, chars=[71,94], words=[9,10]) 0\n", - "[(8.4683739780796756, Span(\"hematological phenotypes\", context=None, chars=[71,94], words=[9,10])), (1.9897015784049445, Span(\"of cardiovascular disease\", context=None, chars=[110,134], words=[16,18])), (1.9897015784049445, Span(\"cardiovascular disease (CVD)\", context=None, chars=[113,140], words=[17,21])), (0.0, Span(\"anemia\", context=None, chars=[62,67], words=[9,9])), (-0.23047794690884227, Span(\"mean corpuscular hemoglobin concentration\", context=None, chars=[102,142], words=[19,22]))]\n", - "\n", - "Document('17903295', Corpus (GWAS Corpus)) Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study.\n", - "Span(\"longevity\", context=None, chars=[22,30], words=[3,3]) 0\n", - "[(13.078313166568094, Span(\"longevity\", context=None, chars=[22,30], words=[3,3])), (8.4683739780796756, Span(\"age-related phenotypes\", context=None, chars=[45,66], words=[6,7])), (-0.23047794690884227, Span(\"age at death\", context=None, chars=[111,122], words=[21,23])), (-0.23047794690884227, Span(\"age at death\", context=None, chars=[84,95], words=[14,16])), (-0.23047794690884227, Span(\"age at death\", context=None, chars=[84,95], words=[15,17]))]\n", - "\n", - "Document('17903296', Corpus (GWAS Corpus)) Genome-wide association with bone mass and geometry in the Framingham Heart Study.\n", - "Span(\"association with bone\", context=None, chars=[12,32], words=[1,3]) 0\n", - "[(14.073206573418766, Span(\"association with bone\", context=None, chars=[12,32], words=[1,3])), (0.76433022464543154, Span(\"bone mineral density\", context=None, chars=[158,177], words=[27,29])), (0.0, Span(\"Osteoporosis\", context=None, chars=[0,11], words=[0,0])), (0.0, Span(\"heritable traits\", context=None, chars=[79,94], words=[12,13])), (-0.23047794690884227, Span(\"test associations with\", context=None, chars=[3,24], words=[1,3]))]\n", - "\n", - "Document('17903297', Corpus (GWAS Corpus)) Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham Study.\n", - "Span(\"of brain\", context=None, chars=[19,26], words=[2,3]) 0\n", - "[(13.078313166568094, Span(\"of brain\", context=None, chars=[19,26], words=[2,3])), (13.078313166568094, Span(\"cognitive test\", context=None, chars=[45,58], words=[8,9])), (1.9897015784049445, Span(\"Alzheimer's disease (AD)\", context=None, chars=[166,189], words=[25,30])), (0.99489340685067074, Span(\"increased risk of developing\", context=None, chars=[116,143], words=[17,20])), (0.99480817155427381, Span(\"resonance\", context=None, chars=[15,23], words=[2,2]))]\n", - "\n", - "Document('17903298', Corpus (GWAS Corpus)) Genome-wide association with diabetes-related traits in the Framingham Heart Study.\n", - "Span(\"diabetes-related traits\", context=None, chars=[29,51], words=[3,4]) 0\n", - "[(8.4683739780796756, Span(\"diabetes-related traits\", context=None, chars=[29,51], words=[3,4])), (0.99489340685067074, Span(\"type 2 diabetes\", context=None, chars=[18,32], words=[2,4])), (0.76433022464543154, Span(\"fasting plasma glucose\", context=None, chars=[178,199], words=[25,27])), (-0.23047794690884227, Span(\"associated with diabetes\", context=None, chars=[46,69], words=[8,10])), (-0.23047794690884227, Span(\"association with diabetes\", context=None, chars=[44,68], words=[6,8]))]\n", - "\n", - "Document('17903300', Corpus (GWAS Corpus)) Genome-wide association to body mass index and waist circumference: the Framingham Heart Study 100K project.\n", - "Span(\"body mass index\", context=None, chars=[27,41], words=[3,5]) 0\n", - "[(14.073206573418766, Span(\"body mass index\", context=None, chars=[27,41], words=[3,5])), (13.078313166568094, Span(\"waist circumference\", context=None, chars=[47,65], words=[7,8])), (1.9897015784049445, Span(\"cardiovascular disease (CVD)\", context=None, chars=[31,58], words=[5,9])), (0.76433022464543154, Span(\"Body mass index\", context=None, chars=[0,14], words=[0,2])), (0.0, Span(\"Obesity\", context=None, chars=[0,6], words=[0,0]))]\n", - "\n", - "Document('17903301', Corpus (GWAS Corpus)) Genome-wide association of echocardiographic dimensions, brachial artery endothelial function and treadmill exercise responses in the Framingham Heart Study.\n", - "Span(\"artery\", context=None, chars=[66,71], words=[7,7]) 0\n", - "[(13.078313166568094, Span(\"artery\", context=None, chars=[66,71], words=[7,7])), (8.4683739780796756, Span(\"exercise responses\", context=None, chars=[108,125], words=[12,13])), (0.99480817155427381, Span(\"artery\", context=None, chars=[123,128], words=[19,19])), (0.0, Span(\", exercise\", context=None, chars=[52,61], words=[7,8])), (0.0, Span(\"cardiovascular disease\", context=None, chars=[199,220], words=[32,33]))]\n", - "\n", - "Document('17903302', Corpus (GWAS Corpus)) Framingham Heart Study 100K Project: genome-wide associations for blood pressure and arterial stiffness.\n", - "Span(\"blood pressure\", context=None, chars=[66,79], words=[9,10]) 0\n", - "[(13.078313166568094, Span(\"blood pressure\", context=None, chars=[66,79], words=[9,10])), (13.078313166568094, Span(\"arterial stiffness\", context=None, chars=[85,102], words=[12,13])), (0.99489340685067074, Span(\", kidney disease\", context=None, chars=[117,132], words=[19,21])), (0.99489340685067074, Span(\"high blood pressure\", context=None, chars=[49,67], words=[8,10])), (0.0, Span(\"stroke,\", context=None, chars=[111,117], words=[18,19]))]\n", - "\n", - "Document('17903303', Corpus (GWAS Corpus)) Genome-wide association study for subclinical atherosclerosis in major arterial territories in the NHLBI's Framingham Heart Study.\n", - "Span(\"atherosclerosis\", context=None, chars=[46,60], words=[5,5]) 0\n", - "[(13.078313166568094, Span(\"atherosclerosis\", context=None, chars=[46,60], words=[5,5])), (0.99489340685067074, Span(\"of cardiovascular disease\", context=None, chars=[139,163], words=[19,21])), (0.99480817155427381, Span(\"atherosclerosis\", context=None, chars=[12,26], words=[1,1])), (0.0, Span(\"heritable phenotypes\", context=None, chars=[73,92], words=[11,12])), (-0.23047794690884227, Span(\"common carotid artery\", context=None, chars=[272,292], words=[52,54]))]\n", - "\n", - "Document('17903304', Corpus (GWAS Corpus)) Framingham Heart Study 100K project: genome-wide associations for cardiovascular disease outcomes.\n", - "Span(\"cardiovascular disease\", context=None, chars=[66,87], words=[9,10]) 0\n", - "[(8.4683739780796756, Span(\"cardiovascular disease\", context=None, chars=[66,87], words=[9,10])), (1.9897015784049445, Span(\"heart failure (HF),\", context=None, chars=[114,132], words=[21,26])), (1.9897015784049445, Span(\"Cardiovascular disease (CVD)\", context=None, chars=[0,27], words=[0,4])), (1.9897015784049445, Span(\"coronary heart disease (CHD),\", context=None, chars=[76,104], words=[12,18])), (1.9897015784049445, Span(\", heart failure\", context=None, chars=[112,126], words=[20,22]))]\n", - "\n", - "Document('17903305', Corpus (GWAS Corpus)) A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study.\n", - "Span(\"prostate cancer\", context=None, chars=[46,60], words=[7,8]) 0\n", - "[(13.078313166568094, Span(\"prostate cancer\", context=None, chars=[46,60], words=[7,8])), (13.078313166568094, Span(\"of breast\", context=None, chars=[32,40], words=[4,5])), (0.0, Span(\"prostate cancer\", context=None, chars=[11,25], words=[2,3])), (0.0, Span(\"Breast\", context=None, chars=[0,5], words=[0,0])), (0.0, Span(\"cancers\", context=None, chars=[54,60], words=[8,8]))]\n", - "\n", - "Document('17903306', Corpus (GWAS Corpus)) Genome-wide association study of electrocardiographic and heart rate variability traits: the Framingham Heart Study.\n", - "Span(\"heart rate\", context=None, chars=[58,67], words=[6,7]) 0\n", - "[(13.078313166568094, Span(\"heart rate\", context=None, chars=[58,67], words=[6,7])), (8.4683739780796756, Span(\"variability traits\", context=None, chars=[69,86], words=[8,9])), (0.99480817155427381, Span(\"heart rate\", context=None, chars=[41,50], words=[6,7])), (0.0, Span(\", conduction\", context=None, chars=[101,112], words=[16,17])), (0.0, Span(\"conduction,\", context=None, chars=[103,113], words=[17,18]))]\n", - "\n", - "Document('17903307', Corpus (GWAS Corpus)) Framingham Heart Study genome-wide association: results for pulmonary function measures.\n", - "Span(\"pulmonary function\", context=None, chars=[60,77], words=[8,9]) 0\n", - "[(13.078313166568094, Span(\"pulmonary function\", context=None, chars=[60,77], words=[8,9])), (0.99489340685067074, Span(\"chronic obstructive pulmonary disease (COPD)\", context=None, chars=[72,115], words=[10,16])), (0.76433022464543154, Span(\"body mass index\", context=None, chars=[212,226], words=[32,34])), (0.76433022464543154, Span(\"vital capacity (FVC), forced\", context=None, chars=[200,227], words=[34,40])), (0.76433022464543154, Span(\"forced vital capacity (FVC),\", context=None, chars=[193,220], words=[33,39]))]\n", - "\n", - "Document('17903308', Corpus (GWAS Corpus)) Genome-wide association of sleep and circadian phenotypes.\n", - "Span(\"sleep\", context=None, chars=[27,31], words=[3,3]) 0\n", - "[(13.078313166568094, Span(\"sleep\", context=None, chars=[27,31], words=[3,3])), (8.4683739780796756, Span(\"circadian phenotypes\", context=None, chars=[37,56], words=[5,6])), (0.0, Span(\"circadian rhythms\", context=None, chars=[62,78], words=[8,9])), (0.0, Span(\"sleepiness\", context=None, chars=[47,56], words=[6,6])), (-1.225371353759513, Span(\"sleep phenotypes\", context=None, chars=[23,38], words=[4,5]))]\n", - "\n", - "Document('17997608', Corpus (GWAS Corpus)) The GLUT9 gene is associated with serum uric acid levels in Sardinia and Chianti cohorts.\n", - "Span(\"Serum Uric Acid Levels\", context=None, chars=[36,57], words=[6,9]) 0\n", - "[(14.073206573418766, Span(\"Serum Uric Acid Levels\", context=None, chars=[36,57], words=[6,9])), (0.99489340685067074, Span(\"serum uric acid levels\", context=None, chars=[5,26], words=[1,4])), (0.0, Span(\"crystal arthropathy\", context=None, chars=[64,82], words=[10,11])), (0.0, Span(\"cardiovascular morbidity\", context=None, chars=[123,146], words=[19,20])), (-0.23047794690884227, Span(\"uric acid levels\", context=None, chars=[217,232], words=[34,36]))]\n", - "\n", - "Document('18159244', Corpus (GWAS Corpus)) Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants.\n", - "Span(\"Obesity Associated\", context=None, chars=[102,119], words=[19,20]) 0\n", - "[(14.07312133812237, Span(\"Obesity Associated\", context=None, chars=[102,119], words=[19,20])), (13.078313166568094, Span(\"Obesity\", context=None, chars=[60,66], words=[11,11])), (13.078313166568094, Span(\"Onset\", context=None, chars=[46,50], words=[9,9])), (0.0, Span(\"problem\", context=None, chars=[26,32], words=[5,5])), (0.0, Span(\"Obesity\", context=None, chars=[0,6], words=[0,0]))]\n", - "\n", - "Document('18262040', Corpus (GWAS Corpus)) LDL-cholesterol concentrations: a genome-wide association study.\n", - "Span(\"LDL-cholesterol\", context=None, chars=[0,14], words=[0,0]) 0\n", - "[(13.078313166568094, Span(\"LDL-cholesterol\", context=None, chars=[0,14], words=[0,0])), (0.99489340685067074, Span(\"of cardiovascular disease\", context=None, chars=[53,77], words=[9,11])), (0.0, Span(\"development\", context=None, chars=[41,51], words=[8,8])), (0.0, Span(\"LDL cholesterol\", context=None, chars=[0,14], words=[0,1])), (-1.225371353759513, Span(\"LDL cholesterol\", context=None, chars=[149,163], words=[42,43]))]\n", - 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"[(13.078313166568094, Span(\"Breast Cancer\", context=None, chars=[89,101], words=[12,13])), (0.0, Span(\"breast cancer\", context=None, chars=[42,54], words=[8,9])), (0.0, Span(\"of breast\", context=None, chars=[39,47], words=[7,8])), (-0.23047794690884227, Span(\"Hereditary breast cancer\", context=None, chars=[159,182], words=[27,29])), (-0.23047794690884227, Span(\"age of onset\", context=None, chars=[90,101], words=[14,16]))]\n", - "\n", - "Document('25533491', Corpus (GWAS Corpus)) Genome-wide association study of survival from sepsis due to pneumonia: an observational cohort study.\n", - "Span(\"due to pneumonia\", context=None, chars=[54,69], words=[7,9]) 0\n", - "[(14.073206573418766, Span(\"due to pneumonia\", context=None, chars=[54,69], words=[7,9])), (13.078313166568094, Span(\"sepsis\", context=None, chars=[47,52], words=[6,6])), (0.99489340685067074, Span(\"major cause of death,\", context=None, chars=[25,45], words=[5,9])), (0.0, Span(\"Sepsis\", context=None, chars=[0,5], words=[0,0])), (0.0, Span(\", disability\", context=None, chars=[45,56], words=[9,10]))]\n", - "\n", - "Document('25551457', Corpus (GWAS Corpus)) No evidence for genome-wide interactions on plasma fibrinogen by smoking, alcohol consumption and body mass index: results from meta-analyses of 80,607 subjects.\n", - "Span(\"Body Mass Index\", context=None, chars=[98,112], words=[14,16]) 0\n", - "[(14.073206573418766, Span(\"Body Mass Index\", context=None, chars=[98,112], words=[14,16])), (14.073206573418766, Span(\", Alcohol Consumption\", context=None, chars=[72,92], words=[10,12])), (13.078313166568094, Span(\"Fibrinogen\", context=None, chars=[51,60], words=[7,7])), (13.078313166568094, Span(\"Smoking,\", context=None, chars=[65,72], words=[9,10])), (1.9897015784049445, Span(\"body mass index\", context=None, chars=[168,182], words=[25,27]))]\n", - "\n", - "Document('25569183', Corpus (GWAS Corpus)) A genome-wide association study of marginal zone lymphoma shows association to the HLA region.\n", - "Span(\"marginal zone lymphoma\", context=None, chars=[35,56], words=[5,7]) 0\n", - "[(14.073206573418766, Span(\"marginal zone lymphoma\", context=None, chars=[35,56], words=[5,7])), (1.9897015784049445, Span(\"Marginal zone lymphoma\", context=None, chars=[0,21], words=[0,2])), (0.99489340685067074, Span(\"B-cell non-Hodgkin lymphoma\", context=None, chars=[65,91], words=[13,15])), (0.76433022464543154, Span(\"Marginal zone lymphoma\", context=None, chars=[0,21], words=[0,2])), (0.0, Span(\"of B-cell\", context=None, chars=[62,70], words=[12,13]))]\n", - "\n", - "Document('25625606', Corpus (GWAS Corpus)) Investigating the Genetics of Hippocampal Volume in Older Adults without Dementia.\n", - "Span(\"Dementia\", context=None, chars=[73,80], words=[10,10]) 0\n", - "Unicode error\n", - "\n", - "Document('25628645', Corpus (GWAS Corpus)) Identification of genetic variants or genes that are associated with Homoharringtonine (HHT) response through a genome-wide association study in human lymphoblastoid cell lines (LCLs).\n", - "Span(\"Homoharringtonine\", context=None, chars=[69,85], words=[10,10]) 0\n", - "[(14.07312133812237, Span(\"Homoharringtonine\", context=None, chars=[69,85], words=[10,10])), (0.99489340685067074, Span(\"chronic myeloid leukemia\", context=None, chars=[87,110], words=[16,18])), (0.99480817155427381, Span(\"Homoharringtonine\", context=None, chars=[0,16], words=[0,0])), (-0.23047794690884227, Span(\"response to HHT\", context=None, chars=[118,132], words=[20,22])), (-0.23047794690884227, Span(\"response to HHT\", context=None, chars=[63,77], words=[10,12]))]\n", - "\n", - "Document('25629512', Corpus (GWAS Corpus)) New loci and coding variants confer risk for age-related macular degeneration in East Asians.\n", - "Span(\"age-related macular degeneration\", context=None, chars=[45,76], words=[8,10]) 0\n", - "[(14.073206573418766, Span(\"age-related macular degeneration\", context=None, chars=[45,76], words=[8,10])), (1.9897015784049445, Span(\"Age-related macular degeneration (AMD)\", context=None, chars=[0,37], words=[0,5])), (0.76433022464543154, Span(\"Age-related macular degeneration (AMD)\", context=None, chars=[0,37], words=[0,5])), (0.0, Span(\"blindness,\", context=None, chars=[59,68], words=[11,12])), (-0.23047794690884227, Span(\"of the disease\", context=None, chars=[167,180], words=[28,30]))]\n", - "\n", - "Document('25705158', Corpus (GWAS Corpus)) Pathway Analysis of Metabolic Syndrome Using a Genome-Wide Association Study of Korea Associated Resource (KARE) Cohorts.\n", - "Span(\"Metabolic Syndrome\", context=None, chars=[20,37], words=[3,4]) 0\n", - "[(13.078313166568094, Span(\"Metabolic Syndrome\", context=None, chars=[20,37], words=[3,4])), (0.99489340685067074, Span(\"disorder related to\", context=None, chars=[39,57], words=[8,10])), (0.76433022464543154, Span(\"platelet-derived growth factor\", context=None, chars=[97,126], words=[14,16])), (0.0, Span(\"inflammation\", context=None, chars=[92,103], words=[17,17])), (0.0, Span(\"obesity,\", context=None, chars=[79,86], words=[14,15]))]\n", - "\n", - "Document('25705159', Corpus (GWAS Corpus)) Genome-wide association study of hepatitis in korean populations.\n", - "Span(\"Hepatitis\", context=None, chars=[33,41], words=[4,4]) 0\n", - "[(13.078313166568094, Span(\"Hepatitis\", context=None, chars=[33,41], words=[4,4])), (0.0, Span(\"Hepatitis\", context=None, chars=[0,8], words=[0,0])), (0.0, Span(\"serious disease\", context=None, chars=[26,40], words=[5,6])), (-0.23047794690884227, Span(\"A and B\", context=None, chars=[29,35], words=[8,10])), (-1.225371353759513, Span(\"hepatitis\", context=None, chars=[145,153], words=[21,21]))]\n", - "\n", - "Document('25705162', Corpus (GWAS Corpus)) Genome-wide association study identifies candidate Loci associated with platelet count in koreans.\n", - "Span(\"Platelet Count\", context=None, chars=[72,85], words=[8,9]) 0\n", - "[(13.078313166568094, Span(\"Platelet Count\", context=None, chars=[72,85], words=[8,9])), (0.0, Span(\"Platelets\", context=None, chars=[0,8], words=[0,0])), (0.0, Span(\"bone marrow\", context=None, chars=[79,89], words=[13,14])), (0.0, Span(\"of bone\", context=None, chars=[76,82], words=[12,13])), (-1.225371353759513, Span(\"value\", context=None, chars=[27,31], words=[4,4]))]\n", - "\n", - "Document('25729143', Corpus (GWAS Corpus)) Genome-wide association study identifies three novel genetic markers associated with elite endurance performance.\n", - "Span(\"transcription factor involved in\", context=None, chars=[162,193], words=[31,34]) 0\n", - "[(-0.23047794690884227, Span(\"transcription factor involved in\", context=None, chars=[162,193], words=[31,34])), (-0.23047794690884227, Span(\"maximal oxygen consumption\", context=None, chars=[88,113], words=[14,16])), (-1.225371353759513, Span(\"values\", context=None, chars=[78,83], words=[15,15])), (-41.732480128703919, Span(\"association\", context=None, chars=[12,22], words=[1,1])), (-44.789809716859239, Span(\"endurance\", context=None, chars=[91,99], words=[11,11]))]\n", - "\n", - "Document('25742292', Corpus (GWAS Corpus)) Genome-wide association study of parity in bangladeshi women.\n", - "Span(\"Parity\", context=None, chars=[33,38], words=[4,4]) 0\n", - "[(13.078313166568094, Span(\"Parity\", context=None, chars=[33,38], words=[4,4])), (0.0, Span(\"fertility\", context=None, chars=[6,14], words=[1,1])), (0.0, Span(\"complex trait\", context=None, chars=[21,33], words=[4,5])), (-0.23047794690884227, Span(\"number of pregnancies\", context=None, chars=[64,84], words=[8,10])), (-0.23047794690884227, Span(\"number of pregnancies\", context=None, chars=[198,218], words=[40,42]))]\n", - "\n", - "Document('25760438', Corpus (GWAS Corpus)) First genome-wide association study in an Australian aboriginal population provides insights into genetic risk factors for body mass index and type 2 diabetes.\n", - "Span(\"Type 2 Diabetes\", context=None, chars=[143,157], words=[20,22]) 0\n", - "[(14.073206573418766, Span(\"Type 2 Diabetes\", context=None, chars=[143,157], words=[20,22])), (14.073206573418766, Span(\"Body Mass Index\", context=None, chars=[123,137], words=[16,18])), (1.9897015784049445, Span(\"body mass index\", context=None, chars=[2,16], words=[1,3])), (-0.0055719707282433362, Span(\"type 2 diabetes\", context=None, chars=[56,70], words=[15,17])), (-1.225371353759513, Span(\"leads\", context=None, chars=[41,45], words=[6,6]))]\n", - "\n" - ] - } - ], - "source": [ - "# doc_set = {c.context.document.name for c in results}\n", - "# missing_docs = {doc.name for doc in corpus.documents} - doc_set\n", - "# docs = sorted(list(missing_docs))\n", - "# print len(docs)\n", - "for d in corpus.documents:\n", - " print d, kb.paper_by_pmid(d.name).title\n", - " print unicode(results.get(d.name, None)), LF_not_true_phen(results.get(d.name))\n", - " try:\n", - " print sorted(score_dict[d.name], reverse=True)[:5]\n", - " except UnicodeEncodeError:\n", - " print 'Unicode error'\n", - " print" - ] - }, - { - "cell_type": "code", - "execution_count": 151, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[u'total cholesterol measurement', u'total cholesterol measurement', u'cholesterol, total', u'total cholesterol levels', u'total cholesterol levels']\n" - ] - } - ], - "source": [ - "# print results.get('19305408').context.position\n", - "# [ngram for ngram in results.get('19305408').pre_ngrams()]\n", - "\n", - "print [ph for ph in efo_phenotype_list if change_name('Total Cholesterol') == change_name(ph)]" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": false - }, - "source": [ - "\n", - "### Save results" - ] - }, - { - "cell_type": "code", - "execution_count": 152, + "execution_count": 68, "metadata": { "collapsed": false }, @@ -6767,34 +1498,27 @@ " while i < len(words):\n", " i += 1\n", " if words[i-1] in nltk_stopword_set or words[i-1] in punctuation: continue\n", - " new_words.append(words[i-1])\n", + " new_word = words[i-1].strip(',.;')\n", + " if new_word.islower() or new_word.isupper(): new_word = new_word.title()\n", + " new_words.append(new_word)\n", " return ' '.join(new_words)\n", "\n", - "with open('phenotypes.extracted.tsv', 'w') as f:\n", + "with open('phenotypes.extracted.latest.tsv', 'w') as f:\n", " for d in corpus.documents:\n", " # pick the top two results:\n", " best = sorted(score_dict[d.name], reverse=True)[:3]\n", " # if both are in title, report both, otherwise report only the best one\n", - " if len(best) == 3 and best[2][1].context.position == 0 and best[1][0] - best[2][0] < 1:\n", + " if len(best) == 3 and best[2][1][0].parent.position == 0 and best[1][0] - best[2][0] < 3:\n", " (_, r1), (_, r2), (_, r3) = best\n", - " phen = '|'.join(set([clean_stopwords(r.get_span()) for s,r in best[:3]]))\n", - " elif len(best) >= 2 and best[1][1].context.position == 0 and best[1][0] > 5:\n", - " phen = '|'.join(set([clean_stopwords(r.get_span()) for s,r in best[:2]])) \n", + " phen = '|'.join(set([clean_stopwords(r[0].get_span()) for s,r in best[:3]]))\n", + " elif len(best) >= 2 and best[1][1][0].parent.position == 0 and best[1][0] > 5:\n", + " phen = '|'.join(set([clean_stopwords(r[0].get_span()) for s,r in best[:2]])) \n", " else:\n", - " phen = clean_stopwords(best[0][1].get_span())\n", + " phen = clean_stopwords(best[0][1][0].get_span())\n", " out_str = u'%s\\t%s\\t\\n' % (d.name, phen) \n", " f.write(out_str.encode(\"UTF-8\"))\n", " " ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] } ], "metadata": { @@ -6814,6 +1538,18 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.2" + }, + "widgets": { + "state": { + "723274901c034be8b4ea1acf29f5eddc": { + "views": [ + { + "cell_index": 63 + } + ] + } + }, + "version": "1.2.0" } }, "nbformat": 4, diff --git a/notebooks/phenotype-table-extraction.ipynb b/notebooks/phenotype-table-extraction.ipynb index b302916..327a3b2 100644 --- a/notebooks/phenotype-table-extraction.ipynb +++ b/notebooks/phenotype-table-extraction.ipynb @@ -7,6 +7,27 @@ "# Phenotype/SNP relation extraction from tables" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here we will demo the module that parses tables in papers and extracts relations between SNPs and phenotypes (in cases in which the paper discusses multiple phenotypes)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Preparations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We start by configuring Jupyter and setting up our environment." + ] + }, { "cell_type": "code", "execution_count": 1, @@ -20,27 +41,39 @@ "\n", "import sys\n", "import cPickle\n", + "import numpy as np\n", + "import sqlalchemy\n", "\n", - "# import snorkel and gwasdb\n", - "sys.path.append('../snorkel')\n", + "# set the paths to snorkel and gwasdb\n", + "sys.path.append('../snorkel-tables')\n", "sys.path.append('../src')\n", "sys.path.append('../src/crawler')\n", "\n", - "# set up paths\n", + "# set up the directory with the input papers\n", "abstract_dir = '../data/db/papers'\n", "\n", "# set up matplotlib\n", - "import numpy as np\n", "import matplotlib\n", "%matplotlib inline\n", - "matplotlib.rcParams['figure.figsize'] = (12,4)" + "matplotlib.rcParams['figure.figsize'] = (12,4)\n", + "\n", + "# create a Snorkel session\n", + "from snorkel import SnorkelSession\n", + "session = SnorkelSession()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Load corpus" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Load corpus" + "We load our usual corpus of GWAS papers." ] }, { @@ -51,10 +84,10 @@ }, "outputs": [], "source": [ - "from snorkel.parser import XMLDocParser\n", "from extractor.parser import UnicodeXMLTableDocParser\n", + "from snorkel.parser import XMLMultiDocParser\n", "\n", - "xml_parser = UnicodeXMLTableDocParser(\n", + "xml_parser = XMLMultiDocParser(\n", " path=abstract_dir,\n", " doc='./*',\n", " text='.//table',\n", @@ -73,42 +106,26 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 13min 55s, sys: 47 s, total: 14min 42s\n", - "Wall time: 22min 16s\n" + "Loaded corpus of 589 documents\n" ] } ], "source": [ - "from snorkel.parser import HTMLParser\n", - "from extractor.parser import UnicodeTableParser\n", - "from snorkel.parser import CorpusParser\n", - "import cPickle\n", + "from snorkel.parser import CorpusParser, OmniParser\n", + "from snorkel.models import Corpus\n", "\n", - "table_parser = UnicodeTableParser()\n", - "html_parser = HTMLParser(path='../data/db/papers/')\n", - "\n", - "corpus_name = 'gwas-table-corpus.pkl'\n", + "# parses tables into rows, cols, cells...\n", + "table_parser = OmniParser(timeout=1000000)\n", "\n", "try:\n", - " with open(corpus_name,\"r\") as pkl:\n", - " corpus = cPickle.load(pkl)\n", + " corpus = session.query(Corpus).filter(Corpus.name == 'GWAS Table Corpus').one()\n", "except:\n", " cp = CorpusParser(xml_parser, table_parser)\n", - " %time corpus = cp.parse_corpus(name='GWAS Corpus')\n", - " # pickling currently doesn't work...\n", - "# with open(corpus_name,\"w\") as pkl:\n", - "# corpus = cPickle.dump(corpus, pkl)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# corpus15 = corpus" + " %time corpus = cp.parse_corpus(name='GWAS Table Corpus', session=session)\n", + " session.add(corpus)\n", + " session.commit()\n", + "\n", + "print 'Loaded corpus of %d documents' % len(corpus)" ] }, { @@ -122,166 +139,74 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### RSid Extraction" + "### Define candidate matchers" ] }, { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, - "outputs": [], + "cell_type": "markdown", + "metadata": {}, "source": [ - "from snorkel.matchers import DictionaryMatch, RegexMatchSpan, Union\n", - "from snorkel.candidates import EntityExtractor\n", - "from snorkel.candidates import TableNgrams\n", - "\n", - "from db.kb import KnowledgeBase\n", - "\n", - "# Define a candidate space\n", - "ngrams = TableNgrams(n_max=1)\n", - "\n", - "# Get a list of all the RSids we know\n", - "kb = KnowledgeBase()\n", - "rs_ids = kb.get_rsid_candidates()\n", - "\n", - "# Define matchers\n", - "dict_rsid_matcher = DictionaryMatch(d=rs_ids, longest_match_only=False)\n", - "regx_rsid_matcher = RegexMatchSpan(rgx=r'rs\\d+(/[ATCG]{1,2})*$')\n", - "rsid_matcher = Union(dict_rsid_matcher, regx_rsid_matcher)\n", - "\n", - "rsid_extractor = EntityExtractor(ngrams, rsid_matcher)\n", - "# %time rs_candidates = rsid_extractor.extract(corpus.get_tables(), name='all')" + "#### RSid matcher" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# for cand in rs_candidates[:10]: \n", - "# print cand\n", - "# print \"%s candidates extracted\" % len(rs_candidates)\n", - "# print rs_candidates[0].context\n", - "# print rs_candidates[0].context.cell" + "from snorkel.matchers import RegexMatchSpan\n", + "rsid_matcher = RegexMatchSpan(rgx=r'rs\\d+(/[ATCG]{1,2})*$')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Statistics" - ] - }, - { - "cell_type": "code", - "execution_count": 226, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'rs_candidates' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mgold_set_rsids\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mrs_id\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mdoc_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrs_id\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mgold_set\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mgold_rsid_stats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrs_candidates\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgold_set\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;31mNameError\u001b[0m: name 'rs_candidates' is not defined" - ] - } - ], - "source": [ - "from extractor.util import gold_rsid_stats, gold_rsid_precision\n", - "\n", - "gold_set = frozenset( [ (doc.name, rs_id) for doc in corpus.documents for rs_id in kb.rsids_by_pmid(int(doc.name)) ] )\n", - "gold_set_rsids = [rs_id for doc_id, rs_id in gold_set]\n", - "\n", - "gold_rsid_stats(rs_candidates, gold_set)" + "#### Phenotype matchers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Interesting: some SNPs seem to be never mentioned (e.g. rs12122100) while others (rs727153) appear only in the text.\n", - "Sometimes, it's not picked up for a different, strange reason: see rs13314993." + "The first matcher checks if we are in a column whose header labels it as a phenotype column." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "cells = rs_candidates[0].context.cell.aligned_cells('row')\n", - "[cell.text for cell in cells]" + "from snorkel.matchers import CellNameDictionaryMatcher\n", + "\n", + "phen_words = ['trait', 'phenotype', 'outcome'] # words that denote phenotypes\n", + "phen_matcher = CellNameDictionaryMatcher(axis='col', d=phen_words, n_max=3, ignore_case=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Phenotypes" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from snorkel.matchers import DictionaryMatch, Union, CellNameDictMatcher\n", - "from snorkel.candidates import EntityExtractor\n", - "from snorkel.candidates import TableNgrams, CellSpace\n", - "\n", - "# Define a candidate space\n", - "ngrams = TableNgrams(n_max=9)\n", - "cells = CellSpace()\n", - "\n", - "# Create a list of possible words that could denote phenotypes\n", - "phen_words = ['trait', 'phenotype', 'outcome']\n", - "\n", - "# Define matchers\n", - "# dict_row_matcher = DictionaryMatch(d=phen_words, longest_match_only=False, stemmer='porter')\n", - "# cell_row_matcher = CellNameMatcher(row_matcher=dict_row_matcher, cand_space=ngrams)\n", - "# dict_col_matcher = DictionaryMatch(d=phen_words, longest_match_only=False, stemmer='porter')\n", - "# cell_col_matcher = CellNameMatcher(col_matcher=dict_col_matcher, cand_space=ngrams)\n", - "# phen_matcher = Union(cell_row_matcher, cell_col_matcher)\n", - "# phen_matcher = CellNameMatcher(col_matcher=dict_col_matcher, cand_space=ngrams)\n", - "phen_matcher = CellNameDictMatcher(axis='col', d=phen_words, n_max=3, ignore_case=True)\n", - "\n", - "phen_extractor1 = EntityExtractor(cells, phen_matcher)\n", - "# %time phen_candidates = phen_extractor.extract(corpus.get_tables(), name='all')" + "The next matcher will match phenotypes in cells that span an entire axis" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ + "from snorkel.matchers import DictionaryMatch\n", "from db.kb import KnowledgeBase\n", - "from snorkel.utils import slice_into_ngrams\n", - "from snorkel.matchers import FullCellDictMatcher\n", - "\n", - "def make_ngrams(L, n_max=10, n_min=3, delim=' '):\n", - " for l in L:\n", - " yield l\n", - " tokens = l.strip().split(delim)\n", - " for ngram in slice_into_ngrams(tokens, n_max=n_max, n_min=n_min, delim=delim):\n", - " yield ngram\n", + "from extractor.util import make_ngrams\n", "\n", "# collect phenotype list\n", "kb = KnowledgeBase()\n", @@ -295,33 +220,7 @@ "chem_phenotype_list = kb.get_phenotype_candidates(source='chemical')\n", "\n", "phenotype_names = efo_phenotype_list + mesh_phenotype_list + chem_phenotype_list\n", - "full_cell_matcher = FullCellDictMatcher(d=phenotype_names, ignore_case=True, stemmer='porter')\n", - "\n", - "cells = CellSpace()\n", - "phen_extractor2 = EntityExtractor(cells, full_cell_matcher)\n", - "select_tables = [table for table in corpus.get_tables() if table.document.name == '19197348']\n", - "# %time phen_candidates = phen_extractor2.extract(select_tables, name='all')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "print \"%s candidates extracted\" % len(phen_candidates)\n", - "for cand in phen_candidates[0:10]: \n", - " print cand.context.document.name, cand.context.table, cand.context.cell\n", - " print unicode(cand)\n", - "# print [span for span in cand.row_ngrams()]\n", - "# print [span for span in cand.col_ngrams()]\n", - "# print\n", - "print\n", - "print phen_candidates[0].context\n", - "print phen_candidates[0].context.document.name, phen_candidates[0].context.table\n", - "print phen_candidates[0].context.cell" + "phen_name_matcher = DictionaryMatch(d=phenotype_names, ignore_case=True, stemmer='porter')" ] }, { @@ -330,158 +229,73 @@ "collapsed": true }, "source": [ - "### Relations" + "### Relation extraction" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "from snorkel.candidates import AlignedTableRelationExtractor, SpanningTableRelationExtractor, UnionExtractor\n", - "relation_extractor1 = AlignedTableRelationExtractor(rsid_extractor, phen_extractor1, axis='row', induced=True)\n", - "relation_extractor2 = SpanningTableRelationExtractor(rsid_extractor, phen_extractor2, axis='col', full1=True)\n", + "from snorkel.candidates import CandidateExtractor\n", + "from snorkel.throttlers import AlignmentThrottler, SeparatingSpanThrottler, OrderingThrottler, CombinedThrottler\n", "\n", - "relation_extractor = UnionExtractor([relation_extractor1, relation_extractor2])\n", + "# create a Snorkel class for the relation we will extract\n", + "from snorkel.models import candidate_subclass\n", + "RsidPhenRel = candidate_subclass('RsidPhenRel', ['rsid','phen'])\n", "\n", + "# define our candidate spaces\n", + "from snorkel.candidates import TableNgrams, TableCells, SpanningTableCells\n", + "unigrams = TableNgrams(n_max=1)\n", + "cells = TableCells()\n", + "spanning_cells = SpanningTableCells(axis='row')\n", "\n", - "tables = corpus.get_tables()\n", + "# we will be looking only at aligned cells\n", + "row_align_filter = AlignmentThrottler(axis='row', infer=True)\n", "\n", - "# create smaller subsets for evaluation/debugging\n", - "easy_tables = [tables[8]]\n", - "# hard_tables = [t for t in tables if t.document.name=='17658951']\n", - "hard_doc = [d for d in corpus.documents if d.name == '17903293'][0]\n", - "hard_tables = [hard_doc.tables[2]]" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 5min 58s, sys: 3.88 s, total: 6min 2s\n", - "Wall time: 6min 1s\n" - ] - } - ], - "source": [ - "%time test_c = relation_extractor2.extract([select_tables[2]], name='all')" + "# and at cells where the phenotype is in a spanning header cell above the rsid cell\n", + "sep_span_filter = SeparatingSpanThrottler(align_axis='col') # rsid and phen are not separated by spanning cells\n", + "col_order_filter = OrderingThrottler(axis='col', first=1) # phen spanning cell comes first\n", + "header_filter = CombinedThrottler([sep_span_filter, col_order_filter]) # combine the two throttlers\n", + "\n", + "# the first extractor looks at phenotype names in columns with a header indicating it's a phenotype\n", + "ce1 = CandidateExtractor(RsidPhenRel, [unigrams, cells], [rsid_matcher, phen_matcher], throttler=row_align_filter)\n", + "\n", + "# the second extractor looks at phenotype names in columns with a header indicating it's a phenotype\n", + "ce2 = CandidateExtractor(RsidPhenRel, [unigrams, spanning_cells], [rsid_matcher, phen_name_matcher], throttler=header_filter, stop_on_duplicates=False)\n", + "\n", + "# collect that cells that will be searched for candidates\n", + "tables = [table for doc in corpus.documents for table in doc.tables]" ] }, { - "cell_type": "code", - "execution_count": 36, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "40\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "print len(test_c)" + "We are now ready to perform relation extraction." ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 1, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SpanPair(Span(\"rs6560749\", context=None, chars=[0,8], words=[0,0]), Span(\"BMI\", context=None, chars=[0,2], words=[0,0]))\n", - "SpanPair(Span(\"rs10486715\", context=None, chars=[0,9], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs17718077\", context=None, chars=[0,9], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs2222328\", context=None, chars=[0,8], words=[0,0]), Span(\"Waist Circumference\", context=None, chars=[0,18], words=[0,1]))\n", - "SpanPair(Span(\"rs613391\", context=None, chars=[0,7], words=[0,0]), Span(\"Waist Circumference\", context=None, chars=[0,18], words=[0,1]))\n", - "SpanPair(Span(\"rs527485\", context=None, chars=[0,7], words=[0,0]), Span(\"Waist Circumference\", context=None, chars=[0,18], words=[0,1]))\n", - "SpanPair(Span(\"rs976731\", context=None, chars=[0,7], words=[0,0]), Span(\"Waist Circumference\", context=None, chars=[0,18], words=[0,1]))\n", - "SpanPair(Span(\"rs976730\", context=None, chars=[0,7], words=[0,0]), Span(\"Waist Circumference\", context=None, chars=[0,18], words=[0,1]))\n", - "SpanPair(Span(\"rs2225614\", context=None, chars=[0,8], words=[0,0]), Span(\"Weight\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs10928195\", context=None, chars=[0,9], words=[0,0]), Span(\"Weight\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs1874326\", context=None, chars=[0,8], words=[0,0]), Span(\"Weight\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs10745259\", context=None, chars=[0,9], words=[0,0]), Span(\"Fasting plasma glucose\", context=None, chars=[0,21], words=[0,2]))\n", - "SpanPair(Span(\"rs755109\", context=None, chars=[0,7], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs6462411\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10983893\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10848704\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs4743136\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10241703\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs6958535\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs925488\", context=None, chars=[0,7], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10983932\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs6959674\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs11514766\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs7804166\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs1877431\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs1588635\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10984516\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs1962785\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs2805809\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs12531984\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10243770\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10119795\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs12539695\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs2805810\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs6956479\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs2668804\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs7036589\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs6909430\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs2808693\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs10245389\", context=None, chars=[0,9], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n", - "SpanPair(Span(\"rs9939609\", context=None, chars=[0,8], words=[0,0]), Span(\"BMI\", context=None, chars=[0,2], words=[0,0]))\n", - "SpanPair(Span(\"rs17782313\", context=None, chars=[0,9], words=[0,0]), Span(\"BMI\", context=None, chars=[0,2], words=[0,0]))\n", - "SpanPair(Span(\"rs6763931\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs6440003\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs724016\", context=None, chars=[0,7], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs6440003\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs1042725\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs6060369\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs798544\", context=None, chars=[0,7], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs3748069\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs7755109\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs1812175\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs7153027\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs6830062\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs3760318\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs7225461\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs2282978\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs967417\", context=None, chars=[0,7], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs4743034\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs678962\", context=None, chars=[0,7], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs12411264\", context=None, chars=[0,9], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs4533267\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs7846385\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs2562784\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs4794665\", context=None, chars=[0,8], words=[0,0]), Span(\"Height\", context=None, chars=[0,5], words=[0,0]))\n", - "SpanPair(Span(\"rs563694\", context=None, chars=[0,7], words=[0,0]), Span(\"Fasting plasma glucose\", context=None, chars=[0,21], words=[0,2]))\n", - "SpanPair(Span(\"rs1799884\", context=None, chars=[0,8], words=[0,0]), Span(\"Fasting plasma glucose\", context=None, chars=[0,21], words=[0,2]))\n", - "SpanPair(Span(\"rs4704397\", context=None, chars=[0,8], words=[0,0]), Span(\"Thyroid Stimulating Hormone\", context=None, chars=[0,26], words=[0,2]))\n" - ] - } - ], + "outputs": [], "source": [ - "for cand in new_candidates: \n", - " if cand.span0.context.document.name == '19197348':\n", - " print cand" + "from snorkel.models import CandidateSet\n", + "\n", + "try:\n", + " rels1 = session.query(CandidateSet).filter(CandidateSet.name == 'RsidPhenRel Set 1').one()\n", + "except:\n", + " %time rels1 = ce1.extract(tables, 'RsidPhenRel Set 1', session)\n", + " \n", + "print \"%s relations extracted, e.g.\" % len(rels1)\n", + "for cand in rels1[:10]:\n", + " print cand" ] }, { @@ -492,9 +306,15 @@ }, "outputs": [], "source": [ - "%time candidates = relation_extractor.extract(tables, name='all')\n", - "print \"%s relations extracted, e.g.\" % len(candidates)\n", - "for cand in candidates[:10]: \n", + "from snorkel.models import CandidateSet\n", + "\n", + "try:\n", + " rels2 = session.query(CandidateSet).filter(CandidateSet.name == 'RsidPhenRel Set 2').one()\n", + "except:\n", + " %time rels2 = ce2.extract(tables, 'RsidPhenRel Set 2', session)\n", + " \n", + "print \"%s relations extracted, e.g.\" % len(rels2)\n", + "for cand in rels2[:10]: \n", " print cand" ] }, @@ -502,12 +322,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Here, we remove nested candidates" + "Finally, we merge the two sets of candiates into a single set." ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 10, "metadata": { "collapsed": false }, @@ -516,44 +336,24 @@ "name": "stdout", "output_type": "stream", "text": [ - "0 candidates dropped, now we have 3739\n" + "3504 candidates in total\n" ] } ], "source": [ - "# load existing candidates into a dict\n", - "span_dict = { str(span_pair.span1.context) : list() for span_pair in candidates }\n", - "for span_pair in candidates:\n", - " span = span_pair.span1\n", - " span_dict[str(span.context)].append( (span.char_start, span.char_end) )\n", + "from snorkel.models import CandidateSet\n", "\n", - "def nested(ivl1, ivl2):\n", - " if ivl1 != ivl2 and ivl2[0] <= ivl1[0] <= ivl1[1] <= ivl2[1]:\n", - " return True\n", - " else:\n", - " return False\n", + "try:\n", + " rels = session.query(CandidateSet).filter(CandidateSet.name == 'RsidPhenRel Canidates').one()\n", + "except:\n", + " rels = CandidateSet(name='RsidPhenRel Canidates')\n", + " for c in rels1: rels.append(c)\n", + " for c in rels2: rels.append(c)\n", "\n", - "new_candidates = list()\n", - "for span_pair in candidates:\n", - " span = span_pair.span1\n", - " span_ivl = span.char_start, span.char_end\n", - " span_name = str(span.context)\n", - " if all([not nested(span_ivl, other_ivl) for other_ivl in span_dict[span_name]]):\n", - " new_candidates.append(span_pair)\n", - " \n", - "print len(candidates) - len(new_candidates), 'candidates dropped, now we have', len(new_candidates)\n", - "# phen_c = new_phen_c" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# candidates15 = candidates" + " session.add(rels)\n", + " session.commit()\n", + "\n", + "print '%d candidates in total' % len(rels)" ] }, { @@ -569,54 +369,77 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Creating a gold set" + "Next, we will train machine learning models to identify which phenotype candidates are actually correct." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "To create a gold set, we save all extracted relations into a csv file. We annotate it manually, and save the result to a second file. It contains pairs of phenotype and rsid strings; if that file exists, we take these as gold truth." + "### Generating a labeled set of examples" ] }, { - "cell_type": "code", - "execution_count": 38, - "metadata": { - "collapsed": false - }, - "outputs": [], + "cell_type": "markdown", + "metadata": {}, "source": [ - "# store relations to annotate\n", - "with open('rels.acroynms.unnanotated.tsv', 'w') as f:\n", - " for span_pair in new_candidates:\n", - " doc_id = span_pair.span0.context.document.name\n", - " table_id = span_pair.span0.context.table.position\n", - " row_num = span_pair.span0.context.cell.row_num\n", - " str1 = span_pair.span0.get_span()\n", - " str2 = span_pair.span1.get_span()\n", - " try:\n", - " f.write('%s\\t%s\\t%d\\t%s\\t%s\\n' % (doc_id, table_id, row_num, str1, str2))\n", - " except:\n", - " continue" + "We first split data into an (unlabeled) training set (since we will use unsupervised risk estimation to train a candidate on it), and a dev/test set." ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 11, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Library/Python/2.7/site-packages/ipykernel/__main__.py:17: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initialized 1752 training and 1752 dev/testing candidates\n" + ] + } + ], "source": [ - "# load annotations\n", - "annotations = dict()\n", - "with open('rels.acronyms.annotated.txt') as f:\n", - " text = f.read()\n", - " for line in text.split('\\r'):\n", - " doc_id, table_id, col_n, rs_id, phen, res = line.strip().split('\\t')\n", - " res = 1 if int(res) == 1 else -1\n", - " annotations[(doc_id, table_id, rs_id, phen)] = res" + "try:\n", + " train_c = session.query(CandidateSet).filter(CandidateSet.name == 'RsidPhenRel Training Candidates').one()\n", + " devtest_c = session.query(CandidateSet).filter(CandidateSet.name == 'RsidPhenRel Dev/Test Candidates').one()\n", + "except:\n", + " # delete any previous sets with that name\n", + " session.query(CandidateSet).filter(CandidateSet.name == 'RsidPhenRel Training Candidates').delete()\n", + " session.query(CandidateSet).filter(CandidateSet.name == 'RsidPhenRel Dev/Test Candidates').delete()\n", + "\n", + " frac_test = 0.5\n", + "\n", + " # initialize the new sets\n", + " train_c = CandidateSet(name='RsidPhenRel Training Candidates')\n", + " devtest_c = CandidateSet(name='RsidPhenRel Dev/Test Candidates')\n", + "\n", + " # choose a random subset for the labeled set\n", + " n_test = len(rels) * frac_test\n", + " test_idx = set(np.random.choice(len(rels), size=(n_test,), replace=False))\n", + "\n", + " # add to the sets\n", + " for i, c in enumerate(rels):\n", + " if i in test_idx:\n", + " devtest_c.append(c)\n", + " else:\n", + " train_c.append(c)\n", + "\n", + " # save the results\n", + " session.add(train_c)\n", + " session.add(devtest_c)\n", + " session.commit()\n", + "\n", + "print 'Initialized %d training and %d dev/testing candidates' % (len(train_c), len(devtest_c))" ] }, { @@ -625,149 +448,92 @@ "collapsed": true }, "source": [ - "### Classify correct relations" + "### Labelling functions" ] }, { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Building feature index...\n", - "Extracting features...\n", - "0/104875\n", - "5000/104875\n", - "10000/104875\n", - "15000/104875\n", - "20000/104875\n", - "25000/104875\n", - "30000/104875\n", - "35000/104875\n", - "40000/104875\n", - "45000/104875\n", - "50000/104875\n", - "55000/104875\n", - "60000/104875\n", - "65000/104875\n", - "70000/104875\n", - "75000/104875\n", - "80000/104875\n", - "85000/104875\n", - "90000/104875\n", - "95000/104875\n", - "100000/104875\n" - ] - }, - { - "data": { - "text/plain": [ - "<3739x104875 sparse matrix of type ''\n", - "\twith 1244486 stored elements in LInked List format>" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "from snorkel.features import TableNgramPairFeaturizer\n", - "\n", - "# pkl_f = 'acro_table_feats.pkl'\n", - "# try:\n", - "# with open(pkl_f, 'rb') as f:\n", - "# featurizer = cPickle.load(f)\n", - "# except:\n", - "featurizer = TableNgramPairFeaturizer()\n", - "featurizer.fit_transform(candidates)" + "Following the data programming approach, we define set of labeling functions. We will learn their accuracy via unsupervised learning and use them for classifying candidates." ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Training set size: 2256\n", - "Gold set size: 1483\n", - "Positive labels in training set: 16\n", - "Negative labels in training set: 0\n", - "Positive labels in gold set: 1344\n", - "Negative labels in gold set: 139\n" + "/Library/Python/2.7/site-packages/bs4/__init__.py:181: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system (\"lxml\"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.\n", + "\n", + "The code that caused this warning is on line 162 of the file /System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/runpy.py. To get rid of this warning, change code that looks like this:\n", + "\n", + " BeautifulSoup([your markup])\n", + "\n", + "to this:\n", + "\n", + " BeautifulSoup([your markup], \"lxml\")\n", + "\n", + " markup_type=markup_type))\n" ] } ], "source": [ - "def spair2uid(span_pair):\n", - " doc_id = span_pair.span0.context.document.name\n", - " table_id = str(span_pair.span0.context.table.position)\n", - " str1 = span_pair.span0.get_span()\n", - " str2 = span_pair.span1.get_span()\n", - " return (doc_id, table_id, str1, str2)\n", - "\n", - "# Split into train and test set\n", - "training_candidates = []\n", - "gold_candidates = []\n", - "gold_labels = []\n", - "n_half = len(candidates)/2\n", - "for c in candidates[:n_half]:\n", - " uid = spair2uid(c)\n", - " if uid in annotations:\n", - " gold_candidates.append(c)\n", - " gold_labels.append(annotations[uid])\n", - " else:\n", - " training_candidates.append(c)\n", - "training_candidates.extend(candidates[n_half:])\n", - "gold_labels = np.array(gold_labels)\n", - "print \"Training set size: %s\" % len(training_candidates)\n", - "print \"Gold set size: %s\" % len(gold_candidates)\n", - "print \"Positive labels in training set: %s\" % len([c for c in training_candidates if annotations.get(spair2uid(c),0)==1])\n", - "print \"Negative labels in training set: %s\" % len([c for c in training_candidates if annotations.get(spair2uid(c),0)==-1])\n", - "print \"Positive labels in gold set: %s\" % len([c for c in gold_candidates if annotations[spair2uid(c)]==1])\n", - "print \"Negative labels in gold set: %s\" % len([c for c in gold_candidates if annotations[spair2uid(c)]==-1])" + "from snorkel.lf_helpers import *\n", + "s=None\n", + "doc = [d for d in corpus.documents if d.name == '17903303'][0]\n", + "table = doc.tables[3]\n", + "for cell in table.cells:\n", + " top_cells = get_aligned_cells(cell, 'col', infer=True)\n", + " top_phrases = [phrase for cell in top_cells for phrase in cell.phrases]\n", + "# rels[0][1].parent.table.cells[0].phrases\n", + "# corpus.documents[0].phrases" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 13, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ + "from snorkel.lf_helpers import *\n", + "\n", "bad_words = ['rs number', 'rs id', 'rsid']\n", "\n", "# negative LFs\n", "def LF_number(m):\n", - " txt = m.span1.get_span()\n", + " txt = m[1].get_span()\n", " frac_num = len([ch for ch in txt if ch.isdigit()]) / float(len(txt))\n", " return -1 if len(txt) > 5 and frac_num > 0.4 or frac_num > 0.6 else 0\n", "\n", "def LF_bad_phen_mentions(m):\n", - " if m.span1.context.cell.spans('row'): return 0\n", - " top_cells = m.span1.context.cell.aligned_cells(axis='col', induced=True)\n", - " top_phrases = [phrase for cell in top_cells for phrase in cell.phrases]\n", + " if cell_spans(m[1].parent.cell, m[1].parent.table, 'row'): return 0\n", + " # if m[1].context.cell.spans('row'): return 0\n", + " top_cells = get_aligned_cells(m[1].parent.cell, 'col', infer=True)\n", + " top_cells = [cell for cell in top_cells]\n", + "# top_cells = m.span1.context.cell.aligned_cells(axis='col', induced=True)\n", + " try:\n", + " top_phrases = [phrase for cell in top_cells for phrase in cell.phrases]\n", + " except:\n", + " for cell in top_cells:\n", + " print cell, cell.phrases\n", " if not top_phrases: return 0\n", " matching_phrases = []\n", " for phrase in top_phrases:\n", - " if any (phen_matcher._f_span(word) for word in phrase.text.split(' ')):\n", + " if any (phen_matcher._f_ngram(word) for word in phrase.text.split(' ')):\n", " matching_phrases.append(phrase)\n", " small_matching_phrases = [phrase for phrase in matching_phrases if len(phrase.text) <= 25]\n", " return -1 if not small_matching_phrases else 0\n", "\n", "def LF_bad_word(m):\n", - " txt = m.span1.get_span()\n", + " txt = m[1].get_span()\n", " return -1 if any(word in txt for word in bad_words) else 0\n", "\n", "LF_tables_neg = [LF_number, LF_bad_phen_mentions]\n", @@ -778,12 +544,19 @@ "\n", "LF_tables_pos = [LF_no_neg]\n", "\n", - "LF_tables = LF_tables_neg + LF_tables_pos" + "LFs = LF_tables_neg + LF_tables_pos" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We generate features for the training set." ] }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 14, "metadata": { "collapsed": false }, @@ -792,6301 +565,222 @@ "name": "stdout", "output_type": "stream", "text": [ - "Applying LFs...\n", - "Featurizing...\n", - "Building feature index...\n", - "Extracting features...\n", - "0/88256\n", - "5000/88256\n", - "10000/88256\n", - "15000/88256\n", - "20000/88256\n", - "25000/88256\n", - "30000/88256\n", - "35000/88256\n", - "40000/88256\n", - "45000/88256\n", - "50000/88256\n", - "55000/88256\n", - "60000/88256\n", - "65000/88256\n", - "70000/88256\n", - "75000/88256\n", - "80000/88256\n", - "85000/88256\n", - "============================================================\n", - "LF Summary Statistics: 3 LFs applied to 2256 candidates\n", - "------------------------------------------------------------\n", - "Coverage (candidates w/ > 0 labels):\t\t100.00%\n", - "Overlap (candidates w/ > 1 labels):\t\t11.26%\n", - "Conflict (candidates w/ conflicting labels):\t0.00%\n", - "============================================================\n" + "Generating annotations for 1752 candidates...\n", + "[========================================] 100%\n", + "Loading sparse Label matrix...\n", + "CPU times: user 9min 23s, sys: 2min 42s, total: 12min 5s\n", + "Wall time: 12min 13s\n" ] } ], "source": [ - "from snorkel.snorkel import TrainingSet\n", - "from snorkel.features import NgramFeaturizer\n", + "from snorkel.annotations import LabelManager\n", + "label_manager = LabelManager()\n", "\n", - "training_set = TrainingSet(training_candidates, LF_tables, featurizer=TableNgramPairFeaturizer())" + "try:\n", + " %time L_train = label_manager.load(session, train_c, 'RsidPhenRel LF Labels6')\n", + "except sqlalchemy.orm.exc.NoResultFound:\n", + " %time L_train = label_manager.create(session, train_c, 'RsidPhenRel LF Labels6', f=LFs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's also look at some basic statistics." ] }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 18, "metadata": { "collapsed": false }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "============================================================\n", - "Testing mu = 1.00e-05, lf_w0 = 1.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-05\n", - "\tLearning epoch = 0\tGradient mag. = 0.009294\n", - "\tLearning epoch = 250\tGradient mag. = 0.016126\n", - "\tLearning epoch = 500\tGradient mag. = 0.033966\n", - "\tLearning epoch = 750\tGradient mag. = 0.059514\n", - "Final gradient magnitude for rate=0.01, mu=1e-05: 0.060\n", - "Applying LFs...\n", - "Featurizing...\n", - "============================================================\n", - "Testing mu = 1.00e-05, lf_w0 = 2.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-05\n", - "\tLearning epoch = 0\tGradient mag. = 0.017941\n", - "\tLearning epoch = 250\tGradient mag. = 0.031757\n", - "\tLearning epoch = 500\tGradient mag. = 0.060985\n", - "\tLearning epoch = 750\tGradient mag. = 0.061324\n", - "Final gradient magnitude for rate=0.01, mu=1e-05: 0.062\n", - "============================================================\n", - "Testing mu = 1.00e-07, lf_w0 = 1.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-07\n", - "\tLearning epoch = 0\tGradient mag. = 0.009294\n", - "\tLearning epoch = 250\tGradient mag. = 0.016619\n", - "\tLearning epoch = 500\tGradient mag. = 0.035820\n", - "\tLearning epoch = 750\tGradient mag. = 0.059530\n", - "Final gradient magnitude for rate=0.01, mu=1e-07: 0.060\n", - "============================================================\n", - "Testing mu = 1.00e-07, lf_w0 = 2.00e+00\n", - "============================================================\n", - "Begin training for rate=0.01, mu=1e-07\n", - "\tLearning epoch = 0\tGradient mag. = 0.017941\n", - "\tLearning epoch = 250\tGradient mag. = 0.032249\n", - "\tLearning epoch = 500\tGradient mag. = 0.060998\n", - "\tLearning epoch = 750\tGradient mag. = 0.061347\n", - "Final gradient magnitude for rate=0.01, mu=1e-07: 0.062\n" - ] - } - ], - "source": [ - "from snorkel.snorkel import Learner\n", - "import snorkel.learning\n", - "from snorkel.learning import LogReg\n", - "\n", - "learner = Learner(training_set, model=LogReg())\n", - "\n", - "# Splitting into CV and test set\n", - "n_half = len(gold_candidates)/2\n", - "test_candidates = gold_candidates[:n_half]\n", - "test_labels = gold_labels[:n_half]\n", - "cv_candidates = gold_candidates[n_half:]\n", - "cv_labels = gold_labels[n_half:]\n", - "\n", - "from snorkel.learning_utils import GridSearch\n", - "gs = GridSearch(learner, ['mu', 'lf_w0'], [[1e-5, 1e-7],[1.0,2.0]])\n", - "gs_stats = gs.fit(cv_candidates, cv_labels)" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Applying LFs...\n", - "Featurizing...\n", - "========================================\n", - "Test set size:\t741\n", - "----------------------------------------\n", - "Precision:\t1.0\n", - "Recall:\t\t1.0\n", - "F1 Score:\t1.0\n", - "----------------------------------------\n", - "TP: 602 | FP: 0 | TN: 139 | FN: 0\n", - "========================================\n" - ] + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " conflicts coverage j overlaps\n", + "LF_number 0 0.144242 0 0.072976\n", + "LF_bad_phen_mentions 0 0.152223 1 0.072976\n", + "LF_no_neg 0 0.776511 2 0.000000\n", + "\n", + "[3 rows x 4 columns]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "learner.test_wmv(test_candidates, test_labels)" + "L_train.lf_stats()" ] }, { - "cell_type": "code", - "execution_count": 47, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19197348 -1.0 None\n", - "Phrase('19197348', 2, 15, 0, u'rs6560749')\n", - "rs6560749 BMI\n", - "[0, 0, 1]\n", - "[Phrase('19197348', 2, 0, 0, u'Rank'), Phrase('19197348', 2, 12, 0, u'1'), Phrase('19197348', 2, 23, 0, u'Height'), Phrase('19197348', 2, 24, 0, u'1'), Phrase('19197348', 2, 35, 0, u'2'), Phrase('19197348', 2, 46, 0, u'Waist Circumference'), Phrase('19197348', 2, 47, 0, u'1'), Phrase('19197348', 2, 58, 0, u'2'), Phrase('19197348', 2, 69, 0, u'3'), Phrase('19197348', 2, 80, 0, u'4'), Phrase('19197348', 2, 91, 0, u'5'), Phrase('19197348', 2, 102, 0, u'Weight'), Phrase('19197348', 2, 103, 0, u'1'), Phrase('19197348', 2, 114, 0, u'2'), Phrase('19197348', 2, 125, 0, u'3'), Phrase('19197348', 2, 136, 0, u'Leptin'), Phrase('19197348', 2, 137, 0, u'1'), Phrase('19197348', 2, 148, 0, u'% body fat'), Phrase('19197348', 2, 149, 0, u'1'), Phrase('19197348', 2, 160, 0, u'2'), Phrase('19197348', 2, 171, 0, u'3'), Phrase('19197348', 2, 182, 0, u'4'), Phrase('19197348', 2, 193, 0, u'5'), Phrase('19197348', 2, 204, 0, u'HDL-C'), Phrase('19197348', 2, 205, 0, u'1'), Phrase('19197348', 2, 216, 0, u'2'), Phrase('19197348', 2, 227, 0, u'LDL-C'), Phrase('19197348', 2, 228, 0, u'1'), Phrase('19197348', 2, 239, 0, u'2'), Phrase('19197348', 2, 250, 0, u'3'), Phrase('19197348', 2, 261, 0, u'Total Cholesterol'), Phrase('19197348', 2, 262, 0, u'1'), Phrase('19197348', 2, 273, 0, u'2'), Phrase('19197348', 2, 284, 0, u'3'), Phrase('19197348', 2, 295, 0, u'4'), Phrase('19197348', 2, 306, 0, u'5'), Phrase('19197348', 2, 317, 0, u'6'), Phrase('19197348', 2, 328, 0, u'7'), Phrase('19197348', 2, 339, 0, u'Triglycerides'), Phrase('19197348', 2, 340, 0, u'1'), Phrase('19197348', 2, 351, 0, u'2'), Phrase('19197348', 2, 362, 0, u'3'), Phrase('19197348', 2, 373, 0, u'4'), Phrase('19197348', 2, 384, 0, u'5'), Phrase('19197348', 2, 395, 0, u'6'), Phrase('19197348', 2, 406, 0, u'7'), Phrase('19197348', 2, 417, 0, u'8'), Phrase('19197348', 2, 428, 0, u'9'), Phrase('19197348', 2, 439, 0, u'10'), Phrase('19197348', 2, 450, 0, u'11'), Phrase('19197348', 2, 461, 0, u'Systolic BP'), Phrase('19197348', 2, 462, 0, u'1'), Phrase('19197348', 2, 473, 0, u'2'), Phrase('19197348', 2, 484, 0, u'3'), Phrase('19197348', 2, 495, 0, u'4'), Phrase('19197348', 2, 506, 0, u'5'), Phrase('19197348', 2, 517, 0, u'Diastolic BP'), Phrase('19197348', 2, 518, 0, u'1'), Phrase('19197348', 2, 529, 0, u'2'), Phrase('19197348', 2, 540, 0, u'Fasting plasma glucose'), Phrase('19197348', 2, 541, 0, u'1'), Phrase('19197348', 2, 552, 0, u'Thyroid Stimulating Hormone'), Phrase('19197348', 2, 553, 0, u'1'), Phrase('19197348', 2, 564, 0, u'2'), Phrase('19197348', 2, 575, 0, u'3'), Phrase('19197348', 2, 586, 0, u'4'), Phrase('19197348', 2, 597, 0, u'5'), Phrase('19197348', 2, 608, 0, u'6'), Phrase('19197348', 2, 619, 0, u'7'), Phrase('19197348', 2, 630, 0, u'8'), Phrase('19197348', 2, 641, 0, u'9'), Phrase('19197348', 2, 652, 0, u'10'), Phrase('19197348', 2, 663, 0, u'11'), Phrase('19197348', 2, 674, 0, u'12'), Phrase('19197348', 2, 685, 0, u'13'), Phrase('19197348', 2, 696, 0, u'14'), Phrase('19197348', 2, 707, 0, u'15'), Phrase('19197348', 2, 718, 0, u'16'), Phrase('19197348', 2, 729, 0, u'17'), Phrase('19197348', 2, 740, 0, u'18'), Phrase('19197348', 2, 751, 0, u'19'), Phrase('19197348', 2, 762, 0, u'20'), Phrase('19197348', 2, 773, 0, u'21'), Phrase('19197348', 2, 784, 0, u'22'), Phrase('19197348', 2, 795, 0, u'23'), Phrase('19197348', 2, 806, 0, u'24'), Phrase('19197348', 2, 817, 0, u'25'), Phrase('19197348', 2, 828, 0, u'26'), Phrase('19197348', 2, 839, 0, u'27'), Phrase('19197348', 2, 850, 0, u'28'), Phrase('19197348', 2, 861, 0, u'C-reactive protein'), Phrase('19197348', 2, 862, 0, u'1'), Phrase('19197348', 2, 873, 0, u'2'), Phrase('19197348', 2, 884, 0, u'3'), Phrase('19197348', 2, 895, 0, u'4'), Phrase('19197348', 2, 906, 0, u'5'), Phrase('19197348', 2, 917, 0, u'6'), Phrase('19197348', 2, 928, 0, u'7'), Phrase('19197348', 2, 939, 0, u'8'), Phrase('19197348', 2, 950, 0, u'9'), Phrase('19197348', 2, 961, 0, u'10'), Phrase('19197348', 2, 972, 0, u'11'), Phrase('19197348', 2, 983, 0, u'12')]\n", - 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"[(u'17', False)]\n", - "[(u'18', False)]\n", - "[(u'19', False)]\n", - "[(u'20', False)]\n", - "[(u'21', False)]\n", - "[(u'22', False)]\n", - "[(u'23', False)]\n", - "[(u'24', False)]\n", - "[(u'25', False)]\n", - "[(u'26', False)]\n", - "[(u'27', False)]\n", - "[(u'28', False)]\n", - "[(u'C-reactive', False), (u'protein', False)]\n", - "[(u'1', False)]\n", - "[(u'2', False)]\n", - "[(u'3', False)]\n", - "[(u'4', False)]\n", - "[(u'5', False)]\n", - "[(u'6', False)]\n", - "[(u'7', False)]\n", - "[(u'8', False)]\n", - "[(u'9', False)]\n", - "[(u'10', False)]\n", - "[(u'11', False)]\n", - "[(u'12', False)]\n", - "\n", - "19197348 -1.0 None\n", - "Phrase('19197348', 2, 710, 0, u'rs10984516')\n", - "rs10984516 Thyroid Stimulating Hormone\n", - "[0, 0, 1]\n", - "[Phrase('19197348', 2, 0, 0, u'Rank'), Phrase('19197348', 2, 11, 0, u'BMI'), Phrase('19197348', 2, 12, 0, u'1'), Phrase('19197348', 2, 23, 0, u'Height'), Phrase('19197348', 2, 24, 0, u'1'), Phrase('19197348', 2, 35, 0, u'2'), Phrase('19197348', 2, 46, 0, u'Waist Circumference'), Phrase('19197348', 2, 47, 0, u'1'), Phrase('19197348', 2, 58, 0, u'2'), Phrase('19197348', 2, 69, 0, u'3'), Phrase('19197348', 2, 80, 0, u'4'), Phrase('19197348', 2, 91, 0, u'5'), Phrase('19197348', 2, 102, 0, u'Weight'), Phrase('19197348', 2, 103, 0, u'1'), Phrase('19197348', 2, 114, 0, u'2'), Phrase('19197348', 2, 125, 0, u'3'), Phrase('19197348', 2, 136, 0, u'Leptin'), Phrase('19197348', 2, 137, 0, u'1'), Phrase('19197348', 2, 148, 0, u'% body fat'), Phrase('19197348', 2, 149, 0, u'1'), Phrase('19197348', 2, 160, 0, u'2'), Phrase('19197348', 2, 171, 0, u'3'), Phrase('19197348', 2, 182, 0, u'4'), Phrase('19197348', 2, 193, 0, u'5'), Phrase('19197348', 2, 204, 0, u'HDL-C'), Phrase('19197348', 2, 205, 0, u'1'), Phrase('19197348', 2, 216, 0, u'2'), Phrase('19197348', 2, 227, 0, u'LDL-C'), Phrase('19197348', 2, 228, 0, u'1'), Phrase('19197348', 2, 239, 0, u'2'), Phrase('19197348', 2, 250, 0, u'3'), Phrase('19197348', 2, 261, 0, u'Total Cholesterol'), Phrase('19197348', 2, 262, 0, u'1'), Phrase('19197348', 2, 273, 0, u'2'), Phrase('19197348', 2, 284, 0, u'3'), Phrase('19197348', 2, 295, 0, u'4'), Phrase('19197348', 2, 306, 0, u'5'), Phrase('19197348', 2, 317, 0, u'6'), Phrase('19197348', 2, 328, 0, u'7'), Phrase('19197348', 2, 339, 0, u'Triglycerides'), Phrase('19197348', 2, 340, 0, u'1'), Phrase('19197348', 2, 351, 0, u'2'), Phrase('19197348', 2, 362, 0, u'3'), Phrase('19197348', 2, 373, 0, u'4'), Phrase('19197348', 2, 384, 0, u'5'), Phrase('19197348', 2, 395, 0, u'6'), Phrase('19197348', 2, 406, 0, u'7'), Phrase('19197348', 2, 417, 0, u'8'), Phrase('19197348', 2, 428, 0, u'9'), Phrase('19197348', 2, 439, 0, u'10'), Phrase('19197348', 2, 450, 0, u'11'), Phrase('19197348', 2, 461, 0, u'Systolic BP'), Phrase('19197348', 2, 462, 0, u'1'), Phrase('19197348', 2, 473, 0, u'2'), Phrase('19197348', 2, 484, 0, u'3'), Phrase('19197348', 2, 495, 0, u'4'), Phrase('19197348', 2, 506, 0, u'5'), Phrase('19197348', 2, 517, 0, u'Diastolic BP'), Phrase('19197348', 2, 518, 0, u'1'), Phrase('19197348', 2, 529, 0, u'2'), Phrase('19197348', 2, 540, 0, u'Fasting plasma glucose'), Phrase('19197348', 2, 541, 0, u'1'), Phrase('19197348', 2, 553, 0, u'1'), Phrase('19197348', 2, 564, 0, u'2'), Phrase('19197348', 2, 575, 0, u'3'), Phrase('19197348', 2, 586, 0, u'4'), Phrase('19197348', 2, 597, 0, u'5'), Phrase('19197348', 2, 608, 0, u'6'), Phrase('19197348', 2, 619, 0, u'7'), Phrase('19197348', 2, 630, 0, u'8'), Phrase('19197348', 2, 641, 0, u'9'), Phrase('19197348', 2, 652, 0, u'10'), Phrase('19197348', 2, 663, 0, u'11'), Phrase('19197348', 2, 674, 0, u'12'), Phrase('19197348', 2, 685, 0, u'13'), Phrase('19197348', 2, 696, 0, u'14'), Phrase('19197348', 2, 707, 0, u'15'), Phrase('19197348', 2, 718, 0, u'16'), Phrase('19197348', 2, 729, 0, u'17'), Phrase('19197348', 2, 740, 0, u'18'), Phrase('19197348', 2, 751, 0, u'19'), Phrase('19197348', 2, 762, 0, u'20'), Phrase('19197348', 2, 773, 0, u'21'), Phrase('19197348', 2, 784, 0, u'22'), Phrase('19197348', 2, 795, 0, u'23'), Phrase('19197348', 2, 806, 0, u'24'), Phrase('19197348', 2, 817, 0, u'25'), Phrase('19197348', 2, 828, 0, u'26'), Phrase('19197348', 2, 839, 0, u'27'), Phrase('19197348', 2, 850, 0, u'28'), Phrase('19197348', 2, 861, 0, u'C-reactive protein'), Phrase('19197348', 2, 862, 0, u'1'), Phrase('19197348', 2, 873, 0, u'2'), Phrase('19197348', 2, 884, 0, u'3'), Phrase('19197348', 2, 895, 0, u'4'), Phrase('19197348', 2, 906, 0, u'5'), Phrase('19197348', 2, 917, 0, u'6'), Phrase('19197348', 2, 928, 0, u'7'), Phrase('19197348', 2, 939, 0, u'8'), Phrase('19197348', 2, 950, 0, u'9'), Phrase('19197348', 2, 961, 0, u'10'), Phrase('19197348', 2, 972, 0, u'11'), Phrase('19197348', 2, 983, 0, u'12')]\n", - 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"[(u'17', False)]\n", - "[(u'18', False)]\n", - "[(u'19', False)]\n", - "[(u'20', False)]\n", - "[(u'21', False)]\n", - "[(u'22', False)]\n", - "[(u'23', False)]\n", - "[(u'24', False)]\n", - "[(u'25', False)]\n", - "[(u'26', False)]\n", - "[(u'27', False)]\n", - "[(u'28', False)]\n", - "[(u'C-reactive', False), (u'protein', False)]\n", - "[(u'1', False)]\n", - "[(u'2', False)]\n", - "[(u'3', False)]\n", - "[(u'4', False)]\n", - "[(u'5', False)]\n", - "[(u'6', False)]\n", - "[(u'7', False)]\n", - "[(u'8', False)]\n", - "[(u'9', False)]\n", - "[(u'10', False)]\n", - "[(u'11', False)]\n", - "[(u'12', False)]\n", - "\n", - "19197348 -1.0 None\n", - "Phrase('19197348', 2, 754, 0, u'rs10243770')\n", - "rs10243770 Thyroid Stimulating Hormone\n", - "[0, 0, 1]\n", - "[Phrase('19197348', 2, 0, 0, u'Rank'), Phrase('19197348', 2, 11, 0, u'BMI'), Phrase('19197348', 2, 12, 0, u'1'), Phrase('19197348', 2, 23, 0, u'Height'), Phrase('19197348', 2, 24, 0, u'1'), Phrase('19197348', 2, 35, 0, u'2'), Phrase('19197348', 2, 46, 0, u'Waist Circumference'), Phrase('19197348', 2, 47, 0, u'1'), Phrase('19197348', 2, 58, 0, u'2'), Phrase('19197348', 2, 69, 0, u'3'), Phrase('19197348', 2, 80, 0, u'4'), Phrase('19197348', 2, 91, 0, u'5'), Phrase('19197348', 2, 102, 0, u'Weight'), Phrase('19197348', 2, 103, 0, u'1'), Phrase('19197348', 2, 114, 0, u'2'), Phrase('19197348', 2, 125, 0, u'3'), Phrase('19197348', 2, 136, 0, u'Leptin'), Phrase('19197348', 2, 137, 0, u'1'), Phrase('19197348', 2, 148, 0, u'% body fat'), Phrase('19197348', 2, 149, 0, u'1'), Phrase('19197348', 2, 160, 0, u'2'), Phrase('19197348', 2, 171, 0, u'3'), Phrase('19197348', 2, 182, 0, u'4'), Phrase('19197348', 2, 193, 0, u'5'), Phrase('19197348', 2, 204, 0, u'HDL-C'), Phrase('19197348', 2, 205, 0, u'1'), Phrase('19197348', 2, 216, 0, u'2'), Phrase('19197348', 2, 227, 0, u'LDL-C'), Phrase('19197348', 2, 228, 0, u'1'), Phrase('19197348', 2, 239, 0, u'2'), Phrase('19197348', 2, 250, 0, u'3'), Phrase('19197348', 2, 261, 0, u'Total Cholesterol'), Phrase('19197348', 2, 262, 0, u'1'), Phrase('19197348', 2, 273, 0, u'2'), Phrase('19197348', 2, 284, 0, u'3'), Phrase('19197348', 2, 295, 0, u'4'), Phrase('19197348', 2, 306, 0, u'5'), Phrase('19197348', 2, 317, 0, u'6'), Phrase('19197348', 2, 328, 0, u'7'), Phrase('19197348', 2, 339, 0, u'Triglycerides'), Phrase('19197348', 2, 340, 0, u'1'), Phrase('19197348', 2, 351, 0, u'2'), Phrase('19197348', 2, 362, 0, u'3'), Phrase('19197348', 2, 373, 0, u'4'), Phrase('19197348', 2, 384, 0, u'5'), Phrase('19197348', 2, 395, 0, u'6'), Phrase('19197348', 2, 406, 0, u'7'), Phrase('19197348', 2, 417, 0, u'8'), Phrase('19197348', 2, 428, 0, u'9'), Phrase('19197348', 2, 439, 0, u'10'), Phrase('19197348', 2, 450, 0, u'11'), Phrase('19197348', 2, 461, 0, u'Systolic BP'), Phrase('19197348', 2, 462, 0, u'1'), Phrase('19197348', 2, 473, 0, u'2'), Phrase('19197348', 2, 484, 0, u'3'), Phrase('19197348', 2, 495, 0, u'4'), Phrase('19197348', 2, 506, 0, u'5'), Phrase('19197348', 2, 517, 0, u'Diastolic BP'), Phrase('19197348', 2, 518, 0, u'1'), Phrase('19197348', 2, 529, 0, u'2'), Phrase('19197348', 2, 540, 0, u'Fasting plasma glucose'), Phrase('19197348', 2, 541, 0, u'1'), Phrase('19197348', 2, 553, 0, u'1'), Phrase('19197348', 2, 564, 0, u'2'), Phrase('19197348', 2, 575, 0, u'3'), Phrase('19197348', 2, 586, 0, u'4'), Phrase('19197348', 2, 597, 0, u'5'), Phrase('19197348', 2, 608, 0, u'6'), Phrase('19197348', 2, 619, 0, u'7'), Phrase('19197348', 2, 630, 0, u'8'), Phrase('19197348', 2, 641, 0, u'9'), Phrase('19197348', 2, 652, 0, u'10'), Phrase('19197348', 2, 663, 0, u'11'), Phrase('19197348', 2, 674, 0, u'12'), Phrase('19197348', 2, 685, 0, u'13'), Phrase('19197348', 2, 696, 0, u'14'), Phrase('19197348', 2, 707, 0, u'15'), Phrase('19197348', 2, 718, 0, u'16'), Phrase('19197348', 2, 729, 0, u'17'), Phrase('19197348', 2, 740, 0, u'18'), Phrase('19197348', 2, 751, 0, u'19'), Phrase('19197348', 2, 762, 0, u'20'), Phrase('19197348', 2, 773, 0, u'21'), Phrase('19197348', 2, 784, 0, u'22'), Phrase('19197348', 2, 795, 0, u'23'), Phrase('19197348', 2, 806, 0, u'24'), Phrase('19197348', 2, 817, 0, u'25'), Phrase('19197348', 2, 828, 0, u'26'), Phrase('19197348', 2, 839, 0, u'27'), Phrase('19197348', 2, 850, 0, u'28'), Phrase('19197348', 2, 861, 0, u'C-reactive protein'), Phrase('19197348', 2, 862, 0, u'1'), Phrase('19197348', 2, 873, 0, u'2'), Phrase('19197348', 2, 884, 0, u'3'), Phrase('19197348', 2, 895, 0, u'4'), Phrase('19197348', 2, 906, 0, u'5'), Phrase('19197348', 2, 917, 0, u'6'), Phrase('19197348', 2, 928, 0, u'7'), Phrase('19197348', 2, 939, 0, u'8'), Phrase('19197348', 2, 950, 0, u'9'), Phrase('19197348', 2, 961, 0, u'10'), Phrase('19197348', 2, 972, 0, u'11'), Phrase('19197348', 2, 983, 0, u'12')]\n", - 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"[(u'rs328', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs12130333', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs17321515', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs17145738', False)]\n", - "[(u'Fasting', False), (u'plasma', False), (u'glucose', False)]\n", - "[(u'rs563694', False)]\n", - "[(u'rs1799884', False)]\n", - "[(u'Thyroid', False), (u'Stimulating', False), (u'Hormone', False)]\n", - "[(u'rs4704397', False)]\n", - "[(u'C-Reactive', False), (u'Protein', False)]\n", - "[(u'rs7553007', False)]\n", - "[(u'rs1892534', False)]\n", - "[(u'rs7310409', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs4129267', False)]\n", - "\n", - "19197348 -1.0 None\n", - "Phrase('19197348', 3, 57, 0, u'rs6440003')\n", - "rs6440003 Height\n", - "[0, 0, 1]\n", - "[Phrase('19197348', 3, 9, 0, u'SNP'), Phrase('19197348', 3, 22, 0, u'BMI'), Phrase('19197348', 3, 23, 0, u'rs9939609'), Phrase('19197348', 3, 36, 0, u'rs17782313'), Phrase('19197348', 3, 50, 0, u'rs6763931'), Phrase('19197348', 3, 63, 0, u'rs724016'), Phrase('19197348', 3, 76, 0, u'rs1042725'), Phrase('19197348', 3, 89, 0, u'rs6060369'), Phrase('19197348', 3, 102, 0, u'rs798544'), Phrase('19197348', 3, 115, 0, u'rs3748069'), Phrase('19197348', 3, 128, 0, u'rs1812175'), Phrase('19197348', 3, 141, 0, u'rs7153027'), Phrase('19197348', 3, 154, 0, u'rs6830062'), Phrase('19197348', 3, 167, 0, u'rs3760318'), Phrase('19197348', 3, 180, 0, u'rs2282978'), Phrase('19197348', 3, 193, 0, u'rs967417'), Phrase('19197348', 3, 206, 0, u'rs4743034'), Phrase('19197348', 3, 219, 0, u'rs678962'), Phrase('19197348', 3, 232, 0, u'rs4533267'), Phrase('19197348', 3, 245, 0, u'rs7846385'), Phrase('19197348', 3, 258, 0, u'rs2562784'), Phrase('19197348', 3, 271, 0, u'rs4794665'), Phrase('19197348', 3, 284, 0, u'HDL-C'), Phrase('19197348', 3, 285, 0, u'rs1800775'), Phrase('19197348', 3, 298, 0, u'rs4846914'), Phrase('19197348', 3, 311, 0, u'rs2156552'), Phrase('19197348', 3, 324, 0, u'rs3890182'), Phrase('19197348', 3, 337, 0, u'rs328'), Phrase('19197348', 3, 350, 0, u'LDL-C'), Phrase('19197348', 3, 351, 0, u'rs12654264'), Phrase('19197348', 3, 364, 0, u'rs693'), Phrase('19197348', 3, 377, 0, u'rs4420638'), Phrase('19197348', 3, 390, 0, u'rs16996148'), Phrase('19197348', 3, 403, 0, u'Triglycerides'), Phrase('19197348', 3, 404, 0, u'rs328'), Phrase('19197348', 3, 417, 0, u'rs693'), Phrase('19197348', 3, 430, 0, u'rs12130333'), Phrase('19197348', 3, 443, 0, u'rs780094'), Phrase('19197348', 3, 456, 0, u'rs17321515'), Phrase('19197348', 3, 469, 0, u'rs16996148'), Phrase('19197348', 3, 482, 0, u'rs4846914'), Phrase('19197348', 3, 495, 0, u'rs17145738'), Phrase('19197348', 3, 508, 0, u'Fasting plasma glucose'), Phrase('19197348', 3, 509, 0, u'rs563694'), Phrase('19197348', 3, 522, 0, u'rs1799884'), Phrase('19197348', 3, 535, 0, u'Thyroid Stimulating Hormone'), Phrase('19197348', 3, 536, 0, u'rs4704397'), Phrase('19197348', 3, 549, 0, u'C-Reactive Protein'), Phrase('19197348', 3, 550, 0, u'rs7553007'), Phrase('19197348', 3, 563, 0, u'rs1892534'), Phrase('19197348', 3, 576, 0, u'rs7310409'), Phrase('19197348', 3, 589, 0, u'rs780094'), Phrase('19197348', 3, 602, 0, u'rs4129267')]\n", - "[(u'SNP', False)]\n", - "[(u'BMI', False)]\n", - "[(u'rs9939609', False)]\n", - "[(u'rs17782313', False)]\n", - "[(u'rs6763931', False)]\n", - "[(u'rs724016', False)]\n", - "[(u'rs1042725', False)]\n", - "[(u'rs6060369', False)]\n", - "[(u'rs798544', False)]\n", - "[(u'rs3748069', False)]\n", - "[(u'rs1812175', False)]\n", - "[(u'rs7153027', False)]\n", - "[(u'rs6830062', False)]\n", - "[(u'rs3760318', False)]\n", - "[(u'rs2282978', False)]\n", - "[(u'rs967417', False)]\n", - "[(u'rs4743034', False)]\n", - "[(u'rs678962', False)]\n", - "[(u'rs4533267', False)]\n", - "[(u'rs7846385', False)]\n", - "[(u'rs2562784', False)]\n", - "[(u'rs4794665', False)]\n", - "[(u'HDL-C', False)]\n", - "[(u'rs1800775', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs2156552', False)]\n", - "[(u'rs3890182', False)]\n", - "[(u'rs328', False)]\n", - "[(u'LDL-C', False)]\n", - "[(u'rs12654264', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs4420638', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'Triglycerides', False)]\n", - 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"[(u'rs328', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs12130333', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs17321515', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs17145738', False)]\n", - "[(u'Fasting', False), (u'plasma', False), (u'glucose', False)]\n", - "[(u'rs563694', False)]\n", - "[(u'rs1799884', False)]\n", - "[(u'Thyroid', False), (u'Stimulating', False), (u'Hormone', False)]\n", - "[(u'rs4704397', False)]\n", - "[(u'C-Reactive', False), (u'Protein', False)]\n", - "[(u'rs7553007', False)]\n", - "[(u'rs1892534', False)]\n", - "[(u'rs7310409', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs4129267', False)]\n", - "\n", - "19197348 -1.0 None\n", - "Phrase('19197348', 3, 76, 0, u'rs1042725')\n", - "rs1042725 Height\n", - "[0, 0, 1]\n", - "[Phrase('19197348', 3, 9, 0, u'SNP'), Phrase('19197348', 3, 22, 0, u'BMI'), Phrase('19197348', 3, 23, 0, u'rs9939609'), Phrase('19197348', 3, 36, 0, u'rs17782313'), Phrase('19197348', 3, 50, 0, u'rs6763931'), Phrase('19197348', 3, 63, 0, u'rs724016'), Phrase('19197348', 3, 76, 0, u'rs1042725'), Phrase('19197348', 3, 89, 0, u'rs6060369'), Phrase('19197348', 3, 102, 0, u'rs798544'), Phrase('19197348', 3, 115, 0, u'rs3748069'), Phrase('19197348', 3, 128, 0, u'rs1812175'), Phrase('19197348', 3, 141, 0, u'rs7153027'), Phrase('19197348', 3, 154, 0, u'rs6830062'), Phrase('19197348', 3, 167, 0, u'rs3760318'), Phrase('19197348', 3, 180, 0, u'rs2282978'), Phrase('19197348', 3, 193, 0, u'rs967417'), Phrase('19197348', 3, 206, 0, u'rs4743034'), Phrase('19197348', 3, 219, 0, u'rs678962'), Phrase('19197348', 3, 232, 0, u'rs4533267'), Phrase('19197348', 3, 245, 0, u'rs7846385'), Phrase('19197348', 3, 258, 0, u'rs2562784'), Phrase('19197348', 3, 271, 0, u'rs4794665'), Phrase('19197348', 3, 284, 0, u'HDL-C'), Phrase('19197348', 3, 285, 0, u'rs1800775'), Phrase('19197348', 3, 298, 0, u'rs4846914'), Phrase('19197348', 3, 311, 0, u'rs2156552'), Phrase('19197348', 3, 324, 0, u'rs3890182'), Phrase('19197348', 3, 337, 0, u'rs328'), Phrase('19197348', 3, 350, 0, u'LDL-C'), Phrase('19197348', 3, 351, 0, u'rs12654264'), Phrase('19197348', 3, 364, 0, u'rs693'), Phrase('19197348', 3, 377, 0, u'rs4420638'), Phrase('19197348', 3, 390, 0, u'rs16996148'), Phrase('19197348', 3, 403, 0, u'Triglycerides'), Phrase('19197348', 3, 404, 0, u'rs328'), Phrase('19197348', 3, 417, 0, u'rs693'), Phrase('19197348', 3, 430, 0, u'rs12130333'), Phrase('19197348', 3, 443, 0, u'rs780094'), Phrase('19197348', 3, 456, 0, u'rs17321515'), Phrase('19197348', 3, 469, 0, u'rs16996148'), Phrase('19197348', 3, 482, 0, u'rs4846914'), Phrase('19197348', 3, 495, 0, u'rs17145738'), Phrase('19197348', 3, 508, 0, u'Fasting plasma glucose'), Phrase('19197348', 3, 509, 0, u'rs563694'), Phrase('19197348', 3, 522, 0, u'rs1799884'), Phrase('19197348', 3, 535, 0, u'Thyroid Stimulating Hormone'), Phrase('19197348', 3, 536, 0, u'rs4704397'), Phrase('19197348', 3, 549, 0, u'C-Reactive Protein'), Phrase('19197348', 3, 550, 0, u'rs7553007'), Phrase('19197348', 3, 563, 0, u'rs1892534'), Phrase('19197348', 3, 576, 0, u'rs7310409'), Phrase('19197348', 3, 589, 0, u'rs780094'), Phrase('19197348', 3, 602, 0, u'rs4129267')]\n", - 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"[(u'Triglycerides', False)]\n", - "[(u'rs328', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs12130333', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs17321515', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs17145738', False)]\n", - "[(u'rs563694', False)]\n", - "[(u'rs1799884', False)]\n", - "[(u'Thyroid', False), (u'Stimulating', False), (u'Hormone', False)]\n", - "[(u'rs4704397', False)]\n", - "[(u'C-Reactive', False), (u'Protein', False)]\n", - "[(u'rs7553007', False)]\n", - "[(u'rs1892534', False)]\n", - "[(u'rs7310409', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs4129267', False)]\n", - "\n", - "19197348 -1.0 None\n", - "Phrase('19197348', 3, 522, 0, u'rs1799884')\n", - "rs1799884 Fasting plasma glucose\n", - "[0, 0, 1]\n", - "[Phrase('19197348', 3, 9, 0, u'SNP'), Phrase('19197348', 3, 22, 0, u'BMI'), Phrase('19197348', 3, 23, 0, u'rs9939609'), Phrase('19197348', 3, 36, 0, u'rs17782313'), Phrase('19197348', 3, 49, 0, u'Height'), Phrase('19197348', 3, 50, 0, u'rs6763931'), Phrase('19197348', 3, 63, 0, u'rs724016'), Phrase('19197348', 3, 76, 0, u'rs1042725'), Phrase('19197348', 3, 89, 0, u'rs6060369'), Phrase('19197348', 3, 102, 0, u'rs798544'), Phrase('19197348', 3, 115, 0, u'rs3748069'), Phrase('19197348', 3, 128, 0, u'rs1812175'), Phrase('19197348', 3, 141, 0, u'rs7153027'), Phrase('19197348', 3, 154, 0, u'rs6830062'), Phrase('19197348', 3, 167, 0, u'rs3760318'), Phrase('19197348', 3, 180, 0, u'rs2282978'), Phrase('19197348', 3, 193, 0, u'rs967417'), Phrase('19197348', 3, 206, 0, u'rs4743034'), Phrase('19197348', 3, 219, 0, u'rs678962'), Phrase('19197348', 3, 232, 0, u'rs4533267'), Phrase('19197348', 3, 245, 0, u'rs7846385'), Phrase('19197348', 3, 258, 0, u'rs2562784'), Phrase('19197348', 3, 271, 0, u'rs4794665'), Phrase('19197348', 3, 284, 0, u'HDL-C'), Phrase('19197348', 3, 285, 0, u'rs1800775'), Phrase('19197348', 3, 298, 0, u'rs4846914'), Phrase('19197348', 3, 311, 0, u'rs2156552'), Phrase('19197348', 3, 324, 0, u'rs3890182'), Phrase('19197348', 3, 337, 0, u'rs328'), Phrase('19197348', 3, 350, 0, u'LDL-C'), Phrase('19197348', 3, 351, 0, u'rs12654264'), Phrase('19197348', 3, 364, 0, u'rs693'), Phrase('19197348', 3, 377, 0, u'rs4420638'), Phrase('19197348', 3, 390, 0, u'rs16996148'), Phrase('19197348', 3, 403, 0, u'Triglycerides'), Phrase('19197348', 3, 404, 0, u'rs328'), Phrase('19197348', 3, 417, 0, u'rs693'), Phrase('19197348', 3, 430, 0, u'rs12130333'), Phrase('19197348', 3, 443, 0, u'rs780094'), Phrase('19197348', 3, 456, 0, u'rs17321515'), Phrase('19197348', 3, 469, 0, u'rs16996148'), Phrase('19197348', 3, 482, 0, u'rs4846914'), Phrase('19197348', 3, 495, 0, u'rs17145738'), Phrase('19197348', 3, 509, 0, u'rs563694'), Phrase('19197348', 3, 522, 0, u'rs1799884'), Phrase('19197348', 3, 535, 0, u'Thyroid Stimulating Hormone'), Phrase('19197348', 3, 536, 0, u'rs4704397'), Phrase('19197348', 3, 549, 0, u'C-Reactive Protein'), Phrase('19197348', 3, 550, 0, u'rs7553007'), Phrase('19197348', 3, 563, 0, u'rs1892534'), Phrase('19197348', 3, 576, 0, u'rs7310409'), Phrase('19197348', 3, 589, 0, u'rs780094'), Phrase('19197348', 3, 602, 0, u'rs4129267')]\n", - "[(u'SNP', False)]\n", - "[(u'BMI', False)]\n", - "[(u'rs9939609', False)]\n", - "[(u'rs17782313', False)]\n", - "[(u'Height', False)]\n", - "[(u'rs6763931', False)]\n", - "[(u'rs724016', False)]\n", - "[(u'rs1042725', False)]\n", - "[(u'rs6060369', False)]\n", - "[(u'rs798544', False)]\n", - "[(u'rs3748069', False)]\n", - "[(u'rs1812175', False)]\n", - "[(u'rs7153027', False)]\n", - "[(u'rs6830062', False)]\n", - "[(u'rs3760318', False)]\n", - "[(u'rs2282978', False)]\n", - "[(u'rs967417', False)]\n", - "[(u'rs4743034', False)]\n", - "[(u'rs678962', False)]\n", - "[(u'rs4533267', False)]\n", - "[(u'rs7846385', False)]\n", - "[(u'rs2562784', False)]\n", - "[(u'rs4794665', False)]\n", - "[(u'HDL-C', False)]\n", - "[(u'rs1800775', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs2156552', False)]\n", - "[(u'rs3890182', False)]\n", - "[(u'rs328', False)]\n", - "[(u'LDL-C', False)]\n", - "[(u'rs12654264', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs4420638', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'Triglycerides', False)]\n", - "[(u'rs328', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs12130333', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs17321515', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs17145738', False)]\n", - "[(u'rs563694', False)]\n", - "[(u'rs1799884', False)]\n", - "[(u'Thyroid', False), (u'Stimulating', False), (u'Hormone', False)]\n", - "[(u'rs4704397', False)]\n", - "[(u'C-Reactive', False), (u'Protein', False)]\n", - "[(u'rs7553007', False)]\n", - "[(u'rs1892534', False)]\n", - "[(u'rs7310409', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs4129267', False)]\n", - "\n", - "19197348 -1.0 None\n", - "Phrase('19197348', 3, 536, 0, u'rs4704397')\n", - "rs4704397 Thyroid Stimulating Hormone\n", - "[0, 0, 1]\n", - "[Phrase('19197348', 3, 9, 0, u'SNP'), Phrase('19197348', 3, 22, 0, u'BMI'), Phrase('19197348', 3, 23, 0, u'rs9939609'), Phrase('19197348', 3, 36, 0, u'rs17782313'), Phrase('19197348', 3, 49, 0, u'Height'), Phrase('19197348', 3, 50, 0, u'rs6763931'), Phrase('19197348', 3, 63, 0, u'rs724016'), Phrase('19197348', 3, 76, 0, u'rs1042725'), Phrase('19197348', 3, 89, 0, u'rs6060369'), Phrase('19197348', 3, 102, 0, u'rs798544'), Phrase('19197348', 3, 115, 0, u'rs3748069'), Phrase('19197348', 3, 128, 0, u'rs1812175'), Phrase('19197348', 3, 141, 0, u'rs7153027'), Phrase('19197348', 3, 154, 0, u'rs6830062'), Phrase('19197348', 3, 167, 0, u'rs3760318'), Phrase('19197348', 3, 180, 0, u'rs2282978'), Phrase('19197348', 3, 193, 0, u'rs967417'), Phrase('19197348', 3, 206, 0, u'rs4743034'), Phrase('19197348', 3, 219, 0, u'rs678962'), Phrase('19197348', 3, 232, 0, u'rs4533267'), Phrase('19197348', 3, 245, 0, u'rs7846385'), Phrase('19197348', 3, 258, 0, u'rs2562784'), Phrase('19197348', 3, 271, 0, u'rs4794665'), Phrase('19197348', 3, 284, 0, u'HDL-C'), Phrase('19197348', 3, 285, 0, u'rs1800775'), Phrase('19197348', 3, 298, 0, u'rs4846914'), Phrase('19197348', 3, 311, 0, u'rs2156552'), Phrase('19197348', 3, 324, 0, u'rs3890182'), Phrase('19197348', 3, 337, 0, u'rs328'), Phrase('19197348', 3, 350, 0, u'LDL-C'), Phrase('19197348', 3, 351, 0, u'rs12654264'), Phrase('19197348', 3, 364, 0, u'rs693'), Phrase('19197348', 3, 377, 0, u'rs4420638'), Phrase('19197348', 3, 390, 0, u'rs16996148'), Phrase('19197348', 3, 403, 0, u'Triglycerides'), Phrase('19197348', 3, 404, 0, u'rs328'), Phrase('19197348', 3, 417, 0, u'rs693'), Phrase('19197348', 3, 430, 0, u'rs12130333'), Phrase('19197348', 3, 443, 0, u'rs780094'), Phrase('19197348', 3, 456, 0, u'rs17321515'), Phrase('19197348', 3, 469, 0, u'rs16996148'), Phrase('19197348', 3, 482, 0, u'rs4846914'), Phrase('19197348', 3, 495, 0, u'rs17145738'), Phrase('19197348', 3, 508, 0, u'Fasting plasma glucose'), Phrase('19197348', 3, 509, 0, u'rs563694'), Phrase('19197348', 3, 522, 0, u'rs1799884'), Phrase('19197348', 3, 536, 0, u'rs4704397'), Phrase('19197348', 3, 549, 0, u'C-Reactive Protein'), Phrase('19197348', 3, 550, 0, u'rs7553007'), Phrase('19197348', 3, 563, 0, u'rs1892534'), Phrase('19197348', 3, 576, 0, u'rs7310409'), Phrase('19197348', 3, 589, 0, u'rs780094'), Phrase('19197348', 3, 602, 0, u'rs4129267')]\n", - "[(u'SNP', False)]\n", - "[(u'BMI', False)]\n", - "[(u'rs9939609', False)]\n", - "[(u'rs17782313', False)]\n", - "[(u'Height', False)]\n", - "[(u'rs6763931', False)]\n", - "[(u'rs724016', False)]\n", - "[(u'rs1042725', False)]\n", - "[(u'rs6060369', False)]\n", - "[(u'rs798544', False)]\n", - "[(u'rs3748069', False)]\n", - "[(u'rs1812175', False)]\n", - "[(u'rs7153027', False)]\n", - "[(u'rs6830062', False)]\n", - "[(u'rs3760318', False)]\n", - "[(u'rs2282978', False)]\n", - "[(u'rs967417', False)]\n", - "[(u'rs4743034', False)]\n", - "[(u'rs678962', False)]\n", - "[(u'rs4533267', False)]\n", - "[(u'rs7846385', False)]\n", - "[(u'rs2562784', False)]\n", - "[(u'rs4794665', False)]\n", - "[(u'HDL-C', False)]\n", - "[(u'rs1800775', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs2156552', False)]\n", - "[(u'rs3890182', False)]\n", - "[(u'rs328', False)]\n", - "[(u'LDL-C', False)]\n", - "[(u'rs12654264', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs4420638', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'Triglycerides', False)]\n", - "[(u'rs328', False)]\n", - "[(u'rs693', False)]\n", - "[(u'rs12130333', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs17321515', False)]\n", - "[(u'rs16996148', False)]\n", - "[(u'rs4846914', False)]\n", - "[(u'rs17145738', False)]\n", - "[(u'Fasting', False), (u'plasma', False), (u'glucose', False)]\n", - "[(u'rs563694', False)]\n", - "[(u'rs1799884', False)]\n", - "[(u'rs4704397', False)]\n", - "[(u'C-Reactive', False), (u'Protein', False)]\n", - "[(u'rs7553007', False)]\n", - "[(u'rs1892534', False)]\n", - "[(u'rs7310409', False)]\n", - "[(u'rs780094', False)]\n", - "[(u'rs4129267', False)]\n", - "\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "# preds = learner.predict_wmv(candidates)\n", - "acronyms = [spair2uid(c) for (c, p) in zip(candidates, preds) if p == 1]\n", - "mislabeled_cand = [(c,p, annotations.get(spair2uid(c), None)) for c, p in zip(candidates, preds)]# if p != annotations.get(spair2uid(c), p)]\n", - "for (c,p,g) in mislabeled_cand:\n", - " if c.span0.context.document.name != '19197348': continue\n", - " print c.span0.context.document.name, p, g\n", - " print c.span0.context \n", - " print c.span0.get_span(), c.span1.get_span()\n", - " txt = c.span1.get_span()\n", - " print [LF(c) for LF in LF_tables]\n", - " top_cells = c.span1.context.cell.aligned_cells(axis='col', induced=True)\n", - " top_phrases = [phrase for cell in top_cells for phrase in cell.phrases]\n", - " print top_phrases\n", - " matching_phrases = []\n", - " for phrase in top_phrases:\n", - " print [(word,phen_matcher._f_span(word)) for word in phrase.text.split(' ')]\n", - " if any (phen_matcher._f_span(word) for word in phrase.text.split(' ')):\n", - " matching_phrases.append(phrase)\n", - " print phrase\n", - "# print phrase, [phen_matcher._f_span(word) for word in phrase.text.split(' ')]\n", - " print" + "### Training a machine learning model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Save the results" + "Next, we train a generative model, just like in the phenotype extraction notebook." ] }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Applying LFs...\n", - "Featurizing...\n", - "2974 relations extracted, e.g.:\n", - "[('17903292', u'rs1158167', u'CysC'), ('17903292', u'rs1712790', u'UAE'), ('17903292', u'rs6977660', u'TSH'), ('17903292', u'rs9322817', u'TSH'), ('17903292', u'rs10499559', u'TSH'), ('17903292', u'rs9305354', u'UAE'), ('17903292', u'rs2145231', u'CysC'), ('17903292', u'rs723464', u'UAE'), ('17903292', u'rs2113379', u'UAE'), ('17903292', u'rs2839235', u'GFR')]\n" + "/Library/Python/2.7/site-packages/matplotlib/__init__.py:1155: UserWarning: This call to matplotlib.use() has no effect\n", + "because the backend has already been chosen;\n", + "matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n", + "or matplotlib.backends is imported for the first time.\n", + "\n", + " warnings.warn(_use_error_msg)\n" ] - } - ], - "source": [ - "preds = learner.predict_wmv(candidates)\n", - "rels = [(c.span0.context.document.name, c.span0.get_span(), c.span1.get_span()) for (c, p) in zip(candidates, preds) if p == 1]\n", - "print len(rels), 'relations extracted, e.g.:'\n", - "print rels[:10]\n", - "\n", - "# store relations to annotate\n", - "with open('rels.acronyms.extracted.tsv', 'w') as f:\n", - " for doc_id, str1, str2 in rels:\n", - " try:\n", - " out = u'{}\\t{}\\t{}\\n'.format(doc_id, unicode(str1), str2)\n", - " f.write(out.encode(\"UTF-8\"))\n", - " except:\n", - " print 'Error in saving:', str1, str2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Resolve acronyms based on ones extracted earlier" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": { - "collapsed": false - }, - "outputs": [ + }, { "name": "stdout", "output_type": "stream", "text": [ - "326 definitions loaded\n" + "================================================================================\n", + "Training marginals (!= 0.5):\t1752\n", + "Features:\t\t\t3\n", + "================================================================================\n", + "Begin training for rate=0.01, mu=1e-06\n", + "\tLearning epoch = 0\tGradient mag. = 0.084432\n", + "\tLearning epoch = 250\tGradient mag. = 0.098711\n", + "\tLearning epoch = 500\tGradient mag. = 0.107868\n", + "\tLearning epoch = 750\tGradient mag. = 0.116008\n", + "\tLearning epoch = 1000\tGradient mag. = 0.122948\n", + "\tLearning epoch = 1250\tGradient mag. = 0.128657\n", + "\tLearning epoch = 1500\tGradient mag. = 0.133226\n", + "\tLearning epoch = 1750\tGradient mag. = 0.136810\n", + "\tLearning epoch = 2000\tGradient mag. = 0.139583\n", + "\tLearning epoch = 2250\tGradient mag. = 0.141712\n", + "\tLearning epoch = 2500\tGradient mag. = 0.143340\n", + "\tLearning epoch = 2750\tGradient mag. = 0.144582\n", + "\tLearning epoch = 3000\tGradient mag. = 0.145530\n", + "\tLearning epoch = 3250\tGradient mag. = 0.146254\n", + "\tLearning epoch = 3500\tGradient mag. = 0.146807\n", + "\tLearning epoch = 3750\tGradient mag. = 0.147231\n", + "\tLearning epoch = 4000\tGradient mag. = 0.147556\n", + "\tLearning epoch = 4250\tGradient mag. = 0.147805\n", + "\tLearning epoch = 4500\tGradient mag. = 0.147996\n", + "\tLearning epoch = 4750\tGradient mag. = 0.148143\n", + "\tLearning epoch = 5000\tGradient mag. = 0.148256\n", + "\tLearning epoch = 5250\tGradient mag. = 0.148343\n", + "\tLearning epoch = 5500\tGradient mag. = 0.148410\n", + "\tLearning epoch = 5750\tGradient mag. = 0.148462\n", + "\tLearning epoch = 6000\tGradient mag. = 0.148501\n", + "\tLearning epoch = 6250\tGradient mag. = 0.148532\n", + "\tLearning epoch = 6500\tGradient mag. = 0.148555\n", + "\tLearning epoch = 6750\tGradient mag. = 0.148574\n", + "\tLearning epoch = 7000\tGradient mag. = 0.148588\n", + "\tLearning epoch = 7250\tGradient mag. = 0.148598\n", + "\tLearning epoch = 7500\tGradient mag. = 0.148607\n", + "\tLearning epoch = 7750\tGradient mag. = 0.148613\n", + "\tLearning epoch = 8000\tGradient mag. = 0.148618\n", + "\tLearning epoch = 8250\tGradient mag. = 0.135731\n", + "\tLearning epoch = 8500\tGradient mag. = 0.120952\n", + "\tLearning epoch = 8750\tGradient mag. = 0.087698\n", + "\tLearning epoch = 9000\tGradient mag. = 0.061846\n", + "\tLearning epoch = 9250\tGradient mag. = 0.043708\n", + "\tLearning epoch = 9500\tGradient mag. = 0.030977\n", + "\tLearning epoch = 9750\tGradient mag. = 0.022038\n", + "Final gradient magnitude for rate=0.01, mu=1e-06: 0.016\n" ] } ], "source": [ - "from extractor.dictionary import Dictionary, unravel\n", + "from snorkel.learning import NaiveBayes\n", "\n", - "D = Dictionary()\n", - "D.load('acronyms.extracted.all.tsv')\n", - "print len(D), 'definitions loaded'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Use dictionary to resolve acronyms" + "gen_model = NaiveBayes()\n", + "gen_model.train(L_train, n_iter=10000, rate=1e-2)" ] }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 16, "metadata": { "collapsed": false }, - "outputs": [], - "source": [ - "new_rels = [ (doc_id, rs_id, unravel(doc_id, phen, D)) for doc_id, rs_id, phen in rels ]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 9.92867574, 9.91268375, 0.98503744])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "## Evaluate extracted relations" + "gen_model.w" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Let's first evaluate the recall w.r.t. GWAS Central" + "## Classify all the candidates" ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -7095,627 +789,31 @@ "name": "stdout", "output_type": "stream", "text": [ - "17447842 22 0\n", - "17658951 26 0\n", - "17684544 32 0\n", - "17903292 14 90\n", - "17903293 70 79\n", - "17903294 42 100\n", - "17903295 38 190\n", - "17903296 70 141\n", - "17903297 50 108\n", - "17903298 4 101\n", - "17903300 12 52\n", - "17903301 20 177\n", - "17903302 27 111\n", - "17903303 16 111\n", - "17903304 6 103\n", - "17903305 17 5\n", - "17903306 4 71\n", - "17903307 21 87\n", - "17903308 6 34\n", - "17997608 42 0\n", - "18159244 15 0\n", - "18262040 27 0\n", - "18282107 4 0\n", - "18369459 3 0\n", - "18455228 4 0\n", - "18464913 48 0\n", - "18483556 14 0\n", - "18604267 4 0\n", - "18776929 2 0\n", - "18823527 4 0\n", - "18840781 5 0\n", - "18846228 4 0\n", - "18941528 2 0\n", - "19043545 16 6\n", - "19056611 8 0\n", - "19081515 4 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0\n", - "24945404 0 25\n", - "24952745 0 0\n", - "24964207 0 0\n", - "24999842 0 0\n", - "25003214 0 0\n", - "25008200 0 0\n", - "25009551 0 0\n", - "25017104 0 0\n", - "25038754 0 0\n", - "25044758 0 0\n", - "25056061 0 0\n", - "25060954 0 0\n", - "25064009 0 0\n", - "25085501 0 0\n", - "25086665 0 0\n", - "25087078 0 9\n", - "25102180 0 0\n", - "25105248 0 0\n", - "25129146 0 0\n", - "25133637 0 25\n", - "25140149 0 0\n", - "25147783 0 0\n", - "25162662 0 0\n", - "25187353 0 0\n", - "25188341 0 11\n", - "25226531 0 0\n", - "25233373 0 0\n", - "25241763 0 0\n", - "25241909 0 0\n", - "25297839 0 0\n", - "25310577 0 0\n", - "25310821 0 0\n", - "25317111 0 0\n", - "25317112 0 0\n", - "25340798 0 54\n", - "25350695 0 0\n", - "25352737 0 0\n", - "25364816 0 0\n", - "25367360 0 7\n", - "25372704 0 0\n", - "25378659 0 0\n", - "25383866 0 0\n", - "25390645 0 0\n", - "25436638 0 0\n", - "25526632 0 0\n", - "25533491 0 0\n", - "25551457 0 0\n", - "25569183 0 0\n", - "25625606 0 0\n", - "25628645 0 0\n", - "25629512 0 0\n", - "25705158 0 0\n", - "25705159 0 0\n", - "25705162 0 0\n", - "25729143 0 0\n", - "25742292 0 0\n", - "25760438 0 0\n" + "Generating annotations for 3504 candidates...\n", + "[========================================] 100%\n", + "Loading sparse Label matrix...\n", + "CPU times: user 13min 15s, sys: 3min 22s, total: 16min 37s\n", + "Wall time: 16min 47s\n" ] } ], "source": [ - "for doc in corpus.documents:\n", - " assocs = [assoc for assoc in kb.assoc_by_pmid(doc.name) if assoc.source == 'gwas_central' and assoc.pvalue < 1e-5]\n", - " print doc.name, len(assocs), len([(pmid, rsid, phen) for pmid, rsid, phen in new_rels if pmid == doc.name])\n", - " " + "from snorkel.annotations import LabelManager\n", + "label_manager = LabelManager()\n", + "\n", + "%time L_all = label_manager.create(session, rels, 'RsidPhenRel LF All Labels', f=LFs)" ] }, { - "cell_type": "code", - "execution_count": 52, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[('17903305', u'rs905883', u'Breast cancer'), ('17903305', u'rs7564590', u'Breast cancer'), ('17903305', u'rs7558615', u'Breast cancer'), ('17903305', u'rs9325782', u'Prostate cancer'), ('17903305', u'rs2410373', u'Prostate cancer')]\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "print ([(pmid, rsid, phen) for pmid, rsid, phen in new_rels if pmid == '17903305'])" + "Save the results" ] }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 18, "metadata": { "collapsed": false }, @@ -7724,131 +822,73 @@ "name": "stdout", "output_type": "stream", "text": [ - "77 573\n" + "2745 relations extracted, e.g.:\n", + "[(u'17903300', u'rs7202384', u'Mean BMI'), (u'17903300', u'rs10486301', u'Mean BMI'), (u'17903300', u'rs7533902', u'Mean BMI'), (u'17903300', u'rs2226351', u'Mean WC'), (u'17903300', u'rs711702', u'Mean BMI'), (u'17903300', u'rs2296465', u'Mean BMI'), (u'17903300', u'rs10517461', u'Mean WC'), (u'17903300', u'rs1875517', u'Mean WC'), (u'17903300', u'rs4312989', u'Mean WC'), (u'17903300', u'rs2361128', u'Mean BMI')]\n" ] } ], "source": [ - "pmids = sorted(list({pmid for pmid, _, _ in new_rels}))\n", + "preds = gen_model.odds(L_all)\n", + "good_rels = [(c[0].parent.document.name, c[0].get_span(), c[1].get_span()) for (c, p) in zip(rels, preds) if p > 0]\n", + "print len(good_rels), 'relations extracted, e.g.:'\n", + "print good_rels[:10]\n", "\n", - "from db.kb import KnowledgeBase\n", - "kb = KnowledgeBase()\n", - "assocs = [assoc for pmid in pmids for assoc in kb.assoc_by_pmid(pmid) if assoc.source == 'gwas_central' and assoc.pvalue < 1e-5]\n", - "print len(pmids), len(assocs)" + "# store relations to annotate\n", + "with open('rels.acronyms.extracted.tsv', 'w') as f:\n", + " for doc_id, str1, str2 in good_rels:\n", + " try:\n", + " out = u'{}\\t{}\\t{}\\n'.format(doc_id, unicode(str1), str2)\n", + " f.write(out.encode(\"UTF-8\"))\n", + " except:\n", + " print 'Error in saving:', str1, str2" ] }, { - "cell_type": "code", - "execution_count": 54, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['17903292', '17903293', '17903294', '17903295', '17903296', '17903297', '17903298', '17903300', '17903301', '17903302', '17903303', '17903304', '17903305', '17903306', '17903307', '17903308', '19043545', '19197348', '19430483', '19448621', '19557161', '19609347', '19721433', '19820699', '20066028', '20195266', '20395239', '20463881', '20526338', '20548944', '20585627', '20694148', '20838585', '20921969', '20927387', '21203500', '21347282', '21386085', '21483430', '21483845', '21552555', '21738479', '21738480', '21738491', '21931564', '22216198', '22291609', '22509378', '22558069', '22589738', '22832964', '22911880', '23028342', '23118974', '23251661', '23408906', '23696099', '23704328', '23754948', '23836780', '23935956', '23966867', '24324551', '24347629', '24376456', '24379826', '24386095', '24586186', '24886709', '24892410', '24903457', '24945404', '25087078', '25133637', '25188341', '25340798', '25367360']\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "print pmids" + "## Resolve acronyms based on ones extracted earlier" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 49, "metadata": { "collapsed": false }, "outputs": [ { - "ename": "NameError", - "evalue": "name 'assocs' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mrel_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpmid\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrsid\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mphen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mgold_rel_dict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpaper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpubmed_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrs_id\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0massocs\u001b[0m \u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0massocs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mgold_rel_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpaper\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpubmed_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrs_id\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mphenotype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'assocs' is not defined" + "name": "stdout", + "output_type": "stream", + "text": [ + "326 definitions loaded\n" ] } ], "source": [ - "# collect resolved relations\n", - "rel_dict = { (pmid, rsid) : set() for (pmid, rsid, phen) in new_rels }\n", - "for (pmid, rsid, phen) in new_rels:\n", - " rel_dict[(pmid, rsid)].add(phen)\n", + "from extractor.dictionary import Dictionary, unravel\n", "\n", - "gold_rel_dict = { (a.paper.pubmed_id, a.snp.rs_id) : set() for a in assocs }\n", - "for a in assocs:\n", - " gold_rel_dict[(a.paper.pubmed_id, a.snp.rs_id)].add(a.phenotype.name)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First, evaluate recall: how many associations in GWAS central can we recover?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "for a in assocs[:500]:\n", - " s1 = gold_rel_dict[(a.paper.pubmed_id, a.snp.rs_id)]\n", - " s2 = rel_dict.get((str(a.paper.pubmed_id), a.snp.rs_id), {})\n", - " if len(s1) != 1 or len(s2) != 1:\n", - " print a.paper.pubmed_id, a.snp.rs_id, a.source\n", - " print 'GWC:', gold_rel_dict[(a.paper.pubmed_id, a.snp.rs_id)]\n", - " print 'US: ', rel_dict.get((str(a.paper.pubmed_id), a.snp.rs_id), None)\n", - " print" + "D = Dictionary()\n", + "D.load('acronyms.extracted.all.tsv')\n", + "print len(D), 'definitions loaded'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Second question: can we learn any more SNPs than the ones that are already in GWAS central?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "pmids = sorted(list({pmid for pmid, _, _ in new_rels if int(pmid) < 17903297}))\n", - "\n", - "from db.kb import KnowledgeBase\n", - "kb = KnowledgeBase()\n", - "assocs = [assoc for pmid in pmids for assoc in kb.assoc_by_pmid(pmid) if assoc.source == 'gwas_central']\n", - "print len(assocs)" + "Use dictionary to resolve acronyms" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "for a in assocs:\n", - " s1 = gold_rel_dict[(a.paper.pubmed_id, a.snp.rs_id)]\n", - " s2 = rel_dict.get((str(a.paper.pubmed_id), a.snp.rs_id), {})\n", - " print a.paper.pubmed_id, a.snp.rs_id, a.source\n", - " print 'GWC:', gold_rel_dict[(a.paper.pubmed_id, a.snp.rs_id)]\n", - " print 'US: ', rel_dict.get((str(a.paper.pubmed_id), a.snp.rs_id), None)\n", - " print" + "new_rels = [ (doc_id, rs_id, unravel(doc_id, phen, D)) for doc_id, rs_id, phen in rels ]" ] }, { @@ -7972,67 +1012,6 @@ "source": [ "print [(c, c.span0.context.cell.row_num, unravel(c.span0.context.document.name, c.span1.get_span(), D)) for c in candidates if c.span0.get_span() == 'rs10500631']" ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "-1" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pval_rsid_dict['17903294'].get(('rs10500631', 1, 5), -1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "for x in pval_rsid_dict['17903294']: \n", - " print x, pval_rsid_dict['17903294'][x]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/notebooks/results/associations.tsv b/notebooks/results/associations.tsv new file mode 100644 index 0000000..655d134 --- /dev/null +++ b/notebooks/results/associations.tsv @@ -0,0 +1,7362 @@ +21738491 rs12143842 Sudden Cardiac Death QT -1.000000 +20585627 rs12931267 Common Traits Red hair -1.000000 +17903295 rs2543600 Age-Related Phenotypes|Longevity Age at death 0.000004 +20838585 rs726914 Cardiovascular Disease systolic BP 0.000001 +20526338 rs4311994 Platelet Aggregation Epi 2 u M 0.000000 +19430483 rs17367504 Blood Pressure SBP 0.000000 +20585627 rs11648785 Common Traits Red hair -1.000000 +19197348 rs6462411 Complex Disease Thyroid Stimulating Hormone 0.000001 +25340798 rs2229238 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +24586186 rs2147896 Metabolic Traits|Metabolite-Disease Trimethylamine 0.000000 +17903304 rs10501920 Cardiovascular Disease atrial fibrillation 0.000009 +23251661 rs17104363 Childhood Obesity|Childhood Dinner intake, adjEER (kcal) 0.000000 +19197348 rs7036589 Complex Disease Thyroid Stimulating Hormone 0.000007 +24386095 rs10045497 Lipid Levels LDL 0.000000 +20838585 rs7210277 Cardiovascular Disease waist circumference 0.000001 +19609347 rs9590141 Hypertension|Blood Pressure DBP 0.000001 +20395239 rs2241970 Optic Disc Size Disc 0.000000 +23408906 rs7825175 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +24324551 rs115744676 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +24386095 rs599839 Lipid Levels LDL 0.000000 +20838585 rs1552257 Cardiovascular Disease insulin 0.000001 +17903296 rs10515148 Association Bone neck section modulus** 0.000001 +20585627 rs12203592 Common Traits Freckling -1.000000 +21386085 rs173539 Metabolic Syndrome MetS 0.000000 +22291609 rs3026968 Inflammation MCP-1 0.000000 +24347629 rs11713199 Periodontal PD2 0.000007 +17903301 rs6847149 Exercise Responses|Artery Stage 2 Exercise heart rate 0.000003 +17903295 rs4471448 Age-Related Phenotypes|Longevity Walking speed exam 7 0.000004 +25340798 rs11575821 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000000 +17903298 rs10486607 Diabetes-Related Traits hemoglobin a1c 0.000008 +21386085 rs2075290 Metabolic Syndrome HDLC-TG 0.000000 +24376456 rs12292796 Blood Pressure PP 0.000000 +24324551 rs73276602 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +17903302 rs10491334 Arterial Stiffness|Blood Pressure blood-pressure 0.000004 +20395239 rs6480314 Optic Disc Size Disc 0.000000 +17903307 rs310558 Pulmonary Function percent predicted fev 0.000005 +21738480 rs2524079 Cell Phenotypes|White Blood Cell Lymphocytes 0.000000 +17903293 rs583012 Biomarker Traits C-reactive protein exam 2 0.000002 +22558069 rs11552708 Immunoglobulin Isotypes|Non-Albumin Protein NAP 0.000000 +24324551 rs78852656 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +22558069 rs4985726 Immunoglobulin Isotypes|Non-Albumin Protein NAP 0.000000 +21931564 rs174547 Metabolite Quantitative Trait PC aa C36:3/PC aa C36:4 -1.000000 +24386095 rs1160985 Lipid Levels LDL 0.000000 +17903297 rs9303401 Brain|Cognitive Test boston naming test 0.000005 +24945404 rs4420311 Bone Mineral Density|Bone TBLH-BMD 0.000000 +20927387 rs17064262 Cell Traits|Red Blood Cell MCV 0.000000 +23966867 rs214679 Body Fat Distribution WHR_pooled 0.000001 +17903295 rs2371208 Age-Related Phenotypes|Longevity Age at death 0.000003 +20838585 rs8131349 Cardiovascular Disease total cholesterol 0.000000 +20548944 rs2278729 Osteoporosis-Related Traits|Gene Expression Profiling NSA 0.000000 +20585627 rs7349332 Common Traits Hair curl -1.000000 +19430483 rs1530440 Blood Pressure DBP 0.000003 +17903297 rs7124781 Brain|Cognitive Test ALLV 0.000000 +24376456 rs2837253 Blood Pressure SBP 0.000001 +20585627 rs4778220 Common Traits Eye color -1.000000 +17903301 rs4920799 Exercise Responses|Artery left ventricular diastolic dimension 0.000007 +17903302 rs935334 Arterial Stiffness|Blood Pressure blood-pressure 0.000003 +20838585 rs781718 Cardiovascular Disease glucose 0.000001 +21203500 rs7159888 Master|Plasma Protein DG1 0.000000 +21386085 rs2206277 Metabolic Syndrome WC-GLUC 0.000000 +19430483 rs1378942 Blood Pressure DBP 0.000000 +22832964 rs1678618 Smoking Behaviors AOI 0.000001 +20927387 rs1800562 Cell Traits|Red Blood Cell MCV 0.000001 +20585627 rs12203592 Common Traits Eye color -1.000000 +20838585 rs12280753 Cardiovascular Disease triglycerides 0.000000 +21931564 rs7094971 Metabolite Quantitative Trait C0 -1.000000 +20195266 rs7108821 Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hip Circumference 0.000000 +20838585 rs5979903 Cardiovascular Disease glucose 0.000000 +17903293 rs2808629 Biomarker Traits C-reactive protein exam 6 0.000000 +20585627 rs10960751 Common Traits Eye color -1.000000 +20195266 rs17661538 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Triglycerides 0.000001 +20548944 rs17201113 Osteoporosis-Related Traits|Gene Expression Profiling NL, men 0.000001 +17903296 rs1552896 Association Bone nsa1 0.000009 +19448621 rs314280 Age Menarche|Menopause Age at Menarche 0.000000 +23251661 rs863002 Childhood Obesity|Childhood MCP-1 (pg/mL) 0.000000 +21347282 rs8078633 Coronary Heart Disease HDL-C 0.000000 +20927387 rs4895441 Cell Traits|Red Blood Cell MCV 0.000000 +24324551 rs2645430 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive EF 0.000000 +17903295 rs7176093 Age-Related Phenotypes|Longevity Biologic age by osseographic scoring system 0.000007 +17903302 rs1963982 Arterial Stiffness|Blood Pressure blood-pressure 0.000003 +17903296 rs4143244 Association Bone NeckW1 0.000001 +17903294 rs9253 Hematological Phenotypes red blood cell count 0.000004 +20463881 rs2835621 Eye Color C HS1 0.000000 +25340798 rs6808835 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000000 +20585627 rs1805009 Common Traits Red hair -1.000000 +20927387 rs7775698 Cell Traits|Red Blood Cell MCV 0.000000 +19721433 rs7635839 Response Treatment|Antipsychotics Olanzapine – Excitement 0.000003 +21203500 rs735396 Master|Plasma Protein DG11 0.000000 +25340798 rs3811448 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +25188341 rs429358 Dementias|Alzheimer's Disease Lewy Body (Case-Control) 0.000000 +17903295 rs32566 Age-Related Phenotypes|Longevity Morbidity-free survival at age 65 0.000000 +21738480 rs9880192 Cell Phenotypes|White Blood Cell Monocytes 0.000000 +20526338 rs12566888 Platelet Aggregation Epi 2 u M 0.000000 +24586186 rs7314056 Metabolic Traits|Metabolite-Disease 2-Hydroxyisobutyrate 0.000000 +20838585 rs1046391 Cardiovascular Disease systolic BP 0.000000 +23251661 rs73175262 Childhood Obesity|Childhood MCP-1 (pg/mL) 0.000000 +21738479 rs3094212 White Blood Cell Count|Cell Phenotypes|White Blood Cell WBC 0.000000 +17903296 rs2165468 Association Bone femoral bmd** 0.000001 +20921969 rs4959235 Cardiac Arrhythmias quetiapine/QTc 0.000000 +17903294 rs1829883 Hematological Phenotypes mean corpuscular hemoglobin 0.000006 +20585627 rs7183877 Common Traits Hair color -1.000000 +19197348 rs10243770 Complex Disease Thyroid Stimulating Hormone 0.000005 +21386085 rs2266788 Metabolic Syndrome WC-TG 0.000000 +24376456 rs7116456 Blood Pressure SBP 0.000000 +19197348 rs10983932 Complex Disease Thyroid Stimulating Hormone 0.000003 +25133637 rs4898878 Body Mass Index Height 0.000001 +17903307 rs3753683 Pulmonary Function percent predicted fef 0.000002 +20463881 rs3768056 Eye Color S 0.000000 +20838585 rs7738656 Cardiovascular Disease LDL-cholesterol 0.000000 +21347282 rs3764261 Coronary Heart Disease HDL-C 0.000000 +21738480 rs10980800 Cell Phenotypes|White Blood Cell Monocytes 0.000000 +17903297 rs1031381 Brain|Cognitive Test f3 0.000006 +24376456 rs9874923 Blood Pressure MAP 0.000000 +20694148 rs4523270 Metabolic Syndrome “ 0.000000 +24324551 rs4408325 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PCR 0.000000 +21738491 rs11970286 Sudden Cardiac Death QT -1.000000 +17903302 rs636864 Arterial Stiffness|Blood Pressure blood-pressure 0.000002 +20838585 rs6552560 Cardiovascular Disease weight 0.000000 +19609347 rs16877320 Hypertension|Blood Pressure SBP 0.000000 +17903297 rs3891355 Brain|Cognitive Test similarities 0.000003 +24945404 rs6726821 Bone Mineral Density|Bone TBLH-BMD 0.000000 +23408906 rs716822 Thyroid|Thyroid-Related Traits|Differences FT4 -1.000000 +23251661 rs6044834 Childhood Obesity|Childhood Total antioxidants(mM) 0.000000 +21347282 rs6753112 Coronary Heart Disease Coronary heart disease 0.000001 +17903296 rs1452928 Association Bone shaft width** 0.000001 +24386095 rs646776 Lipid Levels LDL 0.000000 +20838585 rs12330441 Cardiovascular Disease triglycerides 0.000000 +25133637 rs794149 Body Mass Index BMI 0.000001 +20585627 rs4244187 Common Traits Asparagus -1.000000 +24376456 rs1523351 Blood Pressure Coronary artery disease 0.000001 +20927387 rs9494145 Cell Traits|Red Blood Cell MCH 0.000000 +19197348 rs9939609 Complex Disease BMI 0.000000 +20585627 rs1107267 Common Traits Eye color -1.000000 +25340798 rs4845622 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +21386085 rs780093 Metabolic Syndrome WC-TG 0.000000 +20838585 rs11258628 Cardiovascular Disease LDL 0.000007 +25340798 rs679620 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +17903307 rs10516541 Pulmonary Function mean fvc from two exams 0.000004 +20838585 rs3793275 Cardiovascular Disease glucose 0.000000 +25188341 rs6857 Dementias|Alzheimer's Disease NFT Braak (Ordinal II) 0.000000 +19197348 rs2282978 Complex Disease Height 0.000000 +17903293 rs10489849 Biomarker Traits Monocyte chemoattractant protein-1 0.000001 +21552555 rs10953454 Obesity|Obesity-Related Traits HIP 0.000001 +17903292 rs10499559 Kidney|Endocrine-Related Traits thyroid stimulating hormone 0.000008 +17903303 rs4814615 Atherosclerosis Common carotid artery intimal medial thickness 0.000003 +24945404 rs4420311 Bone Mineral Density|Bone LL-BMD 0.000000 +23966867 rs7672174 Body Fat Distribution WC_pooled 0.000000 +20927387 rs855791 Cell Traits|Red Blood Cell MCV 0.000000 +20838585 rs7738656 Cardiovascular Disease total cholesterol 0.000000 +20585627 rs4911442 Common Traits Freckling -1.000000 +19197348 rs2805809 Complex Disease Thyroid Stimulating Hormone 0.000004 +17903298 rs10497721 Diabetes-Related Traits Incident DM 0.000001 +20585627 rs6497253 Common Traits Eye color -1.000000 +17903302 rs10521232 Arterial Stiffness|Blood Pressure CF-PWV 0.000004 +17903301 rs366676 Exercise Responses|Artery left ventricular fractional shortening 0.000002 +19721433 rs17815774 Response Treatment|Antipsychotics Risperidone – Negative 0.000003 +20838585 rs10044666 Cardiovascular Disease LDL-cholesterol 0.000000 +20838585 rs7890572 Cardiovascular Disease triglycerides 0.000000 +21386085 rs15285 Metabolic Syndrome TG-BP 0.000000 +23408906 rs334699 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +19430483 rs11191548 Blood Pressure SBP 0.000000 +20838585 rs6726786 Cardiovascular Disease triglycerides 0.000004 +20195266 rs17216786 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Triglycerides 0.000001 +22509378 rs13202860 Sexual Dysfunction Arousal 0.000000 +17903303 rs6053733 Atherosclerosis Common carotid artery intimal medial thickness 0.000004 +20195266 rs1771628 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Triglycerides 0.000001 +25188341 rs6857 Dementias|Alzheimer's Disease Neuritic Plaque (Ordinal) 0.000000 +17903308 rs6599077 Circadian Phenotypes|Sleep Sleep duration 0.000000 +23251661 rs28461806 Childhood Obesity|Childhood MCP-1 (pg/mL) 0.000000 +24892410 rs1019102 Onset|Hypertension|Cardiovascular Events Nighttime PP 0.000002 +25133637 rs347313 Body Mass Index Change in BMI: Female 0.000000 +21931564 rs2046813 Metabolite Quantitative Trait PC ae C44:5/PC ae C42:5 0.000000 +24324551 rs3176130 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +20585627 rs12931267 Common Traits Hair color -1.000000 +19197348 rs2805810 Complex Disease Thyroid Stimulating Hormone 0.000006 +20548944 rs17184557 Osteoporosis-Related Traits|Gene Expression Profiling LS BMD 0.000001 +25133637 rs8181969 Body Mass Index Overweight 0.000001 +20838585 rs10498337 Cardiovascular Disease insulin 0.000001 +19197348 rs6060369 Complex Disease Height 0.000000 +20195266 rs1534238 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Triglycerides 0.000003 +21738480 rs4794822 Cell Phenotypes|White Blood Cell WBC 0.000000 +22291609 rs2259816 Inflammation hsCRP 0.000005 +20526338 rs342286 Platelet Aggregation Epi 2 u M 0.000000 +24586186 rs37370 Metabolic Traits|Metabolite-Disease 3-Aminoisobutyrate 0.000000 +17903293 rs2494250 Biomarker Traits Monocyte chemoattractant protein-1 0.000000 +20838585 rs7121446 Cardiovascular Disease waist circumference 0.000000 +17903296 rs1590305 Association Bone lsbmd 0.000003 +24376456 rs2278075 Blood Pressure Cardiovascular disease 0.000000 +25340798 rs11574428 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000000 +20838585 rs4783595 Cardiovascular Disease glucose 0.000000 +17903301 rs1392284 Exercise Responses|Artery left ventricular systolic dimension 0.000006 +17903296 rs10514345 Association Bone lumbar spine bmd** 0.000002 +19448621 rs314262 Age Menarche|Menopause Age at Menarche 0.000000 +21386085 rs3764261 Metabolic Syndrome BP-HDLC 0.000000 +23935956 rs1155865 Red Blood Cell MCHC 0.000000 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Cell Traits|Red Blood Cell MCV 0.000000 +20195266 rs4783227 Antipsychotic Drugs|Metabolic Side Effects Olanzapine - Total Cholesterol 0.000000 +22509378 rs1876525 Sexual Dysfunction Arousal 0.000000 +20838585 rs1552257 Cardiovascular Disease insulin 0.000001 +17903300 rs953536 Waist Circumference|Body Mass Index Mean waist circumference 0.000008 +20526338 rs12566888 Platelet Aggregation Epi 2 u M 0.000000 +17903308 rs10492604 Circadian Phenotypes|Sleep Sleep duration 0.000004 +22216198 rs8119351 Protein C PC 0.000000 +24376456 rs10486744 Blood Pressure Blood pressure 0.000000 +23966867 rs6931262 Body Fat Distribution WHR_BMI_pooled 0.000000 +25340798 rs61812598 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +19430483 rs653178 Blood Pressure DBP 0.000000 +22216198 rs13130255 Protein C funcPS 0.000003 +22832964 rs667282 Smoking Behaviors CPD 0.000000 +20585627 rs12896399 Common Traits Green eyes -1.000000 +23251661 rs2823615 Childhood Obesity|Childhood Sleep RQ 0.000000 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Responses|Artery Post-exercise 3 minute recovery heart rate 0.000004 +17903295 rs10493513 Age-Related Phenotypes|Longevity Age at death 0.000002 +17903296 rs9317284 Association Bone femoral bmd** 0.000000 +24324551 rs75041531 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000001 +17903302 rs3793427 Arterial Stiffness|Blood Pressure FW 0.000002 +19721433 rs10888501 Response Treatment|Antipsychotics Olanzapine – Negative 0.000001 +20927387 rs6569992 Cell Traits|Red Blood Cell RBC count 0.000000 +19197348 rs6909430 Complex Disease Thyroid Stimulating Hormone 0.000008 +23408906 rs7128207 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +25340798 rs6441977 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000001 +17903298 rs2877832 Diabetes-Related Traits Fasting Insulin 0.000002 +23754948 rs2820443 Anthropometric Traits|Sexual WHRadjBMI 0.000000 +20395239 rs1192415 Optic Disc Size Disc 0.000000 +24945404 rs3012465 Bone Mineral Density|Bone SK-BMD 0.000000 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Involved|Inflammation|Alzheimer's Disease CCL4 0.000000 +17903293 rs8005745 Biomarker Traits CD40 Ligand serum 0.000003 +17903294 rs10484128 Hematological Phenotypes platelet aggregation (ADP-induced) 0.000006 +21931564 rs7094971 Metabolite Quantitative Trait C0 0.000000 +24324551 rs182503338 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive QRS 0.000001 +25087078 rs55670112 Epilepsies GGE 0.000000 +24386095 rs10045497 Lipid Levels TC 0.000000 +20694148 rs7865146 Metabolic Syndrome DBP (mmHg) 0.000001 +20838585 rs3019325 Cardiovascular Disease glucose 0.000001 +17903297 rs2832077 Brain|Cognitive Test f3 0.000002 +20927387 rs9376092 Cell Traits|Red Blood Cell RBC count 0.000000 +19197348 rs12539695 Complex Disease Thyroid Stimulating Hormone 0.000006 +17903295 rs4831837 Age-Related Phenotypes|Longevity Morbidity-free survival at age 65 0.000000 +20838585 rs8073909 Cardiovascular Disease total cholesterol 0.000000 +20585627 rs9328192 Common Traits Freckling -1.000000 +23966867 rs10894604 Body Fat Distribution WHR_BMI_pooled 0.000000 +19197348 rs1042725 Complex Disease Height 0.000000 +24324551 rs13078828 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive EIA 0.000000 +24892410 rs9564376 Onset|Hypertension|Cardiovascular Events Daytime PP 0.000005 +20838585 rs12069004 Cardiovascular Disease glucose 0.000001 +23696099 rs9924561 Cell Traits|Red Blood Cell|Resistance MCV 0.000000 +20585627 rs1805009 Common Traits Freckling -1.000000 +19430483 rs16948048 Blood Pressure DBP 0.000005 +21738479 rs12619285 White Blood Cell Count|Cell Phenotypes|White Blood Cell Eosinophils 0.000000 +19430483 rs16998073 Blood Pressure DBP 0.000000 +20585627 rs11018528 Common Traits Green eyes -1.000000 +21738479 rs4794822 White Blood Cell Count|Cell Phenotypes|White Blood Cell Neutrophils 0.000000 +25340798 rs4129267 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +17903307 rs3820928 Pulmonary Function for latest exam 0.000005 +20838585 rs7210277 Cardiovascular Disease waist circumference 0.000001 +17903293 rs1119582 Biomarker Traits C-reactive protein average exams 2,6,7 0.000001 +20838585 rs7738656 Cardiovascular Disease total cholesterol 0.000000 +25340798 rs7926920 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +20195266 rs9658108 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Glucose 0.000000 +22509378 rs739031 Sexual Dysfunction Overall FSD 0.000002 +17903300 rs2206682 Waist Circumference|Body Mass Index Mean waist circumference 0.000004 +24324551 rs117364231 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +24324551 rs2054148 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PCR 0.000001 +20526338 rs1671152 Platelet Aggregation lag 0.000000 +17903294 rs7159841 Hematological Phenotypes Viscosity 0.000000 +19197348 rs527485 Complex Disease Waist Circumference 0.000007 +20463881 rs9782955 Eye Color S 0.000000 +22216198 rs13230047 Protein C PC 0.000008 +21931564 rs2014355 Metabolite Quantitative Trait C3/C4 0.000000 +17903302 rs10488172 Arterial Stiffness|Blood Pressure RW 0.000008 +25087078 rs2947349 Epilepsies GGE 0.000000 +20838585 rs1613695 Cardiovascular Disease insulin 0.000000 +21347282 rs12740374 Coronary Heart Disease LDL-C 0.000000 +24376456 rs13008299 Blood Pressure DBP 0.000000 +22832964 rs1245577 Smoking Behaviors AOI 0.000001 +23118974 rs262825 Pigmentation|Skin Hair M 0.000008 +20585627 rs4904868 Common Traits Eye color -1.000000 +19721433 rs888219 Response Treatment|Antipsychotics Risperidone – Negative 0.000000 +20195266 rs977396 Antipsychotic Drugs|Metabolic Side Effects Olanzapine - Total Cholesterol 0.000000 +20526338 rs12566888 Platelet Aggregation ADP 2 u M 0.000000 +25340798 rs3092960 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000001 +24892410 rs6696698 Onset|Hypertension|Cardiovascular Events Nighttime PP 0.000000 +21738479 rs3184504 White Blood Cell Count|Cell Phenotypes|White Blood Cell Eosinophils 0.000000 +24376456 rs4953404 Blood Pressure PP 0.000001 +20585627 rs8049897 Common Traits Red hair -1.000000 +17903302 rs1588260 Arterial Stiffness|Blood Pressure blood-pressure 0.000003 +19043545 rs4775041 Metabolite rs number -1.000000 +20585627 rs291671 Common Traits Red hair -1.000000 +19721433 rs1040994 Response Treatment|Antipsychotics Olanzapine – Excitement 0.000002 +25133637 rs1392280 Body Mass Index BMI 0.000001 +17903307 rs1409149 Pulmonary Function percent predicted fef 0.000009 +20838585 rs247616 Cardiovascular Disease HDL-cholesterol 0.000001 +23408906 rs944289 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +19197348 rs967417 Complex Disease Height 0.000000 +21738479 rs445 White Blood Cell Count|Cell Phenotypes|White Blood Cell WBC 0.000000 +25340798 rs2228467 Proteins Involved|Inflammation|Alzheimer's Disease CCL2 0.000000 +17903304 rs4776472 Cardiovascular Disease atrial fibrillation 0.000008 +24376456 rs12773465 Blood Pressure MAP 0.000000 +25188341 rs62341097 Dementias|Alzheimer's Disease Neuritic Plaque (Case-Control) 0.000000 +24324551 rs59623110 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +24386095 rs328 Lipid Levels HDL 0.000000 +20585627 rs2153271 Common Traits Freckling -1.000000 +24379826 rs737267 Serum Uric Acid Levels Total antioxidant status 0.000001 +17903297 rs1970546 Brain|Cognitive Test tcbv 0.000000 +23408906 rs657152 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +22558069 rs1260326 Immunoglobulin Isotypes|Non-Albumin Protein ALB 0.000000 +19197348 rs4743034 Complex Disease Height 0.000000 +20838585 rs11258628 Cardiovascular Disease LDL 0.000000 +17903296 rs9291683 Association Bone fnbmd 0.000002 +20585627 rs8049897 Common Traits Freckling -1.000000 +21386085 rs173539 Metabolic Syndrome HDLC-TG 0.000000 +20927387 rs9376092 Cell Traits|Red Blood Cell MCV 0.000000 +17903294 rs561241 Hematological Phenotypes factor vii 0.000000 +17903301 rs746463 Exercise Responses|Artery Post-exercise 3 minute recovery systolic blood pressure 0.000005 +20548944 rs6588313 Osteoporosis-Related Traits|Gene Expression Profiling LSBMD, women 0.000005 +21203500 rs3760776 Master|Plasma Protein FUCA 0.000000 +21347282 rs7801190 Coronary Heart Disease Hypertension 0.000000 +19197348 rs11514766 Complex Disease Thyroid Stimulating Hormone 0.000003 +21386085 rs11823543 Metabolic Syndrome TG-BP 0.000000 +23251661 rs1056513 Childhood Obesity|Childhood BMI (kg/m 2 ) 0.000008 +17903307 rs2906966 Pulmonary Function for latest exam 0.000008 +21738480 rs1449263 Cell Phenotypes|White Blood Cell Monocytes 0.000000 +20838585 rs7121446 Cardiovascular Disease waist circumference 0.000000 +17903293 rs1486140 Biomarker Traits Atrial natriuretic peptide exam 6 0.000002 +21552555 rs17126237 Obesity|Obesity-Related Traits Weight 0.000000 +19609347 rs1550576 Hypertension|Blood Pressure HTN 0.000003 +17903297 rs6914079 Brain|Cognitive Test factor 2:visual memory and organization 0.000002 +24945404 rs7776725 Bone Mineral Density|Bone TBLH-BMD 0.000000 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Traits Eye color -1.000000 +20838585 rs8073909 Cardiovascular Disease LDL 0.000001 +20195266 rs1464500 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - HDL 0.000000 +25340798 rs7926920 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +20395239 rs3858145 Optic Disc Size Disc 0.000000 +24376456 rs2059238 Blood Pressure Cardiac structure and function 0.000003 +17903293 rs746961 Biomarker Traits C-reactive protein exam 6 0.000001 +20927387 rs1800562 Cell Traits|Red Blood Cell MCV 0.000001 +20195266 rs1979096 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Total Cholesterol 0.000001 +20548944 rs10895656 Osteoporosis-Related Traits|Gene Expression Profiling LSBMD, men 0.000003 +23966867 rs7296740 Body Fat Distribution WHR_men 0.000004 +22509378 rs16933243 Sexual Dysfunction Lubrication 0.000003 +19448621 rs12684013 Age Menarche|Menopause Age at Menarche 0.000000 +17903296 rs9287234 Association Bone shaft section modulus** 0.000008 +17903303 rs7715811 Atherosclerosis Ankle brachial index 0.000006 +25133637 rs1331623 Body Mass Index Height: Female 0.000001 +20463881 rs7277820 Eye Color C HS1 0.000000 +23408906 rs7850258 Thyroid|Thyroid-Related Traits|Differences FT4 -1.000000 +17903302 rs3766680 Arterial Stiffness|Blood Pressure FW 0.000004 +20585627 rs2159116 Common Traits Red hair -1.000000 +20838585 rs8131349 Cardiovascular Disease LDL-cholesterol 0.000000 +19197348 rs563694 Complex Disease Fasting plasma glucose 0.000000 +23118974 rs702477 Pigmentation|Skin Eye C' 0.000000 +20927387 rs855791 Cell Traits|Red Blood Cell MCH 0.000000 +19197348 rs1874326 Complex Disease Weight 0.000009 +17903293 rs953402 Biomarker Traits Liver function: Alkaline phosphatase; AST; ALT; gamma-glutamyl transferase 0.000009 +25133637 rs3096483 Body Mass Index BMI 0.000001 +20838585 rs1144036 Cardiovascular Disease height 0.000000 +17903293 rs9288125 Biomarker Traits CD40 Ligand serum 0.000009 +20838585 rs709595 Cardiovascular Disease diastolic BP 0.000001 +17903294 rs1160297 Hematological Phenotypes hemoglobin 0.000001 +23028342 rs7583877 Type 1 Diabetes|Kidney Disease|Diabetic Nephropathy ESRD 0.000000 +20195266 rs17410015 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Triglycerides 0.000002 +21738480 rs10980800 Cell Phenotypes|White Blood Cell Monocytes 0.000000 +20526338 rs2363910 Platelet Aggregation ADP 2 u M 0.000000 +21347282 rs7903146 Coronary Heart Disease Type-2 diabetes 0.000000 +24586186 rs492602 Metabolic Traits|Metabolite-Disease Fucose 0.000000 +17903303 rs10507130 Atherosclerosis Coronary artery calcification 0.000007 +17903293 rs17532515 Biomarker Traits Bilirubin 0.000001 +24892410 rs17513926 Onset|Hypertension|Cardiovascular Events Nighttime PP 0.000007 +21738479 rs12313946 White Blood Cell Count|Cell Phenotypes|White Blood Cell WBC 0.000000 +20921969 rs6468544 Cardiac Arrhythmias risperidone/QTc 0.000001 +20585627 rs12203592 Common Traits Hair color -1.000000 +17903296 rs2053506 Association Bone NeckZ1 0.000004 +21386085 rs2266788 Metabolic Syndrome MetS 0.000000 +20838585 rs4897695 Cardiovascular Disease total cholesterol 0.000000 +17903302 rs1539377 Arterial Stiffness|Blood Pressure FW 0.000005 +24586186 rs3764913 Metabolic Traits|Metabolite-Disease Unknown 0.000000 +19197348 rs1588635 Complex Disease Thyroid Stimulating Hormone 0.000004 +25340798 rs4459609 Proteins Involved|Inflammation|Alzheimer's Disease ACE 0.000000 +20066028 rs1532624 Serum Cholesterol Levels HDL-C 0.000001 +20838585 rs12280753 Cardiovascular Disease triglycerides 0.000000 +17903297 rs9300212 Brain|Cognitive Test wide-range achievement test 0.000008 +17903308 rs1940013 Circadian Phenotypes|Sleep Bedtime 0.000006 +23251661 rs6025590 Childhood Obesity|Childhood Sedentary&lightactivity (min/d) 0.000000 +20694148 rs7903146 Metabolic Syndrome T2D 0.000000 +17903297 rs1155865 Brain|Cognitive Test boston naming test 0.000002 +23408906 rs7860634 Thyroid|Thyroid-Related Traits|Differences FT4/TSH -1.000000 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rs2517524 Cell Phenotypes|White Blood Cell WBC 0.000000 +17903293 rs2387326 Biomarker Traits Vitamin K plasma phylloquinone 0.000001 +24324551 rs191392302 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +21931564 rs7072216 Metabolite Quantitative Trait TMAu -1.000000 +20526338 rs7940646 Platelet Aggregation ADP 10 u M 0.000000 +17903296 rs2054989 Association Bone shaftz1r 0.000001 +17903292 rs6977660 Kidney|Endocrine-Related Traits thyroid stimulating hormone 0.000004 +24945404 rs2908004 Bone Mineral Density|Bone LL-BMD 0.000000 +20927387 rs4820268 Cell Traits|Red Blood Cell MCH 0.000000 +19820699 rs1800562 Erythrocyte MCV -1.000000 +20838585 rs891541 Cardiovascular Disease waist circumference 0.000001 +20585627 rs1474976 Common Traits Freckling -1.000000 +24376456 rs16963349 Blood Pressure SBP 0.000000 +23754948 rs1358980 Anthropometric Traits|Sexual WHRadjBMI 0.000000 +20585627 rs4778232 Common Traits Eye color -1.000000 +24324551 rs1497042 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive EF 0.000000 +17903301 rs10504543 Exercise Responses|Artery left ventricular systolic dimension 0.000005 +20838585 rs16892328 Cardiovascular Disease insulin 0.000000 +21386085 rs301 Metabolic Syndrome HDLC-WC 0.000000 +23408906 rs13015993 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +20585627 rs17565953 Common Traits Eye color -1.000000 +20838585 rs127430 Cardiovascular Disease waist circumference 0.000000 +20195266 rs1187614 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Total Cholesterol 0.000000 +20838585 rs12548494 Cardiovascular Disease glucose 0.000001 +20927387 rs7775698 Cell Traits|Red Blood Cell RBC count 0.000000 +20195266 rs7105881 Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hip Circumference 0.000000 +20548944 rs17463551 Osteoporosis-Related Traits|Gene Expression Profiling LSBMD, women 0.000003 +25188341 rs6857 Dementias|Alzheimer's Disease NFT Braak (Ordinal I) 0.000000 +19448621 rs314277 Age 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DG6 0.000000 +24324551 rs57302454 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PCR 0.000001 +20195266 rs6741819 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Triglycerides 0.000000 +17903302 rs6063312 Arterial Stiffness|Blood Pressure RW 0.000002 +21738480 rs4328821 Cell Phenotypes|White Blood Cell Basophils 0.000000 +23696099 rs7120391 Cell Traits|Red Blood Cell|Resistance MCHC 0.000000 +25340798 rs2228145 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +24586186 rs579459 Metabolic Traits|Metabolite-Disease Unknown 0.000000 +17903304 rs740363 Cardiovascular Disease heart failure 0.000009 +20838585 rs17568778 Cardiovascular Disease waist circumference 0.000001 +17903296 rs10506701 Association Bone trochanter bmd** 0.000001 +22291609 rs4910742 Inflammation ESR 0.000000 +21203500 rs3760776 Master|Plasma Protein DG9 0.000000 +17903302 rs10514688 Arterial Stiffness|Blood Pressure CB-PWV 0.000006 +17903296 rs2548003 Association Bone neck section modulus** 0.000000 +21386085 rs173539 Metabolic Syndrome HDLC-WC 0.000000 +23408906 rs11755845 Thyroid|Thyroid-Related Traits|Differences TSH/FT4 -1.000000 +23966867 rs1355187 Body Fat Distribution WC_pooled 0.000000 +25340798 rs113263161 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000000 +20463881 rs9894429 Eye Color C HS1 0.000000 +21931564 rs174547 Metabolite Quantitative Trait PC aa C36:3/PC aa C36:4 0.000000 +25087078 rs1939012 Epilepsies GGE 0.000000 +20395239 rs690037 Optic Disc Size Cup 0.000000 +21738480 rs11878602 Cell Phenotypes|White Blood Cell Lymphocytes 0.000000 +17903297 rs934299 Brain|Cognitive Test f3 0.000009 +24945404 rs1262476 Bone Mineral Density|Bone UL-BMD 0.000000 +24376456 rs16849553 Blood Pressure MAP 0.000001 +24386095 rs2043085 Lipid Levels HDL 0.000000 +17903292 rs9305354 Kidney|Endocrine-Related Traits urinary albumin excretion 0.000008 +17903297 rs952700 Brain|Cognitive Test tcbv 0.000006 +24945404 rs17536328 Bone Mineral Density|Bone TBLH-BMD 0.000000 +23966867 rs11197515 Body Fat Distribution WHR_men 0.000002 +21347282 rs9306885 Coronary Heart Disease LDL-C 0.000000 +21347282 rs6728440 Coronary Heart Disease LDL-C 0.000000 +20838585 rs6829649 Cardiovascular Disease total cholesterol 0.000000 +25133637 rs955423 Body Mass Index BMI 0.000000 +24376456 rs7094971 Blood Pressure Carnitine 0.000000 +20585627 rs499697 Common Traits Hair curl -1.000000 +21386085 rs2954033 Metabolic Syndrome TG-BP 0.000000 +20585627 rs1800407 Common Traits Eye color -1.000000 +20838585 rs7210277 Cardiovascular Disease waist circumference 0.000001 +25340798 rs4459609 Proteins Involved|Inflammation|Alzheimer's Disease ACE 0.000000 +21386085 rs569805 Metabolic Syndrome HDLC-GLUC 0.000000 +17903300 rs10504576 Waist Circumference|Body Mass Index Mean waist circumference 0.000001 +20838585 rs7890572 Cardiovascular Disease triglycerides 0.000004 +21931564 rs272889 Metabolite Quantitative Trait Val-PTC/C5 -1.000000 +20195266 rs620875 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Triglycerides 0.000003 +17903307 rs3867498 Pulmonary Function longitudinal slope of fev 0.000001 +20838585 rs12069004 Cardiovascular Disease glucose 0.000001 +17903293 rs7552393 Biomarker Traits Tumor necrosis factor alpha 0.000001 +20585627 rs1042602 Common Traits Freckle -1.000000 +19430483 rs11191548 Blood Pressure SBP 0.000000 +17903292 rs1158167 Kidney|Endocrine-Related Traits cst3 0.000000 +17903303 rs590183 Atherosclerosis Ankle brachial index 0.000009 +23966867 rs6739392 Body Fat Distribution WHR_BMI_women 0.000001 +17903295 rs3772255 Age-Related Phenotypes|Longevity Biologic age by osseographic scoring system 0.000008 +20838585 rs4783595 Cardiovascular Disease glucose 0.000000 +20585627 rs11648785 Common Traits Freckling -1.000000 +19197348 rs1877431 Complex Disease Thyroid Stimulating Hormone 0.000003 +17903294 rs10493485 Hematological Phenotypes tissue plasminogen activator 0.000002 +20585627 rs12913832 Common Traits Eye color -1.000000 +20838585 rs12330441 Cardiovascular Disease triglycerides 0.000000 +23408906 rs4804416 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +19197348 rs7846385 Complex Disease Height 0.000000 +17903293 rs1376544 Biomarker Traits Vitamin D, Vitamin K phylloquinone & Vitamin K % undercarboxylated osteocalcin 0.000009 +20195266 rs11663206 Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hemoglobin A1c 0.000002 +22509378 rs4821535 Sexual Dysfunction Overall FSD 0.000002 +21203500 rs3760776 Master|Plasma Protein DG12 0.000000 +22291609 rs12034598 Inflammation ESR 0.000000 +20195266 rs11163585 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - HDL 0.000001 +21738480 rs1449263 Cell Phenotypes|White Blood Cell Monocytes 0.000000 +23966867 rs2548774 Body Fat Distribution WC_BMI_men 0.000001 +17903294 rs2357013 Hematological Phenotypes hemoglobin 0.000006 +25188341 rs429358 Dementias|Alzheimer's Disease Lewy Body (Ordinal I) 0.000000 +17903293 rs1363258 Biomarker Traits C-reactive protein exam 7 0.000009 +23408906 rs4338740 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +17903295 rs10496265 Age-Related Phenotypes|Longevity Age at natural menopause‡ 0.000000 +23251661 rs1056513 Childhood Obesity|Childhood Fat mass (kg) 0.000000 +17903296 rs10503887 Association Bone shaft section modulus** 0.000000 +17903303 rs3849150 Atherosclerosis Abdominal aortic calcification 0.000002 +25133637 rs1161397 Body Mass Index Overweight: Male 0.000001 +20921969 rs16895513 Cardiac Arrhythmias risperidone/QTc 0.000001 +17903306 rs9315385 Heart Rate|Variability Traits TP 0.000008 +20585627 rs4778138 Common Traits Hair color -1.000000 +19197348 rs12531984 Complex Disease Thyroid Stimulating Hormone 0.000005 +24324551 rs8087073 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +20927387 rs1800562 Cell Traits|Red Blood Cell MCV 0.000001 +21931564 rs11158519 Metabolite Quantitative Trait PC ae C38:1/PC aa C28:1 -1.000000 +21552555 rs10216243 Obesity|Obesity-Related Traits HIP 0.000001 +25133637 rs8042988 Body Mass Index Height 0.000000 +17903298 rs2722425 Diabetes-Related Traits fasting plasma glucose 0.000009 +20838585 rs10044666 Cardiovascular Disease LDL-cholesterol 0.000000 +20195266 rs1405687 Antipsychotic Drugs|Metabolic Side Effects Ziprasidone - Hip Circumference 0.000000 +19197348 rs2225614 Complex Disease Weight 0.000003 +21347282 rs247617 Coronary Heart Disease HDL-C 0.000000 +17903303 rs2896103 Atherosclerosis Ankle brachial index 0.000005 +17903297 rs10489896 Brain|Cognitive Test factor 2:visual memory and organization 0.000006 +24386095 rs328 Lipid Levels TG 0.000000 +17903296 rs4811196 Association Bone trochanter bmd** 0.000001 +19609347 rs1867226 Hypertension|Blood Pressure DBP 0.000001 +20838585 rs9909931 Cardiovascular Disease glucose 0.000000 +21347282 rs6674681 Coronary Heart Disease Coronary heart disease 0.000000 +25133637 rs1426654 Body Mass Index BMI 0.000001 +24324551 rs2034842 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PCR 0.000001 +20838585 rs445925 Cardiovascular Disease LDL-cholesterol 0.000002 +25340798 rs2228145 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +17903303 rs1400544 Atherosclerosis Common carotid artery intimal medial thickness 0.000006 +17903293 rs4128725 Biomarker Traits Monocyte chemoattractant protein-1 0.000000 +17903300 rs1333026 Waist Circumference|Body Mass Index Mean body mass index 0.000008 +20694148 rs3764261 Metabolic Syndrome Log HDL-C (mmol/l) 0.000000 +25340798 rs645419 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +20838585 rs4783595 Cardiovascular Disease glucose 0.000000 +24945404 rs13223036 Bone Mineral Density|Bone SK-BMD 0.000000 +20838585 rs1449460 Cardiovascular Disease heart rate 0.000001 +17903292 rs9322817 Kidney|Endocrine-Related Traits thyroid stimulating hormone 0.000006 +24945404 rs754388 Bone Mineral Density|Bone LL-BMD 0.000000 +17903294 rs10488360 Hematological Phenotypes factor vii 0.000007 +23966867 rs11961438 Body Fat Distribution WC_women 0.000001 +23028342 rs12437854 Type 1 Diabetes|Kidney Disease|Diabetic Nephropathy ESRD 0.000000 +21347282 rs16982414 Coronary Heart Disease Smoking 0.000001 +20838585 rs4897695 Cardiovascular Disease total cholesterol 0.000000 +20526338 rs7940646 Platelet Aggregation ADP 10 u M 0.000000 +20585627 rs619865 Common Traits Freckling -1.000000 +19197348 rs1962785 Complex Disease Thyroid Stimulating Hormone 0.000004 +21386085 rs10790162 Metabolic Syndrome HDLC-TG 0.000000 +24376456 rs7902871 Blood Pressure DBP 0.000001 +20585627 rs2240204 Common Traits Eye color -1.000000 +17903301 rs666088 Exercise Responses|Artery left ventricular diastolic dimension 0.000005 +24903457 rs13390641 Blood Pressure SBP 0.000000 +25340798 rs948399 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +20838585 rs8073909 Cardiovascular Disease total cholesterol 0.000000 +17903293 rs1079596 Biomarker Traits Atrial natriuretic peptide exam 6 0.000003 +21386085 rs13702 Metabolic Syndrome HDLC-TG 0.000000 +24376456 rs17669622 Blood Pressure MAP 0.000001 +20838585 rs13290397 Cardiovascular Disease triglycerides 0.000001 +20195266 rs17651157 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Triglycerides 0.000000 +17903293 rs2494250 Biomarker Traits Monocyte chemoattractant protein-1 0.000000 +17903295 rs2639889 Age-Related Phenotypes|Longevity Morbidity-free survival at age 65 0.000001 +19430483 rs16998073 Blood Pressure DBP 0.000000 +17903294 rs4133289 Hematological Phenotypes hemoglobin 0.000000 +22216198 rs1570868 Protein C fPS 0.000000 +24376456 rs1943940 Blood Pressure DBP 0.000001 +23408906 rs737308 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +23966867 rs7601155 Body Fat Distribution WC_pooled 0.000000 +20838585 rs7704530 Cardiovascular Disease diastolic BP 0.000000 +20585627 rs7204478 Common Traits Freckling -1.000000 +25133637 rs347306 Body Mass Index Change in BMI: Female 0.000000 +24376456 rs10826334 Blood Pressure MAP 0.000001 +20585627 rs1827430 Common Traits Green eyes -1.000000 +24324551 rs7387094 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PCR 0.000000 +23251661 rs12104221 Childhood Obesity|Childhood Total energyexpenditure adjweight (kcal/d) 0.000000 +24892410 rs7596980 Onset|Hypertension|Cardiovascular Events Nighttime PP 0.000004 +23966867 rs2570467 Body Fat Distribution WC_Men 0.000000 +23251661 rs61744862 Childhood Obesity|Childhood IGFBP-3 (ng/mL) 0.000000 +23408906 rs1571583 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +17903306 rs1395479 Heart Rate|Variability Traits LF/HF 0.000007 +20195266 rs11954387 Antipsychotic Drugs|Metabolic Side Effects Olanzapine - Hemoglobin A1c 0.000000 +22509378 rs11594963 Sexual Dysfunction Lubrication 0.000002 +20927387 rs855791 Cell Traits|Red Blood Cell MCH 0.000000 +20838585 rs8131349 Cardiovascular Disease LDL-cholesterol 0.000000 +25340798 rs573521 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +20195266 rs17385675 Antipsychotic Drugs|Metabolic Side Effects Clozapine - Triglycerides 0.000003 +21738480 rs2517524 Cell Phenotypes|White Blood Cell WBC 0.000000 +17903296 rs1395548 Association Bone shaftz1r 0.000001 +17903293 rs437021 Biomarker Traits B-type natriuretic peptide 0.000001 +23408906 rs2439302 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +24324551 rs58829748 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PCR 0.000001 +23251661 rs1056513 Childhood Obesity|Childhood Fat free mass (kg) 0.000000 +17903296 rs10506821 Association Bone shaft width** 0.000000 +21552555 rs17126237 Obesity|Obesity-Related Traits HIP 0.000000 +17903294 rs6108011 Hematological Phenotypes red blood cell count 0.000006 +19721433 rs17390445 Response Treatment|Antipsychotics Ziprasidone –Positive 0.000000 +19043545 rs1200826 Metabolite rs number -1.000000 +20927387 rs5756504 Cell Traits|Red Blood Cell MCH 0.000000 +23408906 rs334725 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +25340798 rs603050 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +25133637 rs1426654 Body Mass Index BMI: Female 0.000000 +24376456 rs2735413 Blood Pressure SBP 0.000001 +23754948 rs11743303 Anthropometric Traits|Sexual WCadjBMI 0.000000 +24324551 rs2252567 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive EF 0.000001 +25340798 rs11225434 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +24945404 rs3920498 Bone Mineral Density|Bone SK-BMD 0.000000 +23408906 rs11755845 Thyroid|Thyroid-Related Traits|Differences TSH/FT4 -1.000000 +19430483 rs12946454 Blood Pressure SBP 0.000004 +21552555 rs17126232 Obesity|Obesity-Related Traits HIP 0.000000 +24376456 rs10770612 Blood Pressure Aortic root size 0.000000 +20838585 rs12548494 Cardiovascular Disease glucose 0.000003 +20585627 rs447735 Common Traits Red hair -1.000000 +21347282 rs255052 Coronary Heart Disease HDL-C 0.000000 +19197348 rs10983893 Complex Disease Thyroid Stimulating Hormone 0.000002 +21386085 rs1387153 Metabolic Syndrome BP-GLUC 0.000000 +23251661 rs12075 Childhood Obesity|Childhood MCP-1 (pg/mL) 0.000000 +19197348 rs2668804 Complex Disease Thyroid Stimulating Hormone 0.000006 +25340798 rs2228467 Proteins Involved|Inflammation|Alzheimer's Disease CCL2 0.000000 +20838585 rs17104804 Cardiovascular Disease systolic BP 0.000001 +20694148 rs2083637 Metabolic Syndrome “ 0.000000 +20395239 rs17231602 Optic Disc Size Disc 0.000000 +22291609 rs11829037 Inflammation ESR 0.000000 +20927387 rs4895441 Cell Traits|Red Blood Cell MCV 0.000000 +17903302 rs1322512 Arterial Stiffness|Blood Pressure MAP 0.000008 +20838585 rs8103264 Cardiovascular Disease height 0.000001 +20585627 rs872071 Common Traits Freckling -1.000000 +19197348 rs10486715 Complex Disease Height 0.000003 +19820699 rs3811647 Erythrocyte MCV -1.000000 +19197348 rs798544 Complex Disease Height 0.000000 +20838585 rs10260737 Cardiovascular Disease glucose 0.000001 +20526338 rs10761741 Platelet Aggregation Epi 2 u M 0.000000 +20585627 rs8060934 Common Traits Freckling -1.000000 +21386085 rs2075290 Metabolic Syndrome MetS 0.000000 +20585627 rs1806319 Common Traits Green eyes -1.000000 +21738479 rs1420101 White Blood Cell Count|Cell Phenotypes|White Blood Cell Eosinophils 0.000000 +20395239 rs3858145 Optic Disc Size Cup 0.000000 +22291609 rs10903129 Inflammation ESR 0.000000 +17903293 rs1417352 Biomarker Traits Atrial natriuretic peptide exam 6 0.000002 +22558069 rs10007186 Immunoglobulin Isotypes|Non-Albumin Protein NAP 0.000000 +17903307 rs219349 Pulmonary Function percent predicted fev 0.000006 +21931564 rs2014355 Metabolite Quantitative Trait C3/C4 -1.000000 +20195266 rs8092443 Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hemoglobin A1c 0.000001 +22509378 rs2284024 Sexual Dysfunction Overall FSD 0.000002 +17903295 rs1528753 Age-Related Phenotypes|Longevity Age at death 0.000000 +19043545 rs174548 Metabolite rs number -1.000000 +17903294 rs1200821 Hematological Phenotypes mean corpuscular hemoglobin 0.000006 +20463881 rs7219915 Eye Color C HS1 0.000000 +23408906 rs10420008 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +25087078 rs1044352 Epilepsies GGE 0.000000 +17903295 rs291353 Age-Related Phenotypes|Longevity Age at natural menopause‡ 0.000005 +20838585 rs853773 Cardiovascular Disease glucose 0.000001 +22291609 rs11829037 Inflammation hsCRP 0.000000 +22832964 rs3813570 Smoking Behaviors CPD 0.000001 +20585627 rs16891982 Common Traits Eye color -1.000000 +21931564 rs2046813 Metabolite Quantitative Trait PC ae C44:5/PC ae C42:5 -1.000000 +23251661 rs7030241 Childhood Obesity|Childhood TSH (µIU/mL) 0.000000 +20838585 rs12807555 Cardiovascular Disease glucose 0.000000 +24386095 rs12740374 Lipid Levels LDL 0.000000 +20195266 rs4838255 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Triglycerides 0.000000 +24376456 rs2275588 Blood Pressure Blood pressure 0.000000 +25340798 rs113263161 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000001 +17903293 rs2052028 Biomarker Traits Vitamin K % undercarboxylated osteocalcin 0.000001 +24892410 rs505299 Onset|Hypertension|Cardiovascular Events Daytime PP 0.000004 +20195266 rs11735070 Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Triglycerides 0.000001 +23966867 rs17134146 Body Fat Distribution WHR_pooled 0.000000 +25188341 rs429358 Dementias|Alzheimer's Disease Lewy Body (Ordinal II) 0.000000 +20585627 rs4408545 Common Traits Red hair -1.000000 +20838585 rs3793275 Cardiovascular Disease glucose 0.000001 +20526338 rs2363910 Platelet Aggregation ADP 2 u M 0.000000 +20585627 rs619865 Common Traits Red hair -1.000000 +17903307 rs219326 Pulmonary Function percent predicted fev 0.000009 +17903303 rs9302997 Atherosclerosis Ankle brachial index 0.000005 +19197348 rs10241703 Complex Disease Thyroid Stimulating Hormone 0.000002 +21931564 rs541503 Metabolite Quantitative Trait Orn-PTC/Ser-PTC 0.000000 +19197348 rs976730 Complex Disease Waist Circumference 0.000008 +25340798 rs4845622 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +17903304 rs958546 Cardiovascular Disease atrial fibrillation 0.000005 +23754948 rs10478424 Anthropometric Traits|Sexual WHRadjBMI 0.000000 +17903301 rs7828552 Exercise Responses|Artery Post-exercise 3 minute recovery systolic blood pressure 0.000009 +19609347 rs17365948 Hypertension|Blood Pressure SBP 0.000000 +24892410 rs6556114 Onset|Hypertension|Cardiovascular Events Daytime PP 0.000006 +24945404 rs12272917 Bone Mineral Density|Bone SK-BMD 0.000000 +23408906 rs17776563 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +19197348 rs4533267 Complex Disease Height 0.000000 +24324551 rs72786268 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive QRS 0.000000 +19197348 rs925488 Complex Disease Thyroid Stimulating Hormone 0.000003 +20838585 rs6440031 Cardiovascular Disease heart rate 0.000000 +17903296 rs922948 Association Bone shaft width** 0.000002 +20585627 rs9405675 Common Traits Freckling -1.000000 +19430483 rs12946454 Blood Pressure SBP 0.000004 +17903297 rs502309 Brain|Cognitive Test tcbv 0.000005 +22291609 rs643434 Inflammation IL-6 0.000000 +17903301 rs2553268 Exercise Responses|Artery Stage 2 Exercise systolic blood pressure 0.000006 +25133637 rs1347155 Body Mass Index Change in BMI 0.000000 +21386085 rs10790162 Metabolic Syndrome MetS 0.000000 +24376456 rs9318552 Blood Pressure DBP 0.000000 +20838585 rs7412 Cardiovascular Disease LDL-cholesterol 0.000000 +25340798 rs603050 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +21347282 rs8034802 Coronary Heart Disease HDL-C 0.000000 +21738480 rs1991866 Cell Phenotypes|White Blood Cell Monocytes 0.000000 +17903303 rs2390582 Atherosclerosis Coronary artery calcification 0.000001 +17903293 rs10507577 Biomarker Traits Vitamin D plasma 25(OH)-D 0.000003 +22558069 rs4985726 Immunoglobulin Isotypes|Non-Albumin Protein TP 0.000000 +19609347 rs11160059 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Disease Weight 0.000004 +17903301 rs2016718 Exercise Responses|Artery Post-exercise 3 minute recovery systolic blood pressure 0.000000 +20585627 rs2353033 Common Traits Red hair -1.000000 +17903296 rs4131805 Association Bone necklengf 0.000002 +22216198 rs1607504 Protein C Total PS 0.000008 +17903292 rs1158167 Kidney|Endocrine-Related Traits cst3 0.000000 +21552555 rs17126237 Obesity|Obesity-Related Traits BMI 0.000001 +20838585 rs12807555 Cardiovascular Disease glucose 0.000000 +19721433 rs7968606 Response Treatment|Antipsychotics Olanzapine – Negative 0.000000 +25133637 rs10041997 Body Mass Index Change in BMI 0.000000 +20927387 rs17064262 Cell Traits|Red Blood Cell MCH 0.000000 +20838585 rs7704530 Cardiovascular Disease diastolic BP 0.000000 +25340798 rs4129267 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +21386085 rs439401 Metabolic Syndrome HDLC-TG 0.000000 +24376456 rs10841530 Blood Pressure SBP 0.000001 +20694148 rs174546 Metabolic Syndrome “ 0.000000 +24324551 rs76090503 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 0.000000 +25340798 rs679620 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +24945404 rs2450083 Bone Mineral Density|Bone SK-BMD 0.000000 +23408906 rs10519227 Thyroid|Thyroid-Related Traits|Differences TSH -1.000000 +19197348 rs2562784 Complex Disease Height 0.000000 +21552555 rs17126232 Obesity|Obesity-Related Traits BMI 0.000000 +20838585 rs1144036 Cardiovascular Disease height 0.000000 +17903303 rs10499903 Atherosclerosis Ankle brachial index 0.000004 +21386085 rs2266788 Metabolic Syndrome TG-BP 0.000000 +20927387 rs855791 Cell Traits|Red Blood Cell MCV 0.000000 +17903294 rs4591494 Hematological Phenotypes factor vii 0.000009 +22911880 rs7624327 Behaviors|Personality Traits|Eating BULIMIA 0.000003 +21347282 rs11088655 Coronary Heart Disease Smoking 0.000000 +17903307 rs10922530 Pulmonary Function percent predicted fev 0.000001 +19197348 rs10984516 Complex Disease Thyroid Stimulating Hormone 0.000004 +21386085 rs11820589 Metabolic Syndrome TG-GLUC 0.000000 +23251661 rs657152 Childhood Obesity|Childhood IL-6 (pg/mL) 0.000000 +25340798 rs61812598 Proteins Involved|Inflammation|Alzheimer's Disease IL6R 0.000000 +23696099 rs9924561 Cell Traits|Red Blood Cell|Resistance MCH 0.000000 +20838585 rs13290397 Cardiovascular Disease triglycerides 0.000000 +17903293 rs1474747 Biomarker Traits Monocyte chemoattractant protein-1 0.000003 +21552555 rs11624704 Obesity|Obesity-Related Traits WHR 0.000000 +20694148 rs1535 Metabolic Syndrome “ 0.000001 +21386085 rs1919128 Metabolic Syndrome WC-TG 0.000000 +17903297 rs2179965 Brain|Cognitive Test f3 0.000001 +24324551 rs2274511 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive QRS 0.000001 +20838585 rs1046391 Cardiovascular Disease systolic BP 0.000000 +20548944 rs2062375 Osteoporosis-Related Traits|Gene Expression Profiling LS BMD 0.000000 +20585627 rs4309013 Common Traits Asparagus -1.000000 +22216198 rs12086738 Protein C fPS 0.000003 +23966867 rs6867983 Body Fat Distribution WC_men 0.000000 +20838585 rs709595 Cardiovascular Disease diastolic BP 0.000001 +20526338 rs1671152 Platelet Aggregation Lag 2 u g/mL 0.000000 +20585627 rs11861084 Common Traits Freckling -1.000000 +17903303 rs1376877 Atherosclerosis Internal carotid artery intimal medial thickness 0.000000 +21386085 rs780093 Metabolic Syndrome TG-BP 0.000000 +22832964 rs2036527 Smoking Behaviors CPD 0.000000 +20585627 rs1847134 Common Traits Green eyes -1.000000 +24376456 rs6479671 Blood Pressure Alcohol drinking 0.000000 +20395239 rs1192404 Optic Disc Size Disc 0.000000 +17903307 rs441051 Pulmonary Function mean fvc from two exams 0.000002 +17903293 rs10518765 Biomarker Traits Alkaline phosphatase 0.000001 +21931564 rs9309473 Metabolite Quantitative Trait N-ACu -1.000000 +20195266 rs17100498 Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hemoglobin A1c 0.000000 +20548944 rs11664087 Osteoporosis-Related Traits|Gene Expression Profiling NSA, women 0.000003 +22509378 rs2370759 Sexual Dysfunction Lubrication 0.000002 +17903297 rs3852286 Brain|Cognitive Test tcbv 0.000006 +20463881 rs1003719 Eye Color C HS1 0.000000 +25340798 rs948399 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 0.000000 +25087078 rs111577701 Epilepsies All epilepsy 0.000000 +20838585 rs6052399 Cardiovascular Disease insulin 0.000000 +24376456 rs4494364 Blood Pressure SBP 0.000000 +19430483 rs1530440 Blood Pressure DBP 0.000003 +20585627 rs977588 Common Traits Eye color -1.000000 +17903302 rs3773643 Arterial Stiffness|Blood Pressure MAP 0.000000 +21738479 rs4065321 White Blood Cell Count|Cell Phenotypes|White Blood Cell WBC 0.000000 +19721433 rs11722719 Response Treatment|Antipsychotics Ziprasidone – Positive 0.000001 +23251661 rs10131141 Childhood Obesity|Childhood Urinary nitrogen (g/d) 0.000000 +20838585 rs10260737 Cardiovascular Disease glucose 0.000001 +17903294 rs727979 Hematological Phenotypes red blood cell count 0.000007 +20195266 rs7119817 Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hip Circumference 0.000000 +25340798 rs6762266 Proteins Involved|Inflammation|Alzheimer's Disease CCL4 0.000000 +21347282 rs503662 Coronary Heart Disease LDL-C 0.000000 +19197348 rs4704397 Complex Disease Thyroid Stimulating Hormone 0.000000 +24892410 rs17338512 Onset|Hypertension|Cardiovascular Events Nighttime PP 0.000005 +21738479 rs4857855 White Blood Cell Count|Cell Phenotypes|White Blood Cell Eosinophils 0.000000 +22504420 rs4790881 Bone Mineral Density - 0.000000 +24094242 rs7267979 Serum Alkaline Phosphatase Levels - 0.000000 +23776548 rs3744061 Arterioles - 0.000000 +19169254 rs2066808 Psoriasis - 0.000000 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +22452962 rs889312 Breast Cancer - 0.000000 +23565137 rs11218343 Late-Onset Alzheimer’s Disease - 0.000000 +22504420 rs13245690 Bone Mineral Density - 0.000000 +20169177 rs9271366 Systemic Lupus Erythematosus - 0.000000 +21060863 rs10774625 Cardiovascular Diseases - 0.000000 +18776929 rs2342753 Hip Bone Size|Females - 0.000002 +23382809 rs583583 Schizophrenia - 0.000001 +18776929 rs10168722 Hip Bone Size|Females - 0.000000 +21931564 rs8396 Metabolite Quantitative Trait - 0.000000 +20729852 rs11187842 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +24483146 rs9512755 Biomarkers - 0.000004 +25367360 rs7534824 Astigmatism|Refractive Error - 0.000001 +25364816 rs10894267 Diabetic Retinopathy - 0.000005 +23408906 rs7045138 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21408207 rs1150754 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +23326517 rs9621532 Age-Related Macular Degeneration - 0.000000 +24390342 rs9378815 Rheumatoid Arthritis|Biology - 0.000000 +19571809 rs10484399 Schizophrenia - 0.000000 +23967269 rs4879926 Mite-Specific IgEs|Asthma - 0.000008 +24143190 rs3803662 Breast Cancer|Breast - 0.000000 +23738518 rs4807927 Reading|Language - 0.000001 +21502949 rs4752195 Brain - 0.000006 +25367360 rs7545911 Astigmatism|Refractive Error - 0.000003 +24945404 rs3012465 Bone Mineral Density|Bone - 0.000000 +22359512 rs2945816 Sphingolipids - 0.000000 +23209447 rs2517713 I Antigen|Nasopharyngeal Carcinoma - 0.000000 +20038947 rs7654559 Major Depression - 0.000008 +19609347 rs2183737 Hypertension|Blood Pressure - 0.000001 +23900074 rs7726159 Telomere Length|Cancer - 0.000000 +19247474 rs1402279 Smoking Behaviors|Cigarette Smoking - 0.000005 +22359512 rs4666002 Sphingolipids - 0.000000 +19300500 rs2137064 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000010 +24625756 rs603424 Intermediate Phenotypes - 0.000000 +23350875 rs11996339 Colorectal Cancer - 0.000000 +21980494 rs500498 Venous Thrombosis - 0.000000 +21779181 rs11171747 Systemic Sclerosis - 0.000002 +25129146 rs7447927 Esophageal Squamous Cell Carcinoma - 0.000000 +19197348 rs6489780 Complex Disease - 0.000008 +22832960 rs11163372 Temperament Character Inventory - 0.000003 +23291587 rs7616215 Behçet's Disease - 0.000000 +22479191 rs2453580 Kidney|Follow-Up - 0.000000 +24166486 rs17693963 Schizophrenia - 0.000000 +22452962 rs4784227 Breast Cancer - 0.000000 +19122664 rs1004819 Ulcerative Colitis - 0.000002 +19961619 rs7629719 Respiratory|Atopy - 0.000000 +23143602 rs12688220 Pancreatitis - 0.000000 +20195514 rs5936487 Primary Tooth Development - 0.000000 +24244560 rs730497 Diabetic Retinopathy|Chronic Kidney Disease|Hemoglobin A - 0.000000 +23104006 rs13394619 Endometriosis - 0.000000 +23776548 rs2281827 Arterioles - 0.000000 +25241909 rs2869967 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +19609347 rs11120313 Hypertension|Blood Pressure - 0.000005 +19056611 rs7901695 Type 2 Diabetes - 0.000000 +20932310 rs2899472 Τ Protein Levels - 0.000000 +24871463 rs11697848 Systemic Lupus Erythematosus Sle - 0.000000 +22745674 rs2327620 Coronary Artery Stenosis|Coronary Artery - 0.000002 +25241909 rs185786041 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +23092984 rs3744728 Bipolar Disorder - 0.000003 +22829776 rs10432029 Globulin|Hormone|Steroid Hormone - 0.000000 +25310577 rs7089424 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +19343178 rs12325866 Stature - 0.000003 +24755620 rs474951 Glutamate|Alzheimer's Disease - 0.000001 +22685421 rs2404958 Ocular Axial Length|High Myopia - 0.000005 +21909110 rs871606 Mean Arterial Pressure|Pulse Pressure - 0.000000 +21297633 rs181359 Ulcerative Colitis - 0.000000 +25378659 rs2100944 Long-Chain Saturated Fatty Acids - 0.000000 +19448621 rs365132 Age Menarche|Menopause - 0.000000 +25241909 rs12910412 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000001 +21423239 rs10437629 Attempted Suicide - 0.000004 +20339536 rs4420638 Lipid-Lowering Response|Response Statins - 0.000001 +20932310 rs2768975 Τ Protein Levels - 0.000000 +23408906 rs9915657 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +22085899 rs4773330 Bilirubin Levels - 0.000008 +22470424 rs7707833 Amyotrophic Lateral Sclerosis - 0.000003 +22504420 rs1286083 Bone Mineral Density - 0.000000 +23408906 rs9472138 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21448238 rs986222 Migraine - 0.000003 +21909110 rs2071518 Mean Arterial Pressure|Pulse Pressure - 0.000000 +21750679 rs3821236 Systemic Sclerosis - 0.000000 +20436471 rs499345 Paget’s Disease Bone - 0.000000 +23738518 rs4807927 Reading|Language - 0.000001 +23936387 rs11193120 Celiac Disease - 0.000007 +21076409 rs11710077 Conduction|Qrs Duration - 0.000000 +22504420 rs1566045 Bone Mineral Density - 0.000000 +23028483 rs1342326 Asthma - 0.000000 +24999842 rs6840978 Celiac Disease|Celiac - 0.000000 +23291587 rs17482078 Behçet's Disease - 0.000000 +24047820 rs9257616 Social Communication - 0.000000 +21060863 rs17421627 Cardiovascular Diseases - 0.000000 +23326239 rs477515 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23326239 rs2227139 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23382691 rs12828421 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +20190752 rs11922594 Celiac Disease - 0.000007 +23704328 rs12229918 Tooth Eruption|Height - 0.000000 +17903305 rs10263639 Prostate Cancer|Breast - 0.000003 +23382691 rs886774 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24755620 rs528823 Glutamate|Alzheimer's Disease - 0.000002 +24709693 rs66861122 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000005 +21124946 rs1021188 Bone Mineral Density - 0.000000 +23350875 rs3104964 Colorectal Cancer - 0.000004 +21273288 rs1004565 NT-proBNP - 0.000000 +22504420 rs7217932 Bone Mineral Density - 0.000000 +21297633 rs734999 Ulcerative Colitis - 0.000000 +24740154 rs7514323 Prostate Cancer|Early-Onset - 0.000003 +24403052 rs214782 Basal Cell Carcinoma - 0.000000 +25352737 rs926937 Cataract - 0.000006 +22359512 rs7337573 Sphingolipids - 0.000000 +23437003 rs6909279 Volumetric Bone Mineral Densities - 0.000000 +20953186 rs13196377 Psoriasis|Psoriatic Arthritis - 0.000000 +23958962 rs111325002 Cocaine Dependence - 0.000000 +25017104 rs11819199 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +20339536 rs1260326 Lipid-Lowering Response|Response Statins - 0.000000 +23984888 rs4485561 Airway Responsiveness - 0.000010 +21909115 rs13082711 Cardiovascular Disease|Blood Pressure - 0.000000 +24688116 rs2149954 Longevity|Analysis|Population - 0.000006 +23704328 rs6568401 Tooth Eruption|Height - 0.000008 +21347284 rs3922844 Pr Interval - 0.000000 +23984888 rs7592613 Airway Responsiveness - 0.000009 +23326517 rs429608 Age-Related Macular Degeneration - 0.000000 +19132087 rs9834548 Kawasaki Disease - 0.000010 +24483146 rs4682949 Biomarkers - 0.000002 +25147783 rs34324219 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +24014518 rs7587026 Epilepsy|Febrile Seizures - 0.000000 +20935630 rs713586 Body Mass Index - 0.000000 +19197348 rs4420638 Complex Disease - 0.000005 +25147783 rs1780316 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +22359512 rs12472274 Sphingolipids - 0.000000 +24390342 rs773125 Rheumatoid Arthritis|Biology - 0.000000 +23326517 rs3793917 Age-Related Macular Degeneration - 0.000000 +19430480 rs2664170 Type 1 Diabetes - 0.000000 +19305408 rs2074238 Qt Interval Duration - 0.000000 +23408906 rs7825175 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +18840781 rs17673553 Type 1 Diabetes - 0.000000 +21297633 rs4728142 Ulcerative Colitis - 0.000000 +25390645 rs12120353 Anxiety - 0.000003 +25241909 rs143705409 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +22843504 rs1930165 Autism Spectrum - 0.000000 +22829776 rs7910927 Globulin|Hormone|Steroid Hormone - 0.000000 +21298047 rs1426153 European-Origin|Substance Dependence - 0.000002 +18483556 rs4408545 Hair Color|Skin Pigmentation - 0.000000 +21060863 Rs225717 Cardiovascular Diseases - 0.000000 +23979607 rs73772260 Borderline Personality - 0.000001 +21909115 rs4590817 Cardiovascular Disease|Blood Pressure - 0.000000 +20953189 rs1008953 Psoriasis - 0.000000 +18262040 rs562338 LDL-cholesterol - 0.000000 +23667675 rs314266 Age Menarche - 0.000001 +21980299 rs478222 Type 1 Diabetes - 0.000000 +23326517 rs17586843 Age-Related Macular Degeneration - 0.000002 +20935630 rs2287019 Body Mass Index - 0.000000 +22993228 rs6602024 Lumbar Disc Degeneration - 0.000002 +21298027 rs6516104 Celiac Disease|Crohn's Disease - 0.000001 +21490707 rs6495122 Caffeine Consumption|Cyp1A2 - 0.000001 +21460840 rs610932 Alzheimer’s Disease - 0.000000 +25436638 rs1571583 Serum Thyroid Stimulating Hormone - 0.000000 +24740154 rs7013418 Prostate Cancer|Early-Onset - 0.000004 +19197348 rs4846914 Complex Disease - 0.000000 +19430480 rs10517086 Type 1 Diabetes - 0.000000 +22359512 rs603424 Sphingolipids - 0.000000 +25340798 rs4129267 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +23989986 rs10878630 Hip|Osteoarthritis - 0.000000 +25340798 rs11225434 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +25064009 rs34016896 Parkinson’s Disease - 0.000008 +19300500 rs1512285 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000003 +23704328 rs997154 Tooth Eruption|Height - 0.000007 +21502949 rs234937 Brain - 0.000009 +22368281 rs405509 LDL-c Response|Lpa - 0.000000 +19197348 rs12130333 Complex Disease - 0.000000 +21827660 rs2157719 Increased Disease Risk - 0.000000 +21738478 rs3095254 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +25340798 rs11575821 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +19454037 rs10499859 Left Ventricular Mass - 0.000003 +24871463 rs11073328 Systemic Lupus Erythematosus Sle - 0.000000 +19247474 rs910696 Smoking Behaviors|Cigarette Smoking - 0.000003 +25742292 rs561155 Parity - 0.000008 +24709693 rs61996546 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000003 +18262040 rs2228671 LDL-cholesterol - 0.000000 +21298047 rs12284594 European-Origin|Substance Dependence - 0.000002 +22570627 rs9841621 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000009 +23870195 rs9349379 Coronary Artery|Coronary Artery Calcification - 0.000000 +25188341 rs11771145 Dementias|Alzheimer's Disease - 0.000000 +19609347 rs991316 Hypertension|Blood Pressure - 0.000003 +19668339 rs2075650 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000001 +19343178 rs742106 Stature - 0.000000 +24999842 rs212388 Celiac Disease|Celiac - 0.000000 +22359512 rs10404486 Sphingolipids - 0.000000 +18262040 rs4970834 LDL-cholesterol - 0.000000 +19571809 rs9461219 Schizophrenia - 0.000000 +23300701 rs10795668 Colorectal Cancer - 0.000005 +23565137 rs7519866 Late-Onset Alzheimer’s Disease - 0.000010 +23001564 rs1317082 Homeostasis - 0.000000 +19772629 rs676495 Parkinson Disease|Onset - 0.000009 +25188341 rs17125944 Dementias|Alzheimer's Disease - 0.000000 +18483556 rs8033165 Hair Color|Skin Pigmentation - 0.000000 +22829776 rs10454142 Globulin|Hormone|Steroid Hormone - 0.000000 +23455636 rs3130783 Age-Related Macular Degeneration - 0.000000 +23408906 rs7045138 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +20190752 rs653178 Celiac Disease - 0.000000 +22085899 rs1986655 Bilirubin Levels - 0.000002 +25390645 rs6799682 Anxiety - 0.000008 +19197348 rs2159324 Complex Disease - 0.000002 +22344219 rs9356744 Body Mass Index - 0.000000 +20081858 rs2191349 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +23563607 rs13041126 Anthropometric Traits - 0.000000 +24133439 rs1861572 Autistic-Like Traits - 0.000003 +25310577 rs10821937 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +24097068 rs17404153 Lipid Levels - 0.000000 +22504420 rs163879 Bone Mineral Density - 0.000006 +24348519 rs17817449 Body Mass Index - 0.000000 +19668339 rs12654281 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000000 +22144915 rs2307049 Corneal Astigmatism - 0.000000 +19305408 rs846111 Qt Interval Duration - 0.000000 +23636237 rs12156272 Analysis - 0.000006 +21935397 rs7720663 Extremely|Overweight|Body Mass Index - 0.000006 +18483556 rs6918152 Hair Color|Skin Pigmentation - 0.000000 +21326860 rs10129255 Kawasaki Disease - 0.000007 +22368281 rs721843 LDL-c Response|Lpa - 0.000001 +25367360 rs925931 Astigmatism|Refractive Error - 0.000003 +21297633 rs17293632 Ulcerative Colitis - 0.000000 +25064009 rs6430538 Parkinson’s Disease - 0.000000 +21771975 rs7193788 Adiponectin|Quantitative Trait|Cardiometabolic Outcomes - 0.000000 +21943158 rs2075650 Cardiovascular-Related Traits - 0.000000 +21876539 rs2470893 Cyp1A2 - 0.000000 +24166486 rs4721441 Schizophrenia - 0.000000 +21876539 rs2472297 Cyp1A2 - 0.000000 +21935397 rs887912 Extremely|Overweight|Body Mass Index - 0.000000 +21298047 rs10893366 European-Origin|Substance Dependence - 0.000009 +20861866 rs429608 Age-Related Macular Degeneration - 0.000000 +22044751 rs2518144 Chronic Kidney Disease - 0.000004 +19609347 rs2823756 Hypertension|Blood Pressure - 0.000006 +22504420 rs7521902 Bone Mineral Density - 0.000000 +20661308 rs16902486 Serum Calcium - 0.000004 +21909115 rs17249754 Cardiovascular Disease|Blood Pressure - 0.000000 +19609347 rs13201744 Hypertension|Blood Pressure - 0.000001 +24483146 rs28668016 Biomarkers - 0.000005 +20661308 rs17005914 Serum Calcium - 0.000007 +19571809 rs7776351 Schizophrenia - 0.000000 +18262040 rs478442 LDL-cholesterol - 0.000000 +21408207 rs2669010 Systemic Lupus Erythematosus|Autoantibody - 0.000005 +20935630 rs7359397 Body Mass Index - 0.000000 +21658281 rs2982694 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +22484627 rs9299 Childhood Obesity - 0.000001 +21423239 rs2175671 Attempted Suicide - 0.000002 +19571809 rs17149524 Schizophrenia - 0.000010 +17684544 rs10484545 Ibd Disease - 0.000000 +19197348 rs4846914 Complex Disease - 0.000000 +20729852 rs3765524 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +21060860 rs2981575 Breast Cancer - 0.000000 +22832960 rs2741200 Temperament Character Inventory - 0.000005 +21738491 rs16880395 Sudden Cardiac Death - 0.000005 +22558097 rs6759892 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +23738518 rs11666805 Reading|Language - 0.000006 +24025145 rs16908658 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000001 +20700443 rs4072037 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +25526632 rs11723068 Breast Cancer - 0.000010 +21779381 rs1406961 Migraine|Cardiovascular Events|Cardiovascular - 0.000001 +24097068 rs4917014 Lipid Levels - 0.000000 +19801982 rs2504063 Bone Mineral Density - 0.000000 +20686608 rs11242679 Pancreatic Cancer - 0.000002 +21804549 rs1102000 Asthma - 0.000000 +21298027 rs212388 Celiac Disease|Crohn's Disease - 0.000000 +21483430 rs3806372 Neurocognitive Phenotypes - 0.000006 +23793025 rs7577262 Migraine - 0.000000 +20169177 rs877819 Systemic Lupus Erythematosus - 0.000001 +20729852 rs4072037 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000007 +22558097 rs1105879 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +21060863 rs7824557 Cardiovascular Diseases - 0.000000 +19571809 rs9272535 Schizophrenia - 0.000000 +21297633 rs6584283 Ulcerative Colitis - 0.000000 +23583980 rs868903 Pulmonary Fibrosis - 0.000000 +25060954 rs589636 Kinase|Hearing - 0.000000 +24836286 rs11632715 Colorectal Cancer - 0.000004 +23326239 rs204999 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +22993228 rs2484990 Lumbar Disc Degeneration - 0.000004 +23984888 rs11674314 Airway Responsiveness - 0.000010 +24513273 rs1394125 Serum Uric Acid - 0.000000 +21700879 rs13358260 Adiponectin Levels - 0.000001 +22843504 rs9302952 Autism Spectrum - 0.000000 +20972438 rs798766 Bladder Cancer|Bladder - 0.000000 +22916037 rs16939881 Atherosclerosis - 0.000000 +24740154 rs4665609 Prostate Cancer|Early-Onset - 0.000004 +25147783 rs11254363 Ischemic Stroke|Vitamin|Folate Levels - 0.000001 +23408906 rs7240777 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +20169177 rs10168266 Systemic Lupus Erythematosus - 0.000000 +22423221 rs9494145 Platelet Count|Mean Platelet Volume - 0.000000 +19571809 rs6904071 Schizophrenia - 0.000000 +21156761 rs4305317 Rheumatoid Arthritis - 0.000000 +19359265 rs4407366 Telomere Length - 0.000009 +22479419 rs4699030 Treatment Refractory Schizophrenia - 0.000001 +20700443 rs3740393 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000001 +22916037 rs4810479 Atherosclerosis - 0.000000 +20038947 rs11634319 Major Depression - 0.000006 +24489884 rs1299926 Aggression - 0.000008 +20661308 rs1801725 Serum Calcium - 0.000000 +21980299 rs3184504 Type 1 Diabetes - 0.000000 +25241909 rs11858836 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000001 +23984888 rs4129709 Airway Responsiveness - 0.000010 +17903305 rs10498792 Prostate Cancer|Breast - 0.000003 +24513273 rs2544390 Serum Uric Acid - 0.000000 +25064009 rs1555399 Parkinson’s Disease - 0.000000 +20522523 rs2601828 Partial Epilepsies - 0.000001 +24097068 rs4983559 Lipid Levels - 0.000000 +22044751 rs9375674 Chronic Kidney Disease - 0.000006 +22511988 rs17864683 Cell-Free Dna|Cardiovascular - 0.000000 +20932310 rs7631605 Τ Protein Levels - 0.000001 +23886662 rs6661961 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +21297633 rs4510766 Ulcerative Colitis - 0.000000 +22359512 rs17606561 Sphingolipids - 0.000000 +25390645 rs3097411 Anxiety - 0.000007 +23028341 rs11575839 Complement C3 - 0.000000 +21935397 rs571312 Extremely|Overweight|Body Mass Index - 0.000000 +19772629 rs10773917 Parkinson Disease|Onset - 0.000004 +23966867 rs1294410 Body Fat Distribution - 0.000001 +18776929 rs1808850 Hip Bone Size|Females - 0.000000 +25629512 rs2303790 Age-Related Macular Degeneration - 0.000000 +22570627 rs2117760 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000004 +23583980 rs35705950 Pulmonary Fibrosis - 0.000000 +20339536 rs9644568 Lipid-Lowering Response|Response Statins - 0.000000 +22993228 rs9301951 Lumbar Disc Degeneration - 0.000001 +23382691 rs2072209 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +23666240 rs9905704 Testicular Cancer - 0.000000 +24651765 rs4948102 Homocysteine|Methionine|Metabolism - 0.000000 +21983785 rs3219090 Melanoma - 0.000000 +19668339 rs4773460 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000002 +24166486 rs7799006 Schizophrenia - 0.000000 +24166486 rs3799380 Schizophrenia - 0.000000 +18483556 rs12142165 Hair Color|Skin Pigmentation - 0.000006 +19096518 rs4607517 Glycated Hemoglobin - 0.000000 +20190752 rs12928822 Celiac Disease - 0.000000 +22993228 rs4875102 Lumbar Disc Degeneration - 0.000000 +23472185 rs17411949 Multiple Sclerosis|Oligoclonal Band - 0.000001 +23958962 rs6677435 Cocaine Dependence - 0.000000 +23704328 rs1799922 Tooth Eruption|Height - 0.000000 +21460840 rs670139 Alzheimer’s Disease - 0.000000 +23326239 rs2294884 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +22693455 rs1111875 Obese|Type 2 Diabetes - 0.000000 +24952745 rs735951 Qt Interval|Calcium - 0.000000 +22561518 rs4330287 Generalized Vitiligo - 0.000000 +23326239 rs2854008 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +18483556 rs4238833 Hair Color|Skin Pigmentation - 0.000000 +24097068 rs17695224 Lipid Levels - 0.000000 +18776929 rs989056 Hip Bone Size|Females - 0.000000 +19812673 rs17088254 Autism - 0.000008 +25188341 rs983392 Dementias|Alzheimer's Disease - 0.000000 +21779181 rs9296015 Systemic Sclerosis - 0.000000 +23667675 rs6472983 Age Menarche - 0.000008 +22561518 rs4766578 Generalized Vitiligo - 0.000000 +18846228 rs7737470 Serum IgE Levels - 0.000000 +18604267 rs657152 Antigen|Icam-1 - 0.000000 +23326239 rs2233971 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +19401414 rs2383208 Type 2 Diabetes - 0.000000 +22484627 rs9568856 Childhood Obesity - 0.000000 +21408207 rs2187668 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +23958962 rs116087723 Cocaine Dependence - 0.000000 +23259602 rs788911 Dental Caries - 0.000001 +24651765 rs9296404 Homocysteine|Methionine|Metabolism - 0.000000 +23041239 rs7937106 Ischaemic Stroke - 0.000000 +23437003 rs17638544 Volumetric Bone Mineral Densities - 0.000005 +24513273 rs506338 Serum Uric Acid - 0.000000 +19734902 rs3818361 Alzheimer's Disease - 0.000009 +19056611 rs13266634 Type 2 Diabetes - 0.000007 +24964207 rs17387100 Suicidal Ideation|Attempts Suicidal|Suicide Attempts - 0.000001 +23326517 rs10490924 Age-Related Macular Degeneration - 0.000000 +24516586 rs7699512 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000002 +21076409 rs13165478 Conduction|Qrs Duration - 0.000000 +24280982 rs4650608 Schizophrenia|Bipolar Disorder|Disorder - 0.000000 +23984888 rs13382948 Airway Responsiveness - 0.000003 +23118916 rs11074583 Serum IgM - 0.000000 +24952745 rs17457880 Qt Interval|Calcium - 0.000000 +19798445 rs1466448 Sphingolipid - 0.000000 +24571439 rs1567010 Specific Language Impairment|Genotype Effects - 0.000010 +24166486 rs10275045 Schizophrenia - 0.000000 +23382691 rs7805803 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000009 +19359265 rs7374458 Telomere Length - 0.000005 +22843504 rs1936295 Autism Spectrum - 0.000001 +24166486 rs10927013 Schizophrenia - 0.000000 +19571809 rs11061935 Schizophrenia - 0.000004 +22685421 rs1137 Ocular Axial Length|High Myopia - 0.000004 +20421936 rs1558902 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +22832960 rs10057405 Temperament Character Inventory - 0.000009 +23382691 rs968451 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +22993228 rs10046257 Lumbar Disc Degeneration - 0.000000 +25102180 rs231356 Type 2 Diabetes - 0.000000 +20932310 rs1943816 Τ Protein Levels - 0.000000 +21804549 rs1837253 Asthma - 0.000000 +22359512 rs12051548 Sphingolipids - 0.000000 +23646285 rs16826005 Hypersomnia - 0.000000 +24483146 rs2290344 Biomarkers - 0.000000 +25086665 rs2736098 Pancreatic Cancer - 0.000008 +23092984 rs9834970 Bipolar Disorder - 0.000000 +23984888 rs7579157 Airway Responsiveness - 0.000009 +23544013 rs169201 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +19343178 rs1776897 Stature - 0.000000 +19812673 rs7923367 Autism - 0.000003 +21437268 rs1229984 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +25436638 rs6885813 Serum Thyroid Stimulating Hormone - 0.000000 +20858683 rs1799884 Hemoglobin A - 0.000000 +23056639 rs17658562 Lectin - 0.000007 +23326517 rs1061170 Age-Related Macular Degeneration - 0.000000 +20190752 rs5979785 Celiac Disease - 0.000000 +22479309 rs1476587 Brachial Circumference - 0.000006 +23455636 rs13278062 Age-Related Macular Degeneration - 0.000000 +24390342 rs1950897 Rheumatoid Arthritis|Biology - 0.000000 +25742292 rs3801153 Parity - 0.000005 +23544013 rs2290854 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +23666240 rs7010162 Testicular Cancer - 0.000000 +22087292 rs10491629 Femoral Neck Bone Geometry - 0.000003 +22993228 rs10214886 Lumbar Disc Degeneration - 0.000000 +23636237 rs1191005 Analysis - 0.000002 +23761726 rs11859036 Corneal Astigmatism|Platelet-Derived Growth Factor - 0.000007 +20661308 rs17120351 Serum Calcium - 0.000000 +23408906 rs17776563 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +23958962 rs79794368 Cocaine Dependence - 0.000001 +24483146 rs10495285 Biomarkers - 0.000000 +24763700 rs7553007 C-Reactive Protein Levels - 0.000000 +24651765 rs10934753 Homocysteine|Methionine|Metabolism - 0.000000 +23886662 rs9050 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +23886662 rs20541 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +21827660 rs2736100 Increased Disease Risk - 0.000000 +25367360 rs7518155 Astigmatism|Refractive Error - 0.000003 +20066028 rs9863761 Serum Cholesterol Levels - 0.000005 +21873549 rs7903146 Type 2 Diabetes|Proinsulin Levels - 0.000000 +22916037 rs2731672 Atherosclerosis - 0.000000 +21297633 rs6911490 Ulcerative Colitis - 0.000000 +24347629 rs920455 Periodontal - 0.000009 +24755620 rs157580 Glutamate|Alzheimer's Disease - 0.000000 +22570617 rs2157719 Optic Nerve|Glaucoma - 0.000000 +24097068 rs11694172 Lipid Levels - 0.000000 +23382691 rs2366293 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +21814517 rs987870 Asthma - 0.000000 +23958962 rs7086629 Cocaine Dependence - 0.000001 +24097068 rs1250229 Lipid Levels - 0.000000 +21552555 rs6921953 Obesity|Obesity-Related Traits - 0.000009 +18846228 rs2706347 Serum IgE Levels - 0.000001 +24999842 rs6851362 Celiac Disease|Celiac - 0.000000 +24714607 rs4760851 Chronic Mucus Hypersecretion - 0.000005 +19197348 rs11066587 Complex Disease - 0.000005 +22087292 rs969715 Femoral Neck Bone Geometry - 0.000001 +24223155 rs1789536 Torsades De Pointes - 0.000007 +24483146 rs12050587 Biomarkers - 0.000000 +23056639 rs7586 Lectin - 0.000008 +23544013 rs199534 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +22428042 rs564398 Glaucoma|Optic-Nerve - 0.000000 +22359512 rs4485401 Sphingolipids - 0.000000 +21437268 rs10801805 Cancers|Conducted|Upper Aerodigestive Tract - 0.000003 +23703922 rs17420080 Uric Acid Levels - 0.000000 +19430480 rs11258747 Type 1 Diabetes - 0.000000 +23704328 rs17101923 Tooth Eruption|Height - 0.000000 +23793025 rs4379368 Migraine - 0.000000 +24097068 rs10102164 Lipid Levels - 0.000000 +19597492 rs17042171 Atrial Fibrillation - 0.000000 +21946350 rs2284746 Lung Function|Follow-Up - 0.000000 +20932310 rs895401 Τ Protein Levels - 0.000001 +21901158 rs2407103 Insulin Resistance|Copy Number Variation - 0.000002 +23326239 rs7195 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +19343178 rs3118914 Stature - 0.000000 +22561518 rs3814231 Generalized Vitiligo - 0.000000 +24709693 rs7839040 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000002 +21812969 rs415430 Parkinson's Disease - 0.000001 +24390342 rs678347 Rheumatoid Arthritis|Biology - 0.000000 +23984888 rs13382948 Airway Responsiveness - 0.000003 +23817569 rs2101521 Allergy - 0.000000 +21750679 rs7574865 Systemic Sclerosis - 0.000000 +19714249 rs4756846 Obesity|Osteoporosis Phenotypes - 0.000001 +19300500 rs7655625 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +23958962 rs2005290 Cocaine Dependence - 0.000000 +23382691 rs4930561 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +23307926 rs1046089 Menopause - 0.000000 +21980494 rs11696364 Venous Thrombosis - 0.000002 +19503597 rs505802 Uric Acid - 0.000001 +24513273 rs17050272 Serum Uric Acid - 0.000000 +24886709 rs139961185 Lipid - 0.000000 +24094242 rs12355784 Serum Alkaline Phosphatase Levels - 0.000000 +25367360 rs7528849 Astigmatism|Refractive Error - 0.000003 +20038947 rs10265216 Major Depression - 0.000003 +21935397 rs206936 Extremely|Overweight|Body Mass Index - 0.000000 +20485516 rs12447690 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +25350695 rs2900478 Ldl Cholesterol Response|Response Statins - 0.000002 +23326239 rs2294882 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21490707 rs2472304 Caffeine Consumption|Cyp1A2 - 0.000002 +22589738 rs1558902 Adipose - 0.000001 +24379826 rs17586876 Serum Uric Acid Levels - 0.000002 +21935397 rs10968576 Extremely|Overweight|Body Mass Index - 0.000000 +21658281 rs12429889 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +19132087 rs17531088 Kawasaki Disease - 0.000001 +23593202 rs12146626 Age Menarche|Femoral Neck Bone Geometry - 0.000004 +21124946 rs4280044 Bone Mineral Density - 0.000007 +25129146 rs7447927 Esophageal Squamous Cell Carcinoma - 0.000000 +24886709 rs28680850 Lipid - 0.000003 +20700443 rs7965584 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +24999842 rs11734090 Celiac Disease|Celiac - 0.000000 +21935397 rs7132908 Extremely|Overweight|Body Mass Index - 0.000000 +18823527 Rs157580 Late-Onset Alzheimer's Disease - 0.000000 +23563607 rs4735692 Anthropometric Traits - 0.000000 +19557197 rs981113 Distribution|Adiposity|Waist Circumference - 0.000001 +22504421 rs6581612 Hippocampal Volume - 0.000000 +20700443 rs13146355 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +21876539 rs2470893 Cyp1A2 - 0.000000 +24483146 rs4774760 Biomarkers - 0.000000 +21829377 rs174535 Plasma Phospholipid|Fatty Acids - 0.000000 +23307926 rs365132 Menopause - 0.000000 +23817569 rs9303280 Allergy - 0.000000 +19936222 rs3856637 Cholesterol|Plasma Lipoprotein Size - 0.000000 +25364816 rs7083364 Diabetic Retinopathy - 0.000010 +23326517 rs641153 Age-Related Macular Degeneration - 0.000000 +22423221 rs6490294 Platelet Count|Mean Platelet Volume - 0.000000 +23401653 rs6554163 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000003 +24390342 rs10175798 Rheumatoid Arthritis|Biology - 0.000000 +24097068 rs11563251 Lipid Levels - 0.000000 +24952745 rs17784882 Qt Interval|Calcium - 0.000000 +24688116 rs1625040 Longevity|Analysis|Population - 0.000007 +22561518 rs853308 Generalized Vitiligo - 0.000000 +19571809 rs13219181 Schizophrenia - 0.000000 +18846228 rs3798135 Serum IgE Levels - 0.000000 +23974872 rs778371 Schizophrenia - 0.000000 +20038947 rs10187367 Major Depression - 0.000005 +23900074 rs2487999 Telomere Length|Cancer - 0.000000 +24223155 rs9805984 Torsades De Pointes - 0.000010 +21935397 rs13130484 Extremely|Overweight|Body Mass Index - 0.000002 +23761726 rs7651778 Corneal Astigmatism|Platelet-Derived Growth Factor - 0.000005 +23836780 rs59072263 Intraocular Pressure|Glaucoma - 0.000000 +23297363 rs4771856 Tetralogy Fallot - 0.000000 +20174558 rs7192960 Type 2 Diabetes - 0.000008 +22829776 rs6258 Globulin|Hormone|Steroid Hormone - 0.000000 +25367360 rs6892230 Astigmatism|Refractive Error - 0.000002 +25060954 rs1503363 Kinase|Hearing - 0.000001 +24871463 rs12259 Systemic Lupus Erythematosus Sle - 0.000003 +19056611 rs8050136 Type 2 Diabetes - 0.000000 +21909115 rs1458038 Cardiovascular Disease|Blood Pressure - 0.000000 +18483556 rs7195066 Hair Color|Skin Pigmentation - 0.000000 +22504420 rs12821008 Bone Mineral Density - 0.000000 +23984888 rs4861175 Airway Responsiveness - 0.000005 +25367360 rs2975500 Astigmatism|Refractive Error - 0.000004 +19668339 rs682748 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000008 +19197348 rs4420638 Complex Disease - 0.000000 +22116950 rs11255291 Ovarian Reserve - 0.000002 +23401653 rs6836215 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000004 +21876539 rs382140 Cyp1A2 - 0.000000 +21533074 rs2647012 Diffuse Large B-cell Lymphoma|Follicular Lymphoma|Diffuse - 0.000000 +24625756 rs4343 Intermediate Phenotypes - 0.000000 +20861866 rs3793917 Age-Related Macular Degeneration - 0.000000 +24688116 rs10957550 Longevity|Analysis|Population - 0.000004 +23300701 rs4591517 Colorectal Cancer - 0.000001 +24390342 rs909685 Rheumatoid Arthritis|Biology - 0.000000 +21552555 rs9813516 Obesity|Obesity-Related Traits - 0.000004 +22993228 rs11969002 Lumbar Disc Degeneration - 0.000000 +24025145 rs7919725 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000001 +22479202 rs7133378 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +23472185 rs12674503 Multiple Sclerosis|Oligoclonal Band - 0.000002 +19609347 rs10135446 Hypertension|Blood Pressure - 0.000004 +23326239 rs7754768 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +25297839 rs114864815 Herpes Zoster - 0.000000 +24952745 rs1396515 Qt Interval|Calcium - 0.000000 +21124955 rs4353250 Serum Amyloid A|Type 2 Diabetes - 0.000000 +21658281 rs7307780 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +23989986 rs5009270 Hip|Osteoarthritis - 0.000001 +19571809 rs17693963 Schizophrenia - 0.000000 +22829776 rs2411984 Globulin|Hormone|Steroid Hormone - 0.000000 +20062060 rs6800541 Pr Interval - 0.000000 +21297633 rs678170 Ulcerative Colitis - 0.000000 +22470424 rs6075165 Amyotrophic Lateral Sclerosis - 0.000004 +23092984 rs10255295 Bipolar Disorder - 0.000005 +21379329 rs2673604 Late-Onset Alzheimer's Disease - 0.000003 +23455636 rs429608 Age-Related Macular Degeneration - 0.000000 +21483430 rs11122324 Neurocognitive Phenotypes - 0.000000 +22792070 rs3779381 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +21935397 rs10508503 Extremely|Overweight|Body Mass Index - 0.000000 +25147783 rs2287921 Ischemic Stroke|Vitamin|Folate Levels - 0.000001 +20548946 rs1362756 Optic Disc - 0.000000 +22044751 rs2282335 Chronic Kidney Disease - 0.000004 +19734902 rs3851179 Alzheimer's Disease - 0.000000 +23636237 rs11725988 Analysis - 0.000007 +22423221 rs151361 Platelet Count|Mean Platelet Volume - 0.000000 +21980494 rs6034465 Venous Thrombosis - 0.000007 +21408207 rs12531711 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +19305408 rs8049607 Qt Interval Duration - 0.000001 +23408906 rs11755845 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +22570617 rs10483727 Optic Nerve|Glaucoma - 0.000000 +22561518 rs59374417 Generalized Vitiligo - 0.000000 +21946350 rs11172113 Lung Function|Follow-Up - 0.000000 +21738478 rs11018874 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +21533022 rs1863196 Bone Mineral Density - 0.000000 +19801982 rs7932354 Bone Mineral Density - 0.000000 +22479202 rs6810075 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +20190752 rs5979785 Celiac Disease - 0.000000 +24086445 rs10770359 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000006 +24223155 rs4799838 Torsades De Pointes - 0.000001 +20686608 rs10487687 Pancreatic Cancer - 0.000003 +21399635 rs7774434 Primary Biliary Cirrhosis - 0.000000 +20932310 rs12534221 Τ Protein Levels - 0.000001 +17903307 rs2225434 Pulmonary Function - 0.000010 +21946350 rs12447804 Lung Function|Follow-Up - 0.000000 +25129146 rs1642764 Esophageal Squamous Cell Carcinoma - 0.000000 +23455636 rs5749482 Age-Related Macular Degeneration - 0.000000 +23408906 rs17776563 Thyroid|Thyroid-Related Traits|Differences - 0.000001 +22745674 rs890049 Coronary Artery Stenosis|Coronary Artery - 0.000001 +24489884 rs7578047 Aggression - 0.000004 +22359512 rs9832727 Sphingolipids - 0.000000 +22044751 rs7311875 Chronic Kidney Disease - 0.000010 +24094242 rs10761779 Serum Alkaline Phosphatase Levels - 0.000000 +21935397 rs10047878 Extremely|Overweight|Body Mass Index - 0.000003 +23886662 rs12211410 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +19557197 rs11857639 Distribution|Adiposity|Waist Circumference - 0.000008 +23544013 rs183211 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000003 +19197348 rs2527866 Complex Disease - 0.000003 +21298027 rs10188217 Celiac Disease|Crohn's Disease - 0.000000 +22344219 rs6567160 Body Mass Index - 0.000000 +21297633 rs3197999 Ulcerative Colitis - 0.000000 +23703922 rs2256711 Uric Acid Levels - 0.000004 +21829393 rs2476601 Type 1 Diabetes|Autoantibody - 0.000000 +23382691 rs12718597 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +19651812 rs3847554 Melatonin|Plasma Glucose|Type 2 Diabetes - 0.000000 +22479202 rs1108842 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +22570697 rs2647046 Multiple Sclerosis - 0.000000 +25526632 rs12358475 Breast Cancer - 0.000002 +19247474 rs912969 Smoking Behaviors|Cigarette Smoking - 0.000008 +20011104 rs266717 Adiponectin Levels - 0.000000 +24097068 rs5763662 Lipid Levels - 0.000000 +20729852 rs2274223 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +22001756 rs12263 Dengue Shock Syndrome - 0.000000 +24086445 rs9320486 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000003 +22832961 rs11738335 Alzheimer's Disease - 0.000004 +19557197 rs1555967 Distribution|Adiposity|Waist Circumference - 0.000002 +24094242 rs7214920 Serum Alkaline Phosphatase Levels - 0.000003 +25742292 rs7869190 Parity - 0.000005 +19734902 rs11136000 Alzheimer's Disease - 0.000000 +22558097 rs7586110 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +21935397 rs791903 Extremely|Overweight|Body Mass Index - 0.000005 +23984888 rs11683662 Airway Responsiveness - 0.000009 +22899653 rs10849605 Lung Cancer - 0.000000 +23565137 rs3781834 Late-Onset Alzheimer’s Disease - 0.000000 +19305408 rs16857031 Qt Interval Duration - 0.000000 +23563607 rs2362965 Anthropometric Traits - 0.000000 +22044751 rs2873333 Chronic Kidney Disease - 0.000000 +22511988 rs6742078 Cell-Free Dna|Cardiovascular - 0.000000 +23544013 rs17631303 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000010 +24688116 rs6432832 Longevity|Analysis|Population - 0.000003 +20190752 rs4819388 Celiac Disease - 0.000000 +21408207 rs4956211 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +24390342 rs998731 Rheumatoid Arthritis|Biology - 0.000000 +23408906 rs9915657 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +22368281 rs11053045 LDL-c Response|Lpa - 0.000000 +19734902 rs610932 Alzheimer's Disease - 0.000001 +21060863 rs225717 Cardiovascular Diseases - 0.000000 +24755620 rs405509 Glutamate|Alzheimer's Disease - 0.000000 +21298027 rs16939895 Celiac Disease|Crohn's Disease - 0.000000 +22479202 rs998584 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +22087292 rs10491629 Femoral Neck Bone Geometry - 0.000003 +22832961 rs6856768 Alzheimer's Disease - 0.000005 +22087292 rs6789283 Femoral Neck Bone Geometry - 0.000002 +24483146 rs8024695 Biomarkers - 0.000003 +25188341 rs10948363 Dementias|Alzheimer's Disease - 0.000000 +21909115 rs6015450 Cardiovascular Disease|Blood Pressure - 0.000000 +21829393 rs12708716 Type 1 Diabetes|Autoantibody - 0.000000 +19609347 rs9791170 Hypertension|Blood Pressure - 0.000001 +23936387 rs4911642 Celiac Disease - 0.000005 +22412388 rs7076156 Crohn's Disease - 0.000000 +23382809 rs643410 Schizophrenia - 0.000001 +22693455 rs1470579 Obese|Type 2 Diabetes - 0.000000 +19056611 rs10811661 Type 2 Diabetes - 0.000001 +22993228 rs1250307 Lumbar Disc Degeneration - 0.000004 +21383967 rs653178 Rheumatoid Arthritis|Celiac Disease - 0.000000 +23979607 rs11951568 Borderline Personality - 0.000003 +22544364 rs807624 Wilms Tumor - 0.000000 +22452962 rs13281615 Breast Cancer - 0.000000 +20548946 rs8068952 Optic Disc - 0.000000 +22470424 rs1796991 Amyotrophic Lateral Sclerosis - 0.000008 +25390645 rs4736192 Anxiety - 0.000009 +21980299 rs1990760 Type 1 Diabetes - 0.000000 +23593239 rs1022335 Self-Employment - 0.000003 +22916037 rs10889332 Atherosclerosis - 0.000000 +22470424 rs2703029 Amyotrophic Lateral Sclerosis - 0.000006 +22197932 rs2897442 Atopic Dermatitis - 0.000008 +18776929 rs1371661 Hip Bone Size|Females - 0.000000 +21827660 rs3779505 Increased Disease Risk - 0.000003 +20932310 rs10911736 Τ Protein Levels - 0.000001 +21873549 rs10501320 Type 2 Diabetes|Proinsulin Levels - 0.000000 +22760553 rs4502542 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000002 +22737229 rs3077 Chronic Hepatitis B - 0.000000 +21490707 rs2470893 Caffeine Consumption|Cyp1A2 - 0.000000 +22470424 rs6080544 Amyotrophic Lateral Sclerosis - 0.000003 +22470424 rs2276695 Amyotrophic Lateral Sclerosis - 0.000004 +19430480 rs3024505 Type 1 Diabetes - 0.000000 +24586183 rs2010099 Thyroid Peroxidase Antibodies|Thyroid Disease - 0.000000 +23984888 rs11683662 Airway Responsiveness - 0.000009 +18604267 rs505922 Antigen|Icam-1 - 0.000000 +24348519 rs12964056 Body Mass Index - 0.000001 +24571439 rs980306 Specific Language Impairment|Genotype Effects - 0.000000 +25436638 rs1537424 Serum Thyroid Stimulating Hormone - 0.000000 +21408207 rs10737562 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +25742292 rs1105228 Parity - 0.000001 +19503597 rs1471633 Uric Acid - 0.000000 +23382691 rs404256 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24097068 rs4530754 Lipid Levels - 0.000000 +20190752 rs1893217 Celiac Disease - 0.000000 +22428042 rs7865618 Glaucoma|Optic-Nerve - 0.000000 +24097068 rs1832007 Lipid Levels - 0.000000 +23738518 rs17135159 Reading|Language - 0.000002 +23984888 rs7579157 Airway Responsiveness - 0.000009 +24483146 rs12486452 Biomarkers - 0.000002 +22504420 rs4233949 Bone Mineral Density - 0.000000 +24952745 rs1296720 Qt Interval|Calcium - 0.000000 +22792071 rs2707466 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +22359512 rs1077989 Sphingolipids - 0.000000 +24740154 rs10505477 Prostate Cancer|Early-Onset - 0.000000 +25390645 rs7657455 Anxiety - 0.000003 +22085899 rs11891311 Bilirubin Levels - 0.000000 +24166486 rs6456728 Schizophrenia - 0.000000 +20661308 rs261503 Serum Calcium - 0.000005 +24952745 rs9892651 Qt Interval|Calcium - 0.000000 +24709693 rs4395908 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000001 +24483146 rs7713001 Biomarkers - 0.000001 +24014518 rs11692675 Epilepsy|Febrile Seizures - 0.000000 +21779381 rs1047964 Migraine|Cardiovascular Events|Cardiovascular - 0.000001 +22359512 rs10468017 Sphingolipids - 0.000000 +23958962 rs12956327 Cocaine Dependence - 0.000001 +23886662 rs12153855 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +22685421 rs10779363 Ocular Axial Length|High Myopia - 0.000000 +21297633 rs3194051 Ulcerative Colitis - 0.000000 +21390209 rs252546 Late-Onset Alzheimer's Disease - 0.000008 +21998597 rs6258 Serum Testosterone - 0.000000 +22570697 rs2517646 Multiple Sclerosis - 0.000000 +25742292 rs9325747 Parity - 0.000007 +19197348 rs10431387 Complex Disease - 0.000008 +25140149 rs12261764 Neurodegeneration|Biomarker - 0.000000 +19247474 rs758642 Smoking Behaviors|Cigarette Smoking - 0.000007 +22479191 rs6431731 Kidney|Follow-Up - 0.000000 +20190752 rs2762051 Celiac Disease - 0.000001 +24571439 rs10447141 Specific Language Impairment|Genotype Effects - 0.000000 +19401414 rs7903146 Type 2 Diabetes - 0.000000 +24511991 rs356220 Parkinson’s Disease - 0.000000 +20548946 rs2159128 Optic Disc - 0.000001 +19651812 rs2166706 Melatonin|Plasma Glucose|Type 2 Diabetes - 0.000000 +18840781 rs13330041 Type 1 Diabetes - 0.000000 +22504420 rs4985155 Bone Mineral Density - 0.000000 +24999842 rs1738074 Celiac Disease|Celiac - 0.000000 +22470424 rs11688631 Amyotrophic Lateral Sclerosis - 0.000005 +25064009 rs17649553 Parkinson’s Disease - 0.000000 +24025145 rs857392 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000001 +21804549 rs11078927 Asthma - 0.000000 +23307926 rs4693089 Menopause - 0.000000 +20953189 rs495337 Psoriasis - 0.000001 +19874204 rs8057551 Femoral Neck Bone|Bone Mineral Density - 0.000002 +23326517 rs6721654 Age-Related Macular Degeneration - 0.000006 +25367360 rs11690625 Astigmatism|Refractive Error - 0.000000 +23583980 rs6793295 Pulmonary Fibrosis - 0.000000 +19197348 rs2727789 Complex Disease - 0.000000 +18262040 rs6657811 LDL-cholesterol - 0.000000 +22843504 rs932026 Autism Spectrum - 0.000000 +19116933 rs12046117 Juvenile Idiopathic Arthritis - 0.000001 +23593239 rs6738407 Self-Employment - 0.000000 +22993228 rs17132175 Lumbar Disc Degeneration - 0.000004 +24025145 rs9416306 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000002 +20038947 rs1456139 Major Depression - 0.000008 +23958962 rs2456778 Cocaine Dependence - 0.000000 +22570617 rs284489 Optic Nerve|Glaucoma - 0.000000 +20173747 rs13038095 Lone Atrial Fibrillation - 0.000000 +23738518 rs764255 Reading|Language - 0.000000 +24509480 rs4275659 Type 2 Diabetes - 0.000000 +24133439 rs10778511 Autistic-Like Traits - 0.000004 +22306652 rs11984041 Ischemic Stroke - 0.000000 +19197348 rs780094 Complex Disease - 0.000000 +20729852 rs753724 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +21827660 rs687513 Increased Disease Risk - 0.000003 +22470424 rs1425419 Amyotrophic Lateral Sclerosis - 0.000002 +23936387 rs4842007 Celiac Disease - 0.000009 +19936222 rs7307277 Cholesterol|Plasma Lipoprotein Size - 0.000000 +21552555 rs1861866 Obesity|Obesity-Related Traits - 0.000000 +20932310 rs2986971 Τ Protein Levels - 0.000000 +19430480 rs12251307 Type 1 Diabetes - 0.000000 +21980494 rs16861990 Venous Thrombosis - 0.000000 +19734902 rs1539053 Alzheimer's Disease - 0.000007 +20661308 rs17666460 Serum Calcium - 0.000004 +20932310 rs1021599 Τ Protein Levels - 0.000001 +22504420 rs9921222 Bone Mineral Density - 0.000000 +19798445 rs2351791 Sphingolipid - 0.000000 +23870195 rs10511701 Coronary Artery|Coronary Artery Calcification - 0.000000 +20686608 rs10088262 Pancreatic Cancer - 0.000004 +23509613 rs2357982 Antiphospholipid Antibodies - 0.000003 +19343178 rs2814993 Stature - 0.000000 +18483556 rs6918152 Hair Color|Skin Pigmentation - 0.000002 +19412175 rs6715570 Neuroblastoma - 0.000000 +24379826 rs6786387 Serum Uric Acid Levels - 0.000001 +23563607 rs2531995 Anthropometric Traits - 0.000000 +21297633 rs6871626 Ulcerative Colitis - 0.000000 +23408906 rs6499766 Thyroid|Thyroid-Related Traits|Differences - 0.000001 +18483556 rs6918152 Hair Color|Skin Pigmentation - 0.000000 +19430480 rs7202877 Type 1 Diabetes - 0.000000 +21827660 rs4977756 Increased Disease Risk - 0.000000 +19961619 rs4952590 Respiratory|Atopy - 0.000000 +21750679 rs10488631 Systemic Sclerosis - 0.000000 +21909115 rs11953630 Cardiovascular Disease|Blood Pressure - 0.000000 +20932310 rs1727638 Τ Protein Levels - 0.000001 +22916037 rs4788815 Atherosclerosis - 0.000000 +24516586 rs6820756 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000002 +22561518 rs2456973 Generalized Vitiligo - 0.000000 +19300482 rs8034191 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +19571809 rs6939997 Schizophrenia - 0.000000 +23886662 rs20541 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +23028483 rs1295686 Asthma - 0.000000 +21829377 rs174547 Plasma Phospholipid|Fatty Acids - 0.000000 +23844046 rs1169310 C-Reactive Protein - 0.000000 +21297633 rs5771069 Ulcerative Colitis - 0.000000 +19430480 rs4763879 Type 1 Diabetes - 0.000000 +20932310 rs17189298 Τ Protein Levels - 0.000000 +21946350 rs7068966 Lung Function|Follow-Up - 0.000000 +23979607 rs6882423 Borderline Personality - 0.000002 +20661308 rs261503 Serum Calcium - 0.000004 +20932310 rs7558386 Τ Protein Levels - 0.000001 +19430480 rs10509540 Type 1 Diabetes - 0.000000 +25340798 rs6441977 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +20442857 rs9296510 Phospholipase A - 0.000000 +22291604 rs7329174 Lupus - 0.000002 +23401653 rs4864862 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000003 +18262040 rs2075650 LDL-cholesterol - 0.000000 +23667675 rs1865294 Age Menarche - 0.000008 +24886709 rs78557978 Lipid - 0.000000 +24133439 rs4785276 Autistic-Like Traits - 0.000008 +24068962 rs10491003 Serum Calcium - 0.000000 +19096518 rs730497 Glycated Hemoglobin - 0.000000 +21037568 rs6903608 Hodgkin Lymphoma - 0.000000 +25188341 rs4147929 Dementias|Alzheimer's Disease - 0.000000 +23401653 rs11133315 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000006 +19300500 rs17646919 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000010 +25372704 rs1427407 Sickle Cell Anemia|Fetal Hemoglobin|Sickle Cell - 0.000000 +19798445 rs7157785 Sphingolipid - 0.000000 +22291604 rs2254546 Lupus - 0.000000 +21273288 rs10927698 NT-proBNP - 0.000002 +23636237 rs16993715 Analysis - 0.000008 +24390342 rs793108 Rheumatoid Arthritis|Biology - 0.000000 +20190752 rs13003464 Celiac Disease - 0.000000 +22544364 rs2283873 Wilms Tumor - 0.000000 +21298047 rs11602925 European-Origin|Substance Dependence - 0.000001 +21460841 rs3752246 Late-Onset Alzheimer’s Disease - 0.000000 +18262040 rs646776 LDL-cholesterol - 0.000000 +23844046 rs1183910 C-Reactive Protein - 0.000000 +23667675 rs314270 Age Menarche - 0.000002 +23593239 rs1383043 Self-Employment - 0.000006 +21909108 rs445925 Intima Media Thickness|Plaque - 0.000000 +18262040 rs602633 LDL-cholesterol - 0.000000 +23300701 rs1571218 Colorectal Cancer - 0.000010 +22693459 rs9287638 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +19359265 rs7235755 Telomere Length - 0.000005 +20729852 rs3765524 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +19169254 rs20541 Psoriasis - 0.000000 +20801717 rs2814707 Sporadic Amyotrophic Lateral Sclerosis - 0.000000 +19247474 rs1847461 Smoking Behaviors|Cigarette Smoking - 0.000008 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +25241909 rs2904259 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +19096518 rs13266634 Glycated Hemoglobin - 0.000000 +21738478 rs12988934 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +19503597 rs1183201 Uric Acid - 0.000000 +23358160 rs8057927 Schizophrenia|Cytomegalovirus Infection|Infection Suggests - 0.000001 +23382691 rs1256531 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000004 +24068962 rs7336933 Serum Calcium - 0.000000 +20932310 rs11015839 Τ Protein Levels - 0.000001 +22359512 rs9437689 Sphingolipids - 0.000000 +24511991 rs3129882 Parkinson’s Disease - 0.000000 +25367360 rs10503929 Astigmatism|Refractive Error - 0.000003 +19734902 rs2075650 Alzheimer's Disease - 0.000000 +25367360 rs6997378 Astigmatism|Refractive Error - 0.000005 +24483146 rs9821268 Biomarkers - 0.000002 +23974872 rs1006737 Schizophrenia - 0.000000 +24740154 rs7127900 Prostate Cancer|Early-Onset - 0.000000 +18823527 Rs1911014 Late-Onset Alzheimer's Disease - 0.000004 +22570627 rs7555523 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000006 +20421936 rs17700144 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +21060863 rs2287921 Cardiovascular Diseases - 0.000000 +18483556 rs7495174 Hair Color|Skin Pigmentation - 0.000000 +22570617 rs284495 Optic Nerve|Glaucoma - 0.000000 +20038947 rs389967 Major Depression - 0.000001 +23006423 rs7260598 Lung Cancer|Overall Survival - 0.000006 +21076409 rs7342028 Conduction|Qrs Duration - 0.000000 +24166486 rs3778991 Schizophrenia - 0.000000 +25367360 rs1034071 Astigmatism|Refractive Error - 0.000004 +23382809 rs2945741 Schizophrenia - 0.000004 +25742292 rs28588043 Parity - 0.000004 +18369459 rs2395029 Psoriasis|Psoriatic Arthritis|New Disease - 0.000000 +23667675 rs314272 Age Menarche - 0.000002 +24094242 rs2954021 Serum Alkaline Phosphatase Levels - 0.000000 +19197348 rs7895372 Complex Disease - 0.000006 +19812673 rs952834 Autism - 0.000008 +17684544 rs1992660 Ibd Disease - 0.000000 +23092984 rs3934861 Bipolar Disorder - 0.000004 +23703922 rs714436 Uric Acid Levels - 0.000000 +25436638 rs2046045 Serum Thyroid Stimulating Hormone - 0.000000 +20442857 rs9369631 Phospholipase A - 0.000000 +21076409 rs11153730 Conduction|Qrs Duration - 0.000000 +21983787 rs1485993 Melanoma - 0.000000 +19557197 rs6714750 Distribution|Adiposity|Waist Circumference - 0.000002 +22685421 rs32396 Ocular Axial Length|High Myopia - 0.000008 +23563607 rs13041126 Anthropometric Traits - 0.000000 +18604267 rs687289 Antigen|Icam-1 - 0.000000 +21812969 rs1694037 Parkinson's Disease - 0.000010 +20190752 rs4899260 Celiac Disease - 0.000000 +19734902 rs744373 Alzheimer's Disease - 0.000003 +22368281 rs445925 LDL-c Response|Lpa - 0.000000 +23472185 rs3129871 Multiple Sclerosis|Oligoclonal Band - 0.000000 +25102180 rs7903146 Type 2 Diabetes - 0.000000 +24047820 rs761490 Social Communication - 0.000010 +19801982 rs11995824 Bone Mineral Density - 0.000000 +19734902 rs6859 Alzheimer's Disease - 0.000000 +24513273 rs4148155 Serum Uric Acid - 0.000000 +22792070 rs917726 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23704328 rs11796357 Tooth Eruption|Height - 0.000000 +20038947 rs644695 Major Depression - 0.000000 +22916037 rs12507628 Atherosclerosis - 0.000000 +24625756 rs555044 Intermediate Phenotypes - 0.000000 +23738518 rs4839516 Reading|Language - 0.000000 +22719876 rs2896019 Non-Alcoholic Fatty Liver Disease|Liver Disease - 0.000000 +24166486 rs2039839 Schizophrenia - 0.000000 +20935630 rs10767664 Body Mass Index - 0.000000 +25226531 rs10734234 Suggest|Associated|Linguistic Phenotype - 0.000000 +21383967 rs4626515 Rheumatoid Arthritis|Celiac Disease - 0.000000 +24483146 rs10510741 Biomarkers - 0.000002 +24743840 rs485411 Colorectal Cancer - 0.000000 +23350875 rs1554267 Colorectal Cancer - 0.000003 +20442857 rs1862008 Phospholipase A - 0.000000 +21779181 rs9275390 Systemic Sclerosis - 0.000000 +21738491 rs6507566 Sudden Cardiac Death - 0.000007 +18262040 rs646776 LDL-cholesterol - 0.000000 +23533358 rs2377339 Opiates Addiction|African-Origin - 0.000000 +21408207 rs5754217 Systemic Lupus Erythematosus|Autoantibody - 0.000002 +24086445 rs9488340 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +25367360 rs7823467 Astigmatism|Refractive Error - 0.000000 +23259602 rs9793739 Dental Caries - 0.000001 +23636237 rs1421085 Analysis - 0.000000 +21424380 rs3848562 Breast Cancer - 0.000009 +23326239 rs204999 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +25188341 rs9331896 Dementias|Alzheimer's Disease - 0.000000 +21909115 rs1327235 Cardiovascular Disease|Blood Pressure - 0.000000 +23974872 rs4129585 Schizophrenia - 0.000000 +23900074 rs6772228 Telomere Length|Cancer - 0.000000 +20421936 rs10926984 Onset|Obesity-Related Traits|Body-Weight - 0.000004 +21076409 rs17391905 Conduction|Qrs Duration - 0.000000 +21738491 rs7218928 Sudden Cardiac Death - 0.000004 +22570617 rs2151280 Optic Nerve|Glaucoma - 0.000000 +20661308 rs4695355 Serum Calcium - 0.000006 +23936387 rs10886159 Celiac Disease - 0.000001 +19056611 rs9939609 Type 2 Diabetes - 0.000000 +21804549 rs16929496 Asthma - 0.000000 +24086445 rs11044045 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000003 +23326239 rs3115663 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21408207 rs2187668 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +24571439 rs11158632 Specific Language Impairment|Genotype Effects - 0.000000 +24166486 rs4721190 Schizophrenia - 0.000000 +19609347 rs5743185 Hypertension|Blood Pressure - 0.000000 +21502949 rs1602517 Brain - 0.000006 +24097068 rs499974 Lipid Levels - 0.000000 +21383967 rs1893217 Rheumatoid Arthritis|Celiac Disease - 0.000000 +21408207 rs4963128 Systemic Lupus Erythematosus|Autoantibody - 0.000004 +21242260 rs7758229 Colon Cancer - 0.000000 +23209447 rs5009448 I Antigen|Nasopharyngeal Carcinoma - 0.000000 +23382809 rs6674938 Schizophrenia - 0.000006 +21364930 rs2905 Hiv-1 - 0.000007 +21829393 rs689 Type 1 Diabetes|Autoantibody - 0.000000 +23326239 rs2854275 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23028483 rs2284033 Asthma - 0.000000 +21779381 rs7698623 Migraine|Cardiovascular Events|Cardiovascular - 0.000000 +20686608 rs708224 Pancreatic Cancer - 0.000000 +23593202 rs6578985 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +24564958 rs3761168 Social-Communication|Spectrum Phenotypes - 0.000000 +22570697 rs9261491 Multiple Sclerosis - 0.000000 +20526338 rs1671152 Platelet Aggregation - 0.000000 +21552555 rs10852521 Obesity|Obesity-Related Traits - 0.000000 +22792070 rs2952559 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +20190752 rs10903122 Celiac Disease - 0.000000 +24483146 rs6808448 Biomarkers - 0.000005 +22170493 rs702873 Psoriatic Arthritis - 0.000000 +20041166 rs2395029 Hiv-1 - 0.000000 +24025145 rs1319836 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000001 +22504420 rs6532023 Bone Mineral Density - 0.000000 +20190752 rs653178 Celiac Disease - 0.000000 +19305408 rs12053903 Qt Interval Duration - 0.000000 +20190752 rs11922594 Celiac Disease - 0.000000 +24133439 rs11947645 Autistic-Like Traits - 0.000001 +21408207 rs918959 Systemic Lupus Erythematosus|Autoantibody - 0.000002 +22344219 rs261967 Body Mass Index - 0.000000 +22916037 rs1851024 Atherosclerosis - 0.000000 +24097068 rs731839 Lipid Levels - 0.000000 +21460841 rs1532278 Late-Onset Alzheimer’s Disease - 0.000000 +22170493 rs13017599 Psoriatic Arthritis - 0.000000 +22993228 rs1884158 Lumbar Disc Degeneration - 0.000004 +24755620 rs249166 Glutamate|Alzheimer's Disease - 0.000001 +19454037 rs10499859 Left Ventricular Mass - 0.000003 +18776929 rs10180112 Hip Bone Size|Females - 0.000005 +23382691 rs4132601 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24483146 rs2857891 Biomarkers - 0.000002 +24688116 rs2149954 Longevity|Analysis|Population - 0.000002 +20729852 rs753724 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +20190752 rs13003464 Celiac Disease - 0.000000 +23326239 rs28362680 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +24097068 rs1801689 Lipid Levels - 0.000000 +22359512 rs13106975 Sphingolipids - 0.000000 +22359512 rs12423247 Sphingolipids - 0.000000 +23793025 rs12134493 Migraine - 0.000000 +22792070 rs917727 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23667675 rs314290 Age Menarche - 0.000001 +21873549 rs11603334 Type 2 Diabetes|Proinsulin Levels - 0.000000 +22916037 rs1260326 Atherosclerosis - 0.000000 +21931564 rs2286963 Metabolite Quantitative Trait - 0.000000 +24999842 rs13096142 Celiac Disease|Celiac - 0.000000 +25060954 rs588702 Kinase|Hearing - 0.000000 +20190752 rs2298428 Celiac Disease - 0.000000 +21490949 rs1048886 Type 2 Diabetes|Transferability - 0.000010 +21297633 rs3024505 Ulcerative Colitis - 0.000000 +24740154 rs4665609 Prostate Cancer|Early-Onset - 0.000004 +21156761 rs4305317 Rheumatoid Arthritis - 0.000002 +22832960 rs17680945 Temperament Character Inventory - 0.000002 +23770605 rs3770745 Chronic Lymphocytic Leukemia - 0.000000 +24390342 rs73013527 Rheumatoid Arthritis|Biology - 0.000000 +22675492 rs12059860 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000008 +22832960 rs10172965 Temperament Character Inventory - 0.000006 +24086445 rs9320482 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +24025145 rs1530357 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000004 +19915575 rs17563986 Parkinson’s Disease - 0.000000 +19801982 rs1471403 Bone Mineral Density - 0.000000 +20190752 rs3748816 Celiac Disease - 0.000000 +23667675 rs314276 Age Menarche - 0.000002 +23886662 rs2155219 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +21827660 rs1920116 Increased Disease Risk - 0.000001 +24586186 rs37370 Metabolic Traits|Metabolite-Disease - 0.000000 +22423221 rs8109288 Platelet Count|Mean Platelet Volume - 0.000000 +25352737 rs11835432 Cataract - 0.000008 +24483146 rs6808448 Biomarkers - 0.000002 +24223155 rs1789532 Torsades De Pointes - 0.000008 +23738518 rs2822609 Reading|Language - 0.000000 +21502949 rs5979778 Brain - 0.000003 +23703922 rs4643800 Uric Acid Levels - 0.000000 +20932310 rs11206801 Τ Protein Levels - 0.000000 +22570627 rs11656696 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000000 +21552555 rs9935401 Obesity|Obesity-Related Traits - 0.000000 +20548946 rs17146964 Optic Disc - 0.000000 +21223598 rs10263935 Aortic Root - 0.000000 +22001756 rs37655 Dengue Shock Syndrome - 0.000000 +23544013 rs6682208 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +24097068 rs9376090 Lipid Levels - 0.000000 +22267201 rs3736830 Age Menopause - 0.000000 +22423221 rs8109288 Platelet Count|Mean Platelet Volume - 0.000000 +21909115 rs7129220 Cardiovascular Disease|Blood Pressure - 0.000000 +22170493 rs13017599 Psoriatic Arthritis - 0.000000 +22832960 rs6754640 Temperament Character Inventory - 0.000001 +22693455 rs3916765 Obese|Type 2 Diabetes - 0.000000 +21685912 rs1411478 Progressive Supranuclear Palsy - 0.000000 +23326517 rs1061170 Age-Related Macular Degeneration - 0.000000 +19343178 rs11809207 Stature - 0.000000 +24483146 rs9846155 Biomarkers - 0.000002 +24999842 rs1997179 Celiac Disease|Celiac - 0.000000 +18262040 rs660240 LDL-cholesterol - 0.000000 +19668339 rs10781380 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000001 +20072603 rs6039266 Osteoporosis - 0.000003 +22911880 rs4853643 Behaviors|Personality Traits|Eating - 0.000010 +21980494 rs657152 Venous Thrombosis - 0.000000 +21423719 rs4240624 Metabolic Traits|Nonalcoholic Fatty Liver Disease - 0.000000 +17903302 rs1721359 Arterial Stiffness|Blood Pressure - 0.000010 +21386085 rs2075290 Metabolic Syndrome - 0.000010 +23974872 rs7940866 Schizophrenia - 0.000000 +24025145 rs857373 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000001 +23817569 rs17388568 Allergy - 0.000000 +24166486 rs4721295 Schizophrenia - 0.000000 +23382691 rs4878639 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +19300500 rs1980057 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +21490707 rs12148488 Caffeine Consumption|Cyp1A2 - 0.000002 +18464913 rs6761 Protein Quantitative Trait|Genome|Association - 0.000000 +24097068 rs2606736 Lipid Levels - 0.000000 +21383967 rs11203203 Rheumatoid Arthritis|Celiac Disease - 0.000000 +24964207 rs17173608 Suicidal Ideation|Attempts Suicidal|Suicide Attempts - 0.000000 +21386085 rs9939224 Metabolic Syndrome - 0.000003 +18846228 rs2040704 Serum IgE Levels - 0.000000 +21829393 rs11755527 Type 1 Diabetes|Autoantibody - 0.000000 +21533024 rs11575074 Icam-1 - 0.000000 +23401653 rs6554163 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000009 +19197348 rs2722750 Complex Disease - 0.000004 +21998595 rs994014 Height - 0.000000 +21909115 rs12940887 Cardiovascular Disease|Blood Pressure - 0.000000 +23326239 rs28362683 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21876539 rs9526558 Cyp1A2 - 0.000001 +19668339 rs9301535 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000008 +23459936 rs7762544 Chronic Periodontitis - 0.000000 +24571439 rs4280164 Specific Language Impairment|Genotype Effects - 0.000000 +24166486 rs13194781 Schizophrenia - 0.000000 +24097068 rs702485 Lipid Levels - 0.000000 +20421936 rs13278851 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +22368281 rs6857 LDL-c Response|Lpa - 0.000002 +22561518 rs1129038 Generalized Vitiligo - 0.000000 +21665990 rs9332739 Age-Related Macular Degeneration - 0.000000 +19197348 rs2156552 Complex Disease - 0.000000 +20011104 rs1648707 Adiponectin Levels - 0.000000 +21876539 rs16868941 Cyp1A2 - 0.000000 +24740154 rs1880408 Prostate Cancer|Early-Onset - 0.000007 +21935397 rs17504169 Extremely|Overweight|Body Mass Index - 0.000003 +24483146 rs9878275 Biomarkers - 0.000001 +22916037 rs102275 Atherosclerosis - 0.000000 +21076409 rs11848785 Conduction|Qrs Duration - 0.000000 +23259602 rs788919 Dental Caries - 0.000010 +25064009 rs34311866 Parkinson’s Disease - 0.000000 +22763110 rs10492367 Osteoarthritis - 0.000000 +21935397 rs6571507 Extremely|Overweight|Body Mass Index - 0.000008 +23936387 rs195656 Celiac Disease - 0.000007 +22843504 rs6646569 Autism Spectrum - 0.000001 +24280982 rs4356203 Schizophrenia|Bipolar Disorder|Disorder - 0.000000 +22570697 rs4959093 Multiple Sclerosis - 0.000000 +21490949 rs9295474 Type 2 Diabetes|Transferability - 0.000009 +24097068 rs10904908 Lipid Levels - 0.000000 +18776929 rs4850820 Hip Bone Size|Females - 0.000005 +24483146 rs12188464 Biomarkers - 0.000002 +23667675 rs2076751 Age Menarche - 0.000007 +22291604 rs6590330 Lupus - 0.000000 +18483556 rs9806558 Hair Color|Skin Pigmentation - 0.000003 +21876539 rs2472297 Cyp1A2 - 0.000000 +22452962 rs3817198 Breast Cancer - 0.000000 +24348519 rs8050136 Body Mass Index - 0.000000 +19197348 rs7553007 Complex Disease - 0.000000 +24755620 rs2927438 Glutamate|Alzheimer's Disease - 0.000000 +23704328 rs4937076 Tooth Eruption|Height - 0.000000 +20953189 rs12924903 Psoriasis - 0.000000 +20173747 rs6843082 Lone Atrial Fibrillation - 0.000000 +20190752 rs13098911 Celiac Disease - 0.000010 +21658281 rs16866933 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +23408906 rs6499766 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24097068 rs2287623 Lipid Levels - 0.000000 +23936387 rs4930144 Celiac Disease - 0.000007 +25378659 rs2100944 Long-Chain Saturated Fatty Acids - 0.000000 +20038947 rs10900126 Major Depression - 0.000002 +24376798 rs1130380 Chronic Hepatitis C - 0.000003 +24755620 rs13178362 Glutamate|Alzheimer's Disease - 0.000001 +21408207 rs12629106 Systemic Lupus Erythematosus|Autoantibody - 0.000004 +22760553 rs13423450 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000001 +23667675 rs314263 Age Menarche - 0.000001 +23209447 rs2267633 I Antigen|Nasopharyngeal Carcinoma - 0.000000 +25241909 rs117455145 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +23738518 rs2192161 Reading|Language - 0.000000 +24094242 rs7173947 Serum Alkaline Phosphatase Levels - 0.000000 +25226531 rs1654584 Suggest|Associated|Linguistic Phenotype - 0.000000 +25628645 rs10771093 Homoharringtonine - 0.000003 +24489884 rs2844775 Aggression - 0.000001 +24390342 rs2234067 Rheumatoid Arthritis|Biology - 0.000000 +20190752 rs11221332 Celiac Disease - 0.000000 +22438815 rs356219 Parkinson's Disease - 0.000000 +19300500 rs6471895 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000001 +19772629 rs9904572 Parkinson Disease|Onset - 0.000001 +23703922 rs6845554 Uric Acid Levels - 0.000000 +25064009 rs117896735 Parkinson’s Disease - 0.000000 +23583980 rs1278769 Pulmonary Fibrosis - 0.000000 +22267201 rs1046089 Age Menopause - 0.000000 +21931564 rs603424 Metabolite Quantitative Trait - 0.000000 +22044751 rs13414916 Chronic Kidney Disease - 0.000005 +22570627 rs11656696 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000000 +22452962 rs10510102 Breast Cancer - 0.000002 +23092984 rs2333194 Bipolar Disorder - 0.000001 +22504420 rs7953528 Bone Mineral Density - 0.000000 +25162662 rs1225101 Serum Ferritin - 0.000000 +24390342 rs227163 Rheumatoid Arthritis|Biology - 0.000000 +21943158 rs10468017 Cardiovascular-Related Traits - 0.000000 +23382691 rs10806425 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +19668339 rs11525066 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000003 +21399635 rs3745516 Primary Biliary Cirrhosis - 0.000000 +18840781 rs4839335 Type 1 Diabetes - 0.000000 +23979607 rs73125991 Borderline Personality - 0.000001 +23382691 rs12342831 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +20932310 rs5998432 Τ Protein Levels - 0.000001 +22570697 rs3905495 Multiple Sclerosis - 0.000000 +23844046 rs7310409 C-Reactive Protein - 0.000000 +24204295 rs10995245 Narcolepsy|Influenza|Changes - 0.000000 +25064009 rs356182 Parkinson’s Disease - 0.000000 +24755620 rs1871047 Glutamate|Alzheimer's Disease - 0.000000 +19343178 rs4911494 Stature - 0.000000 +24097068 rs13326165 Lipid Levels - 0.000000 +23817569 rs7720838 Allergy - 0.000000 +19801982 rs599083 Bone Mineral Density - 0.000000 +23984888 rs296282 Airway Responsiveness - 0.000008 +23382809 rs2275552 Schizophrenia - 0.000006 +24836286 rs174537 Colorectal Cancer - 0.000000 +19247474 rs4722613 Smoking Behaviors|Cigarette Smoking - 0.000009 +22238593 rs6930576 Type 2 Diabetes - 0.000001 +21998597 rs6258 Serum Testosterone - 0.000000 +24347629 rs8094794 Periodontal - 0.000006 +20686608 rs7750826 Pancreatic Cancer - 0.000003 +23958962 rs59955083 Cocaine Dependence - 0.000001 +22570617 rs573687 Optic Nerve|Glaucoma - 0.000000 +20729852 rs11187842 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +23326239 rs9268832 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23056639 rs2165179 Lectin - 0.000001 +23028483 rs1588265 Asthma - 0.000000 +19096518 rs560887 Glycated Hemoglobin - 0.000000 +23817569 rs1998359 Allergy - 0.000000 +21738491 rs4665058 Sudden Cardiac Death - 0.000000 +24489884 rs6834498 Aggression - 0.000005 +21437268 rs2299851 Cancers|Conducted|Upper Aerodigestive Tract - 0.000006 +20935630 rs1514175 Body Mass Index - 0.000000 +18262040 rs4803750 LDL-cholesterol - 0.000000 +17903293 rs2808629 Biomarker Traits - 0.000000 +20195514 rs9674544 Primary Tooth Development - 0.000000 +21771975 rs8047711 Adiponectin|Quantitative Trait|Cardiometabolic Outcomes - 0.000000 +22693455 rs4402960 Obese|Type 2 Diabetes - 0.000000 +23563607 rs7989336 Anthropometric Traits - 0.000000 +23974872 rs12991836 Schizophrenia - 0.000000 +21738478 rs445 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +23326517 rs380390 Age-Related Macular Degeneration - 0.000000 +22504420 rs10835187 Bone Mineral Density - 0.000000 +20858683 rs552976 Hemoglobin A - 0.000000 +19401414 rs2237892 Type 2 Diabetes - 0.000000 +24390342 rs2105325 Rheumatoid Arthritis|Biology - 0.000000 +24952745 rs16936870 Qt Interval|Calcium - 0.000000 +23001564 rs9419958 Homeostasis - 0.000000 +24709693 rs11225055 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000001 +20935630 rs29941 Body Mass Index - 0.000000 +21983787 rs258322 Melanoma - 0.000000 +24952745 rs7765828 Qt Interval|Calcium - 0.000000 +20661308 rs12416668 Serum Calcium - 0.000008 +22484627 rs9299 Childhood Obesity - 0.000000 +22087292 rs3849874 Femoral Neck Bone Geometry - 0.000001 +24143190 rs12922061 Breast Cancer|Breast - 0.000005 +20932310 rs2074955 Τ Protein Levels - 0.000000 +21502949 rs5979778 Brain - 0.000006 +21460840 rs3764650 Alzheimer’s Disease - 0.000000 +21935397 rs1424233 Extremely|Overweight|Body Mass Index - 0.000000 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +21502949 rs163035 Brain - 0.000000 +19343178 rs7815788 Stature - 0.000005 +21998595 rs1787200 Height - 0.000000 +19609347 rs12279202 Hypertension|Blood Pressure - 0.000000 +20700443 rs2592394 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +24755620 rs8106922 Glutamate|Alzheimer's Disease - 0.000000 +23382691 rs2413583 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +23974872 rs11532322 Schizophrenia - 0.000000 +22412388 rs9292777 Crohn's Disease - 0.000000 +24014518 rs7587026 Epilepsy|Febrile Seizures - 0.000000 +22504420 rs1053051 Bone Mineral Density - 0.000000 +18483556 rs11855019 Hair Color|Skin Pigmentation - 0.000000 +21829377 rs3798713 Plasma Phospholipid|Fatty Acids - 0.000000 +24483146 rs13171512 Biomarkers - 0.000001 +22829776 rs1573036 Globulin|Hormone|Steroid Hormone - 0.000000 +23563607 rs4735692 Anthropometric Traits - 0.000000 +22993228 rs7896691 Lumbar Disc Degeneration - 0.000002 +24483146 rs7174876 Biomarkers - 0.000000 +23041239 rs556621 Ischaemic Stroke - 0.000000 +20081858 rs4607517 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +17903303 rs6832344 Atherosclerosis - 0.000010 +21386085 rs13702 Metabolic Syndrome - 0.000000 +23974872 rs17504622 Schizophrenia - 0.000000 +23636237 rs7625360 Analysis - 0.000000 +22916037 rs673548 Atherosclerosis - 0.000000 +21779176 rs2300478 Restless Legs Syndrome - 0.000000 +23886662 rs13199524 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +19801982 rs228769 Bone Mineral Density - 0.000000 +21297633 rs7608910 Ulcerative Colitis - 0.000000 +24836286 rs1800469 Colorectal Cancer - 0.000000 +23056639 rs930956 Lectin - 0.000008 +22993228 rs9488238 Lumbar Disc Degeneration - 0.000005 +22993228 rs926849 Lumbar Disc Degeneration - 0.000000 +22763110 rs9350591 Osteoarthritis - 0.000000 +21533175 rs2185570 Dehydroepiandrosterone Sulphate - 0.000000 +22291604 rs548234 Lupus - 0.000002 +19714205 rs6063725 Asthma - 0.000004 +22685421 rs4373767 Ocular Axial Length|High Myopia - 0.000000 +22693455 rs10811661 Obese|Type 2 Diabetes - 0.000007 +24166486 rs4721184 Schizophrenia - 0.000000 +24513273 rs729761 Serum Uric Acid - 0.000000 +23263487 rs10774214 Colorectal Cancer - 0.000000 +25060954 rs6472312 Kinase|Hearing - 0.000001 +22470424 rs7912496 Amyotrophic Lateral Sclerosis - 0.000008 +21935397 rs543874 Extremely|Overweight|Body Mass Index - 0.000000 +19169254 rs17728338 Psoriasis - 0.000000 +18262040 rs488507 LDL-cholesterol - 0.000000 +24097068 rs10490626 Lipid Levels - 0.000000 +24086445 rs11044106 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000009 +19300500 rs1828591 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +23028483 rs3939286 Asthma - 0.000000 +23703922 rs12498956 Uric Acid Levels - 0.000000 +24886709 rs148533712 Lipid - 0.000000 +19609347 rs7902529 Hypertension|Blood Pressure - 0.000006 +20932310 rs1997111 Τ Protein Levels - 0.000000 +23989986 rs10773046 Hip|Osteoarthritis - 0.000001 +21665990 rs1410996 Age-Related Macular Degeneration - 0.000000 +19081515 rs6794719 Creutzfeldt–Jakob Disease - 0.000000 +23844046 rs2794520 C-Reactive Protein - 0.000000 +21448238 rs4939879 Migraine - 0.000002 +21408207 rs6695567 Systemic Lupus Erythematosus|Autoantibody - 0.000004 +19300500 rs994960 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000007 +22961001 rs9257809 Barrett’s Esophagus - 0.000000 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +25064009 rs115185635 Parkinson’s Disease - 0.000000 +22479202 rs2791553 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +23565137 rs4598682 Late-Onset Alzheimer’s Disease - 0.000009 +21980299 rs2903692 Type 1 Diabetes - 0.000000 +20081858 rs35767 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +24743840 rs1269486 Colorectal Cancer - 0.000000 +24513273 rs17786744 Serum Uric Acid - 0.000000 +19734902 rs9446432 Alzheimer's Disease - 0.000003 +21364930 rs12909130 Hiv-1 - 0.000008 +23092984 rs1775715 Bipolar Disorder - 0.000005 +22916037 rs12051548 Atherosclerosis - 0.000000 +24513273 rs7224610 Serum Uric Acid - 0.000000 +23104006 rs1537377 Endometriosis - 0.000000 +23455636 rs6795735 Age-Related Macular Degeneration - 0.000000 +21297633 rs2310173 Ulcerative Colitis - 0.000000 +25367360 rs10086929 Astigmatism|Refractive Error - 0.000001 +25436638 rs4804416 Serum Thyroid Stimulating Hormone - 0.000000 +19305408 rs2074238 Qt Interval Duration - 0.000000 +19503597 rs780094 Uric Acid - 0.000000 +20066028 rs1532624 Serum Cholesterol Levels - 0.000001 +21935397 rs12130212 Extremely|Overweight|Body Mass Index - 0.000002 +19798445 rs7258249 Sphingolipid - 0.000000 +21399635 rs10931468 Primary Biliary Cirrhosis - 0.000000 +23958962 rs150954431 Cocaine Dependence - 0.000000 +23900074 rs7726159 Telomere Length|Cancer - 0.000000 +19197348 rs10498712 Complex Disease - 0.000009 +23350875 rs3104964 Colorectal Cancer - 0.000005 +25526632 rs2921923 Breast Cancer - 0.000005 +23326239 rs9268832 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +20686608 rs6464375 Pancreatic Cancer - 0.000000 +21552555 rs16867321 Obesity|Obesity-Related Traits - 0.000002 +23300701 rs1394349 Colorectal Cancer - 0.000001 +25064009 rs11060180 Parkinson’s Disease - 0.000000 +22001756 rs22742 Dengue Shock Syndrome - 0.000000 +23104006 rs7739264 Endometriosis - 0.000000 +21909115 rs11191548 Cardiovascular Disease|Blood Pressure - 0.000000 +20548946 rs1063192 Optic Disc - 0.000000 +24086445 rs10770359 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000009 +23358160 rs12922317 Schizophrenia|Cytomegalovirus Infection|Infection Suggests - 0.000001 +21909115 rs4373814 Cardiovascular Disease|Blood Pressure - 0.000000 +21379329 rs7007878 Late-Onset Alzheimer's Disease - 0.000007 +24625756 rs12282107 Intermediate Phenotypes - 0.000000 +19503597 rs2231142 Uric Acid - 0.000000 +23455636 rs8017304 Age-Related Macular Degeneration - 0.000000 +23326239 rs2233956 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21998595 rs11658329 Height - 0.000000 +23667675 rs6995390 Age Menarche - 0.000005 +24097068 rs4942486 Lipid Levels - 0.000000 +19197348 rs17711796 Complex Disease - 0.000007 +19448621 rs1551562 Age Menarche|Menopause - 0.000000 +20686608 rs6736997 Pancreatic Cancer - 0.000006 +20442857 rs10948301 Phospholipase A - 0.000000 +23535730 rs1243180 Ovarian Cancer - 0.000000 +22438815 rs7077361 Parkinson's Disease - 0.000000 +21297633 rs1801274 Ulcerative Colitis - 0.000000 +22504420 rs11755164 Bone Mineral Density - 0.000000 +23738518 rs7187223 Reading|Language - 0.000000 +22504420 rs1878526 Bone Mineral Density - 0.000000 +20011104 rs1426810 Adiponectin Levels - 0.000000 +20081858 rs340874 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +19571809 rs13194053 Schizophrenia - 0.000000 +21044948 rs393152 Parkinson's Disease - 0.000000 +20858683 rs6474359 Hemoglobin A - 0.000000 +22693455 rs7754840 Obese|Type 2 Diabetes - 0.000000 +19503088 rs2736340 Rheumatoid Arthritis - 0.000001 +22238593 rs17103805 Type 2 Diabetes - 0.000003 +23259602 rs505982 Dental Caries - 0.000009 +22470424 rs7764218 Amyotrophic Lateral Sclerosis - 0.000009 +23874384 rs12551906 Behavior - 0.000003 +19936222 rs4731702 Cholesterol|Plasma Lipoprotein Size - 0.000000 +20190752 rs3816281 Celiac Disease - 0.000000 +24166486 rs7787274 Schizophrenia - 0.000000 +21909110 rs11222084 Mean Arterial Pressure|Pulse Pressure - 0.000000 +23259602 rs7143579 Dental Caries - 0.000001 +25350695 rs646776 Ldl Cholesterol Response|Response Statins - 0.000001 +19401414 rs1111875 Type 2 Diabetes - 0.000000 +23041239 rs4875812 Ischaemic Stroke - 0.000001 +18604267 rs2116941 Antigen|Icam-1 - 0.000000 +21364930 rs2304418 Hiv-1 - 0.000002 +18483556 rs2353033 Hair Color|Skin Pigmentation - 0.000000 +23593202 rs8113142 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +24651765 rs1047891 Homocysteine|Methionine|Metabolism - 0.000000 +18840781 rs7529353 Type 1 Diabetes - 0.000000 +24094242 rs8176720 Serum Alkaline Phosphatase Levels - 0.000000 +25390645 rs4692589 Anxiety - 0.000001 +18483556 rs11636232 Hair Color|Skin Pigmentation - 0.000000 +23936387 rs2605393 Celiac Disease - 0.000006 +25340798 rs6762266 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +21408207 rs2301271 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +24094242 rs2242420 Serum Alkaline Phosphatase Levels - 0.000000 +21552555 rs8044769 Obesity|Obesity-Related Traits - 0.000000 +17903305 rs1978503 Prostate Cancer|Breast - 0.000001 +22344219 rs4776970 Body Mass Index - 0.000000 +24513273 rs11722228 Serum Uric Acid - 0.000000 +24465473 rs17653722 Telomere Length - 0.000001 +19343178 rs6854334 Stature - 0.000000 +24516586 rs6849717 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000009 +21983787 rs12203592 Melanoma - 0.000000 +24097068 rs4253772 Lipid Levels - 0.000000 +19197348 rs4420638 Complex Disease - 0.000002 +25390645 rs2170820 Anxiety - 0.000005 +23326517 rs2230199 Age-Related Macular Degeneration - 0.000000 +23509613 rs6889746 Antiphospholipid Antibodies - 0.000006 +21298027 rs6708413 Celiac Disease|Crohn's Disease - 0.000000 +22737229 rs9277542 Chronic Hepatitis B - 0.000000 +23817569 rs10189629 Allergy - 0.000000 +22238593 rs3775045 Type 2 Diabetes - 0.000002 +19812673 rs10513025 Autism - 0.000000 +25310577 rs1110701 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +21980494 rs2066865 Venous Thrombosis - 0.000000 +23776548 rs2194025 Arterioles - 0.000000 +23544013 rs2532348 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +22693459 rs10502861 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +22561518 rs79008 Generalized Vitiligo - 0.000000 +21946350 rs12477314 Lung Function|Follow-Up - 0.000000 +19430480 rs2290400 Type 1 Diabetes - 0.000000 +24509480 rs702634 Type 2 Diabetes - 0.000000 +23563607 rs17381664 Anthropometric Traits - 0.000000 +24068962 rs1801725 Serum Calcium - 0.000000 +24348519 rs9939609 Body Mass Index - 0.000000 +21437268 rs2517452 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +21998597 rs12150660 Serum Testosterone - 0.000000 +22570697 rs1736916 Multiple Sclerosis - 0.000000 +23459936 rs12260727 Chronic Periodontitis - 0.000001 +21685912 rs7571971 Progressive Supranuclear Palsy - 0.000000 +19430480 rs7221109 Type 1 Diabetes - 0.000000 +24204295 rs1154155 Narcolepsy|Influenza|Changes - 0.000000 +23382691 rs17348299 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24086445 rs9320481 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +23966204 rs2597972 Bitter Taste|Bitter Taste Perception - 0.000001 +24097068 rs11603023 Lipid Levels - 0.000000 +22291604 rs2230926 Lupus - 0.000000 +19343178 rs710841 Stature - 0.000000 +22470424 rs6075164 Amyotrophic Lateral Sclerosis - 0.000003 +23667675 rs314291 Age Menarche - 0.000001 +20418485 rs3829251 Vitamin D Levels - 0.000001 +23563607 rs6662509 Anthropometric Traits - 0.000000 +21037568 rs501764 Hodgkin Lymphoma - 0.000000 +22479202 rs2925979 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +22438815 rs1491942 Parkinson's Disease - 0.000000 +21490707 rs4410790 Caffeine Consumption|Cyp1A2 - 0.000000 +19343178 rs10472828 Stature - 0.000000 +23936387 rs571879 Celiac Disease - 0.000000 +20932310 rs893769 Τ Protein Levels - 0.000001 +20442857 rs4420638 Phospholipase A - 0.000000 +22916037 rs712964 Atherosclerosis - 0.000000 +18840781 rs1983853 Type 1 Diabetes - 0.000002 +21909115 rs3774372 Cardiovascular Disease|Blood Pressure - 0.000000 +19801982 rs7781370 Bone Mineral Density - 0.000000 +21399635 rs17129789 Primary Biliary Cirrhosis - 0.000000 +25060954 rs681524 Kinase|Hearing - 0.000000 +21980299 rs10758593 Type 1 Diabetes - 0.000000 +23028483 rs9273349 Asthma - 0.000000 +18464913 rs12093699 Protein Quantitative Trait|Genome|Association - 0.000006 +23028483 rs744910 Asthma - 0.000000 +21779176 rs1975197 Restless Legs Syndrome - 0.000000 +22452962 rs3734805 Breast Cancer - 0.000000 +22889924 rs13063502 Tourette Syndrome - 0.000009 +21297633 rs10758669 Ulcerative Colitis - 0.000000 +23459936 rs7762544 Chronic Periodontitis - 0.000000 +20421936 rs12145833 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +22087292 rs11859916 Femoral Neck Bone Geometry - 0.000003 +21946350 rs993925 Lung Function|Follow-Up - 0.000000 +21037568 rs485411 Hodgkin Lymphoma - 0.000000 +23666240 rs3805663 Testicular Cancer - 0.000000 +25241909 rs754388 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000002 +24121790 rs3111601 Barrett’s Esophagus|Esophageal Adenocarcinoma - 0.000003 +24709693 rs60624478 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000006 +24483146 rs11215416 Biomarkers - 0.000002 +24755620 rs10422797 Glutamate|Alzheimer's Disease - 0.000001 +19300499 rs9923231 Cyp2C9|Warfarin - 0.000000 +23386860 rs12378245 Iron Intake|Type 2 Diabetes - 0.000002 +21804549 rs9891949 Asthma - 0.000001 +22291604 rs4728142 Lupus - 0.000000 +24133439 rs10444533 Autistic-Like Traits - 0.000004 +25102180 rs343092 Type 2 Diabetes - 0.000000 +23793025 rs10915437 Migraine - 0.000000 +18604267 rs7256672 Antigen|Icam-1 - 0.000000 +21448238 rs4861775 Migraine - 0.000003 +23844046 rs2075650 C-Reactive Protein - 0.000000 +22829776 rs3779195 Globulin|Hormone|Steroid Hormone - 0.000000 +21738491 rs12517578 Sudden Cardiac Death - 0.000004 +17684544 rs2066845 Ibd Disease - 0.000000 +19305408 rs37062 Qt Interval Duration - 0.000000 +20190752 rs5979785 Celiac Disease - 0.000000 +21037568 rs1432295 Hodgkin Lymphoma - 0.000000 +23382691 rs10276619 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000003 +21658281 rs16942421 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +22087292 rs4804662 Femoral Neck Bone Geometry - 0.000004 +22719876 rs926633 Non-Alcoholic Fatty Liver Disease|Liver Disease - 0.000000 +18483556 rs12203592 Hair Color|Skin Pigmentation - 0.000000 +22087292 rs681900 Femoral Neck Bone Geometry - 0.000008 +22843504 rs4675502 Autism Spectrum - 0.000000 +23349640 rs4530903 Malignancies - 0.000000 +23667675 rs395962 Age Menarche - 0.000001 +20932310 rs2899472 Τ Protein Levels - 0.000000 +24483146 rs2290344 Biomarkers - 0.000000 +21804549 rs335016 Asthma - 0.000000 +18483556 rs7183877 Hair Color|Skin Pigmentation - 0.000000 +25742292 rs7136873 Parity - 0.000007 +24740154 rs7013418 Prostate Cancer|Early-Onset - 0.000004 +18846228 rs12368672 Serum IgE Levels - 0.000002 +22087292 rs681900 Femoral Neck Bone Geometry - 0.000008 +23593239 rs10753804 Self-Employment - 0.000004 +20174558 rs4845624 Type 2 Diabetes - 0.000006 +23028341 rs3753394 Complement C3 - 0.000000 +23636237 rs12356048 Analysis - 0.000002 +23028341 rs3745567 Complement C3 - 0.000000 +20190752 rs4675374 Celiac Disease - 0.000000 +20081858 rs7034200 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +22843504 rs2836439 Autism Spectrum - 0.000001 +24952745 rs1052536 Qt Interval|Calcium - 0.000000 +22829776 rs780093 Globulin|Hormone|Steroid Hormone - 0.000000 +23307926 rs11668344 Menopause - 0.000000 +20011104 rs4311394 Adiponectin Levels - 0.000008 +22359512 rs17101394 Sphingolipids - 0.000000 +20661308 rs12325114 Serum Calcium - 0.000005 +19557197 rs10146997 Distribution|Adiposity|Waist Circumference - 0.000000 +23532257 rs10229583 Type 2 Diabetes - 0.000010 +23974872 rs17691888 Schizophrenia - 0.000000 +22359512 rs2304130 Sphingolipids - 0.000000 +20081858 rs11071657 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +20729852 rs11187842 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +23844046 rs11265260 C-Reactive Protein - 0.000000 +25241909 rs8034191 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000001 +23326517 rs380390 Age-Related Macular Degeneration - 0.000000 +24886709 rs964184 Lipid - 0.000000 +23056639 rs9512645 Lectin - 0.000003 +24908248 rs1920116 Telomere Length|Glioma - 0.000001 +21424380 rs10411161 Breast Cancer - 0.000007 +23408906 rs657152 Thyroid|Thyroid-Related Traits|Differences - 0.000001 +24952745 rs728926 Qt Interval|Calcium - 0.000000 +22205951 rs1039002 Bipolar Disorder - 0.000000 +19772629 rs1420143 Parkinson Disease|Onset - 0.000004 +24097068 rs6831256 Lipid Levels - 0.000000 +24586183 rs1230666 Thyroid Peroxidase Antibodies|Thyroid Disease - 0.000000 +23408906 rs10799824 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +23350875 rs12548021 Colorectal Cancer - 0.000003 +23593202 rs6975557 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +21223598 rs801193 Aortic Root - 0.000004 +22693455 rs6567160 Obese|Type 2 Diabetes - 0.000000 +24483146 rs9816196 Biomarkers - 0.000001 +22792070 rs3801387 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +22792070 rs2908007 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +21297633 rs6584283 Ulcerative Colitis - 0.000000 +22044751 rs9375674 Chronic Kidney Disease - 0.000004 +25352737 rs8044853 Cataract - 0.000002 +21665990 rs1061170 Age-Related Macular Degeneration - 0.000000 +23326239 rs3130070 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21804549 rs11214966 Asthma - 0.000001 +24940741 rs9366816 Infection - 0.000001 +21552555 rs9930333 Obesity|Obesity-Related Traits - 0.000000 +22570617 rs1521774 Optic Nerve|Glaucoma - 0.000000 +21437268 rs4799863 Cancers|Conducted|Upper Aerodigestive Tract - 0.000005 +23646285 rs2134333 Hypersomnia - 0.000002 +21829377 rs174547 Plasma Phospholipid|Fatty Acids - 0.000000 +22359512 rs12051548 Sphingolipids - 0.000000 +20932310 rs2899472 Τ Protein Levels - 0.000000 +22561518 rs1990760 Generalized Vitiligo - 0.000000 +21383967 rs1772408 Rheumatoid Arthritis|Celiac Disease - 0.000001 +23041239 rs6763538 Ischaemic Stroke - 0.000000 +21076409 rs2242285 Conduction|Qrs Duration - 0.000000 +22359512 rs603424 Sphingolipids - 0.000000 +22470424 rs7757630 Amyotrophic Lateral Sclerosis - 0.000008 +21943158 rs7671266 Cardiovascular-Related Traits - 0.000000 +23349640 rs2621416 Malignancies - 0.000004 +19503597 rs12129861 Uric Acid - 0.000000 +18483556 rs8028689 Hair Color|Skin Pigmentation - 0.000000 +22792071 rs10274324 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +20935630 rs2867125 Body Mass Index - 0.000000 +24836286 rs647161 Colorectal Cancer - 0.000000 +24836286 rs704017 Colorectal Cancer - 0.000000 +22760553 rs4398173 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000001 +23583980 rs2609255 Pulmonary Fibrosis - 0.000000 +18840781 rs1230661 Type 1 Diabetes - 0.000000 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +23041239 rs2238151 Ischaemic Stroke - 0.000001 +23509613 rs10492418 Antiphospholipid Antibodies - 0.000002 +24025145 rs3820706 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000000 +24347629 rs733048 Periodontal - 0.000004 +21399635 rs968451 Primary Biliary Cirrhosis - 0.000000 +23041239 rs13407662 Ischaemic Stroke - 0.000000 +22570627 rs216146 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000001 +19056611 rs564398 Type 2 Diabetes - 0.000010 +25233373 rs17648524 Myopia|Hyperopia - 0.000000 +24516586 rs17187075 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000001 +20038947 rs7079573 Major Depression - 0.000010 +22470424 rs9534003 Amyotrophic Lateral Sclerosis - 0.000001 +18483556 rs12203592 Hair Color|Skin Pigmentation - 0.000000 +22368281 rs1627770 LDL-c Response|Lpa - 0.000000 +19081515 rs6107516 Creutzfeldt–Jakob Disease - 0.000000 +21390209 rs10402271 Late-Onset Alzheimer's Disease - 0.000000 +22452962 rs10736303 Breast Cancer - 0.000000 +20729852 rs3781264 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +19197348 rs3809314 Complex Disease - 0.000010 +20485516 rs12447690 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +20972438 rs9642880 Bladder Cancer|Bladder - 0.000000 +23886662 rs1295685 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +22916037 rs173539 Atherosclerosis - 0.000000 +23966204 rs2597963 Bitter Taste|Bitter Taste Perception - 0.000001 +24871463 rs558702 Systemic Lupus Erythematosus Sle - 0.000000 +21665990 rs1999930 Age-Related Macular Degeneration - 0.000000 +20190752 rs11712165 Celiac Disease - 0.000000 +18823527 Rs3754675 Late-Onset Alzheimer's Disease - 0.000006 +24483146 rs12188464 Biomarkers - 0.000002 +22504421 rs7294919 Hippocampal Volume - 0.000000 +21460841 rs7561528 Late-Onset Alzheimer’s Disease - 0.000000 +24709693 rs2294369 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000000 +24945404 rs13223036 Bone Mineral Density|Bone - 0.000000 +25241909 rs924777 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000001 +20801717 rs10260404 Sporadic Amyotrophic Lateral Sclerosis - 0.000000 +18840781 rs3118470 Type 1 Diabetes - 0.000001 +25310577 rs7087507 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +23593202 rs10898723 Age Menarche|Femoral Neck Bone Geometry - 0.000007 +24096698 rs12778749 Cancer - 0.000010 +25742292 rs7869190 Parity - 0.000005 +23092984 rs2962370 Bipolar Disorder - 0.000005 +22470424 rs6816453 Amyotrophic Lateral Sclerosis - 0.000006 +18262040 rs506585 LDL-cholesterol - 0.000000 +23667675 rs7822501 Age Menarche - 0.000007 +21804549 rs2017908 Asthma - 0.000000 +25367360 rs4531042 Astigmatism|Refractive Error - 0.000001 +19571809 rs3751954 Schizophrenia - 0.000005 +22504421 rs7294919 Hippocampal Volume - 0.000000 +23593202 rs7929583 Age Menarche|Femoral Neck Bone Geometry - 0.000004 +24390342 rs12413578 Rheumatoid Arthritis|Biology - 0.000000 +22675492 rs3849491 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000006 +21873549 rs6235 Type 2 Diabetes|Proinsulin Levels - 0.000000 +19430480 rs1465788 Type 1 Diabetes - 0.000000 +23408906 rs9497965 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24688116 rs13114426 Longevity|Analysis|Population - 0.000002 +24516586 rs12499857 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000001 +23408906 rs10519227 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21814517 rs3019885 Asthma - 0.000000 +19096518 rs730497 Glycated Hemoglobin - 0.000000 +23936387 rs4846734 Celiac Disease - 0.000004 +18483556 rs4408545 Hair Color|Skin Pigmentation - 0.000000 +23544013 rs199443 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +25064009 rs3793947 Parkinson’s Disease - 0.000000 +25060954 rs614171 Kinase|Hearing - 0.000000 +22561518 rs4353229 Generalized Vitiligo - 0.000000 +24097068 rs1997243 Lipid Levels - 0.000000 +23793025 rs9349379 Migraine - 0.000000 +23886662 rs6871536 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +24489884 rs670292 Aggression - 0.000000 +24166486 rs7749305 Schizophrenia - 0.000000 +20062060 rs4944092 Pr Interval - 0.000000 +24886709 rs62436827 Lipid - 0.000007 +23408906 rs3813582 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +20364137 rs12413409 Intracranial Aneurysm - 0.000001 +20935630 rs13107325 Body Mass Index - 0.000000 +21750679 rs3130573 Systemic Sclerosis - 0.000000 +24625756 rs7499271 Intermediate Phenotypes - 0.000000 +23455636 rs4698775 Age-Related Macular Degeneration - 0.000000 +22993228 rs980238 Lumbar Disc Degeneration - 0.000009 +22832961 rs17817600 Alzheimer's Disease - 0.000000 +20173748 rs1903003 Chronic Obstructive Pulmonary Disease - 0.000000 +23382809 rs838836 Schizophrenia - 0.000001 +23028341 rs9276606 Complement C3 - 0.000000 +24379826 rs737267 Serum Uric Acid Levels - 0.000000 +21298047 rs10893366 European-Origin|Substance Dependence - 0.000001 +21998595 rs2351491 Height - 0.000000 +20062060 rs3807989 Pr Interval - 0.000000 +23936387 rs12734338 Celiac Disease - 0.000007 +24709693 rs10113213 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000003 +19772629 rs7577851 Parkinson Disease|Onset - 0.000009 +21946350 rs1529672 Lung Function|Follow-Up - 0.000000 +21423239 rs11650719 Attempted Suicide - 0.000007 +21297633 rs4246905 Ulcerative Colitis - 0.000000 +21573004 rs16847897 Telomere Length - 0.000000 +24133439 rs533581 Autistic-Like Traits - 0.000008 +23593202 rs4141232 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +23565137 rs913360 Late-Onset Alzheimer’s Disease - 0.000000 +23326239 rs2213585 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +24023777 rs267766 Adolescent Idiopathic Scoliosis - 0.000004 +18262040 rs4560142 LDL-cholesterol - 0.000000 +24836286 rs3802842 Colorectal Cancer - 0.000000 +21533022 rs9466056 Bone Mineral Density - 0.000004 +18483556 rs12896399 Hair Color|Skin Pigmentation - 0.000000 +21980299 rs6547853 Type 1 Diabetes - 0.000001 +19772629 rs1941184 Parkinson Disease|Onset - 0.000004 +24586183 rs11675434 Thyroid Peroxidase Antibodies|Thyroid Disease - 0.000000 +19936222 rs2480 Cholesterol|Plasma Lipoprotein Size - 0.000000 +23326239 rs3130628 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +18776929 rs4850820 Hip Bone Size|Females - 0.000005 +22306652 rs12932445 Ischemic Stroke - 0.000000 +23563607 rs4735692 Anthropometric Traits - 0.000000 +19305408 rs8049607 Qt Interval Duration - 0.000000 +19448621 rs12611091 Age Menarche|Menopause - 0.000000 +19247474 rs17050782 Smoking Behaviors|Cigarette Smoking - 0.000008 +22916037 rs3798722 Atherosclerosis - 0.000000 +24166486 rs1107592 Schizophrenia - 0.000000 +23028341 rs1052693 Complement C3 - 0.000000 +25017104 rs2155219 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +23793025 rs6478241 Migraine - 0.000000 +21738479 rs9131 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +23936387 rs17760268 Celiac Disease - 0.000004 +21383967 rs6585827 Rheumatoid Arthritis|Celiac Disease - 0.000001 +21935397 rs17104665 Extremely|Overweight|Body Mass Index - 0.000005 +23326517 rs1329424 Age-Related Macular Degeneration - 0.000000 +25340798 rs2228467 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +23326517 rs3793917 Age-Related Macular Degeneration - 0.000000 +20953189 rs12924903 Psoriasis - 0.000000 +21943158 rs17091905 Cardiovascular-Related Traits - 0.000000 +21423239 rs10189155 Attempted Suicide - 0.000005 +23284291 rs11654749 Pulmonary Function|Lung Function - 0.000000 +22479202 rs12051272 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +22829776 rs440837 Globulin|Hormone|Steroid Hormone - 0.000000 +25742292 rs1368013 Parity - 0.000009 +25629512 rs12661281 Age-Related Macular Degeneration - 0.000000 +25350695 rs10455872 Ldl Cholesterol Response|Response Statins - 0.000000 +24133439 rs1420612 Autistic-Like Traits - 0.000003 +24094242 rs174601 Serum Alkaline Phosphatase Levels - 0.000000 +19122664 rs10889677 Ulcerative Colitis - 0.000000 +24097068 rs2290547 Lipid Levels - 0.000000 +24025145 rs857369 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000002 +21483430 rs2487453 Neurocognitive Phenotypes - 0.000000 +19798445 rs10938494 Sphingolipid - 0.000000 +21399635 rs6421571 Primary Biliary Cirrhosis - 0.000000 +22693459 rs2497938 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +25367360 rs4738757 Astigmatism|Refractive Error - 0.000002 +22044751 rs2748531 Chronic Kidney Disease - 0.000004 +24483146 rs11215416 Biomarkers - 0.000010 +24133439 rs10521175 Autistic-Like Traits - 0.000003 +25310577 rs10272724 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +18604267 rs7258015 Antigen|Icam-1 - 0.000000 +21829377 rs2236212 Plasma Phospholipid|Fatty Acids - 0.000000 +25340798 rs4845622 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +21946350 rs2857595 Lung Function|Follow-Up - 0.000000 +21076409 rs9470361 Conduction|Qrs Duration - 0.000000 +21437268 rs1494961 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +25147783 rs12261966 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +22438815 rs34778348 Parkinson's Disease - 0.000000 +18604267 rs281437 Antigen|Icam-1 - 0.000000 +19609347 rs16848861 Hypertension|Blood Pressure - 0.000005 +18483556 rs6497268 Hair Color|Skin Pigmentation - 0.000000 +20700443 rs4072037 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +25147783 rs516246 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +21408207 rs2431697 Systemic Lupus Erythematosus|Autoantibody - 0.000002 +21658281 rs1559040 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +23936387 rs1958589 Celiac Disease - 0.000004 +24483146 rs11215416 Biomarkers - 0.000005 +23936387 rs2664156 Celiac Disease - 0.000006 +24714607 rs6577641 Chronic Mucus Hypersecretion - 0.000004 +25390645 rs17105964 Anxiety - 0.000009 +22832960 rs987360 Temperament Character Inventory - 0.000002 +22693455 rs7766070 Obese|Type 2 Diabetes - 0.000000 +21943158 rs4698036 Cardiovascular-Related Traits - 0.000000 +23646285 rs359268 Hypersomnia - 0.000001 +25340798 rs4343 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +25629512 rs10507047 Age-Related Macular Degeneration - 0.000000 +22558097 rs1105880 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +23326517 rs2075650 Age-Related Macular Degeneration - 0.000001 +22247754 rs482329 Arrhythmias - 0.000005 +23936387 rs1676235 Celiac Disease - 0.000000 +21935397 rs11847697 Extremely|Overweight|Body Mass Index - 0.000000 +22675492 rs11880316 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000004 +25060954 rs1503369 Kinase|Hearing - 0.000000 +19571809 rs1864744 Schizophrenia - 0.000008 +25241909 rs17184313 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000004 +23583980 rs6421972 Pulmonary Fibrosis - 0.000000 +21935397 rs2890652 Extremely|Overweight|Body Mass Index - 0.000000 +21044948 rs2736990 Parkinson's Disease - 0.000000 +23974872 rs2910032 Schizophrenia - 0.000000 +21297633 rs907611 Ulcerative Colitis - 0.000000 +23509613 rs1978968 Antiphospholipid Antibodies - 0.000002 +21829393 rs3788013 Type 1 Diabetes|Autoantibody - 0.000000 +21750679 rs3792783 Systemic Sclerosis - 0.000001 +19772629 rs7076519 Parkinson Disease|Onset - 0.000001 +21460841 rs9349407 Late-Onset Alzheimer’s Disease - 0.000001 +24483146 rs12188464 Biomarkers - 0.000001 +23041239 rs225132 Ischaemic Stroke - 0.000000 +21873549 rs4790333 Type 2 Diabetes|Proinsulin Levels - 0.000000 +21658281 rs2281680 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +21901158 rs604459 Insulin Resistance|Copy Number Variation - 0.000008 +22993228 rs3019449 Lumbar Disc Degeneration - 0.000000 +24908248 rs1920116 Telomere Length|Glioma - 0.000000 +22359512 rs10885997 Sphingolipids - 0.000000 +20011104 rs4311394 Adiponectin Levels - 0.000000 +24999842 rs212402 Celiac Disease|Celiac - 0.000000 +25162662 rs3791770 Serum Ferritin - 0.000004 +21552555 rs10852521 Obesity|Obesity-Related Traits - 0.000000 +23028483 rs2305480 Asthma - 0.000000 +19305408 rs12576239 Qt Interval Duration - 0.000000 +24483146 rs9852733 Biomarkers - 0.000002 +21297633 rs9822268 Ulcerative Colitis - 0.000000 +21873549 rs11558471 Type 2 Diabetes|Proinsulin Levels - 0.000000 +25390645 rs17548918 Anxiety - 0.000009 +24483146 rs402098 Biomarkers - 0.000003 +19197348 rs10245389 Complex Disease - 0.000010 +25526632 rs1728400 Breast Cancer - 0.000006 +24483146 rs7713001 Biomarkers - 0.000002 +19503088 rs13031237 Rheumatoid Arthritis - 0.000000 +23738518 rs2822560 Reading|Language - 0.000000 +24836286 rs10849432 Colorectal Cancer - 0.000000 +24166486 rs3757440 Schizophrenia - 0.000000 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Erythematosus|Autoantibody - 0.000008 +19734902 rs11894266 Alzheimer's Disease - 0.000001 +25372704 rs6545816 Sickle Cell Anemia|Fetal Hemoglobin|Sickle Cell - 0.000000 +22993228 rs7767277 Lumbar Disc Degeneration - 0.000000 +21552555 rs7190492 Obesity|Obesity-Related Traits - 0.000000 +23326239 rs9267947 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +20935630 rs9816226 Body Mass Index - 0.000000 +19247474 rs933688 Smoking Behaviors|Cigarette Smoking - 0.000006 +23593202 rs4141232 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +19132087 rs7199343 Kawasaki Disease - 0.000002 +23028341 rs241428 Complement C3 - 0.000000 +23967269 rs711254 Mite-Specific IgEs|Asthma - 0.000007 +22916037 rs445925 Atherosclerosis - 0.000000 +23936387 rs7144018 Celiac Disease - 0.000004 +19503597 rs17300741 Uric Acid - 0.000000 +22760553 rs6764050 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000001 +22144915 rs3690 Corneal Astigmatism - 0.000001 +20932310 rs11015860 Τ Protein Levels - 0.000001 +18776929 rs12476075 Hip Bone Size|Females - 0.000000 +20700443 rs11144134 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +21779181 rs3135021 Systemic Sclerosis - 0.000000 +23703922 rs10805364 Uric Acid Levels - 0.000000 +23667675 rs2095812 Age Menarche - 0.000001 +18483556 rs7196459 Hair Color|Skin Pigmentation - 0.000000 +22085899 rs12714207 Bilirubin Levels - 0.000000 +19197348 rs3890182 Complex Disease - 0.000000 +23326517 rs1061170 Age-Related Macular Degeneration - 0.000000 +21408207 rs2248932 Systemic Lupus Erythematosus|Autoantibody - 0.000003 +21437268 rs4767364 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +22359512 rs12472274 Sphingolipids - 0.000000 +22087292 rs12098712 Femoral Neck Bone Geometry - 0.000010 +19668339 rs6590322 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000009 +20932310 rs2899472 Τ Protein Levels - 0.000000 +21901158 rs2407314 Insulin Resistance|Copy Number Variation - 0.000008 +19343178 rs849141 Stature - 0.000000 +23667675 rs4946651 Age Menarche - 0.000001 +21533024 rs3136642 Icam-1 - 0.000000 +24513273 rs10480300 Serum Uric Acid - 0.000000 +25129146 rs35597309 Esophageal Squamous Cell Carcinoma - 0.000000 +23326239 rs2239803 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +19651812 rs1387153 Melatonin|Plasma Glucose|Type 2 Diabetes - 0.000000 +20801717 rs2306677 Sporadic Amyotrophic Lateral Sclerosis - 0.000003 +23056639 rs644234 Lectin - 0.000000 +25017104 rs17004598 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +22412388 rs7705924 Crohn's Disease - 0.000000 +21298027 rs10771427 Celiac Disease|Crohn's Disease - 0.000004 +19197348 rs2081302 Complex Disease - 0.000009 +22911880 rs1898111 Behaviors|Personality Traits|Eating - 0.000008 +22470424 rs7764218 Amyotrophic Lateral Sclerosis - 0.000009 +23326239 rs3093970 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +17903297 rs10502991 Brain|Cognitive Test - 0.000010 +22085899 rs11891311 Bilirubin Levels - 0.000000 +24483146 rs13171512 Biomarkers - 0.000002 +23326239 rs2736157 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21983787 rs45430 Melanoma - 0.000000 +21779176 rs2116050 Restless Legs Syndrome - 0.000000 +23056639 rs4652 Lectin - 0.000000 +24513273 rs17300741 Serum Uric Acid - 0.000000 +23563607 rs4735692 Anthropometric Traits - 0.000000 +24688116 rs17760362 Longevity|Analysis|Population - 0.000005 +22675492 rs727479 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000001 +22412388 rs11209026 Crohn's Disease - 0.000000 +22911880 rs1557305 Behaviors|Personality Traits|Eating - 0.000005 +18483556 rs12203592 Hair Color|Skin Pigmentation - 0.000000 +20190752 rs864537 Celiac Disease - 0.000000 +21829393 rs11755527 Type 1 Diabetes|Autoantibody - 0.000001 +19734902 rs8106922 Alzheimer's Disease - 0.000000 +24483146 rs2290344 Biomarkers - 0.000000 +21804549 rs10064618 Asthma - 0.000001 +23056639 rs12443973 Lectin - 0.000002 +20686608 rs3016539 Pancreatic Cancer - 0.000007 +20442857 rs12286037 Phospholipase A - 0.000000 +23646285 rs2043234 Hypersomnia - 0.000004 +21379329 rs2075650 Late-Onset Alzheimer's Disease - 0.000000 +21298027 rs4317904 Celiac Disease|Crohn's Disease - 0.000002 +23326239 rs2294881 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +25390645 rs12703441 Anxiety - 0.000007 +24097068 rs6805251 Lipid Levels - 0.000000 +19096518 rs13266634 Glycated Hemoglobin - 0.000000 +18840781 rs10758593 Type 1 Diabetes - 0.000003 +25340798 rs113263161 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +19557197 rs7138803 Distribution|Adiposity|Waist Circumference - 0.000001 +23727862 rs10208273 Osteosarcoma - 0.000003 +21297633 rs6451493 Ulcerative Colitis - 0.000000 +21685912 rs242557 Progressive Supranuclear Palsy - 0.000000 +23455636 rs4420638 Age-Related Macular Degeneration - 0.000000 +19412176 rs1154155 Narcolepsy - 0.000000 +19430480 rs1534422 Type 1 Diabetes - 0.000002 +21779176 rs6747972 Restless Legs Syndrome - 0.000000 +21935397 rs3817334 Extremely|Overweight|Body Mass Index - 0.000000 +18604267 rs500498 Antigen|Icam-1 - 0.000000 +21873549 rs1549318 Type 2 Diabetes|Proinsulin Levels - 0.000000 +22085899 rs12206204 Bilirubin Levels - 0.000001 +21738479 rs12149261 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +23704328 rs17101923 Tooth Eruption|Height - 0.000000 +19734902 rs10501927 Alzheimer's Disease - 0.000002 +19915575 rs2736990 Parkinson’s Disease - 0.000000 +20548946 rs8068952 Optic Disc - 0.000000 +22792082 rs295114 Asthma|Bronchodilator Response - 0.000006 +22479202 rs601339 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +22087292 rs11998784 Femoral Neck Bone Geometry - 0.000001 +21076409 rs4687718 Conduction|Qrs Duration - 0.000000 +23028356 rs2233434 Rheumatoid Arthritis - 0.000002 +19571809 rs915071 Schizophrenia - 0.000004 +20661308 rs6427310 Serum Calcium - 0.000005 +19197348 rs4420638 Complex Disease - 0.000000 +21347284 rs6599222 Pr Interval - 0.000000 +24945404 rs3765350 Bone Mineral Density|Bone - 0.000000 +23703922 rs7660895 Uric Acid Levels - 0.000000 +23958962 rs200085570 Cocaine Dependence - 0.000000 +23984888 rs10189795 Airway Responsiveness - 0.000003 +22504420 rs9466056 Bone Mineral Density - 0.000000 +23508266 rs11252394 Asthmatics|Bronchodilator Response - 0.000000 +24714607 rs6577641 Chronic Mucus Hypersecretion - 0.000004 +22666496 rs16861476 Cardiovascular Event - 0.000001 +23636237 rs1667320 Analysis - 0.000000 +19609347 rs2146204 Hypertension|Blood Pressure - 0.000003 +25226531 rs7642482 Suggest|Associated|Linguistic Phenotype - 0.000000 +22197932 rs479844 Atopic Dermatitis - 0.000001 +20038947 rs6711718 Major Depression - 0.000002 +24836286 rs7229639 Colorectal Cancer - 0.000000 +24068962 rs7481584 Serum Calcium - 0.000000 +20801717 rs903603 Sporadic Amyotrophic Lateral Sclerosis - 0.000000 +20548946 rs1547014 Optic Disc - 0.000000 +24097068 rs1077514 Lipid Levels - 0.000000 +19936222 rs2909207 Cholesterol|Plasma Lipoprotein Size - 0.000000 +19197348 rs17157663 Complex Disease - 0.000009 +22693455 rs7903146 Obese|Type 2 Diabetes - 0.000000 +24097068 rs4722551 Lipid Levels - 0.000000 +21297633 rs6426833 Ulcerative Colitis - 0.000000 +24516586 rs4622999 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000001 +25310577 rs7089424 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +20686608 rs7779540 Pancreatic Cancer - 0.000000 +22843504 rs1328244 Autism Spectrum - 0.000001 +25378659 rs11666913 Long-Chain Saturated Fatty Acids - 0.000000 +22085899 rs6742078 Bilirubin Levels - 0.000000 +24945404 rs2450083 Bone Mineral Density|Bone - 0.000000 +24755620 rs439401 Glutamate|Alzheimer's Disease - 0.000000 +20935630 rs12444979 Body Mass Index - 0.000000 +21935397 rs2241423 Extremely|Overweight|Body Mass Index - 0.000000 +23423138 rs4837521 Mathematical Abilities|Dyslexia|Myosin - 0.000000 +20190752 rs1738074 Celiac Disease - 0.000000 +18483556 rs10861741 Hair Color|Skin Pigmentation - 0.000002 +21383967 rs11984075 Rheumatoid Arthritis|Celiac Disease - 0.000000 +24133439 rs198198 Autistic-Like Traits - 0.000010 +21804549 rs2381416 Asthma - 0.000000 +24886709 rs11216230 Lipid - 0.000000 +20548946 rs10483727 Optic Disc - 0.000000 +21779181 rs11642873 Systemic Sclerosis - 0.000000 +23408906 rs7860634 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +22116950 rs9396503 Ovarian Reserve - 0.000004 +23667675 rs314289 Age Menarche - 0.000001 +19557197 rs4701252 Distribution|Adiposity|Waist Circumference - 0.000002 +20421936 rs11127485 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +20953189 rs10782001 Psoriasis - 0.000000 +24483146 rs17564430 Biomarkers - 0.000005 +21876539 rs6495122 Cyp1A2 - 0.000000 +22087292 rs12005658 Femoral Neck Bone Geometry - 0.000000 +22504420 rs5934507 Bone Mineral Density - 0.000000 +22511988 rs887829 Cell-Free Dna|Cardiovascular - 0.000000 +24755620 rs3852861 Glutamate|Alzheimer's Disease - 0.000000 +19772629 rs10918270 Parkinson Disease|Onset - 0.000005 +25162662 rs1898560 Serum Ferritin - 0.000000 +21750679 rs9855622 Systemic Sclerosis - 0.000002 +21935397 rs11640537 Extremely|Overweight|Body Mass Index - 0.000010 +25742292 rs1368011 Parity - 0.000009 +21437268 rs7924284 Cancers|Conducted|Upper Aerodigestive Tract - 0.000008 +24513273 rs742132 Serum Uric Acid - 0.000000 +23979607 rs6866910 Borderline Personality - 0.000001 +24483146 rs13171512 Biomarkers - 0.000002 +24755620 rs10402271 Glutamate|Alzheimer's Disease - 0.000000 +20935630 rs10968576 Body Mass Index - 0.000000 +21980299 rs4763879 Type 1 Diabetes - 0.000001 +24836286 rs1535 Colorectal Cancer - 0.000000 +20935630 rs7138803 Body Mass Index - 0.000000 +19169254 rs2082412 Psoriasis - 0.000000 +20038947 rs644377 Major Depression - 0.000002 +19197348 rs16996148 Complex Disease - 0.000000 +22044751 rs17736767 Chronic Kidney Disease - 0.000002 +22832961 rs3748140 Alzheimer's Disease - 0.000000 +23636237 rs838145 Analysis - 0.000000 +22267201 rs2277339 Age Menopause - 0.000000 +22452962 rs10822013 Breast Cancer - 0.000000 +24166486 rs13212651 Schizophrenia - 0.000000 +22267201 rs2307449 Age Menopause - 0.000000 +22423221 rs210134 Platelet Count|Mean Platelet Volume - 0.000000 +23382691 rs11710456 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24047820 rs12115663 Social Communication - 0.000004 +25364816 rs9362054 Diabetic Retinopathy - 0.000000 +20190752 rs842647 Celiac Disease - 0.000000 +24347629 rs10457526 Periodontal - 0.000006 +21998597 rs12150660 Serum Testosterone - 0.000000 +23966204 rs2708377 Bitter Taste|Bitter Taste Perception - 0.000000 +21060863 rs7824557 Cardiovascular Diseases - 0.000000 +22368281 rs1985096 LDL-c Response|Lpa - 0.000001 +20729852 rs4072037 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +23738518 rs11577628 Reading|Language - 0.000005 +22359512 rs964184 Sphingolipids - 0.000000 +17903298 rs2066219 Diabetes-Related Traits - 0.000009 +23958962 rs61751192 Cocaine Dependence - 0.000001 +23834954 rs2063640 Sensory Disturbances|Split - 0.000002 +22247754 rs11856574 Arrhythmias - 0.000005 +21460841 rs6701713 Late-Onset Alzheimer’s Disease - 0.000000 +24740154 rs4430796 Prostate Cancer|Early-Onset - 0.000002 +21804549 rs10173081 Asthma - 0.000000 +23326239 rs652888 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +20169177 rs7097397 Systemic Lupus Erythematosus - 0.000000 +21124955 rs4150642 Serum Amyloid A|Type 2 Diabetes - 0.000000 +23704328 rs1799922 Tooth Eruption|Height - 0.000001 +23028341 rs3763317 Complement C3 - 0.000000 +20190752 rs2074404 Celiac Disease - 0.000000 +24511991 rs12681349 Parkinson’s Disease - 0.000000 +21076409 rs10865879 Conduction|Qrs Duration - 0.000000 +25367360 rs4712652 Astigmatism|Refractive Error - 0.000003 +19197348 rs2554622 Complex Disease - 0.000010 +24324648 rs9264567 Serum IgE - 0.000000 +21943158 rs660240 Cardiovascular-Related Traits - 0.000000 +18262040 rs1713222 LDL-cholesterol - 0.000000 +21124946 rs9525613 Bone Mineral Density - 0.000002 +23307926 rs2277339 Menopause - 0.000000 +22438815 rs11724635 Parkinson's Disease - 0.000000 +22675492 rs815653 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000010 +22511988 rs6744284 Cell-Free Dna|Cardiovascular - 0.000000 +23104006 rs12700667 Endometriosis - 0.000000 +21935397 rs2112347 Extremely|Overweight|Body Mass Index - 0.000000 +23984888 rs702036 Airway Responsiveness - 0.000007 +21935397 rs10938397 Extremely|Overweight|Body Mass Index - 0.000000 +21297633 rs6017342 Ulcerative Colitis - 0.000000 +24068962 rs1570669 Serum Calcium - 0.000000 +21829393 rs478582 Type 1 Diabetes|Autoantibody - 0.000000 +22291604 rs10168266 Lupus - 0.000000 +24483146 rs3135351 Biomarkers - 0.000004 +23382691 rs10272724 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +23408906 rs10519227 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24403052 rs214803 Basal Cell Carcinoma - 0.000000 +22267201 rs16991615 Age Menopause - 0.000000 +21297633 rs2838519 Ulcerative Colitis - 0.000000 +22359512 rs1077989 Sphingolipids - 0.000000 +25162662 rs2289404 Serum Ferritin - 0.000000 +23056639 rs2409784 Lectin - 0.000001 +21460841 rs2588969 Late-Onset Alzheimer’s Disease - 0.000001 +21223598 rs10258739 Aortic Root - 0.000002 +24778558 rs12734338 Coronary Heart Disease - 0.000000 +22675492 rs10514317 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000001 +25436638 rs2046045 Serum Thyroid Stimulating Hormone - 0.000000 +22267201 rs10183486 Age Menopause - 0.000000 +23092984 rs11773966 Bipolar Disorder - 0.000002 +23738518 rs11945798 Reading|Language - 0.000005 +20195514 rs6504340 Primary Tooth Development - 0.000001 +22470424 rs9509608 Amyotrophic Lateral Sclerosis - 0.000010 +21876539 rs16868941 Cyp1A2 - 0.000000 +24740154 rs6789365 Prostate Cancer|Early-Onset - 0.000009 +21399635 rs7665090 Primary Biliary Cirrhosis - 0.000000 +22792070 rs13247600 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23583980 rs7934606 Pulmonary Fibrosis - 0.000000 +23593202 rs7929583 Age Menarche|Femoral Neck Bone Geometry - 0.000004 +22561518 rs736374 Generalized Vitiligo - 0.000000 +21980299 rs3024505 Type 1 Diabetes - 0.000000 +21812969 rs183211 Parkinson's Disease - 0.000000 +21490707 rs4410790 Caffeine Consumption|Cyp1A2 - 0.000000 +19401414 rs4712523 Type 2 Diabetes - 0.000000 +22737229 rs3077 Chronic Hepatitis B - 0.000001 +20711177 rs3129882 Parkinson’s Disease - 0.000000 +22941191 rs2499667 Neuroblastoma - 0.000000 +23408906 rs6885099 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +19412175 rs6435862 Neuroblastoma - 0.000000 +21483430 rs3738398 Neurocognitive Phenotypes - 0.000000 +25742292 rs1105228 Parity - 0.000001 +22291604 rs9501626 Lupus - 0.000000 +24483146 rs9852733 Biomarkers - 0.000009 +22685421 rs4428898 Ocular Axial Length|High Myopia - 0.000000 +19668339 rs2124799 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000009 +22941191 rs2499663 Neuroblastoma - 0.000000 +20038947 rs7151193 Major Depression - 0.000006 +23593202 rs6578986 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +22291604 rs2205960 Lupus - 0.000003 +19430483 rs17367504 Blood Pressure - 0.000010 +24280982 rs10275045 Schizophrenia|Bipolar Disorder|Disorder - 0.000000 +22452962 rs4415084 Breast Cancer - 0.000000 +21037568 rs2608053 Hodgkin Lymphoma - 0.000000 +25147783 rs1697421 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +20953189 rs10782001 Psoriasis - 0.000000 +22745674 rs11186734 Coronary Artery Stenosis|Coronary Artery - 0.000000 +21297633 rs4676406 Ulcerative Colitis - 0.000000 +21533175 rs6738028 Dehydroepiandrosterone Sulphate - 0.000000 +22807686 rs9272105 Chronic Hepatitis B|Hepatitis B Virus|Carriers - 0.000009 +20935630 rs1555543 Body Mass Index - 0.000000 +19305408 rs4725982 Qt Interval Duration - 0.000000 +21297633 rs7608910 Ulcerative Colitis - 0.000000 +21037568 rs2019960 Hodgkin Lymphoma - 0.000000 +23401653 rs1800812 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000003 +24009623 rs4148330 Biomarker - 0.000010 +23382691 rs4917014 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +23593202 rs7064959 Age Menarche|Femoral Neck Bone Geometry - 0.000002 +20661308 rs16827695 Serum Calcium - 0.000004 +23563607 rs17024258 Anthropometric Traits - 0.000000 +18464913 rs2250417 Protein Quantitative Trait|Genome|Association - 0.000000 +19714205 rs720810 Asthma - 0.000005 +23989986 rs1577792 Hip|Osteoarthritis - 0.000000 +24023777 rs12946942 Adolescent Idiopathic Scoliosis - 0.000000 +22511988 rs10168416 Cell-Free Dna|Cardiovascular - 0.000000 +21060863 rs10774625 Cardiovascular Diseases - 0.000000 +23326239 rs2395185 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +24740154 rs7126629 Prostate Cancer|Early-Onset - 0.000000 +22087292 rs16913751 Femoral Neck Bone Geometry - 0.000002 +23666240 rs2839186 Testicular Cancer - 0.000000 +24097068 rs998584 Lipid Levels - 0.000000 +24952745 rs3105593 Qt Interval|Calcium - 0.000000 +21552555 rs9937053 Obesity|Obesity-Related Traits - 0.000000 +22760553 rs6563353 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000002 +21665990 rs10033900 Age-Related Macular Degeneration - 0.000000 +24166486 rs3779003 Schizophrenia - 0.000000 +22504420 rs3905706 Bone Mineral Density - 0.000000 +22504420 rs4796995 Bone Mineral Density - 0.000000 +19247474 rs10411195 Smoking Behaviors|Cigarette Smoking - 0.000006 +21804549 rs2381416 Asthma - 0.000000 +22832960 rs2833693 Temperament Character Inventory - 0.000004 +19801982 rs2941740 Bone Mineral Density - 0.000000 +21573128 rs7605378 Osteoporosis - 0.000004 +23844046 rs2075650 C-Reactive Protein - 0.000000 +21901158 rs12655917 Insulin Resistance|Copy Number Variation - 0.000001 +21901158 rs17589516 Insulin Resistance|Copy Number Variation - 0.000004 +22504420 rs17040773 Bone Mineral Density - 0.000000 +24714607 rs10879509 Chronic Mucus Hypersecretion - 0.000007 +21909110 rs319690 Mean Arterial Pressure|Pulse Pressure - 0.000000 +20364137 rs9298506 Intracranial Aneurysm - 0.000000 +19197348 rs12978414 Complex Disease - 0.000004 +25367360 rs7581641 Astigmatism|Refractive Error - 0.000005 +23666240 rs10510452 Testicular Cancer - 0.000000 +17903307 rs564425 Pulmonary Function - 0.000010 +20442857 rs6901132 Phospholipase A - 0.000000 +22452962 rs1092913 Breast Cancer - 0.000002 +22993228 rs4881085 Lumbar Disc Degeneration - 0.000007 +22267201 rs4886238 Age Menopause - 0.000000 +24390342 rs1877030 Rheumatoid Arthritis|Biology - 0.000000 +22359512 rs7259004 Sphingolipids - 0.000000 +24999842 rs169858 Celiac Disease|Celiac - 0.000000 +23979607 rs6894288 Borderline Personality - 0.000001 +22911880 rs6894268 Behaviors|Personality Traits|Eating - 0.000002 +24513273 rs653178 Serum Uric Acid - 0.000000 +21390209 rs9369240 Late-Onset Alzheimer's Disease - 0.000005 +23041239 rs16851055 Ischaemic Stroke - 0.000001 +19801982 rs2016266 Bone Mineral Density - 0.000000 +23408906 rs17723470 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24023777 rs625039 Adolescent Idiopathic Scoliosis - 0.000000 +19609347 rs11659639 Hypertension|Blood Pressure - 0.000000 +21399635 rs1800693 Primary Biliary Cirrhosis - 0.000000 +21909115 rs1799945 Cardiovascular Disease|Blood Pressure - 0.000000 +22693459 rs2073963 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +21042317 rs17226852 Major Depressive Disorder - 0.000002 +24025145 rs7476422 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000000 +24952745 rs9920 Qt Interval|Calcium - 0.000000 +20081858 rs11605924 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +23834954 rs1998930 Sensory Disturbances|Split - 0.000010 +23984888 rs702036 Airway Responsiveness - 0.000007 +18840781 rs11171710 Type 1 Diabetes - 0.000000 +23300701 rs10879357 Colorectal Cancer - 0.000003 +24740154 rs16911551 Prostate Cancer|Early-Onset - 0.000006 +25436638 rs12515498 Serum Thyroid Stimulating Hormone - 0.000000 +20442857 rs6458511 Phospholipase A - 0.000000 +24564958 rs4453791 Social-Communication|Spectrum Phenotypes - 0.000000 +23770605 rs13401811 Chronic Lymphocytic Leukemia - 0.000000 +22760553 rs7715172 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000003 +21983785 rs6478444 Melanoma - 0.000006 +24509480 rs6813195 Type 2 Diabetes - 0.000000 +21901158 rs7043482 Insulin Resistance|Copy Number Variation - 0.000003 +19571809 rs16941261 Schizophrenia - 0.000001 +25367360 rs6999 Astigmatism|Refractive Error - 0.000004 +23544013 rs2077606 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +24133439 rs4785161 Autistic-Like Traits - 0.000003 +20932310 rs2074955 Τ Protein Levels - 0.000000 +23667675 rs7759938 Age Menarche - 0.000001 +25340798 rs7926920 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +25064009 rs2414739 Parkinson’s Disease - 0.000000 +23593202 rs5980450 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +19247474 rs10859032 Smoking Behaviors|Cigarette Smoking - 0.000008 +21408207 rs10488631 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +21812969 rs10121009 Parkinson's Disease - 0.000003 +24651765 rs234714 Homocysteine|Methionine|Metabolism - 0.000000 +25569183 rs9461741 Marginal Zone Lymphoma - 0.000000 +19772629 rs12261736 Parkinson Disease|Onset - 0.000002 +21386085 rs2266788 Metabolic Syndrome - 0.000000 +22792082 rs295137 Asthma|Bronchodilator Response - 0.000001 +23056639 rs16902429 Lectin - 0.000005 +20686608 rs7832232 Pancreatic Cancer - 0.000005 +19430480 rs3087243 Type 1 Diabetes - 0.000000 +21297633 rs11209026 Ulcerative Colitis - 0.000000 +19801982 rs4729260 Bone Mineral Density - 0.000000 +21935397 rs2798311 Extremely|Overweight|Body Mass Index - 0.000004 +23704328 rs8080944 Tooth Eruption|Height - 0.000000 +23056639 rs2274273 Lectin - 0.000000 +23844046 rs4537545 C-Reactive Protein - 0.000008 +19169254 rs1076160 Psoriasis - 0.000006 +21943158 rs1803274 Cardiovascular-Related Traits - 0.000000 +25352737 rs769056 Cataract - 0.000003 +23817569 rs7203459 Allergy - 0.000000 +25241909 rs147862429 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +23437003 rs1021188 Volumetric Bone Mineral Densities - 0.000000 +24390342 rs6732565 Rheumatoid Arthritis|Biology - 0.000000 +20190752 rs802734 Celiac Disease - 0.000000 +24133439 rs7086205 Autistic-Like Traits - 0.000004 +22792070 rs2254595 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23936387 rs2046000 Celiac Disease - 0.000009 +22087292 rs12005658 Femoral Neck Bone Geometry - 0.000000 +21533175 rs2497306 Dehydroepiandrosterone Sulphate - 0.000000 +24324648 rs943474 Serum IgE - 0.000001 +23326239 rs2507997 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23300701 rs17777943 Colorectal Cancer - 0.000000 +23704328 rs412000 Tooth Eruption|Height - 0.000000 +22504420 rs13336428 Bone Mineral Density - 0.000000 +19734902 rs583791 Alzheimer's Disease - 0.000005 +23408906 rs1571583 Thyroid|Thyroid-Related Traits|Differences - 0.000001 +19430480 rs5753037 Type 1 Diabetes - 0.000000 +20932310 rs2075650 Τ Protein Levels - 0.000000 +24688116 rs1625040 Longevity|Analysis|Population - 0.000003 +20038947 rs11011581 Major Depression - 0.000006 +22396660 rs11746443 Nephrolithiasis - 0.000000 +23459936 rs12883458 Chronic Periodontitis - 0.000000 +20062060 rs7692808 Pr Interval - 0.000000 +25017104 rs2898261 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +22843504 rs10205350 Autism Spectrum - 0.000000 +20066028 rs2292883 Serum Cholesterol Levels - 0.000000 +21901158 rs1401492 Insulin Resistance|Copy Number Variation - 0.000003 +23472185 rs1455158 Multiple Sclerosis|Oligoclonal Band - 0.000002 +23708191 rs870142 Congenital Heart Disease|Atrial Septal Defect - 0.000000 +21935397 rs29941 Extremely|Overweight|Body Mass Index - 0.000000 +19169254 rs2201841 Psoriasis - 0.000000 +18369459 rs10484554 Psoriasis|Psoriatic Arthritis|New Disease - 0.000000 +22993228 rs17034687 Lumbar Disc Degeneration - 0.000000 +24133439 rs9635530 Autistic-Like Traits - 0.000003 +23844046 rs1183910 C-Reactive Protein - 0.000000 +20932310 rs12203791 Τ Protein Levels - 0.000001 +25390645 rs241257 Anxiety - 0.000009 +21827660 rs1063192 Increased Disease Risk - 0.000000 +18262040 rs7575840 LDL-cholesterol - 0.000000 +18604267 rs687621 Antigen|Icam-1 - 0.000000 +20081858 rs11558471 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +20038947 rs1855625 Major Depression - 0.000009 +19300500 rs1877252 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000010 +17684544 rs1992662 Ibd Disease - 0.000000 +23817569 rs9860547 Allergy - 0.000000 +24166486 rs10224497 Schizophrenia - 0.000000 +22829776 rs780093 Globulin|Hormone|Steroid Hormone - 0.000000 +23455636 rs8135665 Age-Related Macular Degeneration - 0.000000 +23382691 rs11755527 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +22570627 rs7894966 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000000 +23408906 rs753760 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21297633 rs2872507 Ulcerative Colitis - 0.000000 +20661308 rs10119 Serum Calcium - 0.000005 +24625756 rs3733402 Intermediate Phenotypes - 0.000000 +21935397 rs734597 Extremely|Overweight|Body Mass Index - 0.000007 +19668339 rs11626056 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000001 +22479202 rs12922394 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +24094242 rs10819937 Serum Alkaline Phosphatase Levels - 0.000000 +24886709 rs5880 Lipid - 0.000000 +21998597 rs12150660 Serum Testosterone - 0.000000 +17903305 rs1529276 Prostate Cancer|Breast - 0.000002 +23593202 rs13230316 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +19448621 rs7718874 Age Menarche|Menopause - 0.000000 +22359512 rs174479 Sphingolipids - 0.000000 +25140149 rs7849530 Neurodegeneration|Biomarker - 0.000000 +25378659 rs11666913 Long-Chain Saturated Fatty Acids - 0.000000 +20190752 rs859637 Celiac Disease - 0.000002 +23974872 rs114002140 Schizophrenia - 0.000000 +19503597 rs12498742 Uric Acid - 0.000000 +25367360 rs885560 Astigmatism|Refractive Error - 0.000003 +25147783 rs11254375 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +21399635 rs8017161 Primary Biliary Cirrhosis - 0.000000 +21829377 rs174538 Plasma Phospholipid|Fatty Acids - 0.000000 +17903293 rs2794520 Biomarker Traits - 0.000000 +23326239 rs3117583 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +22666496 rs10155047 Cardiovascular Event - 0.000001 +21448238 rs9908234 Migraine - 0.000000 +19056611 rs7903146 Type 2 Diabetes - 0.000000 +25310821 rs13069589 Hirschsprung Disease - 0.000007 +19430480 rs2269241 Type 1 Diabetes - 0.000000 +25367360 rs9366427 Astigmatism|Refractive Error - 0.000004 +19412176 rs1263646 Narcolepsy - 0.000000 +20548946 rs1900004 Optic Disc - 0.000000 +23056639 rs17223788 Lectin - 0.000002 +23382691 rs12212193 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24390342 rs968567 Rheumatoid Arthritis|Biology - 0.000000 +21437268 rs1789924 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +23886662 rs12198173 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +23761726 rs979976 Corneal Astigmatism|Platelet-Derived Growth Factor - 0.000008 +21943158 rs10199768 Cardiovascular-Related Traits - 0.000000 +19503597 rs12129861 Uric Acid - 0.000000 +24483146 rs9861198 Biomarkers - 0.000003 +25310821 rs6074578 Hirschsprung Disease - 0.000004 +19430480 rs7111341 Type 1 Diabetes - 0.000000 +22685421 rs4373767 Ocular Axial Length|High Myopia - 0.000000 +21552555 rs9941349 Obesity|Obesity-Related Traits - 0.000000 +21273288 rs6009824 NT-proBNP - 0.000006 +25367360 rs6682062 Astigmatism|Refractive Error - 0.000003 +21408207 rs7927370 Systemic Lupus Erythematosus|Autoantibody - 0.000007 +22993228 rs11754641 Lumbar Disc Degeneration - 0.000008 +18846228 rs2427837 Serum IgE Levels - 0.000000 +23989986 rs12551314 Hip|Osteoarthritis - 0.000001 +25367360 rs6471768 Astigmatism|Refractive Error - 0.000001 +22438815 rs823156 Parkinson's Disease - 0.000000 +24952745 rs17457880 Qt Interval|Calcium - 0.000000 +21076409 rs7784776 Conduction|Qrs Duration - 0.000000 +21750679 rs6919745 Systemic Sclerosis - 0.000008 +23704328 rs10932688 Tooth Eruption|Height - 0.000000 +18840781 rs12029644 Type 1 Diabetes - 0.000006 +24999842 rs1394220 Celiac Disease|Celiac - 0.000001 +24836286 rs2423279 Colorectal Cancer - 0.000000 +22693455 rs9939609 Obese|Type 2 Diabetes - 0.000000 +19714249 rs297325 Obesity|Osteoporosis Phenotypes - 0.000000 +23974872 rs4523957 Schizophrenia - 0.000000 +23646285 rs10988217 Hypersomnia - 0.000003 +21383967 rs7579944 Rheumatoid Arthritis|Celiac Disease - 0.000000 +19668339 rs6881634 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000002 +23984888 rs4129709 Airway Responsiveness - 0.000010 +23259602 rs11850320 Dental Caries - 0.000001 +24097068 rs2013208 Lipid Levels - 0.000000 +24513273 rs3114018 Serum Uric Acid - 0.000000 +21873549 rs9727115 Type 2 Diabetes|Proinsulin Levels - 0.000000 +24483146 rs7631790 Biomarkers - 0.000002 +19305408 rs12029454 Qt Interval Duration - 0.000000 +23817569 rs6473223 Allergy - 0.000000 +21156761 rs2961663 Rheumatoid Arthritis - 0.000004 +23593202 rs4844014 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +22470424 rs6904956 Amyotrophic Lateral Sclerosis - 0.000009 +17903297 rs2893363 Brain|Cognitive Test - 0.000010 +25017104 rs118086209 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +24999842 rs6441961 Celiac Disease|Celiac - 0.000000 +21383967 rs243323 Rheumatoid Arthritis|Celiac Disease - 0.000007 +21552555 rs247916 Obesity|Obesity-Related Traits - 0.000009 +21156761 rs6956740 Rheumatoid Arthritis - 0.000001 +21390209 rs2965101 Late-Onset Alzheimer's Disease - 0.000002 +21297633 rs2155219 Ulcerative Colitis - 0.000000 +21552555 rs3751813 Obesity|Obesity-Related Traits - 0.000000 +19343178 rs6088619 Stature - 0.000001 +19734902 rs11827375 Alzheimer's Disease - 0.000007 +19448621 rs2278493 Age Menarche|Menopause - 0.000000 +24390342 rs13142500 Rheumatoid Arthritis|Biology - 0.000000 +22675492 rs10488084 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000002 +24086445 rs6936717 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +23667675 rs11156429 Age Menarche - 0.000001 +19343178 rs9358913 Stature - 0.000000 +20190752 rs864537 Celiac Disease - 0.000000 +24999842 rs2157453 Celiac Disease|Celiac - 0.000001 +20195514 rs1956529 Primary Tooth Development - 0.000000 +19343178 rs910316 Stature - 0.000000 +24625756 rs17028615 Intermediate Phenotypes - 0.000000 +17903305 rs458685 Prostate Cancer|Breast - 0.000006 +24483146 rs9850725 Biomarkers - 0.000000 +19247474 rs3027409 Smoking Behaviors|Cigarette Smoking - 0.000007 +21935397 rs3849047 Extremely|Overweight|Body Mass Index - 0.000007 +19300482 rs9686327 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +23326517 rs9380272 Age-Related Macular Degeneration - 0.000000 +21935397 rs1555543 Extremely|Overweight|Body Mass Index - 0.000000 +21909108 rs11781551 Intima Media Thickness|Plaque - 0.000000 +19961619 rs13273924 Respiratory|Atopy - 0.000001 +17903293 rs2808629 Biomarker Traits - 0.000000 +21297633 rs267939 Ulcerative Colitis - 0.000000 +22087292 rs854140 Femoral Neck Bone Geometry - 0.000003 +24133439 rs927821 Autistic-Like Traits - 0.000003 +23326517 rs1329428 Age-Related Macular Degeneration - 0.000000 +23382691 rs16861329 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +19300499 rs2108622 Cyp2C9|Warfarin - 0.000000 +24347629 rs7749983 Periodontal - 0.000002 +24740154 rs10993994 Prostate Cancer|Early-Onset - 0.000000 +23966204 rs7297949 Bitter Taste|Bitter Taste Perception - 0.000001 +18840781 rs725613 Type 1 Diabetes - 0.000000 +23382691 rs4598195 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +20935630 rs3810291 Body Mass Index - 0.000000 +22470424 rs6746842 Amyotrophic Lateral Sclerosis - 0.000004 +21297633 rs6451493 Ulcerative Colitis - 0.000000 +23408906 rs11726248 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +23886662 rs7130588 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +22916037 rs16850360 Atherosclerosis - 0.000000 +23704328 rs1994969 Tooth Eruption|Height - 0.000000 +23437003 rs271170 Volumetric Bone Mineral Densities - 0.000000 +19915575 rs823128 Parkinson’s Disease - 0.000000 +20661308 rs17251221 Serum Calcium - 0.000000 +24483146 rs4774760 Biomarkers - 0.000000 +22763110 rs8044769 Osteoarthritis - 0.000000 +22144915 rs2228230 Corneal Astigmatism - 0.000001 +21980494 rs10029715 Venous Thrombosis - 0.000000 +24740154 rs1486307 Prostate Cancer|Early-Onset - 0.000005 +20169177 rs2736340 Systemic Lupus Erythematosus - 0.000009 +25297839 rs114045064 Herpes Zoster - 0.000000 +22792082 rs295137 Asthma|Bronchodilator Response - 0.000003 +21804549 rs11214966 Asthma - 0.000000 +22561518 rs9926296 Generalized Vitiligo - 0.000000 +20700443 rs4561213 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +24133439 rs753858 Autistic-Like Traits - 0.000003 +21408207 rs5754217 Systemic Lupus Erythematosus|Autoantibody - 0.000002 +22470424 rs6840169 Amyotrophic Lateral Sclerosis - 0.000008 +21448238 rs10275320 Migraine - 0.000002 +21076409 rs17020136 Conduction|Qrs Duration - 0.000000 +19122664 rs2395185 Ulcerative Colitis - 0.000000 +23900074 rs9257445 Telomere Length|Cancer - 0.000000 +24390342 rs9603616 Rheumatoid Arthritis|Biology - 0.000000 +23209447 rs417162 I Antigen|Nasopharyngeal Carcinoma - 0.000000 +21297633 rs17085007 Ulcerative Colitis - 0.000000 +25367360 rs12675886 Astigmatism|Refractive Error - 0.000002 +22993228 rs3749982 Lumbar Disc Degeneration - 0.000000 +18464913 rs4796217 Protein Quantitative Trait|Genome|Association - 0.000000 +23974872 rs4380187 Schizophrenia - 0.000000 +22693459 rs6945541 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +23092984 rs1680005 Bipolar Disorder - 0.000007 +18604267 rs2304237 Antigen|Icam-1 - 0.000000 +23703922 rs6030 Uric Acid Levels - 0.000003 +22412388 rs10734105 Crohn's Disease - 0.000000 +23646285 rs7725217 Hypersomnia - 0.000001 +23284291 rs7764819 Pulmonary Function|Lung Function - 0.000000 +22085899 rs887829 Bilirubin Levels - 0.000000 +24847357 rs7152530 Staphylococcus Aureus - 0.000001 +24489884 rs238215 Aggression - 0.000006 +22829776 rs1641537 Globulin|Hormone|Steroid Hormone - 0.000000 +24324648 rs9271682 Serum IgE - 0.000000 +24651765 rs1047891 Homocysteine|Methionine|Metabolism - 0.000000 +24688116 rs4420638 Longevity|Analysis|Population - 0.000000 +23636237 rs1893113 Analysis - 0.000005 +21980299 rs550448 Type 1 Diabetes - 0.000000 +23143602 rs7057398 Pancreatitis - 0.000000 +22470424 rs12929572 Amyotrophic Lateral Sclerosis - 0.000005 +22267201 rs11668344 Age Menopause - 0.000000 +20436471 rs1561570 Paget’s Disease Bone - 0.000000 +19122664 rs2870946 Ulcerative Colitis - 0.000000 +21383967 rs1953126 Rheumatoid Arthritis|Celiac Disease - 0.000000 +25064009 rs1474055 Parkinson’s Disease - 0.000000 +21051773 rs9806256 Handedness|Dyslexia - 0.000000 +22144915 rs7660560 Corneal Astigmatism - 0.000000 +19448621 rs2384687 Age Menarche|Menopause - 0.000000 +23958962 rs4129566 Cocaine Dependence - 0.000000 +24755620 rs714948 Glutamate|Alzheimer's Disease - 0.000000 +23056639 rs17775170 Lectin - 0.000005 +24513273 rs11722228 Serum Uric Acid - 0.000000 +24280982 rs9834970 Schizophrenia|Bipolar Disorder|Disorder - 0.000000 +23326517 rs16851585 Age-Related Macular Degeneration - 0.000005 +23408906 rs1571583 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24097068 rs3822072 Lipid Levels - 0.000000 +21804549 rs4845783 Asthma - 0.000006 +22504421 rs7852872 Hippocampal Volume - 0.000000 +21223598 rs6045666 Aortic Root - 0.000003 +23408906 rs1537424 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24483146 rs427498 Biomarkers - 0.000003 +23326239 rs3130618 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +20661308 rs742393 Serum Calcium - 0.000002 +24086445 rs9488343 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +22993228 rs7103004 Lumbar Disc Degeneration - 0.000009 +24763700 rs7553007 C-Reactive Protein Levels - 0.000000 +23844046 rs11265260 C-Reactive Protein - 0.000000 +20072603 rs13182402 Osteoporosis - 0.000000 +24014518 rs11692675 Epilepsy|Febrile Seizures - 0.000000 +23793025 rs6790925 Migraine - 0.000000 +21909115 rs2521501 Cardiovascular Disease|Blood Pressure - 0.000000 +23459936 rs12260727 Chronic Periodontitis - 0.000001 +20038947 rs7249956 Major Depression - 0.000008 +24836286 rs6687758 Colorectal Cancer - 0.000000 +18262040 rs4605275 LDL-cholesterol - 0.000000 +19772629 rs12261736 Parkinson Disease|Onset - 0.000007 +20935630 rs2112347 Body Mass Index - 0.000000 +24223155 rs9960370 Torsades De Pointes - 0.000006 +17684544 rs2076756 Ibd Disease - 0.000000 +24740154 rs11664910 Prostate Cancer|Early-Onset - 0.000002 +21533024 rs507666 Icam-1 - 0.000000 +24244560 rs1046896 Diabetic Retinopathy|Chronic Kidney Disease|Hemoglobin A - 0.000000 +20932310 rs1997111 Τ Protein Levels - 0.000000 +21935397 rs2867125 Extremely|Overweight|Body Mass Index - 0.000000 +24483146 rs2653165 Biomarkers - 0.000009 +21708048 rs988712 Obesity - 0.000000 +20339536 rs646776 Lipid-Lowering Response|Response Statins - 0.000000 +25436638 rs4804416 Serum Thyroid Stimulating Hormone - 0.000000 +24483146 rs17564430 Biomarkers - 0.000007 +21827660 rs7530361 Increased Disease Risk - 0.000001 +23544013 rs183211 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +19779542 rs11218544 Pathological Myopia - 0.000005 +24133439 rs7499215 Autistic-Like Traits - 0.000003 +21383967 rs975730 Rheumatoid Arthritis|Celiac Disease - 0.000000 +20932310 rs1943816 Τ Protein Levels - 0.000000 +20066028 rs5400 Serum Cholesterol Levels - 0.000002 +24143190 rs2981578 Breast Cancer|Breast - 0.000002 +23703922 rs7092652 Uric Acid Levels - 0.000001 +20062060 rs251253 Pr Interval - 0.000000 +19247474 rs1400363 Smoking Behaviors|Cigarette Smoking - 0.000010 +19454037 rs409045 Left Ventricular Mass - 0.000001 +22843504 rs7834018 Autism Spectrum - 0.000001 +19503597 rs742132 Uric Acid - 0.000000 +21552555 rs3751812 Obesity|Obesity-Related Traits - 0.000000 +19343178 rs7183263 Stature - 0.000000 +20935630 rs2815752 Body Mass Index - 0.000000 +23041239 rs12703165 Ischaemic Stroke - 0.000001 +23300701 rs39453 Colorectal Cancer - 0.000001 +25064009 rs823118 Parkinson’s Disease - 0.000000 +22685421 rs4428898 Ocular Axial Length|High Myopia - 0.000000 +22423221 rs12526480 Platelet Count|Mean Platelet Volume - 0.000000 +24166486 rs6558872 Schizophrenia - 0.000000 +24483146 rs11215416 Biomarkers - 0.000008 +22359512 rs197770 Sphingolipids - 0.000000 +21685912 rs8070723 Progressive Supranuclear Palsy - 0.000000 +23326517 rs1329428 Age-Related Macular Degeneration - 0.000000 +21552555 rs6857327 Obesity|Obesity-Related Traits - 0.000008 +23092984 rs1171113 Bipolar Disorder - 0.000000 +22438815 rs6532194 Parkinson's Disease - 0.000000 +22412388 rs11574514 Crohn's Disease - 0.000000 +20339536 rs1011685 Lipid-Lowering Response|Response Statins - 0.000000 +19430480 rs4948088 Type 1 Diabetes - 0.000000 +20711177 rs356220 Parkinson’s Disease - 0.000000 +20190752 rs12727642 Celiac Disease - 0.000000 +25064009 rs76904798 Parkinson’s Disease - 0.000000 +20038947 rs6694643 Major Depression - 0.000009 +23703922 rs1014290 Uric Acid Levels - 0.000000 +24625756 rs13538 Intermediate Phenotypes - 0.000000 +18483556 rs6918152 Hair Color|Skin Pigmentation - 0.000002 +19734902 rs7561528 Alzheimer's Disease - 0.000003 +24097068 rs1121980 Lipid Levels - 0.000000 +21347284 rs7312625 Pr Interval - 0.000000 +24740154 rs7225566 Prostate Cancer|Early-Onset - 0.000006 +23979607 rs6888413 Borderline Personality - 0.000001 +19081515 rs1799990 Creutzfeldt–Jakob Disease - 0.000000 +23989986 rs17610181 Hip|Osteoarthritis - 0.000002 +20081858 rs174550 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +22558097 rs10168416 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +23104006 rs10859871 Endometriosis - 0.000000 +22504420 rs2887571 Bone Mineral Density - 0.000000 +23408906 rs334699 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +20485516 rs2755237 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +21909108 rs17398575 Intima Media Thickness|Plaque - 0.000000 +19247474 rs950063 Smoking Behaviors|Cigarette Smoking - 0.000009 +23844046 rs1892534 C-Reactive Protein - 0.000000 +22843504 rs1475531 Autism Spectrum - 0.000000 +19801982 rs7117858 Bone Mineral Density - 0.000000 +21935397 rs604388 Extremely|Overweight|Body Mass Index - 0.000001 +19197348 rs4237348 Complex Disease - 0.000003 +23326517 rs11986011 Age-Related Macular Degeneration - 0.000005 +19772629 rs10918270 Parkinson Disease|Onset - 0.000001 +23300701 rs1571218 Colorectal Cancer - 0.000002 +19122664 rs10753575 Ulcerative Colitis - 0.000000 +19300482 rs1828591 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +19798445 rs1000778 Sphingolipid - 0.000001 +23974872 rs2949006 Schizophrenia - 0.000000 +20953189 rs4795067 Psoriasis - 0.000000 +21297633 rs11739663 Ulcerative Colitis - 0.000000 +22087292 rs10928979 Femoral Neck Bone Geometry - 0.000001 +19247474 rs1889899 Smoking Behaviors|Cigarette Smoking - 0.000006 +17903305 rs1926657 Prostate Cancer|Breast - 0.000002 +24483146 rs11215406 Biomarkers - 0.000005 +25008200 rs7254232 Chronic Periodontitis - 0.000003 +22423221 rs7896518 Platelet Count|Mean Platelet Volume - 0.000000 +20932310 rs2986971 Τ Protein Levels - 0.000001 +20169177 rs2663052 Systemic Lupus Erythematosus - 0.000010 +20038947 rs1106634 Major Depression - 0.000001 +20169177 rs877819 Systemic Lupus Erythematosus - 0.000001 +24347629 rs2297778 Periodontal - 0.000010 +18483556 rs7183877 Hair Color|Skin Pigmentation - 0.000000 +22267201 rs12294104 Age Menopause - 0.000000 +21573004 rs12696304 Telomere Length - 0.000000 +19714205 rs1867612 Asthma - 0.000002 +22452962 rs13393577 Breast Cancer - 0.000000 +21738478 rs12748961 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +19343178 rs3131296 Stature - 0.000008 +18262040 rs4970834 LDL-cholesterol - 0.000000 +23738518 rs3213056 Reading|Language - 0.000003 +21297633 rs6920220 Ulcerative Colitis - 0.000000 +23259602 rs1383934 Dental Caries - 0.000000 +24376798 rs9275572 Chronic Hepatitis C - 0.000003 +24097068 rs4142995 Lipid Levels - 0.000000 +21935397 rs1805081 Extremely|Overweight|Body Mass Index - 0.000000 +24709693 rs12652364 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000001 +20081858 rs560887 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +22087292 rs10928979 Femoral Neck Bone Geometry - 0.000004 +19571809 rs17833407 Schizophrenia - 0.000003 +19401414 rs10811661 Type 2 Diabetes - 0.000000 +22993228 rs7204439 Lumbar Disc Degeneration - 0.000004 +24347629 rs11659841 Periodontal - 0.000009 +23423138 rs1399428 Mathematical Abilities|Dyslexia|Myosin - 0.000000 +22511988 rs1105879 Cell-Free Dna|Cardiovascular - 0.000000 +24483146 rs6441911 Biomarkers - 0.000000 +25760438 rs11140653 Type 2 Diabetes|Body Mass Index - 0.000000 +23326517 rs380390 Age-Related Macular Degeneration - 0.000000 +25188341 rs10498633 Dementias|Alzheimer's Disease - 0.000000 +25064009 rs199347 Parkinson’s Disease - 0.000000 +21602797 rs4760506 Cystic Fibrosis|Lung Disease - 0.000001 +21829393 rs7528684 Type 1 Diabetes|Autoantibody - 0.000000 +18483556 rs8039195 Hair Color|Skin Pigmentation - 0.000000 +21297633 rs2297441 Ulcerative Colitis - 0.000000 +19734902 rs9384428 Alzheimer's Disease - 0.000008 +21460840 rs3818361 Alzheimer’s Disease - 0.000000 +25310577 rs7896246 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +21223598 rs2659915 Aortic Root - 0.000004 +21533022 rs13204965 Bone Mineral Density - 0.000000 +21383967 rs7574865 Rheumatoid Arthritis|Celiac Disease - 0.000000 +22423221 rs151361 Platelet Count|Mean Platelet Volume - 0.000000 +21738478 rs7275212 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +19571809 rs17176973 Schizophrenia - 0.000002 +22470424 rs11071021 Amyotrophic Lateral Sclerosis - 0.000002 +24086445 rs9374441 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000008 +21297633 rs943072 Ulcerative Colitis - 0.000000 +21390209 rs624225 Late-Onset Alzheimer's Disease - 0.000005 +21873549 rs11558471 Type 2 Diabetes|Proinsulin Levels - 0.000001 +18262040 rs11668477 LDL-cholesterol - 0.000002 +25060954 rs2687481 Kinase|Hearing - 0.000000 +19343178 rs955748 Stature - 0.000000 +24709693 rs6506122 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000005 +23326239 rs2516049 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +20038947 rs11772451 Major Depression - 0.000006 +20442857 rs9381477 Phospholipase A - 0.000000 +22889924 rs7868992 Tourette Syndrome - 0.000002 +24094242 rs314253 Serum Alkaline Phosphatase Levels - 0.000000 +25086665 rs7190458 Pancreatic Cancer - 0.000004 +22745674 rs13006511 Coronary Artery Stenosis|Coronary Artery - 0.000000 +20729852 rs2274223 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +21935397 rs9816226 Extremely|Overweight|Body Mass Index - 0.000000 +22423221 rs342296 Platelet Count|Mean Platelet Volume - 0.000000 +19571809 rs1635239 Schizophrenia - 0.000003 +23698163 rs1395479 Serum Selenium - 0.000000 +18604267 rs3093030 Antigen|Icam-1 - 0.000000 +22666496 rs2157673 Cardiovascular Event - 0.000006 +21408207 rs7574865 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +21829393 rs2069762 Type 1 Diabetes|Autoantibody - 0.000001 +23834954 rs1054611 Sensory Disturbances|Split - 0.000006 +24800985 rs11231379 Birth - 0.000004 +24940741 rs7453920 Infection - 0.000009 +24740154 rs11664910 Prostate Cancer|Early-Onset - 0.000002 +18262040 rs4420638 LDL-cholesterol - 0.000000 +22085899 rs887829 Bilirubin Levels - 0.000000 +24836286 rs11196172 Colorectal Cancer - 0.000000 +22470424 rs12466517 Amyotrophic Lateral Sclerosis - 0.000006 +19096518 rs6709087 Glycated Hemoglobin - 0.000000 +22368281 rs4420638 LDL-c Response|Lpa - 0.000000 +19936222 rs1818702 Cholesterol|Plasma Lipoprotein Size - 0.000000 +19401414 rs4402960 Type 2 Diabetes - 0.000001 +20661308 rs10846917 Serum Calcium - 0.000006 +24379826 rs13131257 Serum Uric Acid Levels - 0.000000 +21750679 rs4329228 Systemic Sclerosis - 0.000007 +23738518 rs7202575 Reading|Language - 0.000001 +22087292 rs11998784 Femoral Neck Bone Geometry - 0.000001 +21980299 rs1465788 Type 1 Diabetes - 0.000002 +18604267 rs2278442 Antigen|Icam-1 - 0.000000 +20190752 rs917997 Celiac Disease - 0.000000 +21383967 rs17103033 Rheumatoid Arthritis|Celiac Disease - 0.000007 +23703922 rs13129697 Uric Acid Levels - 0.000000 +23408906 rs11624776 Thyroid|Thyroid-Related Traits|Differences - 0.000003 +23593239 rs6906622 Self-Employment - 0.000004 +19734902 rs1408077 Alzheimer's Disease - 0.000008 +22745674 rs9349379 Coronary Artery Stenosis|Coronary Artery - 0.000000 +21423239 rs9320964 Attempted Suicide - 0.000003 +21297633 rs2155219 Ulcerative Colitis - 0.000000 +23118916 rs11078697 Serum IgM - 0.000000 +23984888 rs4972983 Airway Responsiveness - 0.000009 +22291604 rs6964720 Lupus - 0.000000 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +22792070 rs2536189 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +21665990 rs641153 Age-Related Macular Degeneration - 0.000000 +20190752 rs6974491 Celiac Disease - 0.000005 +19801982 rs1430742 Bone Mineral Density - 0.000000 +22561518 rs11940117 Generalized Vitiligo - 0.000000 +24133439 rs1345405 Autistic-Like Traits - 0.000003 +18262040 rs538928 LDL-cholesterol - 0.000000 +23966204 rs7315843 Bitter Taste|Bitter Taste Perception - 0.000004 +21935397 rs4964926 Extremely|Overweight|Body Mass Index - 0.000007 +22001756 rs37403 Dengue Shock Syndrome - 0.000000 +21873549 rs11603334 Type 2 Diabetes|Proinsulin Levels - 0.000000 +23834954 rs1059513 Sensory Disturbances|Split - 0.000007 +21909108 rs1878406 Intima Media Thickness|Plaque - 0.000000 +22423221 rs12526480 Platelet Count|Mean Platelet Volume - 0.000000 +24449572 rs2104286 Rheumatoid Arthritis - 0.000001 +24755620 rs9849434 Glutamate|Alzheimer's Disease - 0.000002 +21297633 rs254560 Ulcerative Colitis - 0.000000 +24625756 rs4343 Intermediate Phenotypes - 0.000000 +22087292 rs10491633 Femoral Neck Bone Geometry - 0.000005 +24755620 rs377702 Glutamate|Alzheimer's Disease - 0.000000 +20932310 rs2928826 Τ Protein Levels - 0.000001 +21909110 rs2782980 Mean Arterial Pressure|Pulse Pressure - 0.000000 +25188341 rs7274581 Dementias|Alzheimer's Disease - 0.000000 +24097068 rs1047891 Lipid Levels - 0.000000 +24871463 rs4684256 Systemic Lupus Erythematosus Sle - 0.000000 +24483146 rs888468 Biomarkers - 0.000005 +21935397 rs4836133 Extremely|Overweight|Body Mass Index - 0.000000 +22666496 rs2129571 Cardiovascular Event - 0.000003 +24952745 rs11153730 Qt Interval|Calcium - 0.000000 +22843504 rs7711337 Autism Spectrum - 0.000001 +19197348 rs2159324 Complex Disease - 0.000000 +22843504 rs6110458 Autism Spectrum - 0.000000 +20072603 rs3212217 Osteoporosis - 0.000005 +22368281 rs4420638 LDL-c Response|Lpa - 0.000000 +22941191 rs17065417 Neuroblastoma - 0.000000 +25233373 rs7744813 Myopia|Hyperopia - 0.000006 +25390645 rs1551277 Anxiety - 0.000007 +21483430 rs12042938 Neurocognitive Phenotypes - 0.000000 +21935397 rs11034952 Extremely|Overweight|Body Mass Index - 0.000006 +22368281 rs395908 LDL-c Response|Lpa - 0.000000 +23408906 rs11726248 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24489884 rs17535407 Aggression - 0.000010 +17684544 rs2066847 Ibd Disease - 0.000000 +22359512 rs9932186 Sphingolipids - 0.000000 +20661308 rs7448017 Serum Calcium - 0.000002 +25742292 rs17809806 Parity - 0.000010 +25064009 rs9275326 Parkinson’s Disease - 0.000000 +24483146 rs7174876 Biomarkers - 0.000000 +22829776 rs6259 Globulin|Hormone|Steroid Hormone - 0.000000 +23817569 rs9266772 Allergy - 0.000000 +21076409 rs6801957 Conduction|Qrs Duration - 0.000000 +20195514 rs2817937 Primary Tooth Development - 0.000003 +19798445 rs2967625 Sphingolipid - 0.000000 +22412388 rs2241880 Crohn's Disease - 0.000000 +21901158 rs17431357 Insulin Resistance|Copy Number Variation - 0.000001 +25064009 rs8118008 Parkinson’s Disease - 0.000000 +23358160 rs4757144 Schizophrenia|Cytomegalovirus Infection|Infection Suggests - 0.000004 +21935397 rs987237 Extremely|Overweight|Body Mass Index - 0.000000 +24449572 rs6859219 Rheumatoid Arthritis - 0.000005 +25297839 rs116062713 Herpes Zoster - 0.000000 +23028483 rs3771166 Asthma - 0.000000 +19430480 rs3184504 Type 1 Diabetes - 0.000000 +23755828 rs12777823 Warfarin - 0.000007 +25742292 rs4295021 Parity - 0.000002 +19772629 rs7556447 Parkinson Disease|Onset - 0.000008 +25367360 rs4799964 Astigmatism|Refractive Error - 0.000001 +21490707 rs6495122 Caffeine Consumption|Cyp1A2 - 0.000005 +19571809 rs6938200 Schizophrenia - 0.000000 +25188341 rs2718058 Dementias|Alzheimer's Disease - 0.000000 +19247474 rs3027409 Smoking Behaviors|Cigarette Smoking - 0.000007 +24086445 rs9400701 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +21408207 rs7574865 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +25008200 rs1026477 Chronic Periodontitis - 0.000003 +19772629 rs17565841 Parkinson Disease|Onset - 0.000001 +25241909 rs1964516 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +20935630 rs10150332 Body Mass Index - 0.000000 +22087292 rs12098712 Femoral Neck Bone Geometry - 0.000009 +19197348 rs16996148 Complex Disease - 0.000000 +24740154 rs11839053 Prostate Cancer|Early-Onset - 0.000000 +22570697 rs3132671 Multiple Sclerosis - 0.000000 +19305408 rs2074518 Qt Interval Duration - 0.000000 +22916037 rs1303 Atherosclerosis - 0.000000 +22412388 rs9258260 Crohn's Disease - 0.000000 +23886662 rs2158177 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +22899653 rs1333040 Lung Cancer - 0.000000 +19247474 rs9289678 Smoking Behaviors|Cigarette Smoking - 0.000004 +21408207 rs4963128 Systemic Lupus Erythematosus|Autoantibody - 0.000004 +21935397 rs17150703 Extremely|Overweight|Body Mass Index - 0.000000 +21124946 rs11875173 Bone Mineral Density - 0.000009 +21876539 rs382140 Cyp1A2 - 0.000000 +19812673 rs12293188 Autism - 0.000001 +22792082 rs4328902 Asthma|Bronchodilator Response - 0.000006 +23326517 rs6857 Age-Related Macular Degeneration - 0.000001 +21533024 rs1049728 Icam-1 - 0.000000 +23984888 rs848788 Airway Responsiveness - 0.000001 +19772629 rs6936388 Parkinson Disease|Onset - 0.000009 +21876539 rs9526558 Cyp1A2 - 0.000001 +21943158 rs3213545 Cardiovascular-Related Traits - 0.000000 +25241909 rs139090846 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +25340798 rs4316 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000010 +19247474 rs6444087 Smoking Behaviors|Cigarette Smoking - 0.000009 +22843504 rs263035 Autism Spectrum - 0.000000 +23382691 rs1122979 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +20548946 rs1362756 Optic Disc - 0.000000 +21909115 rs633185 Cardiovascular Disease|Blood Pressure - 0.000000 +19571809 rs3800307 Schizophrenia - 0.000000 +17903305 rs4466137 Prostate Cancer|Breast - 0.000003 +24465431 rs16862964 Onset|Cardiovascular Disease|Diabetes - 0.000007 +23472185 rs3817963 Multiple Sclerosis|Oligoclonal Band - 0.000000 +22504420 rs3801387 Bone Mineral Density - 0.000000 +22470424 rs6840169 Amyotrophic Lateral Sclerosis - 0.000008 +23738518 rs13307587 Reading|Language - 0.000005 +23667675 rs314273 Age Menarche - 0.000002 +21983787 rs16891982 Melanoma - 0.000002 +24376798 rs9275572 Chronic Hepatitis C - 0.000000 +24945404 rs6726821 Bone Mineral Density|Bone - 0.000000 +22470424 rs5762919 Amyotrophic Lateral Sclerosis - 0.000000 +22570697 rs17421624 Multiple Sclerosis - 0.000000 +23263487 rs647161 Colorectal Cancer - 0.000000 +19668339 rs1888414 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000000 +22470424 rs6904956 Amyotrophic Lateral Sclerosis - 0.000009 +24223155 rs767531 Torsades De Pointes - 0.000007 +22412388 rs11190141 Crohn's Disease - 0.000001 +22479202 rs2980879 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +23263487 rs2423279 Colorectal Cancer - 0.000000 +21460840 rs9349407 Alzheimer’s Disease - 0.000000 +21390209 rs643629 Late-Onset Alzheimer's Disease - 0.000010 +19571809 rs12182446 Schizophrenia - 0.000000 +23738518 rs1357978 Reading|Language - 0.000005 +21935397 rs4929949 Extremely|Overweight|Body Mass Index - 0.000000 +18604267 rs507666 Antigen|Icam-1 - 0.000000 +21983787 rs13016963 Melanoma - 0.000000 +18604267 rs2075741 Antigen|Icam-1 - 0.000000 +19609347 rs1867226 Hypertension|Blood Pressure - 0.000001 +23704328 rs10740993 Tooth Eruption|Height - 0.000000 +20548946 rs17146964 Optic Disc - 0.000000 +23386860 rs10817052 Iron Intake|Type 2 Diabetes - 0.000004 +25064009 rs10797576 Parkinson’s Disease - 0.000000 +19609347 rs16877320 Hypertension|Blood Pressure - 0.000000 +22479191 rs2928148 Kidney|Follow-Up - 0.000000 +24871463 rs7574865 Systemic Lupus Erythematosus Sle - 0.000000 +22044751 rs12785341 Chronic Kidney Disease - 0.000008 +20932310 rs2495832 Τ Protein Levels - 0.000001 +21552555 rs7190492 Obesity|Obesity-Related Traits - 0.000000 +23844046 rs4420638 C-Reactive Protein - 0.000000 +23900074 rs6060627 Telomere Length|Cancer - 0.000001 +21738478 rs2516399 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +23408906 rs9472138 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21658281 rs4621553 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +19503088 rs13017599 Rheumatoid Arthritis - 0.000000 +21980494 rs2420371 Venous Thrombosis - 0.000000 +18483556 rs4785763 Hair Color|Skin Pigmentation - 0.000000 +25162662 rs1550388 Serum Ferritin - 0.000000 +23979607 rs6888413 Borderline Personality - 0.000000 +22832960 rs7387468 Temperament Character Inventory - 0.000003 +19197348 rs3846663 Complex Disease - 0.000005 +19801982 rs16921914 Bone Mineral Density - 0.000000 +23636237 rs4683038 Analysis - 0.000008 +20548946 rs1926320 Optic Disc - 0.000000 +21379329 rs2075650 Late-Onset Alzheimer's Disease - 0.000000 +22368281 rs10844779 LDL-c Response|Lpa - 0.000000 +19197348 rs2849176 Complex Disease - 0.000000 +21750679 rs2056626 Systemic Sclerosis - 0.000001 +19197348 rs10849788 Complex Disease - 0.000009 +25147783 rs12118362 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +18483556 rs12203592 Hair Color|Skin Pigmentation - 0.000000 +21980299 rs924043 Type 1 Diabetes - 0.000000 +20190752 rs864537 Celiac Disease - 0.000000 +24871463 rs2764208 Systemic Lupus Erythematosus Sle - 0.000004 +23886662 rs2897443 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +25629512 rs3894326 Age-Related Macular Degeneration - 0.000006 +19197348 rs2071521 Complex Disease - 0.000000 +25367360 rs10496034 Astigmatism|Refractive Error - 0.000002 +20953186 rs13210247 Psoriasis|Psoriatic Arthritis - 0.000000 +24740154 rs7931342 Prostate Cancer|Early-Onset - 0.000001 +19343178 rs3116607 Stature - 0.000000 +20038947 rs1612122 Major Depression - 0.000007 +20932310 rs1022442 Τ Protein Levels - 0.000000 +24511991 rs2338971 Parkinson’s Disease - 0.000000 +22116950 rs6543833 Ovarian Reserve - 0.000000 +18840781 rs2041670 Type 1 Diabetes - 0.000000 +22843504 rs4150167 Autism Spectrum - 0.000000 +20072603 rs6711417 Osteoporosis - 0.000005 +19056611 rs901130 Type 2 Diabetes - 0.000002 +21437268 rs7431530 Cancers|Conducted|Upper Aerodigestive Tract - 0.000002 +21423239 rs7296262 Attempted Suicide - 0.000001 +23326239 rs7194 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +24166486 rs12666575 Schizophrenia - 0.000000 +19772629 rs7076519 Parkinson Disease|Onset - 0.000001 +23900074 rs1317082 Telomere Length|Cancer - 0.000000 +23636237 rs838145 Analysis - 0.000000 +24068947 rs7182874 Brain - 0.000000 +23979607 rs73772260 Borderline Personality - 0.000000 +19430480 rs1990760 Type 1 Diabetes - 0.000000 +22916037 rs2306786 Atherosclerosis - 0.000000 +22359512 rs174479 Sphingolipids - 0.000000 +21297633 rs11209026 Ulcerative Colitis - 0.000000 +21779176 rs9357271 Restless Legs Syndrome - 0.000000 +21448238 rs11636768 Migraine - 0.000000 +25188341 rs6656401 Dementias|Alzheimer's Disease - 0.000000 +19571809 rs6932590 Schizophrenia - 0.000000 +22719876 rs3810622 Non-Alcoholic Fatty Liver Disease|Liver Disease - 0.000000 +24509480 rs17106184 Type 2 Diabetes - 0.000000 +20421936 rs516175 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +23793025 rs2274316 Migraine - 0.000000 +25760438 rs1347857 Type 2 Diabetes|Body Mass Index - 0.000002 +24586186 rs37370 Metabolic Traits|Metabolite-Disease - 0.000000 +23667675 rs310008 Age Menarche - 0.000004 +19412175 rs7587476 Neuroblastoma - 0.000000 +23703922 rs10022911 Uric Acid Levels - 0.000000 +23979607 rs6894288 Borderline Personality - 0.000001 +22832960 rs1494508 Temperament Character Inventory - 0.000002 +24516586 rs733175 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000002 +23408906 rs13015993 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +20038947 rs2405829 Major Depression - 0.000004 +18483556 rs164741 Hair Color|Skin Pigmentation - 0.000000 +22359512 rs870288 Sphingolipids - 0.000000 +20442857 rs11820589 Phospholipase A - 0.000000 +23984888 rs614664 Airway Responsiveness - 0.000006 +19668339 rs10867752 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000003 +23459936 rs11925054 Chronic Periodontitis - 0.000001 +23382691 rs2108225 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24094242 rs1383023 Serum Alkaline Phosphatase Levels - 0.000002 +23817569 rs6021270 Allergy - 0.000000 +20038947 rs2147256 Major Depression - 0.000009 +20442857 rs12211537 Phospholipase A - 0.000000 +23307926 rs2303369 Menopause - 0.000000 +19300500 rs1017444 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000003 +22685421 rs11954386 Ocular Axial Length|High Myopia - 0.000009 +20442857 rs599839 Phospholipase A - 0.000000 +25628645 rs4531814 Homoharringtonine - 0.000010 +23382691 rs1456893 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +22685421 rs4557020 Ocular Axial Length|High Myopia - 0.000000 +20548946 rs1063192 Optic Disc - 0.000000 +19197348 rs6589567 Complex Disease - 0.000000 +23636237 rs1350036 Analysis - 0.000000 +22470424 rs7242525 Amyotrophic Lateral Sclerosis - 0.000006 +23967269 rs10404342 Mite-Specific IgEs|Asthma - 0.000008 +24871463 rs6946131 Systemic Lupus Erythematosus Sle - 0.000002 +21901158 rs1401492 Insulin Resistance|Copy Number Variation - 0.000005 +20686608 rs6711606 Pancreatic Cancer - 0.000004 +21483430 rs823161 Neurocognitive Phenotypes - 0.000000 +23382691 rs1451375 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000006 +19798445 rs4902242 Sphingolipid - 0.000000 +24999842 Rs8081319 Celiac Disease|Celiac - 0.000001 +23092984 rs10865974 Bipolar Disorder - 0.000002 +25147783 rs492602 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +19430480 rs3825932 Type 1 Diabetes - 0.000000 +22916037 rs6511720 Atherosclerosis - 0.000000 +19300500 rs7707619 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000004 +23028483 rs2977724 Asthma - 0.000006 +24871463 rs10857712 Systemic Lupus Erythematosus Sle - 0.000003 +24513273 rs7188445 Serum Uric Acid - 0.000000 +24097068 rs3198697 Lipid Levels - 0.000000 +18483556 rs7195066 Hair Color|Skin Pigmentation - 0.000000 +21379329 rs201119 Late-Onset Alzheimer's Disease - 0.000000 +25188341 rs190982 Dementias|Alzheimer's Disease - 0.000000 +20861866 rs2230199 Age-Related Macular Degeneration - 0.000000 +19812673 rs7766973 Autism - 0.000001 +23593239 rs994208 Self-Employment - 0.000006 +24009623 rs17664713 Biomarker - 0.000005 +20169177 rs7922169 Systemic Lupus Erythematosus - 0.000010 +24166486 rs13199772 Schizophrenia - 0.000000 +19503597 rs505802 Uric Acid - 0.000000 +22843504 rs12726299 Autism Spectrum - 0.000000 +23958962 rs11944332 Cocaine Dependence - 0.000000 +22561518 rs4785587 Generalized Vitiligo - 0.000000 +21460840 rs11767557 Alzheimer’s Disease - 0.000000 +19801982 rs6426749 Bone Mineral Density - 0.000000 +22843504 rs1328244 Autism Spectrum - 0.000001 +20548946 rs2159128 Optic Disc - 0.000000 +21533022 rs17563605 Bone Mineral Density - 0.000000 +22832961 rs4420638 Alzheimer's Disease - 0.000000 +24999842 rs11938795 Celiac Disease|Celiac - 0.000000 +19936222 rs7938647 Cholesterol|Plasma Lipoprotein Size - 0.000000 +25367360 rs925931 Astigmatism|Refractive Error - 0.000000 +25367360 rs17795358 Astigmatism|Refractive Error - 0.000000 +23844046 rs7310409 C-Reactive Protein - 0.000000 +24086445 rs12581163 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000006 +25064009 rs11158026 Parkinson’s Disease - 0.000000 +23984888 rs4972983 Airway Responsiveness - 0.000009 +19197348 rs1892534 Complex Disease - 0.000000 +23593239 rs9578700 Self-Employment - 0.000007 +21552555 rs1121980 Obesity|Obesity-Related Traits - 0.000000 +21408207 rs525410 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +24324648 rs12173787 Serum IgE - 0.000000 +19571809 rs13212921 Schizophrenia - 0.000000 +23593239 rs6825440 Self-Employment - 0.000004 +21379329 rs7814569 Late-Onset Alzheimer's Disease - 0.000001 +22247754 rs6565373 Arrhythmias - 0.000010 +23401653 rs6554163 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000010 +23509613 rs8060581 Antiphospholipid Antibodies - 0.000001 +23636237 rs10508303 Analysis - 0.000005 +21779181 rs443198 Systemic Sclerosis - 0.000000 +19503597 rs734553 Uric Acid - 0.000000 +19812673 rs10513026 Autism - 0.000005 +25064009 rs12456492 Parkinson’s Disease - 0.000000 +22470424 rs3113494 Amyotrophic Lateral Sclerosis - 0.000001 +22693455 rs8090011 Obese|Type 2 Diabetes - 0.000000 +24025145 rs11666971 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000008 +19197348 rs2808693 Complex Disease - 0.000010 +22792071 rs9525638 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +21483430 rs2082552 Neurocognitive Phenotypes - 0.000000 +22675492 rs4815670 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000010 +20861866 rs3750848 Age-Related Macular Degeneration - 0.000000 +18776929 rs4850447 Hip Bone Size|Females - 0.000002 +19571809 rs13199775 Schizophrenia - 0.000000 +22452962 rs3803662 Breast Cancer - 0.000000 +23386860 rs7048110 Iron Intake|Type 2 Diabetes - 0.000003 +24483146 rs8024695 Biomarkers - 0.000003 +20442857 rs12286037 Phospholipase A - 0.000000 +24945404 rs2908004 Bone Mineral Density|Bone - 0.000000 +24999842 rs9286879 Celiac Disease|Celiac - 0.000001 +20686608 rs1585440 Pancreatic Cancer - 0.000009 +20169177 rs877819 Systemic Lupus Erythematosus - 0.000000 +20364137 rs1333040 Intracranial Aneurysm - 0.000000 +17903303 rs10483853 Atherosclerosis - 0.000010 +22889924 rs6539267 Tourette Syndrome - 0.000007 +19801982 rs2566755 Bone Mineral Density - 0.000000 +24014518 rs11692675 Epilepsy|Febrile Seizures - 0.000001 +24945404 rs1262476 Bone Mineral Density|Bone - 0.000000 +23459936 rs3826782 Chronic Periodontitis - 0.000004 +22843504 rs17083037 Autism Spectrum - 0.000000 +24714607 rs2255953 Chronic Mucus Hypersecretion - 0.000004 +23703922 rs6832439 Uric Acid Levels - 0.000000 +22412388 rs13003464 Crohn's Disease - 0.000000 +20661308 rs1801725 Serum Calcium - 0.000000 +25147783 rs7893634 Ischemic Stroke|Vitamin|Folate Levels - 0.000001 +24097068 rs12748152 Lipid Levels - 0.000000 +24097068 rs13315871 Lipid Levels - 0.000000 +21383967 rs1020388 Rheumatoid Arthritis|Celiac Disease - 0.000000 +19247474 rs7553864 Smoking Behaviors|Cigarette Smoking - 0.000003 +23593239 rs9557259 Self-Employment - 0.000005 +19801982 rs87938 Bone Mineral Density - 0.000000 +21408207 rs6049839 Systemic Lupus Erythematosus|Autoantibody - 0.000008 +21909115 rs1378942 Cardiovascular Disease|Blood Pressure - 0.000000 +22470424 rs7571323 Amyotrophic Lateral Sclerosis - 0.000004 +19343178 rs7533282 Stature - 0.000007 +20190752 rs2298428 Celiac Disease - 0.000000 +23563607 rs1594829 Anthropometric Traits - 0.000000 +23817569 rs10893845 Allergy - 0.000001 +23936387 rs1247697 Celiac Disease - 0.000001 +22479202 rs3001032 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +22504420 rs4727338 Bone Mineral Density - 0.000000 +25367360 rs6688613 Astigmatism|Refractive Error - 0.000003 +23509613 rs11975235 Antiphospholipid Antibodies - 0.000003 +24709693 rs10084630 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000009 +20339536 rs964184 Lipid-Lowering Response|Response Statins - 0.000000 +23936387 rs12144971 Celiac Disease - 0.000000 +24097068 rs314253 Lipid Levels - 0.000000 +23936387 rs11836636 Celiac Disease - 0.000000 +19609347 rs16853574 Hypertension|Blood Pressure - 0.000005 +22479191 rs12124078 Kidney|Follow-Up - 0.000000 +23593239 rs3742467 Self-Employment - 0.000009 +24964207 rs3781878 Suicidal Ideation|Attempts Suicidal|Suicide Attempts - 0.000002 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +23350875 rs11987193 Colorectal Cancer - 0.000010 +21124955 rs4638289 Serum Amyloid A|Type 2 Diabetes - 0.000000 +22558097 rs887829 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +23703922 rs4447863 Uric Acid Levels - 0.000002 +24483146 rs17564430 Biomarkers - 0.000008 +24952745 rs1961102 Qt Interval|Calcium - 0.000000 +20038947 rs6930508 Major Depression - 0.000005 +21827660 rs640030 Increased Disease Risk - 0.000002 +24836286 rs10795668 Colorectal Cancer - 0.000000 +18846228 rs2251746 Serum IgE Levels - 0.000000 +19247474 rs719015 Smoking Behaviors|Cigarette Smoking - 0.000004 +23382691 rs1049110 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24755620 rs1552244 Glutamate|Alzheimer's Disease - 0.000002 +22479202 rs7955516 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +23936387 rs10884387 Celiac Disease - 0.000009 +22504420 rs7084921 Bone Mineral Density - 0.000000 +17903305 rs1876206 Prostate Cancer|Breast - 0.000006 +22423221 rs342293 Platelet Count|Mean Platelet Volume - 0.000000 +23386860 rs470089 Iron Intake|Type 2 Diabetes - 0.000009 +23636237 rs2840445 Analysis - 0.000001 +22993228 rs4554859 Lumbar Disc Degeneration - 0.000009 +24483146 rs28668016 Biomarkers - 0.000005 +21909115 rs17367504 Cardiovascular Disease|Blood Pressure - 0.000000 +22412388 rs11229030 Crohn's Disease - 0.000000 +19571809 rs13025591 Schizophrenia - 0.000000 +24489884 rs16924133 Aggression - 0.000002 +20485516 rs2755237 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +23437003 rs7839059 Volumetric Bone Mineral Densities - 0.000000 +23817569 rs2056417 Allergy - 0.000000 +24094242 rs281377 Serum Alkaline Phosphatase Levels - 0.000000 +20932310 rs2899472 Τ Protein Levels - 0.000000 +25241909 rs7671167 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +20585626 rs4784227 Breast Cancer - 0.000000 +21935397 rs6758546 Extremely|Overweight|Body Mass Index - 0.000009 +23259602 rs1953743 Dental Caries - 0.000002 +25367360 rs1944146 Astigmatism|Refractive Error - 0.000003 +22359512 rs17148090 Sphingolipids - 0.000000 +21399635 rs485499 Primary Biliary Cirrhosis - 0.000000 +21379329 rs201124 Late-Onset Alzheimer's Disease - 0.000001 +19772629 rs4791571 Parkinson Disease|Onset - 0.000006 +24483146 rs17564430 Biomarkers - 0.000002 +21460840 rs744373 Alzheimer’s Disease - 0.000000 +21998597 rs6258 Serum Testosterone - 0.000000 +25310577 rs7090445 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +24390342 rs2671692 Rheumatoid Arthritis|Biology - 0.000000 +19247474 rs7050529 Smoking Behaviors|Cigarette Smoking - 0.000003 +19343178 rs3767141 Stature - 0.000000 +19122664 rs6426833 Ulcerative Colitis - 0.000000 +20190752 rs13314993 Celiac Disease - 0.000000 +23472165 rs2235529 Endometriosis - 0.000000 +20062060 rs11708996 Pr Interval - 0.000000 +25367360 rs428445 Astigmatism|Refractive Error - 0.000002 +18483556 rs8049897 Hair Color|Skin Pigmentation - 0.000000 +24097068 rs12801636 Lipid Levels - 0.000000 +19772629 rs1355637 Parkinson Disease|Onset - 0.000005 +19503597 rs780094 Uric Acid - 0.000000 +22087292 rs2062713 Femoral Neck Bone Geometry - 0.000007 +20038947 rs12526133 Major Depression - 0.000002 +24097068 rs138777 Lipid Levels - 0.000000 +20972438 rs710521 Bladder Cancer|Bladder - 0.000000 +18840781 rs12931878 Type 1 Diabetes - 0.000000 +24133439 rs4964491 Autistic-Like Traits - 0.000006 +25390645 rs2115691 Anxiety - 0.000004 +19096518 rs13266634 Glycated Hemoglobin - 0.000000 +21980299 rs229541 Type 1 Diabetes - 0.000004 +21399635 rs860413 Primary Biliary Cirrhosis - 0.000000 +24166486 rs3778969 Schizophrenia - 0.000000 +21552555 rs8050136 Obesity|Obesity-Related Traits - 0.000000 +23593202 rs13230316 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +23666240 rs2072499 Testicular Cancer - 0.000000 +22452962 rs865686 Breast Cancer - 0.000000 +22570697 rs757262 Multiple Sclerosis - 0.000000 +24755620 rs6859 Glutamate|Alzheimer's Disease - 0.000000 +24740154 rs11228583 Prostate Cancer|Early-Onset - 0.000000 +18776929 rs992603 Hip Bone Size|Females - 0.000000 +23408906 rs11624776 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +25340798 rs2228145 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +23472185 rs4646333 Multiple Sclerosis|Oligoclonal Band - 0.000002 +24086445 rs7746324 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000003 +22087292 rs4804662 Femoral Neck Bone Geometry - 0.000008 +24133439 rs11575088 Autistic-Like Traits - 0.000003 +22675492 rs727428 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000000 +21804549 rs2453626 Asthma - 0.000000 +20548946 rs10483727 Optic Disc - 0.000000 +24097068 rs2710642 Lipid Levels - 0.000000 +23382691 rs11978267 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24740154 rs16911551 Prostate Cancer|Early-Onset - 0.000006 +22428042 rs518394 Glaucoma|Optic-Nerve - 0.000000 +18369459 rs7993214 Psoriasis|Psoriatic Arthritis|New Disease - 0.000002 +20190752 rs13098911 Celiac Disease - 0.000000 +18262040 rs12740374 LDL-cholesterol - 0.000000 +23704328 rs10740993 Tooth Eruption|Height - 0.000000 +17903305 rs2075555 Prostate Cancer|Breast - 0.000000 +23984888 rs848788 Airway Responsiveness - 0.000001 +23870195 rs1333042 Coronary Artery|Coronary Artery Calcification - 0.000000 +23307926 rs16991615 Menopause - 0.000000 +22916037 rs1912826 Atherosclerosis - 0.000000 +22359512 rs1566039 Sphingolipids - 0.000000 +19772629 rs17817190 Parkinson Disease|Onset - 0.000002 +18604267 rs10409243 Antigen|Icam-1 - 0.000000 +21297633 rs2836878 Ulcerative Colitis - 0.000000 +24068962 rs1550532 Serum Calcium - 0.000000 +19557197 rs7932813 Distribution|Adiposity|Waist Circumference - 0.000005 +23297363 rs11066188 Tetralogy Fallot - 0.000000 +22479419 rs461409 Treatment Refractory Schizophrenia - 0.000003 +20548944 rs6543018 Osteoporosis-Related Traits|Gene Expression Profiling - 0.000000 +18846228 rs2511211 Serum IgE Levels - 0.000000 +21602797 rs12793173 Cystic Fibrosis|Lung Disease - 0.000000 +22479191 rs11078903 Kidney|Follow-Up - 0.000000 +23472185 rs1378321 Multiple Sclerosis|Oligoclonal Band - 0.000002 +23979607 rs6866910 Borderline Personality - 0.000001 +25064009 rs62120679 Parkinson’s Disease - 0.000000 +21946350 rs153916 Lung Function|Follow-Up - 0.000000 +17903304 rs2549513 Cardiovascular Disease - 0.000010 +23386860 rs10980495 Iron Intake|Type 2 Diabetes - 0.000005 +23583980 rs2334659 Pulmonary Fibrosis - 0.000004 +19197348 rs7396835 Complex Disease - 0.000000 +22792070 rs718766 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +25162662 rs3791767 Serum Ferritin - 0.000000 +23300701 rs751147 Colorectal Cancer - 0.000000 +25367360 rs2309717 Astigmatism|Refractive Error - 0.000001 +19300500 rs13147758 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000002 +20522523 rs1490157 Partial Epilepsies - 0.000005 +25340798 rs11574428 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +21223598 rs6045676 Aortic Root - 0.000000 +21750679 rs13021401 Systemic Sclerosis - 0.000003 +24166486 rs34706883 Schizophrenia - 0.000000 +22504420 rs7851693 Bone Mineral Density - 0.000000 +21738478 rs9373124 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +22558097 rs4148326 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +24836286 rs10505477 Colorectal Cancer - 0.000000 +22238593 rs7107217 Type 2 Diabetes - 0.000000 +25102180 rs2244020 Type 2 Diabetes - 0.000000 +24097068 rs3780181 Lipid Levels - 0.000000 +24390342 rs28411352 Rheumatoid Arthritis|Biology - 0.000000 +24166486 rs2710323 Schizophrenia - 0.000000 +22368281 rs863626 LDL-c Response|Lpa - 0.000000 +23738518 rs1928007 Reading|Language - 0.000005 +20190752 rs13010713 Celiac Disease - 0.000000 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +24625756 rs4343 Intermediate Phenotypes - 0.000000 +19557197 rs17537900 Distribution|Adiposity|Waist Circumference - 0.000007 +21983787 rs1801516 Melanoma - 0.000000 +22993228 rs6936004 Lumbar Disc Degeneration - 0.000000 +24516586 rs11723970 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000008 +19801982 rs2062377 Bone Mineral Density - 0.000000 +24023777 rs2047176 Adolescent Idiopathic Scoliosis - 0.000002 +21700879 rs2468677 Adiponectin Levels - 0.000001 +25436638 rs9915657 Serum Thyroid Stimulating Hormone - 0.000000 +23386860 rs10817049 Iron Intake|Type 2 Diabetes - 0.000002 +23704328 rs17563 Tooth Eruption|Height - 0.000000 +24390342 rs4409785 Rheumatoid Arthritis|Biology - 0.000000 +23886662 rs2844509 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +23593202 rs4141232 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +21423239 rs12801214 Attempted Suicide - 0.000009 +24516586 rs12508991 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000000 +21901158 rs9792548 Insulin Resistance|Copy Number Variation - 0.000004 +23386860 rs10448267 Iron Intake|Type 2 Diabetes - 0.000007 +18483556 rs7188458 Hair Color|Skin Pigmentation - 0.000000 +24097068 rs2602836 Lipid Levels - 0.000000 +18776929 rs7595412 Hip Bone Size|Females - 0.000000 +23349640 rs9268853 Malignancies - 0.000000 +18823527 Rs439401 Late-Onset Alzheimer's Disease - 0.000000 +21390209 rs6859 Late-Onset Alzheimer's Disease - 0.000000 +21437268 rs1229984 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +19430480 rs4788084 Type 1 Diabetes - 0.000000 +23583980 rs3829223 Pulmonary Fibrosis - 0.000007 +24121790 rs2178146 Barrett’s Esophagus|Esophageal Adenocarcinoma - 0.000002 +22344219 rs574367 Body Mass Index - 0.000000 +21909115 rs419076 Cardiovascular Disease|Blood Pressure - 0.000000 +19503597 rs12356193 Uric Acid - 0.000000 +19454037 rs10499859 Left Ventricular Mass - 0.000003 +25390645 rs17105932 Anxiety - 0.000007 +19343178 rs4711269 Stature - 0.000000 +21297633 rs1893217 Ulcerative Colitis - 0.000000 +19557197 rs4420638 Distribution|Adiposity|Waist Circumference - 0.000004 +18483556 rs258322 Hair Color|Skin Pigmentation - 0.000000 +23382691 rs7158173 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000004 +25147783 rs1801222 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +21390209 rs12664598 Late-Onset Alzheimer's Disease - 0.000007 +20190752 rs6974491 Celiac Disease - 0.000000 +21552555 rs7697609 Obesity|Obesity-Related Traits - 0.000005 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +19343178 rs2011962 Stature - 0.000000 +24513273 rs12356193 Serum Uric Acid - 0.000000 +22693455 rs13266634 Obese|Type 2 Diabetes - 0.000000 +23056639 rs4644 Lectin - 0.000000 +22666496 rs16861467 Cardiovascular Event - 0.000002 +20195514 rs6435957 Primary Tooth Development - 0.000000 +22479202 rs925735 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +20418485 rs2282679 Vitamin D Levels - 0.000000 +18369459 rs10484554 Psoriasis|Psoriatic Arthritis|New Disease - 0.000000 +21423239 rs6076080 Attempted Suicide - 0.000009 +23958962 rs2629540 Cocaine Dependence - 0.000000 +25310577 rs4948492 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +19430480 rs11203203 Type 1 Diabetes - 0.000000 +18483556 rs7204478 Hair Color|Skin Pigmentation - 0.000000 +22306652 rs2200733 Ischemic Stroke - 0.000000 +23761726 rs1151008 Corneal Astigmatism|Platelet-Derived Growth Factor - 0.000001 +22291604 rs9501626 Lupus - 0.000000 +24908248 rs2736100 Telomere Length|Glioma - 0.000000 +21533022 rs1054627 Bone Mineral Density - 0.000001 +25241909 rs13141641 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +20858683 rs1800562 Hemoglobin A - 0.000000 +23028483 rs11071559 Asthma - 0.000000 +19772629 rs12829697 Parkinson Disease|Onset - 0.000007 +23703922 rs17002988 Uric Acid Levels - 0.000006 +21829393 rs3087243 Type 1 Diabetes|Autoantibody - 0.000000 +23408906 rs4804416 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21935397 rs9936385 Extremely|Overweight|Body Mass Index - 0.000000 +22693459 rs12565727 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +23028483 rs2244012 Asthma - 0.000000 +21437268 rs4767364 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +22843504 rs9635542 Autism Spectrum - 0.000000 +20548946 rs1900004 Optic Disc - 0.000000 +21390209 rs1217745 Late-Onset Alzheimer's Disease - 0.000003 +19448621 rs7246479 Age Menarche|Menopause - 0.000000 +22452962 rs2380205 Breast Cancer - 0.000000 +20442857 rs4420638 Phospholipase A - 0.000000 +23382691 rs6421315 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +22916037 rs10127775 Atherosclerosis - 0.000000 +25367360 rs11690252 Astigmatism|Refractive Error - 0.000003 +18262040 rs599839 LDL-cholesterol - 0.000000 +24945404 rs2235529 Bone Mineral Density|Bone - 0.000000 +23793025 rs11172113 Migraine - 0.000000 +23544013 rs3814113 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +18823527 Rs6859 Late-Onset Alzheimer's Disease - 0.000000 +21829393 rs11594656 Type 1 Diabetes|Autoantibody - 0.000002 +25742292 rs11020998 Parity - 0.000007 +24133439 rs2883805 Autistic-Like Traits - 0.000003 +21423239 rs1543002 Attempted Suicide - 0.000005 +24244560 rs1799884 Diabetic Retinopathy|Chronic Kidney Disease|Hemoglobin A - 0.000000 +23455636 rs9542236 Age-Related Macular Degeneration - 0.000000 +21738478 rs10147992 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +20932310 rs2493624 Τ Protein Levels - 0.000001 +23259602 rs635808 Dental Caries - 0.000000 +22087292 rs854140 Femoral Neck Bone Geometry - 0.000002 +21379329 rs10489216 Late-Onset Alzheimer's Disease - 0.000001 +23565137 rs3737529 Late-Onset Alzheimer’s Disease - 0.000004 +22291604 rs2254546 Lupus - 0.000000 +23382691 rs9296009 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +25367360 rs17795388 Astigmatism|Refractive Error - 0.000000 +21738478 rs4328821 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +23593239 rs3847697 Self-Employment - 0.000007 +21998595 rs4315565 Height - 0.000000 +19056611 rs7132840 Type 2 Diabetes - 0.000000 +24086445 rs10277664 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000000 +23667675 rs7114467 Age Menarche - 0.000009 +19571809 rs926300 Schizophrenia - 0.000000 +24133439 rs1345406 Autistic-Like Traits - 0.000003 +19936222 rs3129882 Cholesterol|Plasma Lipoprotein Size - 0.000000 +22087292 rs4804662 Femoral Neck Bone Geometry - 0.000000 +23326517 rs6480975 Age-Related Macular Degeneration - 0.000003 +23326517 rs2049622 Age-Related Macular Degeneration - 0.000009 +19714205 rs2378383 Asthma - 0.000007 +25436638 rs11755845 Serum Thyroid Stimulating Hormone - 0.000000 +22470424 rs564053 Amyotrophic Lateral Sclerosis - 0.000010 +23646285 rs2174009 Hypersomnia - 0.000001 +24513273 rs4148152 Serum Uric Acid - 0.000000 +23297363 rs233722 Tetralogy Fallot - 0.000000 +17903293 rs2808629 Biomarker Traits - 0.000000 +19343178 rs6570507 Stature - 0.000000 +25241909 rs12914385 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000001 +21297633 rs7554511 Ulcerative Colitis - 0.000000 +18483556 rs28777 Hair Color|Skin Pigmentation - 0.000000 +21408207 rs10488631 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +19096518 rs1402837 Glycated Hemoglobin - 0.000000 +22085899 rs4149056 Bilirubin Levels - 0.000000 +20953189 rs12586317 Psoriasis - 0.000000 +20190752 rs6806528 Celiac Disease - 0.000000 +22561518 rs4409785 Generalized Vitiligo - 0.000000 +21946350 rs2865531 Lung Function|Follow-Up - 0.000000 +23326517 rs1329424 Age-Related Macular Degeneration - 0.000000 +24999842 rs13132933 Celiac Disease|Celiac - 0.000000 +23974872 rs4801131 Schizophrenia - 0.000000 +24952745 rs2273905 Qt Interval|Calcium - 0.000000 +19305408 rs12143842 Qt Interval Duration - 0.000000 +17903292 rs723464 Kidney|Endocrine-Related Traits - 0.000010 +24097068 rs10019888 Lipid Levels - 0.000000 +23636237 rs1549309 Analysis - 0.000002 +19197348 rs16874905 Complex Disease - 0.000010 +24952745 rs7122937 Qt Interval|Calcium - 0.000000 +23437003 rs9287237 Volumetric Bone Mineral Densities - 0.000000 +22760553 rs16965962 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000000 +25436638 rs1382879 Serum Thyroid Stimulating Hormone - 0.000000 +23284291 rs7594321 Pulmonary Function|Lung Function - 0.000000 +23936387 rs11952677 Celiac Disease - 0.000008 +21533175 rs11761528 Dehydroepiandrosterone Sulphate - 0.000000 +21779181 rs3129763 Systemic Sclerosis - 0.000000 +22792082 rs10940113 Asthma|Bronchodilator Response - 0.000001 +21946350 rs1036429 Lung Function|Follow-Up - 0.000000 +24166486 rs12699477 Schizophrenia - 0.000000 +21901158 rs6576507 Insulin Resistance|Copy Number Variation - 0.000007 +23326517 rs10737680 Age-Related Macular Degeneration - 0.000000 +18464913 rs505922 Protein Quantitative Trait|Genome|Association - 0.000000 +24945404 rs10835187 Bone Mineral Density|Bone - 0.000000 +20548946 rs1192415 Optic Disc - 0.000000 +24945404 rs9525638 Bone Mineral Density|Bone - 0.000000 +24952745 rs6793245 Qt Interval|Calcium - 0.000000 +19197348 rs17145738 Complex Disease - 0.000000 +22760553 rs3810046 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000000 +23326517 rs3764261 Age-Related Macular Degeneration - 0.000001 +24133439 rs16946880 Autistic-Like Traits - 0.000003 +20173748 rs7671167 Chronic Obstructive Pulmonary Disease - 0.000000 +21297633 rs35675666 Ulcerative Colitis - 0.000000 +21076409 rs1886512 Conduction|Qrs Duration - 0.000000 +19305408 rs846111 Qt Interval Duration - 0.000000 +24390342 rs10774624 Rheumatoid Arthritis|Biology - 0.000000 +24952745 rs246196 Qt Interval|Calcium - 0.000000 +18483556 rs1540771 Hair Color|Skin Pigmentation - 0.000003 +21829393 rs4971154 Type 1 Diabetes|Autoantibody - 0.000000 +21223598 rs4876662 Aortic Root - 0.000002 +21364930 rs1046099 Hiv-1 - 0.000010 +21552555 rs9930333 Obesity|Obesity-Related Traits - 0.000000 +20935630 rs11847697 Body Mass Index - 0.000000 +19668339 rs10074258 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000000 +19197348 rs693 Complex Disease - 0.000000 +25378659 rs2100944 Long-Chain Saturated Fatty Acids - 0.000000 +25310577 rs9415635 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +24390342 rs9826828 Rheumatoid Arthritis|Biology - 0.000000 +24886709 rs118146573 Lipid - 0.000000 +23974872 rs6550435 Schizophrenia - 0.000000 +19915575 rs11240572 Parkinson’s Disease - 0.000001 +23936387 rs10946659 Celiac Disease - 0.000002 +22087292 rs1389728 Femoral Neck Bone Geometry - 0.000001 +23326239 rs9273327 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23028483 rs4714586 Asthma - 0.000009 +19734902 rs157580 Alzheimer's Disease - 0.000000 +18776929 rs4850833 Hip Bone Size|Females - 0.000007 +19300482 rs11219732 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000004 +24952745 rs2072413 Qt Interval|Calcium - 0.000000 +19412176 rs12587781 Narcolepsy - 0.000000 +23958962 rs72840936 Cocaine Dependence - 0.000001 +21502949 rs1299288 Brain - 0.000004 +19668339 rs12657273 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000009 +25367360 rs1327866 Astigmatism|Refractive Error - 0.000003 +20442857 rs12528857 Phospholipase A - 0.000000 +22412388 rs12677663 Crohn's Disease - 0.000000 +25742292 rs7239865 Parity - 0.000006 +21298047 rs12273605 European-Origin|Substance Dependence - 0.000004 +22558097 rs3771341 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +24097068 rs267733 Lipid Levels - 0.000000 +23056639 rs11919628 Lectin - 0.000001 +23472185 rs6659742 Multiple Sclerosis|Oligoclonal Band - 0.000001 +24483146 rs10513968 Biomarkers - 0.000001 +21490707 rs12148488 Caffeine Consumption|Cyp1A2 - 0.000001 +19197348 rs10508517 Complex Disease - 0.000006 +21998595 rs12393627 Height - 0.000000 +19343178 rs12189801 Stature - 0.000000 +19557197 rs6837818 Distribution|Adiposity|Waist Circumference - 0.000005 +20190752 rs6691768 Celiac Disease - 0.000000 +24483146 rs2928445 Biomarkers - 0.000002 +23209447 rs9260734 I Antigen|Nasopharyngeal Carcinoma - 0.000000 +19300499 rs1799853 Cyp2C9|Warfarin - 0.000000 +24509480 rs6808574 Type 2 Diabetes - 0.000000 +22306652 rs19065993 Ischemic Stroke - 0.000000 +24709693 rs144444502 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000006 +21998595 rs2589113 Height - 0.000000 +22291604 rs6964720 Lupus - 0.000000 +22144915 rs4864872 Corneal Astigmatism - 0.000001 +24483146 rs11215406 Biomarkers - 0.000002 +17903294 rs727435 Hematological Phenotypes - 0.000010 +20932310 rs11015860 Τ Protein Levels - 0.000001 +24097068 rs8077889 Lipid Levels - 0.000000 +25390645 rs10762651 Anxiety - 0.000006 +19197348 rs655601 Complex Disease - 0.000005 +19772629 rs11899121 Parkinson Disease|Onset - 0.000003 +23886662 rs7130588 Psoriasis|Atopic Dermatitis|Asthma - 0.000001 +24390342 rs3783782 Rheumatoid Arthritis|Biology - 0.000000 +24166486 rs6904596 Schizophrenia - 0.000000 +22423221 rs477895 Platelet Count|Mean Platelet Volume - 0.000000 +25340798 rs948399 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +23984888 rs6731443 Airway Responsiveness - 0.000002 +22561518 rs3757247 Generalized Vitiligo - 0.000000 +20686608 rs1737947 Pancreatic Cancer - 0.000008 +20729852 rs2274223 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +23636237 rs3114727 Analysis - 0.000006 +22570697 rs12722489 Multiple Sclerosis - 0.000000 +23593202 rs12146626 Age Menarche|Femoral Neck Bone Geometry - 0.000004 +23984888 rs4861175 Airway Responsiveness - 0.000005 +23509613 rs6681460 Antiphospholipid Antibodies - 0.000007 +21602797 rs7924717 Cystic Fibrosis|Lung Disease - 0.000003 +21326860 rs8005468 Kawasaki Disease - 0.000009 +23703922 rs6449213 Uric Acid Levels - 0.000000 +19096518 rs552976 Glycated Hemoglobin - 0.000000 +20436471 rs10494112 Paget’s Disease Bone - 0.000000 +20364137 rs11661542 Intracranial Aneurysm - 0.000000 +23974872 rs1538774 Schizophrenia - 0.000000 +23544013 rs3814113 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +22993228 rs4802666 Lumbar Disc Degeneration - 0.000005 +22843504 rs11211996 Autism Spectrum - 0.000000 +24952745 rs846111 Qt Interval|Calcium - 0.000000 +19801982 rs9533090 Bone Mineral Density - 0.000000 +23958962 rs4861386 Cocaine Dependence - 0.000001 +20011104 rs6444175 Adiponectin Levels - 0.000000 +23936387 rs12734338 Celiac Disease - 0.000000 +21909115 rs1173771 Cardiovascular Disease|Blood Pressure - 0.000000 +19197348 rs6066085 Complex Disease - 0.000002 +22829776 rs293428 Globulin|Hormone|Steroid Hormone - 0.000002 +21297633 rs6908425 Ulcerative Colitis - 0.000000 +17903293 rs2808629 Biomarker Traits - 0.000000 +24952745 rs10919070 Qt Interval|Calcium - 0.000000 +21602797 rs93138 Cystic Fibrosis|Lung Disease - 0.000005 +23382691 rs8007846 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000009 +23583980 rs4727443 Pulmonary Fibrosis - 0.000000 +21490949 rs2833610 Type 2 Diabetes|Transferability - 0.000004 +21552555 rs8044769 Obesity|Obesity-Related Traits - 0.000000 +18840781 rs10876864 Type 1 Diabetes - 0.000000 +21298047 rs10893365 European-Origin|Substance Dependence - 0.000009 +20072603 rs2504063 Osteoporosis - 0.000000 +24586183 rs653178 Thyroid Peroxidase Antibodies|Thyroid Disease - 0.000000 +25367360 rs6901423 Astigmatism|Refractive Error - 0.000002 +19247474 rs2268983 Smoking Behaviors|Cigarette Smoking - 0.000007 +20173747 rs13376333 Lone Atrial Fibrillation - 0.000000 +22916037 rs1998013 Atherosclerosis - 0.000000 +22423221 rs477895 Platelet Count|Mean Platelet Volume - 0.000000 +24688116 rs11834614 Longevity|Analysis|Population - 0.000010 +21076409 rs2051211 Conduction|Qrs Duration - 0.000000 +20190752 rs6441961 Celiac Disease - 0.000000 +21124946 rs7338502 Bone Mineral Density - 0.000000 +20686608 rs11242674 Pancreatic Cancer - 0.000003 +25310821 rs11725593 Hirschsprung Disease - 0.000002 +21060863 rs2287921 Cardiovascular Diseases - 0.000000 +20861866 rs1329428 Age-Related Macular Degeneration - 0.000000 +23738518 rs479526 Reading|Language - 0.000003 +21379329 rs4145454 Late-Onset Alzheimer's Disease - 0.000001 +22719876 rs2076211 Non-Alcoholic Fatty Liver Disease|Liver Disease - 0.000000 +22359512 rs4500751 Sphingolipids - 0.000000 +24133439 rs16946876 Autistic-Like Traits - 0.000003 +22843504 rs12331851 Autism Spectrum - 0.000001 +20661308 rs17666460 Serum Calcium - 0.000005 +21533175 rs2637125 Dehydroepiandrosterone Sulphate - 0.000000 +24449572 rs1047022 Rheumatoid Arthritis - 0.000001 +24800985 rs6140038 Birth - 0.000000 +22693459 rs6047844 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +24347629 rs12799172 Periodontal - 0.000005 +23844046 rs4420638 C-Reactive Protein - 0.000000 +19779542 rs577948 Pathological Myopia - 0.000000 +24513273 rs734553 Serum Uric Acid - 0.000000 +19668339 rs2073145 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000002 +22504420 rs6426749 Bone Mineral Density - 0.000004 +20442857 rs12286037 Phospholipase A - 0.000000 +19874204 rs9630182 Femoral Neck Bone|Bone Mineral Density - 0.000000 +23844046 rs1892534 C-Reactive Protein - 0.000000 +25188341 rs10838725 Dementias|Alzheimer's Disease - 0.000000 +20081858 rs780094 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +24836286 rs7014346 Colorectal Cancer - 0.000000 +23870195 rs3218020 Coronary Artery|Coronary Artery Calcification - 0.000000 +21076409 rs10850409 Conduction|Qrs Duration - 0.000000 +24483146 rs1565214 Biomarkers - 0.000002 +20038947 rs7977950 Major Depression - 0.000001 +24449572 rs6920220 Rheumatoid Arthritis - 0.000000 +22359512 rs11662721 Sphingolipids - 0.000000 +22558097 rs17863787 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +23834954 rs6537883 Sensory Disturbances|Split - 0.000003 +20442857 rs1805017 Phospholipase A - 0.000000 +20932310 rs4925189 Τ Protein Levels - 0.000001 +25147783 rs12611820 Ischemic Stroke|Vitamin|Folate Levels - 0.000001 +20038947 rs867722 Major Depression - 0.000005 +25436638 rs989758 Serum Thyroid Stimulating Hormone - 0.000000 +24166486 rs2056480 Schizophrenia - 0.000000 +23667675 rs314274 Age Menarche - 0.000001 +24465431 rs6595551 Onset|Cardiovascular Disease|Diabetes - 0.000006 +25340798 rs4968782 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +23455636 rs10490924 Age-Related Macular Degeneration - 0.000000 +21980494 rs495828 Venous Thrombosis - 0.000000 +23696099 rs9924561 Cell Traits|Red Blood Cell|Resistance - 0.000000 +21483430 rs11122322 Neurocognitive Phenotypes - 0.000000 +25017104 rs2055376 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +21980299 rs12679857 Type 1 Diabetes - 0.000000 +18483556 rs4778211 Hair Color|Skin Pigmentation - 0.000000 +20195514 rs12424086 Primary Tooth Development - 0.000004 +24390342 rs2664035 Rheumatoid Arthritis|Biology - 0.000000 +23509613 rs17791782 Antiphospholipid Antibodies - 0.000007 +20190752 rs1464510 Celiac Disease - 0.000000 +23793025 rs2651899 Migraine - 0.000000 +20081858 rs4506565 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +24347629 rs7816221 Periodontal - 0.000009 +19197348 rs780094 Complex Disease - 0.000000 +24516586 rs2240723 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000009 +20711177 rs199533 Parkinson’s Disease - 0.000001 +24489884 rs6012564 Aggression - 0.000007 +18604267 rs5498 Antigen|Icam-1 - 0.000000 +24483146 rs4392391 Biomarkers - 0.000002 +21386085 rs9987289 Metabolic Syndrome - 0.000001 +22344219 rs6265 Body Mass Index - 0.000000 +22504420 rs344081 Bone Mineral Density - 0.000000 +22470424 rs6075164 Amyotrophic Lateral Sclerosis - 0.000003 +24836286 rs4939827 Colorectal Cancer - 0.000000 +21437268 rs2287802 Cancers|Conducted|Upper Aerodigestive Tract - 0.000004 +21935397 rs7359397 Extremely|Overweight|Body Mass Index - 0.000000 +18483556 rs4238833 Hair Color|Skin Pigmentation - 0.000000 +24143190 rs12922061 Breast Cancer|Breast - 0.000000 +21876539 rs6495122 Cyp1A2 - 0.000000 +24945404 rs884205 Bone Mineral Density|Bone - 0.000000 +21779181 rs3129882 Systemic Sclerosis - 0.000000 +18483556 rs11855019 Hair Color|Skin Pigmentation - 0.000000 +21935397 rs3810291 Extremely|Overweight|Body Mass Index - 0.000000 +20932310 rs12643654 Τ Protein Levels - 0.000000 +23738518 rs10508253 Reading|Language - 0.000004 +21076409 rs1362212 Conduction|Qrs Duration - 0.000000 +23974872 rs2373000 Schizophrenia - 0.000000 +24223155 rs2276314 Torsades De Pointes - 0.000000 +22470424 rs2867161 Amyotrophic Lateral Sclerosis - 0.000004 +23958962 rs4782559 Cocaine Dependence - 0.000001 +24625756 rs507080 Intermediate Phenotypes - 0.000000 +21935397 rs10987417 Extremely|Overweight|Body Mass Index - 0.000005 +20686608 rs6879627 Pancreatic Cancer - 0.000008 +19503597 rs2078267 Uric Acid - 0.000000 +23437003 rs9287237 Volumetric Bone Mineral Densities - 0.000000 +25367360 rs12212674 Astigmatism|Refractive Error - 0.000001 +24513273 rs2231142 Serum Uric Acid - 0.000000 +20935630 rs2890652 Body Mass Index - 0.000000 +22452962 rs4973768 Breast Cancer - 0.000001 +21552555 rs8050136 Obesity|Obesity-Related Traits - 0.000000 +25352737 rs2574730 Cataract - 0.000003 +25060954 rs1827524 Kinase|Hearing - 0.000000 +21076409 rs4074536 Conduction|Qrs Duration - 0.000000 +22504420 rs430727 Bone Mineral Density - 0.000000 +25436638 rs9472138 Serum Thyroid Stimulating Hormone - 0.000000 +21829393 rs1990760 Type 1 Diabetes|Autoantibody - 0.000000 +19430480 rs425105 Type 1 Diabetes - 0.000000 +25008200 rs10501568 Chronic Periodontitis - 0.000009 +22087292 rs3849874 Femoral Neck Bone Geometry - 0.000001 +23667675 rs1106419 Age Menarche - 0.000003 +25340798 rs4316 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +21297633 rs6871626 Ulcerative Colitis - 0.000000 +22344219 rs6545814 Body Mass Index - 0.000000 +22693459 rs12373124 Onset|Androgenetic Alopecia|Common Diseases - 0.000000 +23761726 rs438465 Corneal Astigmatism|Platelet-Derived Growth Factor - 0.000007 +23056639 rs4652 Lectin - 0.000003 +25367360 rs1401327 Astigmatism|Refractive Error - 0.000000 +24999842 rs10796045 Celiac Disease|Celiac - 0.000000 +18455228 rs3736228 Bone Mineral Density|Osteoporosis - 0.000000 +21156761 rs6972219 Rheumatoid Arthritis - 0.000002 +22087292 rs13299777 Femoral Neck Bone Geometry - 0.000001 +19609347 rs1550576 Hypertension|Blood Pressure - 0.000010 +18369459 rs2395029 Psoriasis|Psoriatic Arthritis|New Disease - 0.000000 +22087292 rs17037864 Femoral Neck Bone Geometry - 0.000004 +22359512 rs1061808 Sphingolipids - 0.000000 +25129146 rs35597309 Esophageal Squamous Cell Carcinoma - 0.000001 +22085899 rs16928809 Bilirubin Levels - 0.000000 +22087292 rs1368998 Femoral Neck Bone Geometry - 0.000000 +22763110 rs4836732 Osteoarthritis - 0.000000 +22843504 rs1718101 Autism Spectrum - 0.000000 +24086445 rs10233386 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +18483556 rs2241039 Hair Color|Skin Pigmentation - 0.000000 +19714205 rs2247572 Asthma - 0.000002 +20861866 rs10490924 Age-Related Macular Degeneration - 0.000000 +21602797 rs11645366 Cystic Fibrosis|Lung Disease - 0.000002 +23974872 rs14403 Schizophrenia - 0.000000 +25526632 rs421379 Breast Cancer - 0.000001 +21779176 rs3104788 Restless Legs Syndrome - 0.000000 +24166486 rs3800917 Schizophrenia - 0.000000 +24086445 rs12580062 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000005 +20041166 rs333 Hiv-1 - 0.000000 +23326517 rs1410996 Age-Related Macular Degeneration - 0.000000 +21602797 rs1403543 Cystic Fibrosis|Lung Disease - 0.000000 +21060863 rs17421627 Cardiovascular Diseases - 0.000000 +21804549 rs4845783 Asthma - 0.000001 +21779181 rs987870 Systemic Sclerosis - 0.000000 +22561518 rs12913832 Generalized Vitiligo - 0.000000 +21460841 rs3865444 Late-Onset Alzheimer’s Disease - 0.000000 +21297633 rs2836878 Ulcerative Colitis - 0.000000 +24097068 rs1936800 Lipid Levels - 0.000000 +23703922 rs13131257 Uric Acid Levels - 0.000000 +19343178 rs7596521 Stature - 0.000003 +23563607 rs2362965 Anthropometric Traits - 0.000000 +23382691 rs7453920 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +21273288 rs10864721 NT-proBNP - 0.000001 +23984888 rs7592613 Airway Responsiveness - 0.000009 +19571809 rs9467626 Schizophrenia - 0.000000 +25372704 rs1427407 Sickle Cell Anemia|Fetal Hemoglobin|Sickle Cell - 0.000000 +22085899 rs11891311 Bilirubin Levels - 0.000000 +19503597 rs2231142 Uric Acid - 0.000000 +18840781 rs706779 Type 1 Diabetes - 0.000000 +22368281 rs6857 LDL-c Response|Lpa - 0.000000 +21399635 rs911263 Primary Biliary Cirrhosis - 0.000000 +20953186 rs13191343 Psoriasis|Psoriatic Arthritis - 0.000000 +24483146 rs28668016 Biomarkers - 0.000000 +24094242 rs7025162 Serum Alkaline Phosphatase Levels - 0.000000 +19557197 rs17476669 Distribution|Adiposity|Waist Circumference - 0.000008 +20195514 rs9386463 Primary Tooth Development - 0.000001 +18464913 rs4129267 Protein Quantitative Trait|Genome|Association - 0.000000 +24952745 rs2485376 Qt Interval|Calcium - 0.000000 +18483556 rs12896399 Hair Color|Skin Pigmentation - 0.000000 +19798445 rs680379 Sphingolipid - 0.000000 +22452962 rs1562430 Breast Cancer - 0.000001 +23326517 rs3793917 Age-Related Macular Degeneration - 0.000000 +24025145 rs7318267 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000004 +23455636 rs920915 Age-Related Macular Degeneration - 0.000000 +21602797 rs525202 Cystic Fibrosis|Lung Disease - 0.000000 +22829776 rs1573036 Globulin|Hormone|Steroid Hormone - 0.000000 +21076409 rs11708996 Conduction|Qrs Duration - 0.000000 +23704328 rs7924176 Tooth Eruption|Height - 0.000000 +22916037 rs964184 Atherosclerosis - 0.000000 +24952745 rs3026445 Qt Interval|Calcium - 0.000000 +24709693 rs757278 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000001 +22197932 rs2164983 Atopic Dermatitis - 0.000000 +23408906 rs4804416 Thyroid|Thyroid-Related Traits|Differences - 0.000002 +21297633 rs7134599 Ulcerative Colitis - 0.000000 +21980299 rs9268645 Type 1 Diabetes - 0.000000 +17903301 rs10519181 Exercise Responses|Artery - 0.000010 +24324648 rs1399315 Serum IgE - 0.000001 +21502949 rs9378688 Brain - 0.000004 +21998595 rs9470004 Height - 0.000000 +18483556 rs28777 Hair Color|Skin Pigmentation - 0.000000 +24763700 rs2393791 C-Reactive Protein Levels - 0.000000 +24025145 rs6725180 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000004 +22359512 rs10468017 Sphingolipids - 0.000000 +20190752 rs296547 Celiac Disease - 0.000000 +24836286 rs10411210 Colorectal Cancer - 0.000003 +23382691 rs1240874 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000001 +19609347 rs9301196 Hypertension|Blood Pressure - 0.000007 +25436638 rs11755845 Serum Thyroid Stimulating Hormone - 0.000000 +22693455 rs5015480 Obese|Type 2 Diabetes - 0.000000 +19571809 rs3800318 Schizophrenia - 0.000000 +21750679 rs342070 Systemic Sclerosis - 0.000005 +25340798 rs650108 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +19571809 rs13219354 Schizophrenia - 0.000000 +25017104 rs2000260 Allergic Disease|Eosinophilic Esophagitis - 0.000001 +25367360 rs1401327 Astigmatism|Refractive Error - 0.000000 +22993228 rs9469300 Lumbar Disc Degeneration - 0.000000 +24483146 rs6128386 Biomarkers - 0.000001 +24871463 rs6084875 Systemic Lupus Erythematosus Sle - 0.000002 +24836286 rs4813802 Colorectal Cancer - 0.000010 +24836286 rs174550 Colorectal Cancer - 0.000000 +23844046 rs1169310 C-Reactive Protein - 0.000000 +22760553 rs6040399 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000001 +25241909 rs34391416 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +24094242 rs657152 Serum Alkaline Phosphatase Levels - 0.000000 +23382691 rs4730273 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000005 +23667675 rs12800752 Age Menarche - 0.000003 +22829776 rs2411984 Globulin|Hormone|Steroid Hormone - 0.000000 +19570815 rs139909 C-type Natriuretic Peptide|Height - 0.000000 +25526632 rs10457678 Breast Cancer - 0.000009 +22170493 rs171511 Psoriatic Arthritis - 0.000009 +21408207 rs12537284 Systemic Lupus Erythematosus|Autoantibody - 0.000002 +24625756 rs4363 Intermediate Phenotypes - 0.000000 +20038947 rs270592 Major Depression - 0.000002 +19609347 rs8039294 Hypertension|Blood Pressure - 0.000006 +22829776 rs293428 Globulin|Hormone|Steroid Hormone - 0.000000 +20935630 rs571312 Body Mass Index - 0.000000 +19343178 rs13437082 Stature - 0.000000 +19343178 rs7086883 Stature - 0.000003 +17684544 rs1793004 Ibd Disease - 0.000000 +21298047 rs12284594 European-Origin|Substance Dependence - 0.000000 +23793025 rs4559 Migraine - 0.000000 +23636237 rs11640535 Analysis - 0.000004 +20661308 rs13203335 Serum Calcium - 0.000000 +22479419 rs230529 Treatment Refractory Schizophrenia - 0.000000 +23455636 rs3812111 Age-Related Macular Degeneration - 0.000000 +22719876 rs1010023 Non-Alcoholic Fatty Liver Disease|Liver Disease - 0.000000 +19571809 rs13195040 Schizophrenia - 0.000000 +23593239 rs562487 Self-Employment - 0.000004 +25526632 rs12358475 Breast Cancer - 0.000007 +23886662 rs2251396 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +21273288 rs4869419 NT-proBNP - 0.000004 +25367360 rs12212674 Astigmatism|Refractive Error - 0.000001 +22511988 rs4148325 Cell-Free Dna|Cardiovascular - 0.000000 +23326517 rs1410996 Age-Related Macular Degeneration - 0.000000 +24740154 rs2005705 Prostate Cancer|Early-Onset - 0.000001 +20935630 rs4836133 Body Mass Index - 0.000000 +21779381 rs2143678 Migraine|Cardiovascular Events|Cardiovascular - 0.000000 +19557197 rs2365642 Distribution|Adiposity|Waist Circumference - 0.000004 +23870195 rs1537375 Coronary Artery|Coronary Artery Calcification - 0.000000 +21399635 rs12134279 Primary Biliary Cirrhosis - 0.000000 +22116950 rs6488619 Ovarian Reserve - 0.000001 +21297633 rs3024505 Ulcerative Colitis - 0.000000 +21124946 rs9541712 Bone Mineral Density - 0.000006 +22544364 rs5955543 Wilms Tumor - 0.000000 +24324648 rs3106598 Serum IgE - 0.000001 +23667675 rs314268 Age Menarche - 0.000001 +22085899 rs887829 Bilirubin Levels - 0.000000 +21935397 rs713586 Extremely|Overweight|Body Mass Index - 0.000000 +20935630 rs887912 Body Mass Index - 0.000000 +24483146 rs316871 Biomarkers - 0.000003 +21533022 rs6710518 Bone Mineral Density - 0.000000 +24086445 rs11044026 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000005 +21423239 rs300774 Attempted Suicide - 0.000000 +21738491 rs174230 Sudden Cardiac Death - 0.000000 +21399635 rs1372072 Primary Biliary Cirrhosis - 0.000000 +21483430 rs12030517 Neurocognitive Phenotypes - 0.000000 +24847357 rs2455012 Staphylococcus Aureus - 0.000001 +22267201 rs7606918 Age Menopause - 0.000000 +21483430 rs11122319 Neurocognitive Phenotypes - 0.000000 +25340798 rs495366 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +18776929 rs7595412 Hip Bone Size|Females - 0.000000 +22511988 rs17863787 Cell-Free Dna|Cardiovascular - 0.000000 +24740154 rs2150333 Prostate Cancer|Early-Onset - 0.000003 +18604267 rs923366 Antigen|Icam-1 - 0.000000 +20190752 rs12727642 Celiac Disease - 0.000000 +20195514 rs10506525 Primary Tooth Development - 0.000000 +19668339 rs1373549 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000008 +21502949 rs9378688 Brain - 0.000009 +19430480 rs229541 Type 1 Diabetes - 0.000000 +22792071 rs2707466 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +21379329 rs2075650 Late-Onset Alzheimer's Disease - 0.000000 +19609347 rs11160059 Hypertension|Blood Pressure - 0.000000 +21935397 rs4771122 Extremely|Overweight|Body Mass Index - 0.000000 +21399635 rs12924729 Primary Biliary Cirrhosis - 0.000000 +23583980 rs7934606 Pulmonary Fibrosis - 0.000000 +23984888 rs7595130 Airway Responsiveness - 0.000009 +19448621 rs402511 Age Menarche|Menopause - 0.000000 +22438815 rs10847864 Parkinson's Disease - 0.000000 +22087292 rs16913782 Femoral Neck Bone Geometry - 0.000000 +25188341 rs11218343 Dementias|Alzheimer's Disease - 0.000000 +21379329 rs62209 Late-Onset Alzheimer's Disease - 0.000000 +22760553 rs6646773 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000001 +23326239 rs3130048 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +19448621 rs1172822 Age Menarche|Menopause - 0.000000 +23056639 rs4876386 Lectin - 0.000003 +25367360 rs1366200 Astigmatism|Refractive Error - 0.000001 +24133439 rs11860027 Autistic-Like Traits - 0.000003 +20038947 rs5990417 Major Depression - 0.000006 +23028483 rs3894194 Asthma - 0.000000 +19571809 rs1851196 Schizophrenia - 0.000002 +22666496 rs13279522 Cardiovascular Event - 0.000000 +23408906 rs10032216 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +19430480 rs12444268 Type 1 Diabetes - 0.000000 +19430483 rs17367504 Blood Pressure - 0.000010 +19359265 rs2162440 Telomere Length - 0.000003 +24133439 rs1345404 Autistic-Like Traits - 0.000003 +23936387 rs1032355 Celiac Disease - 0.000005 +19343178 rs6763931 Stature - 0.000000 +21935397 rs910320 Extremely|Overweight|Body Mass Index - 0.000003 +22675492 rs402675 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000006 +22238593 rs7560163 Type 2 Diabetes - 0.000000 +21483430 rs1417584 Neurocognitive Phenotypes - 0.000000 +24509480 rs9505118 Type 2 Diabetes - 0.000000 +21980299 rs2476601 Type 1 Diabetes - 0.000000 +24999842 rs11711054 Celiac Disease|Celiac - 0.000000 +23563607 rs17024258 Anthropometric Traits - 0.000000 +24625756 rs603424 Intermediate Phenotypes - 0.000000 +21738478 rs10956483 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +19197348 rs6066084 Complex Disease - 0.000002 +20169177 rs1128334 Systemic Lupus Erythematosus - 0.000000 +23535730 rs11782652 Ovarian Cancer - 0.000000 +21124946 rs16877095 Bone Mineral Density - 0.000006 +24945404 rs4420311 Bone Mineral Density|Bone - 0.000000 +24871463 rs8023715 Systemic Lupus Erythematosus Sle - 0.000000 +24390342 rs4780401 Rheumatoid Arthritis|Biology - 0.000000 +22359512 rs10769780 Sphingolipids - 0.000000 +21700879 rs10447248 Adiponectin Levels - 0.000000 +19874204 rs8061992 Femoral Neck Bone|Bone Mineral Density - 0.000009 +23874384 rs151997 Behavior - 0.000005 +23738518 rs11158345 Reading|Language - 0.000003 +23936387 rs17029173 Celiac Disease - 0.000008 +20548946 rs12025126 Optic Disc - 0.000000 +21297633 rs4246905 Ulcerative Colitis - 0.000000 +21980299 rs425105 Type 1 Diabetes - 0.000006 +20932310 rs1445093 Τ Protein Levels - 0.000001 +24688116 rs11977641 Longevity|Analysis|Population - 0.000007 +22470424 rs6574039 Amyotrophic Lateral Sclerosis - 0.000005 +23408906 rs17723470 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24166486 rs3778994 Schizophrenia - 0.000000 +23563607 rs17381664 Anthropometric Traits - 0.000000 +21297633 rs16940202 Ulcerative Colitis - 0.000000 +23401653 rs7678144 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000003 +24379826 rs6832439 Serum Uric Acid Levels - 0.000000 +24952745 rs174583 Qt Interval|Calcium - 0.000000 +21379329 rs201119 Late-Onset Alzheimer's Disease - 0.000000 +20932310 rs7558386 Τ Protein Levels - 0.000000 +18262040 rs611917 LDL-cholesterol - 0.000000 +21326860 rs362794 Kawasaki Disease - 0.000004 +23817569 rs1438673 Allergy - 0.000000 +18483556 rs8028689 Hair Color|Skin Pigmentation - 0.000000 +24449572 rs1678542 Rheumatoid Arthritis - 0.000000 +17903307 rs1994169 Pulmonary Function - 0.000010 +23092984 rs2860031 Bipolar Disorder - 0.000003 +25140149 rs4866650 Neurodegeneration|Biomarker - 0.000000 +24509480 rs3130501 Type 2 Diabetes - 0.000000 +24133439 rs1009301 Autistic-Like Traits - 0.000003 +23989986 rs6094710 Hip|Osteoarthritis - 0.000000 +22693455 rs16896390 Obese|Type 2 Diabetes - 0.000000 +20169177 rs10857650 Systemic Lupus Erythematosus - 0.000005 +23593239 rs17166082 Self-Employment - 0.000006 +21980494 rs6825454 Venous Thrombosis - 0.000000 +21408207 rs10488631 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +22359512 rs17718828 Sphingolipids - 0.000000 +19668339 rs337847 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000007 +21076409 rs1733724 Conduction|Qrs Duration - 0.000000 +20038947 rs17077540 Major Depression - 0.000000 +21124946 rs8102334 Bone Mineral Density - 0.000003 +24390342 rs72634030 Rheumatoid Arthritis|Biology - 0.000000 +19571809 rs6913660 Schizophrenia - 0.000000 +22368281 rs11053068 LDL-c Response|Lpa - 0.000000 +21060863 rs225717 Cardiovascular Diseases - 0.000000 +22570617 rs1063192 Optic Nerve|Glaucoma - 0.000000 +22423221 rs7896518 Platelet Count|Mean Platelet Volume - 0.000000 +24483146 rs7183960 Biomarkers - 0.000000 +23936387 rs10439884 Celiac Disease - 0.000002 +22511988 rs11690786 Cell-Free Dna|Cardiovascular - 0.000000 +21297633 rs2872507 Ulcerative Colitis - 0.000000 +24740154 rs1146298 Prostate Cancer|Early-Onset - 0.000008 +24097068 rs2328223 Lipid Levels - 0.000000 +23326517 rs1410996 Age-Related Macular Degeneration - 0.000000 +23667675 rs364663 Age Menarche - 0.000001 +22570697 rs2857439 Multiple Sclerosis - 0.000000 +22763110 rs12107036 Osteoarthritis - 0.000000 +21297633 rs1297265 Ulcerative Colitis - 0.000000 +18483556 rs7174027 Hair Color|Skin Pigmentation - 0.000000 +22911880 rs218361 Behaviors|Personality Traits|Eating - 0.000007 +21076409 rs883079 Conduction|Qrs Duration - 0.000000 +24023777 rs9496346 Adolescent Idiopathic Scoliosis - 0.000000 +24086445 rs12581163 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000003 +22368281 rs445925 LDL-c Response|Lpa - 0.000000 +22993228 rs6457690 Lumbar Disc Degeneration - 0.000000 +20661308 rs16827695 Serum Calcium - 0.000003 +21779181 rs6901221 Systemic Sclerosis - 0.000000 +21909115 rs10850411 Cardiovascular Disease|Blood Pressure - 0.000000 +21931564 rs211718 Metabolite Quantitative Trait - 0.000000 +23974872 rs2905424 Schizophrenia - 0.000000 +17903294 rs1510107 Hematological Phenotypes - 0.000010 +25129146 rs1642764 Esophageal Squamous Cell Carcinoma - 0.000000 +21909110 rs13002573 Mean Arterial Pressure|Pulse Pressure - 0.000000 +21533024 rs281437 Icam-1 - 0.000000 +25310821 rs4299518 Hirschsprung Disease - 0.000003 +22843504 rs11118968 Autism Spectrum - 0.000000 +19454037 rs409045 Left Ventricular Mass - 0.000001 +22359512 rs4500751 Sphingolipids - 0.000000 +18369459 rs3812888 Psoriasis|Psoriatic Arthritis|New Disease - 0.000010 +23829686 rs9301462 Childhood|Childhood Asthma - 0.000007 +23696099 rs9924561 Cell Traits|Red Blood Cell|Resistance - 0.000000 +22001756 rs11187 Dengue Shock Syndrome - 0.000000 +24133439 rs1362594 Autistic-Like Traits - 0.000004 +23455636 rs1864163 Age-Related Macular Degeneration - 0.000000 +21347284 rs6798015 Pr Interval - 0.000000 +24625756 rs10788817 Intermediate Phenotypes - 0.000000 +20686608 rs12615966 Pancreatic Cancer - 0.000007 +25017104 rs3806933 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +22238593 rs2722769 Type 2 Diabetes - 0.000002 +21460841 rs4938933 Late-Onset Alzheimer’s Disease - 0.000000 +21873549 rs6235 Type 2 Diabetes|Proinsulin Levels - 0.000005 +24097068 rs7248104 Lipid Levels - 0.000000 +24097068 rs364585 Lipid Levels - 0.000000 +24489884 rs2045797 Aggression - 0.000010 +25436638 rs9915657 Serum Thyroid Stimulating Hormone - 0.000000 +23408906 rs6885099 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24023777 rs11598564 Adolescent Idiopathic Scoliosis - 0.000000 +21602797 rs12188164 Cystic Fibrosis|Lung Disease - 0.000001 +18483556 rs258322 Hair Color|Skin Pigmentation - 0.000000 +23326517 rs493258 Age-Related Macular Degeneration - 0.000000 +22993228 rs12805875 Lumbar Disc Degeneration - 0.000009 +22916037 rs12678919 Atherosclerosis - 0.000000 +22116950 rs12295403 Ovarian Reserve - 0.000005 +22144915 rs7677751 Corneal Astigmatism - 0.000000 +25526632 rs2921923 Breast Cancer - 0.000004 +24740154 rs10993994 Prostate Cancer|Early-Onset - 0.000000 +19448621 rs16991615 Age Menarche|Menopause - 0.000000 +20169177 rs9275328 Systemic Lupus Erythematosus - 0.000001 +23408906 rs13015993 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24886709 rs78536982 Lipid - 0.000008 +19798445 rs4695267 Sphingolipid - 0.000001 +23326517 rs10490924 Age-Related Macular Degeneration - 0.000000 +20729852 rs738722 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +21980299 rs12251307 Type 1 Diabetes - 0.000000 +22829776 rs7910927 Globulin|Hormone|Steroid Hormone - 0.000000 +23326517 rs4293143 Age-Related Macular Degeneration - 0.000008 +18262040 rs693 LDL-cholesterol - 0.000000 +24483146 rs7713001 Biomarkers - 0.000002 +24513273 rs1183201 Serum Uric Acid - 0.000000 +19772629 rs1420143 Parkinson Disease|Onset - 0.000007 +24952745 rs2363719 Qt Interval|Calcium - 0.000000 +24390342 rs1893592 Rheumatoid Arthritis|Biology - 0.000000 +18483556 rs8033165 Hair Color|Skin Pigmentation - 0.000000 +24755620 rs346763 Glutamate|Alzheimer's Disease - 0.000000 +24166486 rs10239050 Schizophrenia - 0.000000 +23703922 rs4698036 Uric Acid Levels - 0.000000 +21829393 rs2069763 Type 1 Diabetes|Autoantibody - 0.000000 +25760438 rs11240074 Type 2 Diabetes|Body Mass Index - 0.000006 +23886662 rs1295686 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +20686608 rs1886449 Pancreatic Cancer - 0.000009 +20935630 rs987237 Body Mass Index - 0.000000 +25436638 rs2046045 Serum Thyroid Stimulating Hormone - 0.000000 +24097068 rs12145743 Lipid Levels - 0.000000 +22359512 rs4666002 Sphingolipids - 0.000000 +21827660 rs501700 Increased Disease Risk - 0.000001 +24513273 rs1165205 Serum Uric Acid - 0.000000 +21829393 rs3184504 Type 1 Diabetes|Autoantibody - 0.000000 +22916037 rs10211524 Atherosclerosis - 0.000000 +19430480 rs7804356 Type 1 Diabetes - 0.000000 +20421936 rs2783963 Onset|Obesity-Related Traits|Body-Weight - 0.000009 +24625756 rs603424 Intermediate Phenotypes - 0.000000 +22087292 rs6789283 Femoral Neck Bone Geometry - 0.000000 +23408906 rs334699 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +20700443 rs3925584 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +21738478 rs4794822 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +25241909 rs13118928 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +20485516 rs1006368 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +19122664 rs1558744 Ulcerative Colitis - 0.000000 +24625756 rs3733402 Intermediate Phenotypes - 0.000000 +24094242 rs1780324 Serum Alkaline Phosphatase Levels - 0.000000 +22267201 rs10852344 Age Menopause - 0.000000 +25233373 rs12193446 Myopia|Hyperopia - 0.000000 +23593202 rs4929957 Age Menarche|Femoral Neck Bone Geometry - 0.000005 +23056639 rs8101416 Lectin - 0.000002 +19915575 rs3857059 Parkinson’s Disease - 0.000000 +23834954 rs6833812 Sensory Disturbances|Split - 0.000007 +23958962 rs75686122 Cocaine Dependence - 0.000001 +21408207 rs2736340 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +20190752 rs12928822 Celiac Disease - 0.000000 +18464913 rs6761276 Protein Quantitative Trait|Genome|Association - 0.000007 +23817569 rs6906021 Allergy - 0.000000 +21437268 rs971074 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +22760553 rs2903308 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000002 +22368281 rs10455872 LDL-c Response|Lpa - 0.000000 +23382691 rs11755527 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +23958962 rs7899919 Cocaine Dependence - 0.000000 +24586183 rs11675434 Thyroid Peroxidase Antibodies|Thyroid Disease - 0.000000 +24390342 rs67250450 Rheumatoid Arthritis|Biology - 0.000000 +20858683 rs16926246 Hemoglobin A - 0.000000 +22570617 rs3217992 Optic Nerve|Glaucoma - 0.000000 +21297633 rs12720356 Ulcerative Colitis - 0.000000 +21909110 rs1446468 Mean Arterial Pressure|Pulse Pressure - 0.000000 +22832960 rs11018023 Temperament Character Inventory - 0.000007 +24348519 rs8192472 Body Mass Index - 0.000001 +24740154 rs2150333 Prostate Cancer|Early-Onset - 0.000003 +19571809 rs2072806 Schizophrenia - 0.000001 +17903294 rs1954971 Hematological Phenotypes - 0.000010 +21076409 rs9851724 Conduction|Qrs Duration - 0.000000 +22470424 rs7777387 Amyotrophic Lateral Sclerosis - 0.000006 +22792082 rs10940113 Asthma|Bronchodilator Response - 0.000005 +25551457 rs10519203 Fibrinogen|Alcohol Consumption|Body Mass Index - 0.000000 +22832960 rs12494658 Temperament Character Inventory - 0.000005 +22267201 rs2153157 Age Menopause - 0.000000 +22993228 rs10998466 Lumbar Disc Degeneration - 0.000004 +23326239 rs204999 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23382691 rs7159888 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +25241909 rs2045517 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +23565137 rs17125523 Late-Onset Alzheimer’s Disease - 0.000003 +18776929 rs4850823 Hip Bone Size|Females - 0.000000 +21909115 rs2932538 Cardiovascular Disease|Blood Pressure - 0.000000 +25352737 rs12296937 Cataract - 0.000001 +23056639 rs2274273 Lectin - 0.000004 +23509613 rs12204683 Antiphospholipid Antibodies - 0.000007 +24376798 rs9275572 Chronic Hepatitis C - 0.000010 +22993228 rs7744666 Lumbar Disc Degeneration - 0.000000 +20686608 rs1427593 Pancreatic Cancer - 0.000007 +21347284 rs7312625 Pr Interval - 0.000000 +25064009 rs35749011 Parkinson’s Disease - 0.000000 +19772629 rs1572662 Parkinson Disease|Onset - 0.000008 +20522523 rs1989647 Partial Epilepsies - 0.000009 +24836286 rs12603526 Colorectal Cancer - 0.000000 +22558097 rs3755319 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +22792070 rs2707520 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +21490949 rs2063640 Type 2 Diabetes|Transferability - 0.000003 +24513273 rs3114018 Serum Uric Acid - 0.000000 +22832961 rs12808148 Alzheimer's Disease - 0.000001 +23817569 rs2107357 Allergy - 0.000000 +25147783 rs2267739 Ischemic Stroke|Vitamin|Folate Levels - 0.000001 +22993228 rs7118412 Lumbar Disc Degeneration - 0.000009 +22001756 rs75372 Dengue Shock Syndrome - 0.000000 +21533024 rs5498 Icam-1 - 0.000000 +17903293 rs2794520 Biomarker Traits - 0.000000 +23704328 rs7924176 Tooth Eruption|Height - 0.000000 +25367360 rs17712049 Astigmatism|Refractive Error - 0.000004 +25188341 rs9271192 Dementias|Alzheimer's Disease - 0.000000 +22479419 rs10218843 Treatment Refractory Schizophrenia - 0.000000 +19343178 rs1480474 Stature - 0.000000 +19668339 rs4845552 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000006 +23958962 rs9664175 Cocaine Dependence - 0.000000 +22359512 rs1424760 Sphingolipids - 0.000000 +23028341 rs2071278 Complement C3 - 0.000000 +21298047 rs11220015 European-Origin|Substance Dependence - 0.000002 +22504420 rs1373004 Bone Mineral Density - 0.000000 +23667675 rs6431393 Age Menarche - 0.000004 +22087292 rs10491633 Femoral Neck Bone Geometry - 0.000005 +21738478 rs4328821 White Blood Cell Count|Cell Phenotypes|White Blood Cell - 0.000000 +19961619 rs9376221 Respiratory|Atopy - 0.000000 +22116950 rs12465811 Ovarian Reserve - 0.000000 +21448238 rs4742323 Migraine - 0.000010 +24390342 rs1516971 Rheumatoid Arthritis|Biology - 0.000000 +23326517 rs9332739 Age-Related Macular Degeneration - 0.000000 +20421936 rs9935401 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +22504421 rs17178006 Hippocampal Volume - 0.000000 +23326517 rs621313 Age-Related Macular Degeneration - 0.000003 +19096518 rs906216 Glycated Hemoglobin - 0.000000 +18941528 rs1327328 Multiple Sclerosis - 0.000000 +18840781 rs7073236 Type 1 Diabetes - 0.000000 +22511988 rs6722076 Cell-Free Dna|Cardiovascular - 0.000000 +19430480 rs2292239 Type 1 Diabetes - 0.000000 +22666496 rs9859901 Cardiovascular Event - 0.000002 +22829776 rs9901675 Globulin|Hormone|Steroid Hormone - 0.000000 +21935397 rs8067056 Extremely|Overweight|Body Mass Index - 0.000008 +21399635 rs12531711 Primary Biliary Cirrhosis - 0.000000 +22504420 rs3755955 Bone Mineral Density - 0.000000 +23936387 rs2068824 Celiac Disease - 0.000006 +19343178 rs3125945 Stature - 0.000004 +23118916 rs11552708 Serum IgM - 0.000000 +24571439 rs6895329 Specific Language Impairment|Genotype Effects - 0.000001 +20038947 rs270584 Major Depression - 0.000000 +23593239 rs10776614 Self-Employment - 0.000005 +21602797 rs10836312 Cystic Fibrosis|Lung Disease - 0.000000 +19801982 rs9303521 Bone Mineral Density - 0.000000 +20364137 rs10958409 Intracranial Aneurysm - 0.000000 +20081858 rs7944584 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +17903308 rs949175 Circadian Phenotypes|Sleep - 0.000010 +24489884 rs2148710 Aggression - 0.000000 +19772629 rs10420134 Parkinson Disease|Onset - 0.000007 +24886709 rs3902354 Lipid - 0.000000 +22479202 rs592423 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +19430480 rs16956936 Type 1 Diabetes - 0.000001 +25367360 rs12638075 Astigmatism|Refractive Error - 0.000005 +25060954 rs2521030 Kinase|Hearing - 0.000000 +22087292 rs11859916 Femoral Neck Bone Geometry - 0.000003 +24999842 rs4558075 Celiac Disease|Celiac - 0.000000 +23326239 rs2858870 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000004 +23593202 rs4844014 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +21602797 rs11032829 Cystic Fibrosis|Lung Disease - 0.000002 +21779181 rs12540874 Systemic Sclerosis - 0.000003 +24094242 rs9467160 Serum Alkaline Phosphatase Levels - 0.000000 +19197348 rs2071523 Complex Disease - 0.000000 +24513273 rs4148152 Serum Uric Acid - 0.000000 +17903307 rs156697 Pulmonary Function - 0.000010 +23974872 rs10789369 Schizophrenia - 0.000000 +21943158 rs2437258 Cardiovascular-Related Traits - 0.000000 +23326517 rs13278062 Age-Related Macular Degeneration - 0.000000 +19597492 rs17375901 Atrial Fibrillation - 0.000000 +20953186 rs12188300 Psoriasis|Psoriatic Arthritis - 0.000000 +23472185 rs6926377 Multiple Sclerosis|Oligoclonal Band - 0.000006 +25060954 rs6134479 Kinase|Hearing - 0.000001 +22452962 rs1011970 Breast Cancer - 0.000000 +24513273 rs11264341 Serum Uric Acid - 0.000000 +24379826 rs6449213 Serum Uric Acid Levels - 0.000002 +22116950 rs10061804 Ovarian Reserve - 0.000001 +21779181 rs11047102 Systemic Sclerosis - 0.000010 +22829776 rs8023580 Globulin|Hormone|Steroid Hormone - 0.000000 +25760438 rs12816270 Type 2 Diabetes|Body Mass Index - 0.000008 +20686608 rs4924935 Pancreatic Cancer - 0.000008 +22558097 rs4148324 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +21297633 rs9268853 Ulcerative Colitis - 0.000000 +20442857 rs11820589 Phospholipase A - 0.000000 +24379826 rs7652782 Serum Uric Acid Levels - 0.000001 +19571809 rs2072803 Schizophrenia - 0.000001 +25340798 rs645419 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +21700879 rs2120576 Adiponectin Levels - 0.000003 +21935397 rs10150332 Extremely|Overweight|Body Mass Index - 0.000000 +25390645 rs10016872 Anxiety - 0.000004 +21909115 rs805303 Cardiovascular Disease|Blood Pressure - 0.000000 +21347284 rs6798015 Pr Interval - 0.000000 +21490949 rs7119 Type 2 Diabetes|Transferability - 0.000001 +22267201 rs2517388 Age Menopause - 0.000000 +24014518 rs11692675 Epilepsy|Febrile Seizures - 0.000005 +23636237 rs7086704 Analysis - 0.000010 +25129146 rs35597309 Esophageal Squamous Cell Carcinoma - 0.000004 +21383967 rs11043097 Rheumatoid Arthritis|Celiac Disease - 0.000000 +25629512 rs2287921 Age-Related Macular Degeneration - 0.000008 +22558097 rs4148325 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +20858683 rs1387153 Hemoglobin A - 0.000000 +20038947 rs329640 Major Depression - 0.000006 +21399635 rs7208487 Primary Biliary Cirrhosis - 0.000001 +25233373 rs10113215 Myopia|Hyperopia - 0.000000 +23326239 rs2213586 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +18840781 rs1217407 Type 1 Diabetes - 0.000000 +25233373 rs7744813 Myopia|Hyperopia - 0.000000 +23667675 rs3862645 Age Menarche - 0.000002 +22438815 rs11248060 Parkinson's Disease - 0.000000 +21658281 rs11624056 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +24952745 rs3857067 Qt Interval|Calcium - 0.000000 +21060863 rs10774625 Cardiovascular Diseases - 0.000000 +25742292 rs7036692 Parity - 0.000007 +21602797 rs7929679 Cystic Fibrosis|Lung Disease - 0.000001 +23297363 rs17696736 Tetralogy Fallot - 0.000000 +22829776 rs4149056 Globulin|Hormone|Steroid Hormone - 0.000000 +20935630 rs2241423 Body Mass Index - 0.000000 +20190752 rs13151961 Celiac Disease - 0.000000 +23259602 rs7150062 Dental Caries - 0.000001 +19343178 rs1182188 Stature - 0.000000 +24651765 rs234714 Homocysteine|Methionine|Metabolism - 0.000000 +23770605 rs8024033 Chronic Lymphocytic Leukemia - 0.000000 +21935397 rs13078807 Extremely|Overweight|Body Mass Index - 0.000000 +20522523 rs16834756 Partial Epilepsies - 0.000004 +22792070 rs4727924 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +20072603 rs16894980 Osteoporosis - 0.000005 +22666496 rs13314266 Cardiovascular Event - 0.000006 +23408906 rs3813582 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21980299 rs1701704 Type 1 Diabetes - 0.000000 +19448621 rs2153157 Age Menarche|Menopause - 0.000000 +20081858 rs780094 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +21297633 rs10761659 Ulcerative Colitis - 0.000000 +23886662 rs2155219 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +20038947 rs644695 Major Depression - 0.000000 +20686608 rs2257205 Pancreatic Cancer - 0.000008 +23092984 rs11710433 Bipolar Disorder - 0.000001 +19801982 rs7524102 Bone Mineral Density - 0.000000 +25367360 rs6901423 Astigmatism|Refractive Error - 0.000003 +19503597 rs17300741 Uric Acid - 0.000000 +21297633 rs6556412 Ulcerative Colitis - 0.000000 +23886662 rs9368699 Psoriasis|Atopic Dermatitis|Asthma - 0.000000 +22570697 rs7382297 Multiple Sclerosis - 0.000000 +25241909 rs4416442 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +21502949 rs5979778 Brain - 0.000001 +19503597 rs780093 Uric Acid - 0.000000 +22087292 rs1389728 Femoral Neck Bone Geometry - 0.000001 +25367360 rs2871434 Astigmatism|Refractive Error - 0.000003 +19430480 rs2281808 Type 1 Diabetes - 0.000000 +23667675 rs314280 Age Menarche - 0.000001 +19454037 rs10499859 Left Ventricular Mass - 0.000003 +20729852 rs753724 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +21076409 rs17608766 Conduction|Qrs Duration - 0.000000 +20932310 rs2935776 Τ Protein Levels - 0.000001 +22693455 rs7903146 Obese|Type 2 Diabetes - 0.000000 +21935397 rs1002158 Extremely|Overweight|Body Mass Index - 0.000007 +24483146 rs2414409 Biomarkers - 0.000000 +20190752 rs1250552 Celiac Disease - 0.000000 +19197348 rs1039302 Complex Disease - 0.000005 +19401414 rs7754840 Type 2 Diabetes - 0.000000 +25352737 rs1929494 Cataract - 0.000002 +19122664 rs3806308 Ulcerative Colitis - 0.000000 +20858683 rs4737009 Hemoglobin A - 0.000000 +23284291 rs7594321 Pulmonary Function|Lung Function - 0.000010 +23259602 rs17057381 Dental Caries - 0.000000 +24025145 rs2282048 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000006 +23382691 rs7224668 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +21829393 rs2292239 Type 1 Diabetes|Autoantibody - 0.000000 +19571809 rs3800316 Schizophrenia - 0.000000 +22916037 rs2657880 Atherosclerosis - 0.000000 +23738518 rs12482528 Reading|Language - 0.000001 +23974872 rs6878284 Schizophrenia - 0.000000 +21873549 rs7903146 Type 2 Diabetes|Proinsulin Levels - 0.000000 +21490707 rs2470893 Caffeine Consumption|Cyp1A2 - 0.000000 +23092984 rs1930961 Bipolar Disorder - 0.000009 +25064009 rs12637471 Parkinson’s Disease - 0.000000 +21829393 rs7171171 Type 1 Diabetes|Autoantibody - 0.000000 +22685421 rs7544369 Ocular Axial Length|High Myopia - 0.000000 +23984888 rs6731443 Airway Responsiveness - 0.000002 +25390645 rs7141336 Anxiety - 0.000006 +23259602 rs10805050 Dental Caries - 0.000002 +21423239 rs300774 Attempted Suicide - 0.000001 +23704328 rs6568401 Tooth Eruption|Height - 0.000000 +25233373 rs12193446 Myopia|Hyperopia - 0.000009 +22423221 rs11653144 Platelet Count|Mean Platelet Volume - 0.000000 +23834954 rs2817461 Sensory Disturbances|Split - 0.000000 +23382809 rs2860223 Schizophrenia - 0.000002 +22685421 rs10779363 Ocular Axial Length|High Myopia - 0.000001 +22829776 rs12150660 Globulin|Hormone|Steroid Hormone - 0.000000 +21552555 rs2887180 Obesity|Obesity-Related Traits - 0.000002 +21297633 rs10758669 Ulcerative Colitis - 0.000000 +24483146 rs12631341 Biomarkers - 0.000002 +19412175 rs6712055 Neuroblastoma - 0.000000 +23326517 rs1713985 Age-Related Macular Degeneration - 0.000000 +24952745 rs12143842 Qt Interval|Calcium - 0.000000 +25436638 rs657152 Serum Thyroid Stimulating Hormone - 0.000000 +22470424 rs688858 Amyotrophic Lateral Sclerosis - 0.000007 +19936222 rs12768534 Cholesterol|Plasma Lipoprotein Size - 0.000000 +21502949 rs163030 Brain - 0.000000 +25760438 rs11240074 Type 2 Diabetes|Body Mass Index - 0.000006 +18483556 rs2353033 Hair Color|Skin Pigmentation - 0.000000 +18483556 rs8007923 Hair Color|Skin Pigmentation - 0.000001 +22916037 rs1532085 Atherosclerosis - 0.000000 +22359512 rs102275 Sphingolipids - 0.000000 +21829377 rs174535 Plasma Phospholipid|Fatty Acids - 0.000000 +23565137 rs4598682 Late-Onset Alzheimer’s Disease - 0.000009 +18840781 rs9976767 Type 1 Diabetes - 0.000000 +22452962 rs2046210 Breast Cancer - 0.000000 +21658281 rs597503 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +21297633 rs7524102 Ulcerative Colitis - 0.000000 +22832960 rs10995356 Temperament Character Inventory - 0.000003 +25241909 rs114384494 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000001 +19570815 rs10472828 C-type Natriuretic Peptide|Height - 0.000000 +22829776 rs17496332 Globulin|Hormone|Steroid Hormone - 0.000000 +24847357 rs470093 Staphylococcus Aureus - 0.000007 +18483556 rs7188458 Hair Color|Skin Pigmentation - 0.000000 +21829377 rs3798713 Plasma Phospholipid|Fatty Acids - 0.000000 +21390209 rs157580 Late-Onset Alzheimer's Disease - 0.000000 +19915575 rs393152 Parkinson’s Disease - 0.000000 +23636237 rs11699457 Analysis - 0.000009 +20661308 rs10455097 Serum Calcium - 0.000010 +19247474 rs6437740 Smoking Behaviors|Cigarette Smoking - 0.000000 +22544364 rs1027643 Wilms Tumor - 0.000000 +20686608 rs4663158 Pancreatic Cancer - 0.000007 +22745674 rs2327620 Coronary Artery Stenosis|Coronary Artery - 0.000000 +20485516 rs2721051 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +19597492 rs2106261 Atrial Fibrillation - 0.000000 +21424380 rs1092913 Breast Cancer - 0.000002 +19300499 rs1057910 Cyp2C9|Warfarin - 0.000000 +22693455 rs7766070 Obese|Type 2 Diabetes - 0.000000 +18840781 rs10758593 Type 1 Diabetes - 0.000007 +22843504 rs600695 Autism Spectrum - 0.000000 +21552555 rs1477196 Obesity|Obesity-Related Traits - 0.000000 +21738491 rs2650907 Sudden Cardiac Death - 0.000000 +23326517 rs10406174 Age-Related Macular Degeneration - 0.000006 +18604267 rs1799969 Antigen|Icam-1 - 0.000000 +23326239 rs10947261 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +17903296 rs10486661 Association Bone - 0.000009 +23401653 rs7673984 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000006 +22916037 rs10500569 Atherosclerosis - 0.000000 +23437003 rs1021188 Volumetric Bone Mineral Densities - 0.000000 +22570617 rs1412829 Optic Nerve|Glaucoma - 0.000000 +22267201 rs1635501 Age Menopause - 0.000000 +24483146 rs2290344 Biomarkers - 0.000000 +18262040 rs576203 LDL-cholesterol - 0.000000 +22116950 rs12213875 Ovarian Reserve - 0.000000 +21829377 rs780094 Plasma Phospholipid|Fatty Acids - 0.000000 +18483556 rs4778211 Hair Color|Skin Pigmentation - 0.000000 +22267201 rs890835 Age Menopause - 0.000000 +20038947 rs10007831 Major Depression - 0.000001 +19247474 rs6862125 Smoking Behaviors|Cigarette Smoking - 0.000008 +23563607 rs7989336 Anthropometric Traits - 0.000000 +20421936 rs17150703 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +22843504 rs29456 Autism Spectrum - 0.000000 +23104006 rs4141819 Endometriosis - 0.000000 +24688116 rs2109265 Longevity|Analysis|Population - 0.000003 +25064009 rs329648 Parkinson’s Disease - 0.000000 +24133439 rs16946931 Autistic-Like Traits - 0.000002 +21665990 rs4711751 Age-Related Macular Degeneration - 0.000000 +23307926 rs12461110 Menopause - 0.000000 +24999842 rs654690 Celiac Disease|Celiac - 0.000000 +24483146 rs9809107 Biomarkers - 0.000002 +21124955 rs2896526 Serum Amyloid A|Type 2 Diabetes - 0.000000 +19247474 rs6452953 Smoking Behaviors|Cigarette Smoking - 0.000007 +23259602 rs4251631 Dental Caries - 0.000000 +23408906 rs11755845 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +22993228 rs710924 Lumbar Disc Degeneration - 0.000010 +23041239 rs17696736 Ischaemic Stroke - 0.000000 +22368281 rs4803760 LDL-c Response|Lpa - 0.000000 +22479419 rs11265461 Treatment Refractory Schizophrenia - 0.000000 +21483430 rs3738401 Neurocognitive Phenotypes - 0.000000 +23593202 rs4805257 Age Menarche|Femoral Neck Bone Geometry - 0.000002 +19096518 rs2305198 Glycated Hemoglobin - 0.000000 +22144915 rs17084051 Corneal Astigmatism - 0.000002 +20801717 rs12608932 Sporadic Amyotrophic Lateral Sclerosis - 0.000000 +23386860 rs10980508 Iron Intake|Type 2 Diabetes - 0.000001 +25742292 rs510579 Parity - 0.000006 +24483146 rs2172820 Biomarkers - 0.000002 +22452962 rs2180341 Breast Cancer - 0.000000 +22087292 rs4507747 Femoral Neck Bone Geometry - 0.000002 +23563607 rs584438 Anthropometric Traits - 0.000000 +22570627 rs7555523 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000000 +22760553 rs13430864 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000001 +19343178 rs4842838 Stature - 0.000000 +19798445 rs1959033 Sphingolipid - 0.000000 +25310577 rs10821936 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +23698163 rs891684 Serum Selenium - 0.000000 +24886709 rs4360309 Lipid - 0.000002 +22843504 rs288604 Autism Spectrum - 0.000000 +24740154 rs6983267 Prostate Cancer|Early-Onset - 0.000000 +24390342 rs73194058 Rheumatoid Arthritis|Biology - 0.000000 +22570627 rs1826598 Primary Open-Angle Glaucoma|Intraocular Pressure - 0.000006 +25340798 rs3092960 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +23667675 rs6472982 Age Menarche - 0.000007 +19801982 rs11898505 Bone Mineral Density - 0.000000 +25742292 rs186478 Parity - 0.000009 +25241909 rs2298019 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000001 +21076409 rs9436640 Conduction|Qrs Duration - 0.000000 +21980494 rs630014 Venous Thrombosis - 0.000000 +21909115 rs381815 Cardiovascular Disease|Blood Pressure - 0.000000 +21298027 rs1517605 Celiac Disease|Crohn's Disease - 0.000003 +21829393 rs657152 Type 1 Diabetes|Autoantibody - 0.000000 +19503597 rs942379 Uric Acid - 0.000000 +23350875 rs8180040 Colorectal Cancer - 0.000002 +23704328 rs12229918 Tooth Eruption|Height - 0.000000 +22504420 rs7017914 Bone Mineral Density - 0.000000 +20190752 rs2327832 Celiac Disease - 0.000000 +23593202 rs7064959 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +23979607 rs6882423 Borderline Personality - 0.000001 +21935397 rs12145833 Extremely|Overweight|Body Mass Index - 0.000000 +21383967 rs10876993 Rheumatoid Arthritis|Celiac Disease - 0.000004 +23974872 rs7085104 Schizophrenia - 0.000000 +22570617 rs10120688 Optic Nerve|Glaucoma - 0.000000 +25367360 rs6708111 Astigmatism|Refractive Error - 0.000004 +21297633 rs17388568 Ulcerative Colitis - 0.000001 +21980494 rs505922 Venous Thrombosis - 0.000000 +24390342 rs6715284 Rheumatoid Arthritis|Biology - 0.000000 +21946350 rs2798641 Lung Function|Follow-Up - 0.000000 +22359512 rs102275 Sphingolipids - 0.000000 +21829377 rs3798713 Plasma Phospholipid|Fatty Acids - 0.000000 +22792070 rs2536150 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23738518 rs7777159 Reading|Language - 0.000006 +20932310 rs11069178 Τ Protein Levels - 0.000000 +18483556 rs7174027 Hair Color|Skin Pigmentation - 0.000000 +25367360 rs1878856 Astigmatism|Refractive Error - 0.000004 +22267201 rs12461110 Age Menopause - 0.000000 +24886709 rs79236614 Lipid - 0.000000 +20526338 rs1671152 Platelet Aggregation - 0.000000 +25367360 rs11690625 Astigmatism|Refractive Error - 0.000000 +19430480 rs7020673 Type 1 Diabetes - 0.000000 +23508266 rs6988229 Asthmatics|Bronchodilator Response - 0.000009 +23936387 rs7097380 Celiac Disease - 0.000003 +21383967 rs1876518 Rheumatoid Arthritis|Celiac Disease - 0.000000 +22993228 rs1205863 Lumbar Disc Degeneration - 0.000006 +19343178 rs7871764 Stature - 0.000002 +19343178 rs1402078 Stature - 0.000006 +19734902 rs1157242 Alzheimer's Disease - 0.000007 +23028341 rs2075799 Complement C3 - 0.000000 +23967269 rs1038770 Mite-Specific IgEs|Asthma - 0.000009 +19798445 rs11666866 Sphingolipid - 0.000000 +24625756 rs4343 Intermediate Phenotypes - 0.000000 +18823527 Rs201825 Late-Onset Alzheimer's Disease - 0.000001 +23455636 rs10737680 Age-Related Macular Degeneration - 0.000000 +23326517 rs10033900 Age-Related Macular Degeneration - 0.000000 +23544013 rs4691139 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000003 +21242260 rs7758229 Colon Cancer - 0.000001 +24483146 rs11636687 Biomarkers - 0.000002 +21901158 rs6576507 Insulin Resistance|Copy Number Variation - 0.000000 +19454037 rs409045 Left Ventricular Mass - 0.000001 +24709693 rs11113818 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000004 +23563607 rs1594829 Anthropometric Traits - 0.000000 +20421936 rs9935401 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +23708191 rs16835979 Congenital Heart Disease|Atrial Septal Defect - 0.000000 +23936387 rs1032355 Celiac Disease - 0.000004 +21935397 rs2815752 Extremely|Overweight|Body Mass Index - 0.000000 +19609347 rs17365948 Hypertension|Blood Pressure - 0.000000 +21804549 rs11735820 Asthma - 0.000000 +22993228 rs1029295 Lumbar Disc Degeneration - 0.000000 +23593202 rs5980450 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +21390209 rs2927488 Late-Onset Alzheimer's Disease - 0.000003 +18604267 rs5498 Antigen|Icam-1 - 0.000000 +21297633 rs6911490 Ulcerative Colitis - 0.000000 +24945404 rs7466269 Bone Mineral Density|Bone - 0.000000 +20339536 rs1883025 Lipid-Lowering Response|Response Statins - 0.000001 +19801982 rs884205 Bone Mineral Density - 0.000000 +23667675 rs3862642 Age Menarche - 0.000005 +23509613 rs6080100 Antiphospholipid Antibodies - 0.000007 +19448621 rs691141 Age Menarche|Menopause - 0.000000 +22087292 rs16913782 Femoral Neck Bone Geometry - 0.000000 +24324648 rs7939777 Serum IgE - 0.000001 +21750679 rs4958881 Systemic Sclerosis - 0.000006 +23408906 rs7860634 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +21298047 rs750338 European-Origin|Substance Dependence - 0.000000 +21390209 rs4551716 Late-Onset Alzheimer's Disease - 0.000008 +19197348 rs4628581 Complex Disease - 0.000004 +19122664 rs11209026 Ulcerative Colitis - 0.000000 +21750679 rs2233287 Systemic Sclerosis - 0.000000 +24094242 rs6911965 Serum Alkaline Phosphatase Levels - 0.000000 +19197348 rs3846663 Complex Disease - 0.000001 +20953189 rs12586317 Psoriasis - 0.000001 +22763110 rs10948172 Osteoarthritis - 0.000000 +24483146 rs12188464 Biomarkers - 0.000002 +20038947 rs1895943 Major Depression - 0.000009 +22829776 rs12150660 Globulin|Hormone|Steroid Hormone - 0.000000 +21771975 rs4783244 Adiponectin|Quantitative Trait|Cardiometabolic Outcomes - 0.000000 +22558097 rs6742078 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +24483146 rs1450679 Biomarkers - 0.000001 +20062060 rs11897119 Pr Interval - 0.000000 +24651765 rs10934753 Homocysteine|Methionine|Metabolism - 0.000000 +23382691 rs11755527 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +20421936 rs1558902 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +23408906 rs2235544 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +25742292 rs4712710 Parity - 0.000003 +22452962 rs704010 Breast Cancer - 0.000000 +21533175 rs17277546 Dehydroepiandrosterone Sulphate - 0.000000 +25367360 rs6708111 Astigmatism|Refractive Error - 0.000001 +23583980 rs7122936 Pulmonary Fibrosis - 0.000007 +25367360 rs7934985 Astigmatism|Refractive Error - 0.000003 +24483146 rs967285 Biomarkers - 0.000002 +22412388 rs1906493 Crohn's Disease - 0.000003 +23408906 rs10799824 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +19734902 rs405509 Alzheimer's Disease - 0.000000 +24068962 rs1801725 Serum Calcium - 0.000000 +21156761 rs2173035 Rheumatoid Arthritis - 0.000001 +21980299 rs3741208 Type 1 Diabetes - 0.000000 +24166486 rs4129585 Schizophrenia - 0.000000 +23326517 rs1999930 Age-Related Macular Degeneration - 0.000000 +20066028 rs10513684 Serum Cholesterol Levels - 0.000001 +19772629 rs4771006 Parkinson Disease|Onset - 0.000007 +25551457 rs11102001 Fibrinogen|Alcohol Consumption|Body Mass Index - 0.000001 +24086445 rs11044106 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000004 +23666240 rs3790672 Testicular Cancer - 0.000000 +24516586 rs717615 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000003 +23382691 rs3757247 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000001 +24023777 rs6570507 Adolescent Idiopathic Scoliosis - 0.000000 +20418485 rs1993116 Vitamin D Levels - 0.000000 +22745674 rs9349379 Coronary Artery Stenosis|Coronary Artery - 0.000000 +23974872 rs6461049 Schizophrenia - 0.000000 +22832961 rs7561528 Alzheimer's Disease - 0.000000 +22452962 rs7716600 Breast Cancer - 0.000001 +21943158 rs173539 Cardiovascular-Related Traits - 0.000000 +21700879 rs3774261 Adiponectin Levels - 0.000001 +24025145 rs3820706 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000000 +19571809 rs7746199 Schizophrenia - 0.000000 +21935397 rs13107325 Extremely|Overweight|Body Mass Index - 0.000000 +23056639 rs4351827 Lectin - 0.000002 +20038947 rs9870680 Major Depression - 0.000006 +25352737 rs9927153 Cataract - 0.000009 +22423221 rs13236689 Platelet Count|Mean Platelet Volume - 0.000000 +23636237 rs9553939 Analysis - 0.000004 +23307926 rs2307449 Menopause - 0.000000 +20661308 rs1550532 Serum Calcium - 0.000004 +23408906 rs657152 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +22843504 rs6752370 Autism Spectrum - 0.000001 +20953189 rs12580100 Psoriasis - 0.000001 +19300482 rs13118928 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +21390209 rs10485435 Late-Onset Alzheimer's Disease - 0.000001 +18483556 rs11636232 Hair Color|Skin Pigmentation - 0.000000 +24047820 rs2352908 Social Communication - 0.000001 +24513273 rs6770152 Serum Uric Acid - 0.000000 +22438815 rs11711441 Parkinson's Disease - 0.000000 +19197348 rs12654264 Complex Disease - 0.000000 +21946350 rs9978142 Lung Function|Follow-Up - 0.000000 +22087292 rs13299777 Femoral Neck Bone Geometry - 0.000001 +24483146 rs1565215 Biomarkers - 0.000002 +22544364 rs3755132 Wilms Tumor - 0.000000 +22685421 rs7544369 Ocular Axial Length|High Myopia - 0.000001 +25017104 rs77569859 Allergic Disease|Eosinophilic Esophagitis - 0.000000 +25162662 rs3791773 Serum Ferritin - 0.000000 +24483146 rs8024695 Biomarkers - 0.000000 +24625756 rs2433610 Intermediate Phenotypes - 0.000000 +23974872 rs171748 Schizophrenia - 0.000000 +20169177 rs6590330 Systemic Lupus Erythematosus - 0.000009 +21829393 rs4971154 Type 1 Diabetes|Autoantibody - 0.000000 +20661308 rs7448017 Serum Calcium - 0.000001 +19305408 rs1805128 Qt Interval Duration - 0.000000 +24390342 rs3806624 Rheumatoid Arthritis|Biology - 0.000000 +23386860 rs17177078 Iron Intake|Type 2 Diabetes - 0.000005 +22719876 rs738407 Non-Alcoholic Fatty Liver Disease|Liver Disease - 0.000000 +19056611 rs10946398 Type 2 Diabetes - 0.000001 +20485516 rs11245330 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +20190752 rs17810546 Celiac Disease - 0.000000 +25367360 rs12607243 Astigmatism|Refractive Error - 0.000002 +25102180 rs3842770 Type 2 Diabetes - 0.000000 +20729852 rs3765524 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +24390342 rs9373594 Rheumatoid Arthritis|Biology - 0.000000 +22479191 rs3925584 Kidney|Follow-Up - 0.000000 +19714249 rs297325 Obesity|Osteoporosis Phenotypes - 0.000001 +23817569 rs7032572 Allergy - 0.000000 +18262040 rs599839 LDL-cholesterol - 0.000000 +24714607 rs1894307 Chronic Mucus Hypersecretion - 0.000007 +23593239 rs2712008 Self-Employment - 0.000010 +19247474 rs800082 Smoking Behaviors|Cigarette Smoking - 0.000003 +23092984 rs12617721 Bipolar Disorder - 0.000007 +24836286 rs10774214 Colorectal Cancer - 0.000000 +21408207 rs3130320 Systemic Lupus Erythematosus|Autoantibody - 0.000003 +23936387 rs13128441 Celiac Disease - 0.000008 +23974872 rs1198588 Schizophrenia - 0.000000 +21909108 rs1878406 Intima Media Thickness|Plaque - 0.000002 +23104006 rs7521902 Endometriosis - 0.000000 +23382691 rs4510766 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +22792070 rs17509082 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23966204 rs10772420 Bitter Taste|Bitter Taste Perception - 0.000001 +24513273 rs12129861 Serum Uric Acid - 0.000000 +22760553 rs17135437 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000000 +19668339 rs429358 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000000 +25147783 rs1256335 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +23834954 rs502281 Sensory Disturbances|Split - 0.000001 +23297363 rs7982677 Tetralogy Fallot - 0.000000 +23297363 rs233716 Tetralogy Fallot - 0.000000 +19169254 rs12191877 Psoriasis - 0.000000 +23459936 rs2521634 Chronic Periodontitis - 0.000002 +18262040 rs629301 LDL-cholesterol - 0.000000 +23666240 rs2720460 Testicular Cancer - 0.000000 +21390209 rs4846486 Late-Onset Alzheimer's Disease - 0.000002 +19343178 rs2714357 Stature - 0.000005 +23401653 rs4864863 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000003 +19197348 rs7561273 Complex Disease - 0.000006 +20442857 rs12192544 Phospholipase A - 0.000000 +20932310 rs10784496 Τ Protein Levels - 0.000000 +21423239 rs5752388 Attempted Suicide - 0.000005 +22792070 rs2908004 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +21665990 rs2230199 Age-Related Macular Degeneration - 0.000000 +19503597 rs9393672 Uric Acid - 0.000000 +21980299 rs2281808 Type 1 Diabetes - 0.000002 +24483146 rs7719624 Biomarkers - 0.000004 +21437268 rs16837730 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +25297839 rs112660930 Herpes Zoster - 0.000000 +24014518 rs7587026 Epilepsy|Febrile Seizures - 0.000000 +25340798 rs6808835 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +20700443 rs7965584 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000006 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +24025145 rs7476422 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000000 +18464913 rs5751901 Protein Quantitative Trait|Genome|Association - 0.000000 +22832960 rs17608059 Temperament Character Inventory - 0.000000 +19300482 rs1051730 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +24513273 rs17632159 Serum Uric Acid - 0.000000 +19197348 rs254893 Complex Disease - 0.000005 +24800985 rs2267386 Birth - 0.000001 +17684544 rs2066844 Ibd Disease - 0.000000 +22359512 rs7258249 Sphingolipids - 0.000000 +24489884 rs4628571 Aggression - 0.000010 +25188341 rs28834970 Dementias|Alzheimer's Disease - 0.000000 +23263487 rs647161 Colorectal Cancer - 0.000003 +22470424 rs2161829 Amyotrophic Lateral Sclerosis - 0.000009 +23703922 rs4698014 Uric Acid Levels - 0.000000 +19343178 rs10946808 Stature - 0.000000 +24571439 rs17194068 Specific Language Impairment|Genotype Effects - 0.000001 +21658281 rs7157599 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +23544013 rs3814113 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +23667675 rs167539 Age Menarche - 0.000002 +19557197 rs17201502 Distribution|Adiposity|Waist Circumference - 0.000004 +19401414 rs13266634 Type 2 Diabetes - 0.000000 +24836286 rs4779584 Colorectal Cancer - 0.000005 +21490949 rs6583826 Type 2 Diabetes|Transferability - 0.000007 +20935630 rs4771122 Body Mass Index - 0.000000 +19571809 rs10140896 Schizophrenia - 0.000001 +24086445 rs1107952 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000001 +20686608 rs2039553 Pancreatic Cancer - 0.000007 +23307926 rs10852344 Menopause - 0.000000 +21448238 rs6107848 Migraine - 0.000006 +19936222 rs983309 Cholesterol|Plasma Lipoprotein Size - 0.000000 +24143190 rs3803662 Breast Cancer|Breast - 0.000000 +18483556 rs164741 Hair Color|Skin Pigmentation - 0.000000 +25436638 rs9687206 Serum Thyroid Stimulating Hormone - 0.000000 +19812673 rs16910194 Autism - 0.000004 +20729852 rs3781264 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +19197348 rs17321515 Complex Disease - 0.000000 +20062060 rs11047543 Pr Interval - 0.000000 +24390342 rs4452313 Rheumatoid Arthritis|Biology - 0.000000 +20339536 rs8014194 Lipid-Lowering Response|Response Statins - 0.000000 +23437003 rs271170 Volumetric Bone Mineral Densities - 0.000000 +22205951 rs2727943 Bipolar Disorder - 0.000000 +24068962 rs780094 Serum Calcium - 0.000000 +24513273 rs2231142 Serum Uric Acid - 0.000000 +19961619 rs2501618 Respiratory|Atopy - 0.000000 +22044751 rs17736767 Chronic Kidney Disease - 0.000007 +24390342 rs726288 Rheumatoid Arthritis|Biology - 0.000000 +20442857 rs4420638 Phospholipase A - 0.000000 +23698163 rs1506807 Serum Selenium - 0.000000 +23408906 rs2235544 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +19570815 rs6717918 C-type Natriuretic Peptide|Height - 0.000000 +19609347 rs11846013 Hypertension|Blood Pressure - 0.000005 +22916037 rs4841132 Atherosclerosis - 0.000000 +20861866 rs1061170 Age-Related Macular Degeneration - 0.000000 +21602797 rs12883884 Cystic Fibrosis|Lung Disease - 0.000001 +23817569 rs10497813 Allergy - 0.000000 +20169177 rs7574865 Systemic Lupus Erythematosus - 0.000000 +18604267 rs281440 Antigen|Icam-1 - 0.000000 +23326239 rs10947262 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21076409 rs7562790 Conduction|Qrs Duration - 0.000000 +21379329 rs2075650 Late-Onset Alzheimer's Disease - 0.000000 +22085899 rs4148323 Bilirubin Levels - 0.000000 +23408906 rs10032216 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +19300500 rs973796 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000007 +20190752 rs17035378 Celiac Disease - 0.000000 +20932310 rs4431886 Τ Protein Levels - 0.000000 +22570697 rs3094157 Multiple Sclerosis - 0.000000 +19247474 rs3112740 Smoking Behaviors|Cigarette Smoking - 0.000006 +22570617 rs4977756 Optic Nerve|Glaucoma - 0.000000 +25310577 rs4245597 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +22570617 rs7049105 Optic Nerve|Glaucoma - 0.000000 +19915575 rs199533 Parkinson’s Disease - 0.000000 +24097068 rs2758886 Lipid Levels - 0.000000 +24347629 rs3783412 Periodontal - 0.000008 +21909115 rs932764 Cardiovascular Disease|Blood Pressure - 0.000000 +19557197 rs7338657 Distribution|Adiposity|Waist Circumference - 0.000001 +22470424 rs617459 Amyotrophic Lateral Sclerosis - 0.000005 +24143190 rs2981578 Breast Cancer|Breast - 0.000000 +22452962 rs13387042 Breast Cancer - 0.000000 +23382691 rs11847263 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +24489884 rs12249434 Aggression - 0.000004 +21437268 rs1573496 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +22511988 rs4148324 Cell-Free Dna|Cardiovascular - 0.000000 +20485516 rs9938149 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease - 0.000000 +19936222 rs7923609 Cholesterol|Plasma Lipoprotein Size - 0.000000 +24945404 rs12272917 Bone Mineral Density|Bone - 0.000000 +21552555 rs4784323 Obesity|Obesity-Related Traits - 0.000004 +24740154 rs1880408 Prostate Cancer|Early-Onset - 0.000007 +24403052 rs7006527 Basal Cell Carcinoma - 0.000000 +19247474 rs886716 Smoking Behaviors|Cigarette Smoking - 0.000008 +22368281 rs5004272 LDL-c Response|Lpa - 0.000000 +24836286 rs6983267 Colorectal Cancer - 0.000000 +21273288 rs10845158 NT-proBNP - 0.000009 +22544364 rs790356 Wilms Tumor - 0.000000 +19587794 rs11153730 Sudden Cardiac Death - 0.000004 +22993228 rs2187689 Lumbar Disc Degeneration - 0.000000 +20442857 rs599839 Phospholipase A - 0.000000 +23958962 rs34831910 Cocaine Dependence - 0.000001 +23874384 rs10865864 Behavior - 0.000004 +25436638 rs1571583 Serum Thyroid Stimulating Hormone - 0.000000 +20190752 rs2074404 Celiac Disease - 0.000001 +24755620 rs2075650 Glutamate|Alzheimer's Disease - 0.000000 +22087292 rs10928979 Femoral Neck Bone Geometry - 0.000001 +22247754 rs3848198 Arrhythmias - 0.000010 +19430480 rs4900384 Type 1 Diabetes - 0.000000 +21390209 rs2502562 Late-Onset Alzheimer's Disease - 0.000002 +19081515 rs1799990 Creutzfeldt–Jakob Disease - 0.000000 +24871463 rs7574865 Systemic Lupus Erythematosus Sle - 0.000000 +24489884 rs6954895 Aggression - 0.000000 +21935397 rs12444979 Extremely|Overweight|Body Mass Index - 0.000000 +21156761 rs6448119 Rheumatoid Arthritis - 0.000007 +24688116 rs4466755 Longevity|Analysis|Population - 0.000003 +20169177 rs2254546 Systemic Lupus Erythematosus - 0.000010 +22085899 rs4236644 Bilirubin Levels - 0.000002 +19961619 rs4952590 Respiratory|Atopy - 0.000002 +20081858 rs11708067 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +19197348 rs2527865 Complex Disease - 0.000004 +21829377 rs3734398 Plasma Phospholipid|Fatty Acids - 0.000000 +21347284 rs3922844 Pr Interval - 0.000000 +20190752 rs9792269 Celiac Disease - 0.000000 +21738491 rs4665058 Sudden Cardiac Death - 0.000000 +23092984 rs4450798 Bipolar Disorder - 0.000002 +19197348 rs4420638 Complex Disease - 0.000000 +21297633 rs12261843 Ulcerative Colitis - 0.000000 +18604267 rs1799969 Antigen|Icam-1 - 0.000000 +19247474 rs11082304 Smoking Behaviors|Cigarette Smoking - 0.000006 +25367360 rs17795358 Astigmatism|Refractive Error - 0.000000 +22267201 rs4693089 Age Menopause - 0.000000 +25188341 rs1476679 Dementias|Alzheimer's Disease - 0.000000 +17903300 rs1106683 Waist Circumference|Body Mass Index - 0.000004 +21909115 rs13139571 Cardiovascular Disease|Blood Pressure - 0.000000 +19798445 rs12889954 Sphingolipid - 0.000000 +22484627 rs9568856 Childhood Obesity - 0.000001 +21804549 rs4653433 Asthma - 0.000001 +23667675 rs4735738 Age Menarche - 0.000005 +20195514 rs4844096 Primary Tooth Development - 0.000000 +25162662 rs5742933 Serum Ferritin - 0.000000 +21738491 rs12601622 Sudden Cardiac Death - 0.000000 +23958962 rs13381416 Cocaine Dependence - 0.000001 +24204295 rs2854536 Narcolepsy|Influenza|Changes - 0.000000 +20932310 rs6850199 Τ Protein Levels - 0.000000 +23593202 rs6975557 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +23583980 rs11191865 Pulmonary Fibrosis - 0.000000 +19343178 rs2282978 Stature - 0.000000 +20548946 rs12025126 Optic Disc - 0.000000 +18941528 rs4284505 Multiple Sclerosis - 0.000004 +22763110 rs6976 Osteoarthritis - 0.000000 +25352737 rs207145 Cataract - 0.000008 +21665990 rs10468017 Age-Related Macular Degeneration - 0.000000 +21297633 rs11676348 Ulcerative Colitis - 0.000000 +21738491 rs11626637 Sudden Cardiac Death - 0.000010 +22745674 rs7964864 Coronary Artery Stenosis|Coronary Artery - 0.000007 +23593239 rs4867424 Self-Employment - 0.000008 +22589738 rs2815752 Adipose - 0.000004 +21700879 rs822354 Adiponectin Levels - 0.000000 +18823527 Rs7798395 Late-Onset Alzheimer's Disease - 0.000002 +19668339 rs7727656 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000008 +24740154 rs3734234 Prostate Cancer|Early-Onset - 0.000007 +20442857 rs4970834 Phospholipase A - 0.000000 +23326239 rs3130626 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23423138 rs133885 Mathematical Abilities|Dyslexia|Myosin - 0.000000 +22763110 rs835487 Osteoarthritis - 0.000000 +22666496 rs13318232 Cardiovascular Event - 0.000004 +23703922 rs1769242 Uric Acid Levels - 0.000003 +23696099 rs1050828 Cell Traits|Red Blood Cell|Resistance - 0.000000 +21804549 rs11078927 Asthma - 0.000000 +21779181 rs6457617 Systemic Sclerosis - 0.000000 +23326239 rs652888 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23870195 rs4977575 Coronary Artery|Coronary Artery Calcification - 0.000000 +23382691 rs1847472 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +18483556 rs4785763 Hair Color|Skin Pigmentation - 0.000000 +24489884 rs3752433 Aggression - 0.000000 +19343178 rs3118916 Stature - 0.000000 +19812673 rs4742409 Autism - 0.000008 +19571809 rs10865802 Schizophrenia - 0.000007 +24836286 rs4246215 Colorectal Cancer - 0.000000 +20436471 rs484959 Paget’s Disease Bone - 0.000000 +20038947 rs11710109 Major Depression - 0.000000 +24709693 rs10128264 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000001 +23844046 rs2794520 C-Reactive Protein - 0.000000 +22470424 rs2278170 Amyotrophic Lateral Sclerosis - 0.000007 +19961619 rs2330183 Respiratory|Atopy - 0.000000 +24489884 rs16840114 Aggression - 0.000009 +21297633 rs10781499 Ulcerative Colitis - 0.000000 +22993228 rs1981483 Lumbar Disc Degeneration - 0.000004 +22423221 rs8109288 Platelet Count|Mean Platelet Volume - 0.000000 +19197348 rs7917302 Complex Disease - 0.000002 +22916037 rs1440581 Atherosclerosis - 0.000000 +22675492 rs424950 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000005 +21829377 rs174547 Plasma Phospholipid|Fatty Acids - 0.000000 +23984888 rs296282 Airway Responsiveness - 0.000008 +23583980 rs2076295 Pulmonary Fibrosis - 0.000000 +21076409 rs991014 Conduction|Qrs Duration - 0.000000 +21437268 rs1431918 Cancers|Conducted|Upper Aerodigestive Tract - 0.000007 +24097068 rs4650994 Lipid Levels - 0.000000 +20339536 rs7633531 Lipid-Lowering Response|Response Statins - 0.000000 +23704328 rs1994969 Tooth Eruption|Height - 0.000000 +23666240 rs8046148 Testicular Cancer - 0.000000 +19772629 rs10767971 Parkinson Disease|Onset - 0.000001 +21297633 rs941823 Ulcerative Colitis - 0.000000 +24709693 rs7800668 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000006 +23974872 rs4687552 Schizophrenia - 0.000000 +19081515 rs6107516 Creutzfeldt–Jakob Disease - 0.000000 +21665990 rs9621532 Age-Related Macular Degeneration - 0.000000 +20436471 rs2957128 Paget’s Disease Bone - 0.000000 +20861866 rs641153 Age-Related Macular Degeneration - 0.000000 +18776929 rs10180112 Hip Bone Size|Females - 0.000005 +19668339 rs8115854 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000002 +22558097 rs10168155 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +21448238 rs1146161 Migraine - 0.000009 +22504420 rs7071206 Bone Mineral Density - 0.000000 +21909115 rs3184504 Cardiovascular Disease|Blood Pressure - 0.000000 +19430480 rs12708716 Type 1 Diabetes - 0.000000 +22368281 rs1985096 LDL-c Response|Lpa - 0.000000 +18823527 Rs16916856 Late-Onset Alzheimer's Disease - 0.000008 +19305408 rs2968864 Qt Interval Duration - 0.000000 +22993228 rs1029296 Lumbar Disc Degeneration - 0.000000 +22693455 rs7178572 Obese|Type 2 Diabetes - 0.000000 +21738491 rs2178490 Sudden Cardiac Death - 0.000006 +23382691 rs909674 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +23455636 rs2230199 Age-Related Macular Degeneration - 0.000000 +25188341 rs3865444 Dementias|Alzheimer's Disease - 0.000003 +18483556 rs7495174 Hair Color|Skin Pigmentation - 0.000000 +24513273 rs16890979 Serum Uric Acid - 0.000000 +22993228 rs737631 Lumbar Disc Degeneration - 0.000004 +21448238 rs140174 Migraine - 0.000007 +21437268 rs698 Cancers|Conducted|Upper Aerodigestive Tract - 0.000000 +24513273 rs10821905 Serum Uric Acid - 0.000000 +25188341 rs6733839 Dementias|Alzheimer's Disease - 0.000000 +25060954 rs1393902 Kinase|Hearing - 0.000000 +21533175 rs7181230 Dehydroepiandrosterone Sulphate - 0.000000 +17903293 rs2794520 Biomarker Traits - 0.000000 +23041239 rs7432308 Ischaemic Stroke - 0.000002 +24740154 rs8064701 Prostate Cancer|Early-Onset - 0.000005 +20953186 rs13190932 Psoriasis|Psoriatic Arthritis - 0.000000 +23738518 rs6954796 Reading|Language - 0.000002 +22961001 rs9936833 Barrett’s Esophagus - 0.000000 +22504420 rs7584262 Bone Mineral Density - 0.000000 +24133439 rs11859884 Autistic-Like Traits - 0.000003 +18823527 Rs13397414 Late-Onset Alzheimer's Disease - 0.000000 +22558097 rs2070959 Total Bilirubin|Sickle Cell Anemia|Sickle Cell - 0.000000 +22359512 rs17101394 Sphingolipids - 0.000000 +23382691 rs2186369 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +20661308 rs17120351 Serum Calcium - 0.000000 +23984888 rs4485561 Airway Responsiveness - 0.000010 +24324648 rs2078158 Serum IgE - 0.000001 +22085899 rs2117032 Bilirubin Levels - 0.000000 +22666496 rs2492367 Cardiovascular Event - 0.000006 +19915575 rs2896905 Parkinson’s Disease - 0.000005 +23386860 rs1525739 Iron Intake|Type 2 Diabetes - 0.000006 +20442857 rs10846744 Phospholipase A - 0.000000 +22693455 rs11708067 Obese|Type 2 Diabetes - 0.000000 +20700443 rs7197653 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000002 +24483146 rs2274870 Biomarkers - 0.000004 +20522523 rs346291 Partial Epilepsies - 0.000000 +23455636 rs334353 Age-Related Macular Degeneration - 0.000000 +20932310 rs11015839 Τ Protein Levels - 0.000001 +24483146 rs316823 Biomarkers - 0.000003 +21983785 rs7412746 Melanoma - 0.000000 +20190752 rs1033180 Celiac Disease - 0.000000 +21935397 rs734597 Extremely|Overweight|Body Mass Index - 0.000000 +22832961 rs1357692 Alzheimer's Disease - 0.000003 +24625756 rs4343 Intermediate Phenotypes - 0.000000 +23001564 rs412658 Homeostasis - 0.000000 +22561518 rs3184504 Generalized Vitiligo - 0.000000 +25129146 rs7447927 Esophageal Squamous Cell Carcinoma - 0.000003 +19096518 rs13266634 Glycated Hemoglobin - 0.000000 +24709693 rs2802369 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000007 +21079607 rs9839776 Anorexia Nervosa - 0.000000 +24778558 rs3883013 Coronary Heart Disease - 0.000000 +19772629 rs3887942 Parkinson Disease|Onset - 0.000006 +25390645 rs6463447 Anxiety - 0.000008 +22685421 rs12055210 Ocular Axial Length|High Myopia - 0.000009 +23401653 rs6850748 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000003 +21297633 rs2838519 Ulcerative Colitis - 0.000000 +22941191 rs9404576 Neuroblastoma - 0.000000 +18840781 rs7072793 Type 1 Diabetes - 0.000000 +25129146 rs1642764 Esophageal Squamous Cell Carcinoma - 0.000002 +24709693 rs10956445 Methotrexate Response|Juvenile Idiopathic Arthritis - 0.000000 +23704328 rs997154 Tooth Eruption|Height - 0.000000 +23974872 rs11995572 Schizophrenia - 0.000000 +19197348 rs693 Complex Disease - 0.000000 +22843504 rs3782000 Autism Spectrum - 0.000000 +25060954 rs1393901 Kinase|Hearing - 0.000000 +22675492 rs12596210 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000009 +18840781 rs8035957 Type 1 Diabetes - 0.000004 +24571439 rs3181384 Specific Language Impairment|Genotype Effects - 0.000002 +23382691 rs4730276 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000009 +24086445 rs11044045 Schizophrenia|Quantitative Phenotype|Matter Volume - 0.000005 +23646285 rs12471007 Hypersomnia - 0.000000 +19122664 rs11465804 Ulcerative Colitis - 0.000001 +17903307 rs156697 Pulmonary Function - 0.000010 +22452962 rs9498283 Breast Cancer - 0.000005 +21502949 rs9392374 Brain - 0.000005 +21297633 rs2297441 Ulcerative Colitis - 0.000000 +22359512 rs680379 Sphingolipids - 0.000000 +23667675 rs9391253 Age Menarche - 0.000001 +23958962 rs114903983 Cocaine Dependence - 0.000000 +19122664 rs7134599 Ulcerative Colitis - 0.000000 +22452962 rs2048672 Breast Cancer - 0.000006 +18941528 rs4284505 Multiple Sclerosis - 0.000000 +17684544 rs2241880 Ibd Disease - 0.000001 +24478790 rs10466239 Telomere Length - 0.000006 +19801982 rs1366594 Bone Mineral Density - 0.000000 +20038947 rs12462886 Major Depression - 0.000002 +21156761 rs3807306 Rheumatoid Arthritis - 0.000000 +18483556 rs12913832 Hair Color|Skin Pigmentation - 0.000000 +22452962 rs11249433 Breast Cancer - 0.000000 +19343178 rs8756 Stature - 0.000000 +21399635 rs2293370 Primary Biliary Cirrhosis - 0.000000 +22412388 rs6545946 Crohn's Disease - 0.000000 +20038947 rs17144465 Major Depression - 0.000005 +21909115 rs13107325 Cardiovascular Disease|Blood Pressure - 0.000000 +21273288 rs1023252 NT-proBNP - 0.000000 +24714607 rs7836298 Chronic Mucus Hypersecretion - 0.000004 +19197348 rs6018089 Complex Disease - 0.000002 +21437268 rs11067362 Cancers|Conducted|Upper Aerodigestive Tract - 0.000006 +24952745 rs11779860 Qt Interval|Calcium - 0.000000 +22666496 rs4830819 Cardiovascular Event - 0.000008 +24513273 rs2941484 Serum Uric Acid - 0.000000 +25367360 rs17795388 Astigmatism|Refractive Error - 0.000000 +23704328 rs11796357 Tooth Eruption|Height - 0.000000 +23326239 rs3130557 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +20041166 rs9264942 Hiv-1 - 0.000000 +21552555 rs925642 Obesity|Obesity-Related Traits - 0.000007 +23936387 rs4240931 Celiac Disease - 0.000000 +23593239 rs2358531 Self-Employment - 0.000005 +23544013 rs11196175 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +22675492 rs6016142 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000000 +21814517 rs2281389 Asthma - 0.000000 +23326517 rs1329428 Age-Related Macular Degeneration - 0.000000 +23326517 rs3793917 Age-Related Macular Degeneration - 0.000000 +22561518 rs4822024 Generalized Vitiligo - 0.000000 +23459936 rs11925054 Chronic Periodontitis - 0.000001 +21901158 rs4819143 Insulin Resistance|Copy Number Variation - 0.000001 +25129146 rs7447927 Esophageal Squamous Cell Carcinoma - 0.000004 +22829776 rs4149056 Globulin|Hormone|Steroid Hormone - 0.000002 +19798445 rs12881815 Sphingolipid - 0.000000 +23563607 rs7503807 Anthropometric Traits - 0.000000 +19668339 rs1082714 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000005 +23326517 rs1329424 Age-Related Macular Degeneration - 0.000000 +21408207 rs1463525 Systemic Lupus Erythematosus|Autoantibody - 0.000008 +21298027 rs40254 Celiac Disease|Crohn's Disease - 0.000007 +19401414 rs7756992 Type 2 Diabetes - 0.000000 +23563607 rs584438 Anthropometric Traits - 0.000000 +18262040 rs10402271 LDL-cholesterol - 0.000000 +24908248 rs6010620 Telomere Length|Glioma - 0.000000 +21423719 rs738409 Metabolic Traits|Nonalcoholic Fatty Liver Disease - 0.000000 +25226531 rs11176749 Suggest|Associated|Linguistic Phenotype - 0.000001 +22916037 rs4149310 Atherosclerosis - 0.000000 +25526632 rs1149185 Breast Cancer - 0.000002 +21223598 rs1825630 Aortic Root - 0.000008 +22396660 rs12669187 Nephrolithiasis - 0.000001 +22561518 rs10768122 Generalized Vitiligo - 0.000000 +25140149 rs6887649 Neurodegeneration|Biomarker - 0.000000 +21423719 rs2228603 Metabolic Traits|Nonalcoholic Fatty Liver Disease - 0.000000 +20038947 rs9870680 Major Depression - 0.000001 +22504420 rs4796995 Bone Mineral Density - 0.000000 +23326517 rs10737680 Age-Related Macular Degeneration - 0.000000 +24586183 rs10944479 Thyroid Peroxidase Antibodies|Thyroid Disease - 0.000000 +18464913 rs7770628 Protein Quantitative Trait|Genome|Association - 0.000000 +19571809 rs17149424 Schizophrenia - 0.000008 +24449572 rs3890745 Rheumatoid Arthritis - 0.000001 +24097068 rs4883201 Lipid Levels - 0.000000 +20935630 rs10938397 Body Mass Index - 0.000000 +24778558 rs3853444 Coronary Heart Disease - 0.000005 +23817569 rs17228058 Allergy - 0.000000 +24143190 rs1219648 Breast Cancer|Breast - 0.000010 +22087292 rs16913751 Femoral Neck Bone Geometry - 0.000002 +24871463 rs4544377 Systemic Lupus Erythematosus Sle - 0.000002 +19668339 rs6031882 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000006 +19300500 rs13147758 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +24952745 rs7561149 Qt Interval|Calcium - 0.000000 +22911880 rs10519201 Behaviors|Personality Traits|Eating - 0.000006 +22843504 rs1718101 Autism Spectrum - 0.000000 +21552555 rs9941349 Obesity|Obesity-Related Traits - 0.000000 +20661308 rs6111021 Serum Calcium - 0.000008 +21901158 rs16962638 Insulin Resistance|Copy Number Variation - 0.000006 +20038947 rs2326810 Major Depression - 0.000007 +21901158 rs591044 Insulin Resistance|Copy Number Variation - 0.000006 +21685912 rs1768208 Progressive Supranuclear Palsy - 0.000000 +21390209 rs12989701 Late-Onset Alzheimer's Disease - 0.000005 +23984888 rs614664 Airway Responsiveness - 0.000006 +22504420 rs1564981 Bone Mineral Density - 0.000000 +23472165 rs6907340 Endometriosis - 0.000005 +21552555 rs3751812 Obesity|Obesity-Related Traits - 0.000000 +24763700 rs735396 C-Reactive Protein Levels - 0.000000 +22675492 rs909814 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000001 +19096518 rs563694 Glycated Hemoglobin - 0.000000 +24324648 rs3130941 Serum IgE - 0.000000 +21423239 rs7296262 Attempted Suicide - 0.000009 +22693455 rs7903146 Obese|Type 2 Diabetes - 0.000000 +18483556 rs7196459 Hair Color|Skin Pigmentation - 0.000000 +19571809 rs9272219 Schizophrenia - 0.000000 +25147783 rs526934 Ischemic Stroke|Vitamin|Folate Levels - 0.000000 +19305408 rs11756438 Qt Interval Duration - 0.000000 +22675492 rs10795130 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000007 +21533024 rs738409 Icam-1 - 0.000000 +24097068 rs970548 Lipid Levels - 0.000000 +17903305 rs9311171 Prostate Cancer|Breast - 0.000002 +22044751 rs17111435 Chronic Kidney Disease - 0.000003 +19801982 rs10048146 Bone Mineral Density - 0.000000 +25310821 rs12639288 Hirschsprung Disease - 0.000005 +23636237 rs2609186 Analysis - 0.000001 +22479202 rs2590838 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +21901158 rs8026527 Insulin Resistance|Copy Number Variation - 0.000001 +18823527 Rs727153 Late-Onset Alzheimer's Disease - 0.000003 +22452962 rs16886165 Breast Cancer - 0.000000 +21076409 rs9912468 Conduction|Qrs Duration - 0.000000 +23455636 rs943080 Age-Related Macular Degeneration - 0.000000 +17903305 rs6556756 Prostate Cancer|Breast - 0.000000 +23593202 rs6578987 Age Menarche|Femoral Neck Bone Geometry - 0.000001 +17903305 rs10490113 Prostate Cancer|Breast - 0.000005 +23834954 rs13236243 Sensory Disturbances|Split - 0.000004 +22359512 rs7259004 Sphingolipids - 0.000000 +24571439 rs2144494 Specific Language Impairment|Genotype Effects - 0.000000 +20173748 rs2869967 Chronic Obstructive Pulmonary Disease - 0.000001 +23028483 rs2073643 Asthma - 0.000000 +24094242 rs16856332 Serum Alkaline Phosphatase Levels - 0.000000 +22044751 rs10744391 Chronic Kidney Disease - 0.000001 +25436638 rs1537424 Serum Thyroid Stimulating Hormone - 0.000000 +23593202 rs13230316 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +19571809 rs2162361 Schizophrenia - 0.000009 +23583980 rs12610495 Pulmonary Fibrosis - 0.000000 +25233373 rs10089517 Myopia|Hyperopia - 0.000000 +24483146 rs10510741 Biomarkers - 0.000005 +24847357 rs3804047 Staphylococcus Aureus - 0.000003 +22792071 rs2908004 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23472165 rs4654783 Endometriosis - 0.000000 +24755620 rs249153 Glutamate|Alzheimer's Disease - 0.000000 +22470424 rs17145184 Amyotrophic Lateral Sclerosis - 0.000005 +22044751 rs1572050 Chronic Kidney Disease - 0.000006 +25378659 rs680379 Long-Chain Saturated Fatty Acids - 0.000000 +20442857 rs1421378 Phospholipase A - 0.000000 +21297633 rs1297265 Ulcerative Colitis - 0.000000 +22412388 rs2076756 Crohn's Disease - 0.000000 +19571809 rs6809315 Schizophrenia - 0.000008 +23307926 rs2153157 Menopause - 0.000000 +20661308 rs17005914 Serum Calcium - 0.000006 +21533074 rs10484561 Diffuse Large B-cell Lymphoma|Follicular Lymphoma|Diffuse - 0.000000 +19096518 rs7072268 Glycated Hemoglobin - 0.000000 +24945404 rs2130604 Bone Mineral Density|Bone - 0.000000 +21998595 rs724577 Height - 0.000000 +25340798 rs679620 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +22561518 rs6510827 Generalized Vitiligo - 0.000000 +22291604 rs10168266 Lupus - 0.000000 +23761726 rs11841001 Corneal Astigmatism|Platelet-Derived Growth Factor - 0.000004 +24390342 rs11089637 Rheumatoid Arthritis|Biology - 0.000000 +23703922 rs1860910 Uric Acid Levels - 0.000000 +23459936 rs3826782 Chronic Periodontitis - 0.000001 +25188341 rs10792832 Dementias|Alzheimer's Disease - 0.000000 +20200953 rs16864755 Osteoporosis-Related Phenotypes - 0.000004 +22452962 rs10411161 Breast Cancer - 0.000007 +24952745 rs938291 Qt Interval|Calcium - 0.000000 +22359512 rs680379 Sphingolipids - 0.000000 +22760553 rs11935103 Global Disease|Depression|Citalopram-Induced Side Effects - 0.000001 +21223598 rs12600277 Aortic Root - 0.000003 +23028483 rs7216389 Asthma - 0.000000 +21658281 rs17718586 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +20190752 rs10806425 Celiac Disease - 0.000000 +21700879 rs10517133 Adiponectin Levels - 0.000001 +20522523 rs9341799 Partial Epilepsies - 0.000000 +24755620 rs440277 Glutamate|Alzheimer's Disease - 0.000000 +24483146 rs4774760 Biomarkers - 0.000002 +24625756 rs12288023 Intermediate Phenotypes - 0.000000 +22267201 rs365132 Age Menopause - 0.000000 +21502949 rs4752194 Brain - 0.000006 +21750679 rs9275224 Systemic Sclerosis - 0.000000 +24047820 rs11625667 Social Communication - 0.000004 +24097068 rs7640978 Lipid Levels - 0.000000 +20935630 rs3817334 Body Mass Index - 0.000000 +21297633 rs7554511 Ulcerative Colitis - 0.000000 +22504421 rs6741949 Hippocampal Volume - 0.000000 +24483146 rs9861198 Biomarkers - 0.000005 +24999842 rs531930 Celiac Disease|Celiac - 0.000001 +23646285 rs16966389 Hypersomnia - 0.000001 +20686608 rs9502893 Pancreatic Cancer - 0.000000 +19197348 rs10518224 Complex Disease - 0.000007 +23118916 rs11653545 Serum IgM - 0.000000 +24094242 rs7186908 Serum Alkaline Phosphatase Levels - 0.000000 +24347629 rs10457525 Periodontal - 0.000003 +19430480 rs1893217 Type 1 Diabetes - 0.000000 +19343178 rs1812175 Stature - 0.000000 +19430480 rs4505848 Type 1 Diabetes - 0.000000 +24755620 rs10405693 Glutamate|Alzheimer's Disease - 0.000000 +21980299 rs3087243 Type 1 Diabetes - 0.000000 +20548946 rs1547014 Optic Disc - 0.000000 +24871463 rs10911628 Systemic Lupus Erythematosus Sle - 0.000000 +22941191 rs4079063 Neuroblastoma - 0.000000 +24483146 rs11636687 Biomarkers - 0.000000 +22511988 rs17864701 Cell-Free Dna|Cardiovascular - 0.000000 +20729852 rs4460629 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +23583980 rs1981997 Pulmonary Fibrosis - 0.000000 +19772629 rs17565841 Parkinson Disease|Onset - 0.000002 +21738491 rs3193970 Sudden Cardiac Death - 0.000001 +21935397 rs7138803 Extremely|Overweight|Body Mass Index - 0.000000 +20932310 rs10763625 Τ Protein Levels - 0.000001 +22479202 rs2925979 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +20972438 rs2294008 Bladder Cancer|Bladder - 0.000000 +21379329 rs201099 Late-Onset Alzheimer's Disease - 0.000000 +21980299 rs539514 Type 1 Diabetes - 0.000000 +19197348 rs6560749 Complex Disease - 0.000007 +22719876 rs738409 Non-Alcoholic Fatty Liver Disease|Liver Disease - 0.000000 +17684544 rs11209026 Ibd Disease - 0.000000 +19714249 rs4756846 Obesity|Osteoporosis Phenotypes - 0.000001 +19571809 rs16897515 Schizophrenia - 0.000000 +22470424 rs639964 Amyotrophic Lateral Sclerosis - 0.000005 +21460841 rs561655 Late-Onset Alzheimer’s Disease - 0.000000 +25551457 rs7120820 Fibrinogen|Alcohol Consumption|Body Mass Index - 0.000002 +23326239 rs3130623 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +20953189 rs4795067 Psoriasis - 0.000000 +24094242 rs2236653 Serum Alkaline Phosphatase Levels - 0.000000 +20169177 rs7097397 Systemic Lupus Erythematosus - 0.000000 +21935397 rs8089364 Extremely|Overweight|Body Mass Index - 0.000000 +20169177 rs729302 Systemic Lupus Erythematosus - 0.000010 +24489884 rs555017 Aggression - 0.000004 +22693455 rs3802177 Obese|Type 2 Diabetes - 0.000000 +19412175 rs17487792 Neuroblastoma - 0.000000 +21779176 rs12593813 Restless Legs Syndrome - 0.000000 +23667675 rs314262 Age Menarche - 0.000001 +25064009 rs14235 Parkinson’s Disease - 0.000000 +19801982 rs1524058 Bone Mineral Density - 0.000000 +21827660 rs506044 Increased Disease Risk - 0.000002 +24166486 rs12537914 Schizophrenia - 0.000000 +19448621 rs897798 Age Menarche|Menopause - 0.000000 +21124946 rs17066364 Bone Mineral Density - 0.000004 +23593239 rs7904494 Self-Employment - 0.000007 +23966204 rs10743937 Bitter Taste|Bitter Taste Perception - 0.000001 +24280982 rs1006737 Schizophrenia|Bipolar Disorder|Disorder - 0.000000 +22170493 rs6596086 Psoriatic Arthritis - 0.000010 +23817569 rs962993 Allergy - 0.000000 +23593202 rs6975557 Age Menarche|Femoral Neck Bone Geometry - 0.000000 +21460841 rs11767557 Late-Onset Alzheimer’s Disease - 0.000000 +21980494 rs1208134 Venous Thrombosis - 0.000000 +21298047 rs10893365 European-Origin|Substance Dependence - 0.000000 +22116950 rs9875589 Ovarian Reserve - 0.000004 +22504420 rs3736228 Bone Mineral Density - 0.000000 +24625756 rs7422339 Intermediate Phenotypes - 0.000000 +22843504 rs14135 Autism Spectrum - 0.000000 +19772629 rs10147486 Parkinson Disease|Onset - 0.000001 +21829393 rs763361 Type 1 Diabetes|Autoantibody - 0.000000 +23979607 rs11951568 Borderline Personality - 0.000003 +23326517 rs10737680 Age-Related Macular Degeneration - 0.000000 +24908248 rs2736100 Telomere Length|Glioma - 0.000000 +22412388 rs3091316 Crohn's Disease - 0.000000 +20686608 rs4683235 Pancreatic Cancer - 0.000010 +22675492 rs8077059 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000005 +25129146 rs35597309 Esophageal Squamous Cell Carcinoma - 0.000000 +21399635 rs11117432 Primary Biliary Cirrhosis - 0.000000 +23408906 rs10799824 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +23958962 rs1757939 Cocaine Dependence - 0.000001 +20935630 rs206936 Body Mass Index - 0.000000 +23593239 rs521326 Self-Employment - 0.000003 +20935630 rs543874 Body Mass Index - 0.000000 +24379826 rs6786174 Serum Uric Acid Levels - 0.000001 +23936387 rs157640 Celiac Disease - 0.000005 +24166486 rs3800913 Schizophrenia - 0.000000 +25340798 rs573521 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +19343178 rs2401171 Stature - 0.000000 +23028483 rs1420101 Asthma - 0.000000 +24166486 rs10098073 Schizophrenia - 0.000000 +23326517 rs7750345 Age-Related Macular Degeneration - 0.000007 +25064009 rs6812193 Parkinson’s Disease - 0.000000 +19609347 rs9590141 Hypertension|Blood Pressure - 0.000001 +21998595 rs6440003 Height - 0.000000 +21326860 rs1568657 Kawasaki Disease - 0.000007 +22829776 rs12150660 Globulin|Hormone|Steroid Hormone - 0.000000 +24945404 rs754388 Bone Mineral Density|Bone - 0.000000 +22504420 rs479336 Bone Mineral Density - 0.000000 +22087292 rs969715 Femoral Neck Bone Geometry - 0.000001 +23667675 rs7822914 Age Menarche - 0.000007 +19343178 rs6817306 Stature - 0.000000 +20862305 rs5015480 Type 2 Diabetes - 0.000009 +21408207 rs7574865 Systemic Lupus Erythematosus|Autoantibody - 0.000008 +23703922 rs6827754 Uric Acid Levels - 0.000000 +22479202 rs1597466 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +18840781 rs1004446 Type 1 Diabetes - 0.000000 +19454037 rs409045 Left Ventricular Mass - 0.000001 +22238593 rs6451146 Type 2 Diabetes - 0.000010 +20339536 rs247616 Lipid-Lowering Response|Response Statins - 0.000000 +24945404 rs3920498 Bone Mineral Density|Bone - 0.000000 +22675492 rs9905820 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000004 +19197348 rs7069923 Complex Disease - 0.000001 +25367360 rs885560 Astigmatism|Refractive Error - 0.000000 +23667675 rs1744206 Age Menarche - 0.000001 +23350875 rs7087402 Colorectal Cancer - 0.000005 +21658281 rs12189362 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +24886709 rs9989419 Lipid - 0.000000 +21347284 rs10865355 Pr Interval - 0.000000 +23667675 rs3889461 Age Menarche - 0.000006 +21750679 rs2725466 Systemic Sclerosis - 0.000005 +23307926 rs2517388 Menopause - 0.000000 +21665990 rs3764261 Age-Related Macular Degeneration - 0.000000 +25760438 rs10841048 Type 2 Diabetes|Body Mass Index - 0.000001 +19056611 rs8050136 Type 2 Diabetes - 0.000000 +24390342 rs4272 Rheumatoid Arthritis|Biology - 0.000000 +19503597 rs2199936 Uric Acid - 0.000000 +22470424 rs6453104 Amyotrophic Lateral Sclerosis - 0.000007 +21873549 rs4502156 Type 2 Diabetes|Proinsulin Levels - 0.000000 +22993228 rs2017567 Lumbar Disc Degeneration - 0.000009 +24513273 rs505802 Serum Uric Acid - 0.000000 +23936387 rs1871350 Celiac Disease - 0.000008 +22829776 rs9303218 Globulin|Hormone|Steroid Hormone - 0.000000 +18455228 rs4355801 Bone Mineral Density|Osteoporosis - 0.000000 +22470424 rs17263670 Amyotrophic Lateral Sclerosis - 0.000010 +22479202 rs6810075 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +20038947 rs2203374 Major Depression - 0.000003 +25569183 rs2922994 Marginal Zone Lymphoma - 0.000000 +20038947 rs435206 Major Depression - 0.000001 +19557197 rs569406 Distribution|Adiposity|Waist Circumference - 0.000005 +19081515 rs1799990 Creutzfeldt–Jakob Disease - 0.000000 +21408207 rs9888739 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +21060863 rs17421627 Cardiovascular Diseases - 0.000000 +22428042 rs523096 Glaucoma|Optic-Nerve - 0.000000 +25390645 rs10893268 Anxiety - 0.000001 +25350695 rs445925 Ldl Cholesterol Response|Response Statins - 0.000000 +22267201 rs4246511 Age Menopause - 0.000000 +23761726 rs1164064 Corneal Astigmatism|Platelet-Derived Growth Factor - 0.000001 +22693455 rs11708067 Obese|Type 2 Diabetes - 0.000000 +22911880 rs7690467 Behaviors|Personality Traits|Eating - 0.000007 +24133439 rs1009302 Autistic-Like Traits - 0.000003 +24390342 rs2469434 Rheumatoid Arthritis|Biology - 0.000000 +22829776 rs17496332 Globulin|Hormone|Steroid Hormone - 0.000000 +23738518 rs2041660 Reading|Language - 0.000003 +23028483 rs2786098 Asthma - 0.000000 +25241909 rs139257032 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +23297363 rs11065987 Tetralogy Fallot - 0.000000 +25340798 rs3811448 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +20932310 rs239713 Τ Protein Levels - 0.000000 +22570697 rs9261471 Multiple Sclerosis - 0.000000 +23708191 rs6824295 Congenital Heart Disease|Atrial Septal Defect - 0.000000 +23667675 rs12200251 Age Menarche - 0.000001 +21873549 rs10838687 Type 2 Diabetes|Proinsulin Levels - 0.000000 +24025145 rs1530361 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000009 +23886662 rs7927894 Psoriasis|Atopic Dermatitis|Asthma - 0.000002 +19874204 rs2036417 Femoral Neck Bone|Bone Mineral Density - 0.000010 +23984888 rs11674314 Airway Responsiveness - 0.000010 +23703922 rs4698050 Uric Acid Levels - 0.000000 +23408906 rs9497965 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +18776929 rs10183584 Hip Bone Size|Females - 0.000002 +22570697 rs16896944 Multiple Sclerosis - 0.000000 +23704328 rs9316505 Tooth Eruption|Height - 0.000000 +21552555 rs3912607 Obesity|Obesity-Related Traits - 0.000008 +22044751 rs11099681 Chronic Kidney Disease - 0.000006 +17684544 rs1553575 Ibd Disease - 0.000002 +20169177 rs10893872 Systemic Lupus Erythematosus - 0.000000 +25340798 rs2229238 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +22570697 rs9292777 Multiple Sclerosis - 0.000000 +25064009 rs11724635 Parkinson’s Disease - 0.000000 +22792070 rs2536182 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +23259602 rs9287022 Dental Caries - 0.000004 +19197348 rs1800775 Complex Disease - 0.000000 +22993228 rs11918654 Lumbar Disc Degeneration - 0.000007 +19936222 rs2076530 Cholesterol|Plasma Lipoprotein Size - 0.000000 +23817569 rs2155219 Allergy - 0.000000 +20858683 rs1046896 Hemoglobin A - 0.000000 +22438815 rs4538475 Parkinson's Disease - 0.000000 +19343178 rs6830062 Stature - 0.000000 +21533024 rs1801714 Icam-1 - 0.000000 +25188341 rs35349669 Dementias|Alzheimer's Disease - 0.000000 +22832960 rs291272 Temperament Character Inventory - 0.000005 +24511991 rs199498 Parkinson’s Disease - 0.000001 +21552555 rs10891096 Obesity|Obesity-Related Traits - 0.000001 +18604267 rs507666 Antigen|Icam-1 - 0.000000 +24513273 rs1178977 Serum Uric Acid - 0.000000 +20038947 rs346101 Major Depression - 0.000006 +23793025 rs10504861 Migraine - 0.000000 +23738518 rs12050412 Reading|Language - 0.000005 +22763110 rs11177 Osteoarthritis - 0.000000 +20700443 rs13146355 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +24513273 rs780094 Serum Uric Acid - 0.000000 +19430480 rs2476601 Type 1 Diabetes - 0.000000 +17903293 rs2794520 Biomarker Traits - 0.000000 +22291604 rs2230926 Lupus - 0.000000 +22001756 rs37812 Dengue Shock Syndrome - 0.000000 +19557197 rs17008958 Distribution|Adiposity|Waist Circumference - 0.000005 +22829776 rs440837 Globulin|Hormone|Steroid Hormone - 0.000000 +22216198 rs2523674 Protein C - 0.000010 +21408207 rs10036748 Systemic Lupus Erythematosus|Autoantibody - 0.000002 +23936387 rs1470379 Celiac Disease - 0.000010 +22238593 rs7542900 Type 2 Diabetes - 0.000006 +23326239 rs4248166 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +23326517 rs429608 Age-Related Macular Degeneration - 0.000000 +22085899 rs2417940 Bilirubin Levels - 0.000000 +23349640 rs9268853 Malignancies - 0.000000 +23350875 rs12548021 Colorectal Cancer - 0.000001 +23382691 rs1061808 Immunoglobulin G|Human Immunoglobulin|-Glycosylation - 0.000000 +22792070 rs2536180 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +24513273 rs7193778 Serum Uric Acid - 0.000000 +22504420 rs10416218 Bone Mineral Density - 0.000000 +23326517 rs10468017 Age-Related Macular Degeneration - 0.000000 +22570617 rs1063192 Optic Nerve|Glaucoma - 0.000000 +20442857 rs11820589 Phospholipase A - 0.000000 +19571809 rs4452638 Schizophrenia - 0.000000 +20953189 rs495337 Psoriasis - 0.000000 +24763700 rs9375813 C-Reactive Protein Levels - 0.000000 +23646285 rs11854769 Hypersomnia - 0.000001 +24133439 rs11575089 Autistic-Like Traits - 0.000003 +24347629 rs12589327 Periodontal - 0.000007 +19430480 rs9388489 Type 1 Diabetes - 0.000000 +18823527 Rs405509 Late-Onset Alzheimer's Disease - 0.000000 +21804549 rs1101999 Asthma - 0.000000 +19343178 rs3752556 Stature - 0.000001 +18262040 rs4591370 LDL-cholesterol - 0.000000 +21935397 rs8067056 Extremely|Overweight|Body Mass Index - 0.000008 +25340798 rs603050 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +19412175 rs2229571 Neuroblastoma - 0.000003 +22666496 rs12556591 Cardiovascular Event - 0.000010 +24097068 rs38855 Lipid Levels - 0.000000 +21552555 rs7206790 Obesity|Obesity-Related Traits - 0.000000 +18483556 rs12913832 Hair Color|Skin Pigmentation - 0.000000 +22829776 rs8023580 Globulin|Hormone|Steroid Hormone - 0.000000 +23307926 rs12294104 Menopause - 0.000000 +19343178 rs1523632 Stature - 0.000008 +20038947 rs7978310 Major Depression - 0.000007 +21750679 rs6457617 Systemic Sclerosis - 0.000000 +19798445 rs4459477 Sphingolipid - 0.000000 +22470424 rs564053 Amyotrophic Lateral Sclerosis - 0.000010 +23455636 rs13081855 Age-Related Macular Degeneration - 0.000000 +20932310 rs121724 Τ Protein Levels - 0.000000 +23583980 rs2034650 Pulmonary Fibrosis - 0.000000 +21297633 rs798502 Ulcerative Colitis - 0.000000 +21935397 rs970843 Extremely|Overweight|Body Mass Index - 0.000005 +22570617 rs1412832 Optic Nerve|Glaucoma - 0.000000 +23563607 rs7503807 Anthropometric Traits - 0.000000 +25378659 rs11666913 Long-Chain Saturated Fatty Acids - 0.000000 +23437003 rs6909279 Volumetric Bone Mineral Densities - 0.000000 +25340798 rs61812598 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +19668339 rs1364705 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000009 +23307926 rs4886238 Menopause - 0.000000 +19300482 rs735243 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000000 +20038947 rs724568 Major Depression - 0.000005 +18483556 rs8049897 Hair Color|Skin Pigmentation - 0.000000 +22685421 rs282544 Ocular Axial Length|High Myopia - 0.000004 +23459936 rs12883458 Chronic Periodontitis - 0.000000 +23326239 rs9267522 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +21658281 rs10765792 Coronary Artery Disease|Sudden Cardiac Arrest - 0.000000 +22993228 rs1154053 Lumbar Disc Degeneration - 0.000004 +21297633 rs12261843 Ulcerative Colitis - 0.000000 +24755620 rs8103315 Glutamate|Alzheimer's Disease - 0.000000 +21390209 rs4497357 Late-Onset Alzheimer's Disease - 0.000009 +24688116 rs4693331 Longevity|Analysis|Population - 0.000007 +22452962 rs10483813 Breast Cancer - 0.000000 +20661308 rs16902486 Serum Calcium - 0.000005 +22085899 rs6742078 Bilirubin Levels - 0.000000 +24688116 rs4420638 Longevity|Analysis|Population - 0.000000 +23583980 rs2736100 Pulmonary Fibrosis - 0.000000 +20700443 rs448378 Potassium|Serum Magnesium|Serum Magnesium Levels - 0.000000 +23958962 rs116439821 Cocaine Dependence - 0.000000 +21909110 rs17477177 Mean Arterial Pressure|Pulse Pressure - 0.000000 +23326239 rs7192 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +18840781 rs1701704 Type 1 Diabetes - 0.000000 +21909115 rs17608766 Cardiovascular Disease|Blood Pressure - 0.000000 +18483556 rs7204478 Hair Color|Skin Pigmentation - 0.000000 +20858683 rs7998202 Hemoglobin A - 0.000000 +23041239 rs7407640 Ischaemic Stroke - 0.000002 +24740154 rs17632542 Prostate Cancer|Early-Onset - 0.000000 +24133439 rs16946881 Autistic-Like Traits - 0.000003 +23703922 rs737267 Uric Acid Levels - 0.000000 +18604267 rs8111930 Antigen|Icam-1 - 0.000000 +22470424 rs7740421 Amyotrophic Lateral Sclerosis - 0.000007 +24047820 rs4218 Social Communication - 0.000000 +22412388 rs3091338 Crohn's Disease - 0.000000 +22368281 rs1619785 LDL-c Response|Lpa - 0.000000 +21935397 rs699363 Extremely|Overweight|Body Mass Index - 0.000005 +21827660 rs1412829 Increased Disease Risk - 0.000000 +25340798 rs4459609 Proteins Involved|Inflammation|Alzheimer's Disease - 0.000000 +21779176 rs3104767 Restless Legs Syndrome - 0.000000 +17903292 rs10485409 Kidney|Endocrine-Related Traits - 0.000010 +21347284 rs10865355 Pr Interval - 0.000000 +21779381 rs4975709 Migraine|Cardiovascular Events|Cardiovascular - 0.000001 +19772629 rs17663983 Parkinson Disease|Onset - 0.000008 +20339536 rs4775041 Lipid-Lowering Response|Response Statins - 0.000000 +20038947 rs17144465 Major Depression - 0.000001 +19300500 rs17086172 Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function - 0.000003 +23636237 rs8019546 Analysis - 0.000005 +22666496 rs10429616 Cardiovascular Event - 0.000008 +19772629 rs12261736 Parkinson Disease|Onset - 0.000000 +22675492 rs2727261 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000003 +24651765 rs9296404 Homocysteine|Methionine|Metabolism - 0.000000 +19430480 rs11755527 Type 1 Diabetes - 0.000000 +22993228 rs763014 Lumbar Disc Degeneration - 0.000005 +20729852 rs3781264 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma - 0.000000 +25310577 rs17133807 Acute Lymphoblastic Leukemia|Childhood - 0.000000 +24516586 rs3733585 Tobacco Smoke|Chromosome 4|Cleft Palate - 0.000000 +23350875 rs8180040 Colorectal Cancer - 0.000002 +23703922 rs3733585 Uric Acid Levels - 0.000001 +24121790 rs3950627 Barrett’s Esophagus|Esophageal Adenocarcinoma - 0.000002 +19197348 rs11066595 Complex Disease - 0.000007 +24347629 rs3870371 Periodontal - 0.000006 +25102180 rs2283228 Type 2 Diabetes - 0.000000 +23408906 rs6885099 Thyroid|Thyroid-Related Traits|Differences - 0.000000 +24280982 rs17693963 Schizophrenia|Bipolar Disorder|Disorder - 0.000000 +23984888 rs10189795 Airway Responsiveness - 0.000004 +21383967 rs2298428 Rheumatoid Arthritis|Celiac Disease - 0.000000 +24223155 rs10141001 Torsades De Pointes - 0.000010 +22044751 rs6686423 Chronic Kidney Disease - 0.000008 +20548946 rs1926320 Optic Disc - 0.000000 +19668339 rs9918508 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000008 +24952745 rs246185 Qt Interval|Calcium - 0.000000 +24483146 rs28668016 Biomarkers - 0.000000 +24449572 rs1043099 Rheumatoid Arthritis - 0.000000 +23143602 rs10273639 Pancreatitis - 0.000000 +22470424 rs7740421 Amyotrophic Lateral Sclerosis - 0.000007 +22829776 rs1625895 Globulin|Hormone|Steroid Hormone - 0.000000 +21909115 rs1813353 Cardiovascular Disease|Blood Pressure - 0.000000 +21460840 rs3865444 Alzheimer’s Disease - 0.000000 +22479202 rs4805885 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +20935630 rs1558902 Body Mass Index - 0.000000 +23989986 rs3757837 Hip|Osteoarthritis - 0.000000 +22843504 rs6646569 Autism Spectrum - 0.000001 +19343178 rs6088813 Stature - 0.000000 +22666496 rs1524962 Cardiovascular Event - 0.000004 +24483146 rs13171512 Biomarkers - 0.000008 +24945404 rs798943 Bone Mineral Density|Bone - 0.000000 +21980299 rs10509540 Type 1 Diabetes - 0.000003 +23326239 rs3130048 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +19412175 rs1048108 Neuroblastoma - 0.000000 +20038947 rs17133921 Major Depression - 0.000005 +24755620 rs249167 Glutamate|Alzheimer's Disease - 0.000001 +22916037 rs560887 Atherosclerosis - 0.000000 +21423719 rs780094 Metabolic Traits|Nonalcoholic Fatty Liver Disease - 0.000000 +21399635 rs538147 Primary Biliary Cirrhosis - 0.000000 +22479419 rs12533497 Treatment Refractory Schizophrenia - 0.000010 +23326517 rs1967689 Age-Related Macular Degeneration - 0.000005 +24999842 rs2474619 Celiac Disease|Celiac - 0.000000 +23001564 rs3027234 Homeostasis - 0.000000 +24097068 rs2030746 Lipid Levels - 0.000000 +24740154 rs11839053 Prostate Cancer|Early-Onset - 0.000000 +19247474 rs10989661 Smoking Behaviors|Cigarette Smoking - 0.000006 +21502949 rs335636 Brain - 0.000000 +18483556 rs12203592 Hair Color|Skin Pigmentation - 0.000000 +22675492 rs17829302 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000010 +23509613 rs17011455 Antiphospholipid Antibodies - 0.000005 +20038947 rs4620978 Major Depression - 0.000006 +22792082 rs4452682 Asthma|Bronchodilator Response - 0.000003 +25367360 rs2296837 Astigmatism|Refractive Error - 0.000004 +25742292 rs7919841 Parity - 0.000007 +22792071 rs7776725 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +22044751 rs580140 Chronic Kidney Disease - 0.000003 +24999842 rs2249937 Celiac Disease|Celiac - 0.000000 +24743840 rs4143094 Colorectal Cancer - 0.000000 +20038947 rs6711718 Major Depression - 0.000008 +22561518 rs11021232 Generalized Vitiligo - 0.000000 +21124946 rs211804 Bone Mineral Density - 0.000000 +23793025 rs13208321 Migraine - 0.000000 +23307926 rs10183486 Menopause - 0.000000 +23636237 rs10152629 Analysis - 0.000008 +24999842 rs13151961 Celiac Disease|Celiac - 0.000000 +25742292 rs35320143 Parity - 0.000009 +23544013 rs17631303 Breast Cancer|Breast Ovarian Cancer|Carriers - 0.000000 +25390645 rs12153327 Anxiety - 0.000002 +23437003 rs7839059 Volumetric Bone Mineral Densities - 0.000000 +24571439 rs2281472 Specific Language Impairment|Genotype Effects - 0.000000 +17903305 rs345013 Prostate Cancer|Breast - 0.000005 +24952745 rs12997023 Qt Interval|Calcium - 0.000000 +22087292 rs1368998 Femoral Neck Bone Geometry - 0.000000 +21935397 rs10767664 Extremely|Overweight|Body Mass Index - 0.000000 +24625756 rs887829 Intermediate Phenotypes - 0.000000 +21829377 rs2236212 Plasma Phospholipid|Fatty Acids - 0.000000 +21042317 rs2384061 Major Depressive Disorder - 0.000006 +21383967 rs864537 Rheumatoid Arthritis|Celiac Disease - 0.000000 +22438815 rs2390669 Parkinson's Disease - 0.000000 +22291604 rs6590330 Lupus - 0.000000 +19343178 rs7742369 Stature - 0.000000 +20686608 rs225190 Pancreatic Cancer - 0.000006 +22087292 rs6789283 Femoral Neck Bone Geometry - 0.000000 +19668339 rs10276619 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease - 0.000003 +21665990 rs10490924 Age-Related Macular Degeneration - 0.000000 +22675492 rs10495024 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000006 +25241909 rs7671167 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +23326517 rs9646096 Age-Related Macular Degeneration - 0.000006 +23958962 rs6912117 Cocaine Dependence - 0.000001 +23401653 rs7682912 Platelet-Derived Growth Factor|Quantitative Trait|Corneal - 0.000006 +20364137 rs9315204 Intracranial Aneurysm - 0.000000 +24047820 rs1834180 Social Communication - 0.000000 +25241909 rs2869967 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis - 0.000000 +20081858 rs11920090 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis - 0.000000 +19412175 rs3768716 Neuroblastoma - 0.000000 +24513273 rs6598541 Serum Uric Acid - 0.000000 +24204295 rs2834188 Narcolepsy|Influenza|Changes - 0.000000 +23509613 rs9315762 Antiphospholipid Antibodies - 0.000007 +20195514 rs8079702 Primary Tooth Development - 0.000000 +21552555 rs9931494 Obesity|Obesity-Related Traits - 0.000000 +23667675 rs7114000 Age Menarche - 0.000002 +22916037 rs217181 Atherosclerosis - 0.000000 +21490707 rs2472304 Caffeine Consumption|Cyp1A2 - 0.000000 +22843504 rs6879627 Autism Spectrum - 0.000000 +19936222 rs10778213 Cholesterol|Plasma Lipoprotein Size - 0.000000 +21051773 rs11855415 Handedness|Dyslexia - 0.000000 +24094242 rs651007 Serum Alkaline Phosphatase Levels - 0.000000 +21408207 rs9462015 Systemic Lupus Erythematosus|Autoantibody - 0.000000 +23667675 rs369065 Age Menarche - 0.000008 +19169254 rs610604 Psoriasis - 0.000000 +23593239 rs2331548 Self-Employment - 0.000002 +22792070 rs7776725 Bone Mineral Density|Bone|Osteoporotic Fracture - 0.000000 +22504420 rs7812088 Bone Mineral Density - 0.000000 +19734902 rs662196 Alzheimer's Disease - 0.000005 +22001756 rs3132468 Dengue Shock Syndrome - 0.000000 +21223598 rs875971 Aortic Root - 0.000004 +20038947 rs1612122 Major Depression - 0.000005 +21297633 rs10781499 Ulcerative Colitis - 0.000000 +22205951 rs12563333 Bipolar Disorder - 0.000000 +20190752 rs10936599 Celiac Disease - 0.000000 +24166486 rs17750424 Schizophrenia - 0.000000 +19961619 rs7843085 Respiratory|Atopy - 0.000000 +20932310 rs17189298 Τ Protein Levels - 0.000001 +21750679 rs9498419 Systemic Sclerosis - 0.000008 +22479202 rs731839 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels - 0.000000 +19915575 rs11931074 Parkinson’s Disease - 0.000000 +22832960 rs1996720 Temperament Character Inventory - 0.000002 +20548946 rs1900004 Optic Disc - 0.000000 +24097068 rs11246602 Lipid Levels - 0.000000 +19343178 rs753628 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Hormone-Binding Globulin|Testosterone|Estradiol - 0.000003 +24166486 rs9379858 Schizophrenia - 0.000000 +24025145 rs1219862 Chemotherapy-Induced Alopecia|Breast Cancer - 0.000003 +22438815 rs947211 Parkinson's Disease - 0.000000 +24871463 rs11655550 Systemic Lupus Erythematosus Sle - 0.000001 +23326239 rs10885 Antibodies|Epstein-Barr Virus Nuclear Antigen - 0.000000 +22675492 rs11132733 Sex Hormone-Binding Globulin|Testosterone|Estradiol - 0.000003 +23593202 rs4141232 Age Menarche|Femoral Neck Bone Geometry - 0.000006 +23563607 rs2531995 Anthropometric Traits - 0.000000 +21297633 rs6499188 Ulcerative Colitis - 0.000000 +22504420 rs3801387 Bone Mineral Density - 0.000000 +23703922 rs11599917 Uric Acid Levels - 0.000001 +20858683 rs2779116 Hemoglobin A - 0.000000 +20421936 rs11127485 Onset|Obesity-Related Traits|Body-Weight - 0.000000 +25629512 rs2295334 Age-Related Macular Degeneration - 0.000000 +22359512 rs13106975 Sphingolipids - 0.000000 +24143190 rs2981578 Breast Cancer|Breast - 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rs1361108 Age Menarche - -1.000000 +20881960 rs7916441 Height - -1.000000 +23128233 rs10865331 Inflammatory Bowel Disease - -1.000000 +23509962 rs7714670 Venous Thrombosis - -1.000000 +23509613 rs2517448 Antiphospholipid Antibodies - -1.000000 +20881960 rs2256183 Height - -1.000000 +21738487 rs823156 Parkinson's Disease - -1.000000 +20881960 rs4711336 Height - -1.000000 +23128233 rs2823286 Inflammatory Bowel Disease - -1.000000 +23128233 rs1847472 Inflammatory Bowel Disease - -1.000000 +23509613 rs2894254 Antiphospholipid Antibodies - -1.000000 +21738487 rs11030104 Parkinson's Disease - -1.000000 +20834067 rs4891159 Longevity - -1.000000 +23667675 rs6438424 Age Menarche - -1.000000 +23128233 rs6592362 Inflammatory Bowel Disease - -1.000000 +23509613 rs9295888 Antiphospholipid Antibodies - -1.000000 +23128233 rs9847710 Inflammatory Bowel Disease - -1.000000 +20834067 rs9616906 Longevity - -1.000000 +23509613 rs2734573 Antiphospholipid Antibodies - -1.000000 +23128233 rs6568421 Inflammatory Bowel Disease - -1.000000 +23509962 rs9945428 Venous Thrombosis - -1.000000 +23128233 rs194749 Inflammatory Bowel Disease - -1.000000 +23128233 rs516246 Inflammatory Bowel Disease - -1.000000 +23128233 rs6545800 Inflammatory Bowel Disease - -1.000000 +23509613 rs502055 Antiphospholipid Antibodies - -1.000000 +23128233 rs529866 Inflammatory Bowel Disease - -1.000000 +23128233 rs2155219 Inflammatory Bowel Disease - -1.000000 +21738487 rs11711441 Parkinson's Disease - -1.000000 +20881960 rs2724475 Height - -1.000000 +23509613 rs11539216 Antiphospholipid Antibodies - -1.000000 +23509613 rs2395357 Antiphospholipid Antibodies - -1.000000 +23509962 rs877228 Venous Thrombosis - -1.000000 +23408906 rs2983521 Thyroid|Thyroid-Related Traits|Differences - -1.000000 +20834067 rs10445407 Longevity - -1.000000 +23667675 rs7642134 Age Menarche - -1.000000 +23128233 rs9286879 Inflammatory Bowel Disease - -1.000000 +20834067 rs13053175 Longevity - -1.000000 +23128233 rs3851228 Inflammatory Bowel Disease - -1.000000 +20881960 rs7689420 Height - -1.000000 +23128233 rs559928 Inflammatory Bowel Disease - -1.000000 +23128233 rs4899554 Inflammatory Bowel Disease - -1.000000 +23128233 rs925255 Inflammatory Bowel Disease - -1.000000 +23509613 rs3132722 Antiphospholipid Antibodies - -1.000000 +21738487 rs11248060 Parkinson's Disease - -1.000000 +20881960 rs2070776 Height - -1.000000 +23128233 rs483905 Inflammatory Bowel Disease - -1.000000 +23509613 rs3129900 Antiphospholipid Antibodies - -1.000000 diff --git a/notebooks/results/nb-output/acronyms.extracted.all.tsv b/notebooks/results/nb-output/acronyms.extracted.all.tsv new file mode 100644 index 0000000..4edc5c6 --- /dev/null +++ b/notebooks/results/nb-output/acronyms.extracted.all.tsv @@ -0,0 +1,693 @@ +17903292 PHENOTYPE Candidate gene +17903292 Candidate gene PHENOTYPE +17903292 CysC CST3 +17903292 CST3 CysC +17903292 CysC CST3 +17903292 CST3 CysC +17903292 CysC CST3 +17903292 CST3 CysC +17903292 CysC CST3 +17903292 CST3 CysC +17903292 CKD APOE +17903292 APOE CKD +17903292 PHENOTYPE Candidate gene +17903292 Candidate gene PHENOTYPE +17903292 CysC CST3 +17903292 CST3 CysC +17903292 CysC CST3 +17903292 CST3 CysC +17903292 UAE ≥ 30* CST3 +17903292 CST3 UAE ≥ 30* +17903293 CD40 Ligand, serum & plasma CD40L +17903293 C-reactive protein CRP +17903293 Intercellular adhesion molecule-1 ICAM1 +17903293 Interleukin-6 IL6 +17903293 Urinary isoprostanes/creatinine IsoCrUrine +17903293 Monocyte chemoattractant protein-1 MCP1 +17903293 Myeloperoxidase MPO +17903293 Osteoprotegerin OPG +17903293 P-selectin Pselectin +17903293 Tumor necrosis factor alpha TNFA +17903293 Tumor necrosis factor receptor-2 TNFRII +17903293 N-terminal pro-atrial natriuretic peptide ANP +17903293 B-type natriuretic peptide BNP +17903293 Bilirubin Bili +17903293 Aspartate aminotransferase ** AST +17903293 Alanine aminotransferase ALT +17903293 Alkaline phosphatase AlkPhos +17903293 Gamma-glutamyl transferase GGT +17903293 Vitamin K plasma phylloquinone VitKPhylloq +17903293 Vitamin K percentage of undercarboxylated osteocalcin VitKPucOC +17903293 Vitamin D plasma 25(OH)-D VitD25OH +17903296 Femoral BMD** FNBMD +17903296 Femoral BMD** FNBMDf +17903296 Femoral BMD** FNBMDm +17903296 Trochanter BMD** TRBMD +17903296 Trochanter BMD** TRBMDf +17903296 Trochanter BMD** TRBMDm +17903296 Lumbar spine BMD** LSBMD +17903296 Lumbar spine BMD** LSBMDf +17903296 Lumbar spine BMD** LSBMDm +17903296 Broadband ultrasound attenuation** BUA +17903296 Speed of Sound SOS +17903296 Neck-shaft angle** NSA1 +17903296 Neck-shaft angle** NSAf +17903296 Neck-shaft angle** NSAm +17903296 Femoral neck length** NeckLeng1 +17903296 Femoral neck length** NeckLengf +17903296 Femoral neck length** NeckLengm +17903296 Neck width** NeckW1r +17903296 Neck width** NeckW1rf +17903296 Neck width** NeckW1rm +17903296 Neck section modulus** NeckZ1r +17903296 Neck section modulus** NeckZ1rf +17903296 Neck section modulus** NeckZ1rm +17903296 Neck Cross-Sectional Moment of Inertia NeckCSMI1r +17903296 Neck Cross-Sectional Moment of Inertia NeckCSMI1rf +17903296 Neck Cross-Sectional Moment of Inertia NeckCSMI1rm +17903296 Neck Average Buckling Ratio NeckAvgBR1r +17903296 Neck Average Buckling Ratio NeckAvgBR1rf +17903296 Neck Average Buckling Ratio NeckAvgBR1rm +17903296 Shaft width** ShaftW1 +17903296 Shaft width** ShaftW1f +17903296 Shaft width** ShaftW1m +17903296 Shaft Section modulus** ShaftZ1r +17903296 Shaft Section modulus** ShaftZ1rf +17903296 Shaft Section modulus** ShaftZ1rm +17903296 Shaft Cross-Sectional Moment of Inertia ShaftCSMIr +17903296 Shaft Cross-Sectional Moment of Inertia ShaftCSMIrf +17903296 Shaft Cross-Sectional Moment of Inertia ShaftCSMIrm +17903296 Shaft Average Buckling Ratio ShaftAvgBR1r +17903296 Shaft Average Buckling Ratio ShaftAvgBR1rf +17903296 Shaft Average Buckling Ratio ShaftAvgBR1rm +17903296 Inter-Trochanteric Average Buckling Ratio ITAvgBR1r +17903296 Inter-Trochanteric Average Buckling Ratio ITAvgBR1rf +17903296 Inter-Trochanteric Average Buckling Ratio ITAvgBR1rm +17903296 NSA1 ShaftZ1rm +17903296 ShaftZ1rm NSA1 +17903296 NeckLengf NSAm +17903296 NSAm NeckLengf +17903296 NeckW1rf ShaftZ1R +17903296 ShaftZ1R NeckW1rf +17903296 FNBMD BUA +17903296 BUA FNBMD +17903296 FNBMDf ShaftZ1rm +17903296 ShaftZ1rm FNBMDf +17903296 LSBMD NeckZ1rm +17903296 NeckZ1rm LSBMD +17903296 NSA1 NSA1 +17903296 NSA1 NSA1 +17903296 NSA1 NSA1 +17903296 NSA1 NSA1 +17903296 ShaftWm NeckW1rf +17903296 NeckW1rf ShaftWm +17903297 MRI phenotype showing strongest association with SNP Selected Phenotype : (p < 0.001) +17903297 Selected Phenotype : (p < 0.001) MRI phenotype showing strongest association with SNP +17903297 APBV TCBV +17903297 TCBV APBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 ATBV TCBV +17903297 TCBV ATBV +17903297 AFBV TCBV +17903297 TCBV AFBV +17903297 ATBV TCBV +17903297 TCBV ATBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 AFBV TCBV +17903297 TCBV AFBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 Phenotype showing strongest association with SNP Selected Phenotype : (p < 0.001) +17903297 Selected Phenotype : (p < 0.001) Phenotype showing strongest association with SNP +17903297 AFBV TCBV +17903297 TCBV AFBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 AFBV TCBV +17903297 TCBV AFBV +17903297 ATCBV TCBV +17903297 TCBV ATCBV +17903297 AFBV TCBV +17903297 TCBV AFBV +17903297 AFBV TCBV +17903297 TCBV AFBV +17903297 Phenotype showing strongest association with SNP Selected Phenotype : (p < 0.001) +17903297 Selected Phenotype : (p < 0.001) Phenotype showing strongest association with SNP +17903297 Sim F1 +17903297 F1 Sim +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F1 F1 +17903297 F3 F1 +17903297 F1 F3 +17903297 F3 F3 +17903297 F3 F3 +17903297 F3 F3 +17903297 F3 F3 +17903297 F3 F3 +17903297 F3 F3 +17903297 F3 F3 +17903297 F3 F3 +17903305 Cohort- and sex-specific All Cancer* (excluding non-melanoma skin cancer) +17903305 1. All Cancer* (excluding non-melanoma skin cancer) +17903305 age at study entry (allcancer1) All Cancer* (excluding non-melanoma skin cancer) +17903305 2. All Cancer* (excluding non-melanoma skin cancer) +17903305 multivariable adjusted for age, body mass index, and cigarette smoking at study entry (allcancer2) All Cancer* (excluding non-melanoma skin cancer) +17903305 All Cancer* (excluding non-melanoma skin cancer) Cohort- and sex-specific +17903305 All Cancer* (excluding non-melanoma skin cancer) 1. +17903305 All Cancer* (excluding non-melanoma skin cancer) age at study entry (allcancer1) +17903305 All Cancer* (excluding non-melanoma skin cancer) 2. +17903305 All Cancer* (excluding non-melanoma skin cancer) multivariable adjusted for age, body mass index, and cigarette smoking at study entry (allcancer2) +17903305 Cohort-specific Breast Cancer (women) +17903305 1. Breast Cancer (women) +17903305 age at study entry (breastcancer1) Breast Cancer (women) +17903305 2. Breast Cancer (women) +17903305 multivariable adjusted for age, parity, and body mass index at study entry (breastcancer2) Breast Cancer (women) +17903305 Breast Cancer (women) Cohort-specific +17903305 Breast Cancer (women) 1. +17903305 Breast Cancer (women) age at study entry (breastcancer1) +17903305 Breast Cancer (women) 2. +17903305 Breast Cancer (women) multivariable adjusted for age, parity, and body mass index at study entry (breastcancer2) +17903305 Cohort-specific Prostate Cancer (men) +17903305 1. Prostate Cancer (men) +17903305 age at study entry (prostatecancer1) Prostate Cancer (men) +17903305 Prostate Cancer (men) Cohort-specific +17903305 Prostate Cancer (men) 1. +17903305 Prostate Cancer (men) age at study entry (prostatecancer1) +17903306 QT sex-pooled QTPOOL +17903306 QT men only QTMEN** +17903306 QT women only QTWOMEN** +17903306 RR sex-pooled RRPOOL +17903306 RR men only RRMEN** +17903306 RR women only RRWOMEN** +17903306 PR sex-pooled PRAdjRRPOOL +17903306 SDNN sex-pooled SDNNHRV +17903306 Total power sex-pooled TOTPWRHRV +17903306 Low frequency/high frequency power sex-pooled LFHFHRV +17903307 Percent predicted FEV ppfev1 +17903307 for latest exam ppfev1 +17903307 Percent predicted FVC for latest exam ppfvc +17903307 Percent predicted FEV ppratio +17903307 /FVC for latest exam ppratio +17903307 Percent predicted FEF ppfef +17903307 for latest exam ppfef +17903307 Percent predicted FEF ppfefrat +17903307 /FVC for latest exam ppfefrat +17903307 Mean FEV meanfev1 +17903307 from two exams meanfev1 +17903307 Mean FVC from two exams meanfvc +17903307 Mean FEV meanratio +17903307 /FVC from two exams meanratio +17903307 Longitudinal slope of FEV fev1slope +17903307 Longitudinal slope of FEF fefslope +17903292 Glomerular Filtration Rate GFR +17903292 Thyroid stimulation hormone TSH +17903292 Dehydroepiandrosterone sulfate DHEAS +17903292 Physical Location Mb +17903292 Physical Location Mb +17903292 Physical location Mb +17903292 Mean p-value GEE +17903292 Mean p-value FBAT +17903292 P_value GEE +17903294 Sample size min-max +17903295 558 558 +17903296 Bone mineral density BMD +17903296 Combined 1141 +17903296 Females 646 +17903296 Males 495 +17903296 Combined 1117 +17903296 Females 641 +17903296 Males 486 +17903296 Quantitative ultrasound QUS +17903296 Combined 1105 +17903296 Combined 1104 +17903296 Combined 1096 +17903296 Females 622 +17903296 Males 474 +17903296 Combined 1090 +17903296 Females 619 +17903296 Males 471 +17903296 Combined 1095 +17903296 Females 618 +17903296 Males 477 +17903296 Combined 1096 +17903296 Females 618 +17903296 Males 478 +17903296 Combined 1094 +17903296 Females 618 +17903296 Males 476 +17903296 Combined 1096 +17903296 Females 618 +17903296 Males 478 +17903296 Combined 1028 +17903296 Females 599 +17903296 Males 429 +17903296 Combined 1028 +17903296 Females 599 +17903296 Males 429 +17903296 Combined 1026 +17903296 Females 599 +17903296 Males 427 +17903296 Combined 1028 +17903296 Females 599 +17903296 Males 429 +17903296 Combined 1024 +17903296 Females 596 +17903296 Males 428 +17903297 Total Cerebral Brain Volume ATCBV +17903297 Frontal Brain volume AFBV +17903297 Parietal Brain Volume APBV +17903297 Occipital Brain Volume AOBV +17903297 Temporal Brain volume ATBV +17903297 Hippocampal Volume AHPV +17903297 Factor 1:Verbal Memory F1 +17903297 Factor 2:Visual Memory and Organization F2 +17903297 Factor 3: Measure of attention and executive function-Trails A and B F3 +17903297 Boston Naming Test Nam +17903297 Similarities Sim +17903297 Wide-Range Achievement Test WRAT +17903298 Fasting plasma glucose FPG +17903298 Hemoglobin A1c HbA1c +17903298 28 yr time averaged FPG tFPG +17903298 Homeostasis model insulin resistance HOMA-IR +17903298 0–120 min insulin sensitivity ISI_0-120 +17903300 Physical Position Mb +17903300 Physical Location Mb +17903301 LV mass LVM +17903301 LV diastolic dimension LVDD +17903301 LV systolic dimension LVDS +17903301 LV wall thickness LVWT +17903301 LV fractional shortening LVFS +17903301 Left atrial diameter LAD +17903301 Aortic root diameter AOR +17903301 Stage 2 Exercise systolic blood pressure SBP +17903301 Stage 2 Exercise diastolic blood pressure DBP +17903305 age at study entry allcancer1 +17903306 position Mb +17903308 Unadjusted Mean SD +17903308 Heritability SE +18262040 Pooled β-coefficient SE +18369459 Location hg18 +18369459 Location hg18 +18369459 Location hg18 +18455228 Bone mineral density SD +18455228 Osteoporotic fracture OR +18455228 Osteoporosis OR +18483556 rs8039195 rs916977 +18840781 Stage 1 GWA +19043545 rs1148259 rs1200826 +19081515 p vCJD +19081515 p iCJD +19081515 p sCJD +19096518 P-Value one-sided +19116933 Birth cohort directly genotyped CS +19116933 0 0 +19116933 Yes NA +19116933 Yes NA +19116933 Birth cohort directly genotyped CS +19116933 0 0 +19116933 0 0 +19116933 0 0 +19169254 Age at Onset Mean +19169254 Age at Exam Mean +19197348 Position Mb +19300482 p value PBAT +19300499 Replication 588 +19300499 Combined 1641 +19305408 Beta SD +19305408 Beta SD +19343178 Beta SE +19343178 Beta SE +19343178 Beta SE +19359265 β GWA SE +19359265 β replication SE +19359265 β combined SE +19430483 Lolipop Europeans +19430483 Position NCBI35 +19430483 position NCBI35 +19454037 Distance Mb +19454037 Distance Mb +19454037 Distance Mb +19557161 β SE +19587794 Beta SE +19609347 Body mass index BMI +19651812 Systolic blood pressure mmHg +19651812 Diastolic blood pressure mmHg +19798445 4p12 ATP10D +19798445 4p12 ATP10D +19798445 4p12 ATP10D +19798445 Meta OR 95CI +19820699 rs1800562 HFE +19820699 rs3811647 TF +19936222 0 0 +19936222 0 0 +19936222 0 0 +19936222 0 0 +19961619 COL29A1 COL6A5 +19961619 Position build36 +20011104 Adiponectin SD +20011104 Adiponectin Males SD +20011104 Adiponectin Females SD +20011104 Age SD +20038947 GenotypedSNPs post-QC +20038947 All cases Broad +20038947 C21orf94 187075 +20038947 C8orf71 28772 +20038947 mRNA BC053410 LOC643542 +20066028 Glucose transporter type 2 GLUT-2 +20066028 Protein kinase C iota type nPKC-iota +20066028 Glucose transporter type 2 GLUT-2 +20066028 Glucose transporter type 12 GLUT-12 +20066028 Vitamin D-binding protein Precursor DBP +20066028 Alzheimer disease amyloid protein ABPP +20066028 Zinc transporter ZIP12 +20066028 Protein kinase C iota type nPKC-iota +20066028 Protein kinase C iota type nPKC-iota +20066028 Glucose transporter type 2 GLUT-2 +20066028 Low-density lipoprotein receptor-related protein LRP-DIT +20066028 Transforming growth factor-beta receptor type II TGFR-2 +20066028 NADH dehydrogenase 8 iron-sulfur protein 4 CI-AQDQ +20066028 Mitogen-activated protein kinase 4 MEKKK4 +20066028 Parathyroid hormone-responsive B1 gene protein PTHB1 +17903292 Glomerular Filtration Rate GFR +17903292 Thyroid stimulation hormone TSH +17903292 Luteinizing hormone LH +17903292 Follicle stimulating hormone FSH +17903292 Dehydroepiandrosterone sulfate DHEAS +17903292 Physical Location Mb +17903292 Physical Location Mb +17903292 Physical location Mb +17903292 Mean p-value GEE +17903292 Mean p-value FBAT +17903292 P_value GEE +17903294 Sample size min-max +17903295 558 558 +17903296 Bone mineral density BMD +17903296 Combined 1141 +17903296 Females 646 +17903296 Males 495 +17903296 Combined 1117 +17903296 Females 641 +17903296 Males 486 +17903296 Quantitative ultrasound QUS +17903296 Combined 1105 +17903296 Combined 1104 +17903296 Combined 1096 +17903296 Females 622 +17903296 Males 474 +17903296 Combined 1090 +17903296 Females 619 +17903296 Males 471 +17903296 Combined 1095 +17903296 Females 618 +17903296 Males 477 +17903296 Combined 1096 +17903296 Females 618 +17903296 Males 478 +17903296 Combined 1094 +17903296 Females 618 +17903296 Males 476 +17903296 Combined 1096 +17903296 Females 618 +17903296 Males 478 +17903296 Combined 1028 +17903296 Females 599 +17903296 Males 429 +17903296 Combined 1028 +17903296 Females 599 +17903296 Males 429 +17903296 Combined 1026 +17903296 Females 599 +17903296 Males 427 +17903296 Combined 1028 +17903296 Females 599 +17903296 Males 429 +17903296 Combined 1024 +17903296 Females 596 +17903296 Males 428 +17903297 Total Cerebral Brain Volume ATCBV +17903297 Cerebral Brain Volume ATCBV +17903297 Frontal Brain volume AFBV +17903297 Parietal Brain Volume APBV +17903297 Occipital Brain Volume AOBV +17903297 Temporal Brain volume ATBV +17903297 Hippocampal Volume AHPV +17903297 Lateral Ventricular Volume ALVV +17903297 Factor 1:Verbal Memory F1 +17903297 Boston Naming Test Nam +17903297 Naming Test Nam +17903297 Similarities Sim +17903297 Wide-Range Achievement Test WRAT +17903298 Fasting plasma glucose FPG +17903298 Hemoglobin A1c HbA1c +17903298 28 yr time averaged FPG tFPG +17903298 Homeostasis model insulin resistance HOMA-IR +17903300 Physical Position Mb +17903300 Physical Location Mb +17903301 LV mass LVM +17903301 LV diastolic dimension LVDD +17903301 LV systolic dimension LVDS +17903301 LV wall thickness LVWT +17903301 LV fractional shortening LVFS +17903301 Left atrial diameter LAD +17903301 Aortic root diameter AOR +17903301 Exercise Treadmill Test ETT +17903301 systolic blood pressure SBP +17903301 diastolic blood pressure DBP +17903301 Brachial Artery BA +17903301 flow-mediated dilation FMD +17903305 age at study entry allcancer1 +17903306 position Mb +17903308 Unadjusted Mean SD +17903308 Heritability SE +18262040 Pooled β-coefficient SE +18369459 Location hg18 +18369459 Location hg18 +18369459 Location hg18 +18455228 Bone mineral density SD +18455228 Osteoporotic fracture OR +18455228 Osteoporosis OR +18483556 rs8039195 rs916977 +18840781 Stage 1 GWA +19043545 rs1148259 rs1200826 +19081515 p vCJD +19081515 p iCJD +19081515 p sCJD +19096518 P-Value one-sided +19116933 Birth cohort directly genotyped CS +19116933 0 0 +19116933 Yes NA +19116933 Yes NA +19116933 Birth cohort directly genotyped CS +19116933 0 0 +19116933 0 0 +19116933 0 0 +19169254 Age at Onset Mean +19169254 Age at Exam Mean +19197348 Position Mb +19300482 p value PBAT +19300499 Replication 588 +19300499 Combined 1641 +19305408 Beta SD +19305408 Beta SD +19343178 Beta SE +19343178 Beta SE +19343178 Beta SE +19359265 β GWA SE +19359265 β replication SE +19359265 β combined SE +19430483 Lolipop Europeans +19430483 Position NCBI35 +19430483 position NCBI35 +19454037 Distance Mb +19454037 Distance Mb +19454037 Distance Mb +19557161 Effect allele frequency EAF +19557161 β SE +19578366 Adult Glioma Study AGS +19587794 Beta SE +19609347 Body mass index BMI +19609347 calcium/calmodulin-dependent kinase CaMK +19651812 Systolic blood pressure mmHg +19651812 Diastolic blood pressure mmHg +19798445 4p12 ATP10D +19798445 4p12 ATP10D +19798445 4p12 ATP10D +19798445 Meta OR 95CI +19820699 rs1800562 HFE +19820699 rs3811647 TF +19936222 0 0 +19936222 0 0 +19936222 0 0 +19936222 0 0 +19961619 COL29A1 COL6A5 +19961619 Position build36 +20011104 Age SD +20038947 GenotypedSNPs post-QC +20038947 All cases Broad +20038947 C21orf94 187075 +20038947 C8orf71 28772 +20066028 Glucose transporter type 2 GLUT-2 +20066028 Protein kinase C iota type nPKC-iota +20066028 Glucose transporter type 2 GLUT-2 +20066028 Glucose transporter type 12 GLUT-12 +20066028 Gastrotropin GT +20066028 Vitamin D-binding protein Precursor DBP +20066028 D-binding protein Precursor DBP +20066028 Alzheimer disease amyloid protein ABPP +20066028 Zinc transporter ZIP12 +20066028 Protein kinase C iota type nPKC-iota +20066028 Protein kinase C iota type nPKC-iota +20066028 Glucose transporter type 2 GLUT-2 +20066028 Low-density lipoprotein receptor-related protein LRP-DIT +20066028 Mitogen-activated protein kinase 4 MEKKK4 +20066028 Parathyroid hormone-responsive B1 gene protein PTHB1 +17447842 Crohn disease CD +17447842 Crohn disease CD +17447842 linkage disequilibrium LD +17447842 transmission disequilibrium test TDT +17658951 body mass index BMI +17684544 Crohn disease CD +17684544 inflammatory bowel disease IBD +17684544 ulcerative colitis UC +17684544 Crohn disease CD +17684544 ulcerative colitis UC +17684544 nel-like 1 precursor-encoding gene NELL1 +17903292 Glomerular filtration rate GFR +17903292 urinary albumin excretion UAE +17903292 single nucleotide polymorphism SNP +17903292 cystatin-C cysC +17903292 Thyroid stimulating hormone TSH +17903292 generalized estimating equations GEE +17903292 family-based association tests FBAT +17903292 Chronic kidney disease CKD +17903292 Urinary albumin excretion UAE +17903292 glomerular filtration rate GFR +17903292 thyroid stimulating hormone TSH +17903293 Genome-wide association studies GWAS +17903293 Generalized Estimating Equations GEE +17903293 Family Based Association Tests FBAT +17903293 monocyte chemoattractant protein-1 MCP1 +17903293 C-reactive protein CRP +17903293 C-reactive protein CRP +17903294 single nucleotide polymorphism SNP +17903294 Framingham Heart Study FHS +17903294 generalized estimating equations GEE +17903294 family-based association test FBAT +17903294 linkage disequilibrium LD +17903294 plasminogen activator inhibitor PAI-1 +17903294 von Willebrand factor vWF +17903294 tissue plasminogen activator tPA +17903294 factor VII FVII +17903294 coronary heart disease CHD +17903294 hemoglobin Hgb +17903294 red blood cell count RBCC +17903294 mean corpuscular volume MCV +17903294 mean corpuscular hemoglobin MCH +17903294 adenosine 5'-diphosphate ADP +17903294 epinephrine Epi +17903294 FGB), fibrinogen-α FGA +17903294 fibrinogen-α FGA +17903294 FGA), fibrinogen-Îł FGG +17903294 fibrinogen-Îł FGG +17903294 single nucleotide polymorphism SNP +17903294 genome-wide association study GWAS +17903295 family-based association test FBAT +17903295 generalized estimating equation GEE +17903295 genome-wide association studies GWAS +17903295 Framingham Heart Study FHS +17903296 Framingham Heart Study FHS +17903296 bone mineral density BMD +17903296 generalized estimating equation GEE +17903296 family-based association tests FBAT +17903296 dual-energy X-ray absorptiometry DXA +17903296 quantitative ultrasound QUS +17903296 Framingham Heart Study FHS +17903296 bone mineral density BMD +17903297 magnetic resonance imaging MRI +17903297 Alzheimer's disease AD +17903297 genome-wide association GWA +17903297 generalized estimating equations GEE +17903297 family based association tests FBAT +17903297 white matter hyperintensity WMH +17903297 Alzheimer's disease AD +17903297 genome-wide association studies GWAS +17903297 single nucleotide polymorphism SNP +17903298 fasting plasma glucose FPG +17903298 generalized estimating equations GEE +17903298 family-based association test FBAT +17903298 rs757110), KCNJ11 E23K rs5219 +17903298 peroxisome proliferator-activated receptor-g PPARG +17903298 genome-wide association GWA +17903298 Framingham Heart Study FHS +17903298 genome-wide association GWA +17903300 Body mass index BMI +17903300 waist circumference WC +17903300 Generalized Estimating Equations GEE +17903300 Family Based Association Test FBAT +17903300 Cardiovascular disease CVD +17903300 body mass index BMI +17903300 waist circumference WC +17903300 single nucleotide polymorphisms SNP +17903300 Hardy-Weinberg equilibrium HWE +17903301 left ventricular LV +17903301 brachial artery BA +17903301 genome-wide association study GWAS +17903301 flow-mediated dilation FMD +17903301 Generalized estimating equations GEE +17903301 family-based association tests FBAT +17903301 Cardiovascular disease CVD +17903301 left ventricular LV +17903301 LV remodeling) and mass LVM +17903301 exercise treadmill stress testing ETT +17903301 brachial artery BA +17903301 flow-mediated dilation FMD +17903301 echocardiography Echo +17903301 genome-wide association studies GWAS +17903301 single nucleotide polymorphism SNP +17903301 LV internal dimension in diastole LVDD +17903301 LVDD) and systole LVDS +17903301 posterior wall PW +17903301 left atrium LA +17903301 LV wall thickness LVWT +17903302 blood-pressure BP +17903302 family based association testing FBAT +17903302 generalized estimating equation GEE +17903303 Subclinical atherosclerosis SCA +17903303 genome-wide association study GWAS +17903303 intimal medial thickness IMT +17903303 generalized estimating equations GEE +17903303 family-based association testing FBAT +17903303 ankle-brachial index ABI +17903303 intimal medial thickness IMT +17903303 coronary artery calcium CAC +17903303 calcium CAC +17903303 and abdominal aortic calcium AAC +17903303 abdominal aortic calcium AAC +17903303 Genome-wide association studies GWAS +17903304 Cardiovascular disease CVD +17903304 coronary heart disease CHD +17903304 heart failure HF +17903304 and atrial fibrillation AF +17903304 atrial fibrillation AF +17903304 cardiovascular disease CVD +17903304 Cardiovascular disease CVD +17903304 coronary heart disease CHD +17903304 heart failure HF +17903304 and atrial fibrillation AF +17903304 atrial fibrillation AF diff --git a/notebooks/results/nb-output/phen-rsid.table.rel.all.tsv b/notebooks/results/nb-output/phen-rsid.table.rel.all.tsv new file mode 100644 index 0000000..689b2ff --- /dev/null +++ b/notebooks/results/nb-output/phen-rsid.table.rel.all.tsv @@ -0,0 +1,2253 @@ +17903292 rs1158167 cst3 0.0 table 1 3 1 +17903292 rs1712790 urinary albumin excretion 2e-06 table 1 4 1 +17903292 rs6977660 thyroid stimulating hormone 4e-06 table 1 5 1 +17903292 rs9322817 thyroid stimulating hormone 6e-06 table 1 6 1 +17903292 rs10499559 thyroid stimulating hormone 8e-06 table 1 7 1 +17903292 rs9305354 urinary albumin excretion 8e-06 table 1 8 1 +17903292 rs1243400 urinary albumin excretion 5e-06 table 1 34 1 +17903292 rs723464 urinary albumin excretion 1e-05 table 1 39 1 +17903292 rs754958 Serum Phosphorous -1 table 1 64 1 +17903292 rs10495487 Uric acid -1 table 1 65 1 +17903292 rs10489578 Serum creatinine (exam 6) -1 table 1 66 1 +17903292 rs10515134 Luteinizing Hormone -1 table 1 67 1 +17903292 rs10489578 glomerular filtration rate (exam 6) -1 table 1 68 1 +17903292 rs10484370 Serum Calcium -1 table 1 69 1 +17903292 rs10511176 glomerular filtration rate (exam 7) -1 table 1 70 1 +17903292 rs10502302 Serum creatinine (exam 5) -1 table 1 71 1 +17903292 rs10512437 glomerular filtration rate -1 table 2 2 2 +17903292 rs2480555 glomerular filtration rate -1 table 2 3 2 +17903292 rs10486135 glomerular filtration rate -1 table 2 4 2 +17903292 rs727087 glomerular filtration rate -1 table 2 5 2 +17903292 rs1005066 glomerular filtration rate -1 table 2 6 2 +17903292 rs2885618 glomerular filtration rate -1 table 2 7 2 +17903292 rs10496887 glomerular filtration rate -1 table 2 8 2 +17903292 rs1712790 urinary albumin excretion 1e-06 table 2 9 2 +17903292 rs10485409 urinary albumin excretion 1e-05 table 2 10 2 +17903292 rs1158167 cst3 0.0 table 3 3 2 +17903292 rs911122 cst3 -1 table 3 6 2 +17903292 rs3760626 chronic kidney disease -1 table 3 7 2 +17903292 rs1158167 cst3 -1 table 3 13 2 +17903292 rs2145231 cst3 -1 table 3 14 2 +17903292 rs911122 urinary albumin excretion ≥ 30* -1 table 3 15 2 +17903293 rs2494250 Monocyte chemoattractant protein-1 0.0 table 1 3 1 +17903293 rs4128725 Monocyte chemoattractant protein-1 0.0 table 1 4 1 +17903293 rs2794520 C-reactive protein average exams 2,6,7 0.0 table 1 5 1 +17903293 rs2808629 C-reactive protein average exams 2,6,7 0.0 table 1 6 1 +17903293 rs2794520 C-reactive protein exam 6 0.0 table 1 7 1 +17903293 rs2808629 C-reactive protein exam 6 0.0 table 1 8 1 +17903293 rs7552393 Tumor necrosis factor alpha 1e-06 table 1 9 1 +17903293 rs746961 C-reactive protein exam 6 1e-06 table 1 10 1 +17903293 rs17532515 Bilirubin 1e-06 table 1 11 1 +17903293 rs1998303 Alanine aminotransferase 1e-06 table 1 12 1 +17903293 rs10489849 Monocyte chemoattractant protein-1 1e-06 table 1 13 1 +17903293 rs10518765 Alkaline phosphatase 1e-06 table 1 14 1 +17903293 rs2387326 Vitamin K plasma phylloquinone 1e-06 table 1 15 1 +17903293 rs1119582 C-reactive protein average exams 2,6,7 1e-06 table 1 16 1 +17903293 rs10485165 Vitamin D plasma 25(OH)-D 1e-06 table 1 17 1 +17903293 rs1417352 Atrial natriuretic peptide exam 6 2e-06 table 1 18 1 +17903293 rs583012 C-reactive protein exam 2 2e-06 table 1 19 1 +17903293 rs1486139 Atrial natriuretic peptide exam 6 2e-06 table 1 20 1 +17903293 rs1486140 Atrial natriuretic peptide exam 6 2e-06 table 1 21 1 +17903293 rs10492681 Alanine aminotransferase exam 2 2e-06 table 1 22 1 +17903293 rs10507577 Vitamin D plasma 25(OH)-D 3e-06 table 1 23 1 +17903293 rs1079596 Atrial natriuretic peptide exam 6 3e-06 table 1 24 1 +17903293 rs1474747 Monocyte chemoattractant protein-1 3e-06 table 1 25 1 +17903293 rs7778619 CD40 Ligand serum 3e-06 table 1 26 1 +17903293 rs8005745 CD40 Ligand serum 3e-06 table 1 27 1 +17903293 rs4128725 Monocyte chemoattractant protein-1 0.0 table 1 33 1 +17903293 rs2494250 Monocyte chemoattractant protein-1 0.0 table 1 34 1 +17903293 rs437021 B-type natriuretic peptide 1e-06 table 1 35 1 +17903293 rs2052028 Vitamin K % undercarboxylated osteocalcin 1e-06 table 1 36 1 +17903293 rs2372184 CD40 Ligand plasma 2e-06 table 1 37 1 +17903293 rs717145 Urinary isoprostanes/creatinine 5e-06 table 1 38 1 +17903293 rs4664604 CD40 Ligand serum 8e-06 table 1 39 1 +17903293 rs9288125 CD40 Ligand serum 9e-06 table 1 40 1 +17903293 rs1363258 C-reactive protein exam 7 9e-06 table 1 41 1 +17903293 rs17532515 Bilirubin 1e-06 table 1 42 1 +17903293 rs496269 Osteoprotegerin 9e-06 table 1 43 1 +17903293 rs3849944 Intercellular adhesion molecule-1 5e-06 table 1 49 1 +17903293 rs1457590 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 9 1 +17903293 rs6848323 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 10 1 +17903293 rs3110134 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 11 1 +17903293 rs2016740 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 12 1 +17903293 rs719006 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 13 1 +17903293 rs877936 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 14 1 +17903293 rs1436136 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 15 1 +17903293 rs1436336 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 16 1 +17903293 rs698270 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 17 1 +17903293 rs847428 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 18 1 +17903293 rs2359763 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 19 1 +17903293 rs7969455 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 20 1 +17903293 rs10503717 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 21 1 +17903293 rs4899940 Interleukin-6, C-reactive protein and Fibrinogen -1 table 2 22 1 +17903293 rs9319160 C-reactive protein: exams 2, 5, 6, 7 -1 table 2 30 1 +17903293 rs910232 C-reactive protein: exams 2, 5, 6, 7 -1 table 2 31 1 +17903293 rs4911146 Liver function: Alkaline phosphatase; AST; ALT; gamma-glutamyl transferase 8e-06 table 2 32 1 +17903293 rs953402 Liver function: Alkaline phosphatase; AST; ALT; gamma-glutamyl transferase 9e-06 table 2 33 1 +17903293 rs1376544 Vitamin D, Vitamin K phylloquinone & Vitamin K % undercarboxylated osteocalcin 9e-06 table 2 34 1 +17903294 rs966321 factor vii 8e-06 table 1 5 1 +17903294 rs4591494 factor vii 9e-06 table 1 10 1 +17903294 rs10488360 factor vii 7e-06 table 1 11 1 +17903294 rs727435 factor vii 1e-05 table 1 12 1 +17903294 rs561241 factor vii 0.0 table 1 14 1 +17903294 rs4460176 PAI1 3e-06 table 1 16 1 +17903294 rs10493485 tissue plasminogen activator 2e-06 table 1 17 1 +17903294 rs1954971 von willebrand factor 1e-05 table 1 24 1 +17903294 rs4133289 hemoglobin 0.0 table 2 1 1 +17903294 rs1510107 hemoglobin 1e-05 table 2 2 1 +17903294 rs1160297 hemoglobin 1e-06 table 2 3 1 +17903294 rs2357013 hemoglobin 6e-06 table 2 4 1 +17903294 rs7844723 hemoglobin 2e-06 table 2 5 1 +17903294 rs1829883 mean corpuscular hemoglobin 6e-06 table 2 6 1 +17903294 rs1200821 mean corpuscular hemoglobin 6e-06 table 2 7 1 +17903294 rs1397048 mean corpuscular hemoglobin 0.0 table 2 8 1 +17903294 rs10484128 platelet aggregation (ADP-induced) 6e-06 table 2 10 1 +17903294 rs565229 platelet aggregation (collagen-induced) 4e-06 table 2 12 1 +17903294 rs10506458 platelet aggregation (collagen-induced) 5e-06 table 2 13 1 +17903294 rs9253 red blood cell count 4e-06 table 2 17 1 +17903294 rs10489087 red blood cell count 5e-06 table 2 18 1 +17903294 rs636864 red blood cell count 6e-06 table 2 19 1 +17903294 rs727979 red blood cell count 7e-06 table 2 20 1 +17903294 rs6108011 red blood cell count 6e-06 table 2 21 1 +17903294 rs7159841 Viscosity 0.0 table 2 25 1 +17903294 rs1273819 Fibrinogen -1 table 3 1 1 +17903294 rs1542535 factor vii -1 table 3 2 1 +17903294 rs2400107 factor vii -1 table 3 3 1 +17903294 rs10514670 von willebrand factor -1 table 3 5 1 +17903294 rs4148751 platelet aggregation (ADP-induced) -1 table 3 6 1 +17903294 rs17310225 platelet aggregation (collagen-induced) -1 table 3 7 1 +17903294 rs2412522 hemoglobin -1 table 3 8 1 +17903294 rs10514838 hemoglobin -1 table 3 9 1 +17903294 rs38993 MCVavg12 -1 table 3 10 1 +17903294 rs9299952 MCVavg12 -1 table 3 11 1 +17903294 rs10522006 MCVavg12 -1 table 3 12 1 +17903294 rs956275 red blood cell count -1 table 3 13 1 +17903294 rs2023048 red blood cell count -1 table 3 14 1 +17903294 rs10500769 red blood cell count -1 table 3 15 1 +17903294 rs10500770 red blood cell count -1 table 3 16 1 +17903294 rs2178692 red blood cell count -1 table 3 17 1 +17903294 rs10498633 red blood cell count -1 table 3 18 1 +17903294 rs2271090 red blood cell count -1 table 3 20 1 +17903294 rs486633 red blood cell count -1 table 3 21 1 +17903294 rs20037 red blood cell count -1 table 3 22 1 +17903294 rs561241 FVII, exam 5 0.0 table 6 1 1 +17903294 rs2066864 Fibrinogen, average -1 table 6 2 1 +17903294 rs2066864 Fibrinogen, exam 5 -1 table 6 3 1 +17903294 rs2066864 Fibrinogen, exam 6 -1 table 6 4 1 +17903294 rs2066864 Fibrinogen, exam 7 -1 table 6 5 1 +17903294 rs1074801 Fibrinogen, average -1 table 6 6 1 +17903294 rs1074801 Fibrinogen, exam 5 -1 table 6 7 1 +17903294 rs1074801 Fibrinogen, exam 6 -1 table 6 8 1 +17903294 rs1074801 Fibrinogen, exam 7 -1 table 6 9 1 +17903294 rs4525555 Platelet Aggregation, ADP, exam 5 -1 table 6 10 1 +17903294 rs4525555 Platelet Aggregation, Collagen, exam 5 -1 table 6 11 1 +17903294 rs4525555 Platelet Aggregation, epinephrine, exam 5 -1 table 6 12 1 +17903294 rs10514919 Platelet Aggregation, ADP, exam 5 -1 table 6 13 1 +17903294 rs10514919 Platelet Aggregation, Collagen, exam 5 -1 table 6 14 1 +17903294 rs10514919 Platelet Aggregation, epinephrine, exam 5 -1 table 6 15 1 +17903294 rs2015729 Platelet Aggregation, ADP, exam 5 -1 table 6 16 1 +17903294 rs2015729 Platelet Aggregation, Collagen, exam 5 -1 table 6 17 1 +17903294 rs2015729 Platelet Aggregation, epinephrine, exam 5 -1 table 6 18 1 +17903294 rs6950982 PAI1, average -1 table 6 19 1 +17903294 rs6950982 PAI1, exam 5 -1 table 6 20 1 +17903294 rs6950982 PAI1, exam 6 -1 table 6 21 1 +17903294 rs6956010 PAI1, average -1 table 6 22 1 +17903294 rs6956010 PAI1, exam 5 -1 table 6 23 1 +17903294 rs6956010 PAI1, exam 6 -1 table 6 24 1 +17903294 rs917858 wVW, exam 5 -1 table 6 25 1 +17903294 rs917859 wVW, exam 5 -1 table 6 26 1 +17903294 rs2239138 wVW, exam 5 -1 table 6 27 1 +17903294 rs216901 wVW, exam 5 -1 table 6 28 1 +17903294 rs216903 wVW, exam 5 -1 table 6 29 1 +17903294 rs216904 wVW, exam 5 -1 table 6 30 1 +17903295 rs1528753 Age at death 0.0 table 1 4 1 +17903295 rs2371208 Age at death 3e-06 table 1 5 1 +17903295 rs1412337 Morbidity-free survival at age 65 0.0 table 1 10 1 +17903295 rs32566 Morbidity-free survival at age 65 0.0 table 1 11 1 +17903295 rs10484246 Morbidity-free survival at age 65 0.0 table 1 12 1 +17903295 rs4831837 Morbidity-free survival at age 65 0.0 table 1 13 1 +17903295 rs2639889 Morbidity-free survival at age 65 1e-06 table 1 14 1 +17903295 rs10496265 Age at natural menopause‡ 0.0 table 1 16 1 +17903295 rs10496262 Age at natural menopause‡ 0.0 table 1 17 1 +17903295 rs958672 Age at natural menopause‡ 2e-06 table 1 18 1 +17903295 rs291353 Age at natural menopause‡ 5e-06 table 1 19 1 +17903295 rs7137869 Walking speed exam 7 1e-06 table 1 22 1 +17903295 rs1463605 Biologic age by osseographic scoring system 0.0 table 1 29 1 +17903295 rs7176093 Biologic age by osseographic scoring system 7e-06 table 1 30 1 +17903295 rs3772255 Biologic age by osseographic scoring system 8e-06 table 1 31 1 +17903295 rs10493513 Age at death 2e-06 table 1 40 1 +17903295 rs10493514 Age at death 3e-06 table 1 41 1 +17903295 rs4471448 Walking speed exam 7 4e-06 table 1 64 1 +17903295 rs1371217 Age at natural menopause -1 table 1 82 1 +17903295 rs10509024 Age at natural menopause -1 table 1 83 1 +17903295 rs4793513 Age at natural menopause -1 table 1 84 1 +17903295 rs2769261 Walking speed, exam 7 -1 table 1 86 1 +17903295 rs921055 Walking speed, exam 7 -1 table 1 87 1 +17903295 rs2602044 Walking speed, exam 7 -1 table 1 88 1 +17903295 rs8011773 Walking speed, exam 7 -1 table 1 89 1 +17903295 rs1362626 Walking speed, exam 7 -1 table 1 90 1 +17903295 rs353810 Biologic age by osseographic scoring system -1 table 1 92 1 +17903295 rs1203981 Biologic age by osseographic scoring system -1 table 1 93 1 +17903295 rs2248383 Biologic age by osseographic scoring system -1 table 1 94 1 +17903295 rs6682403 Age at Death -1 table 2 3 2 +17903295 rs6682403 Morbidity-free at 65 -1 table 2 3 2 +17903295 rs10488907 Age at Death -1 table 2 4 2 +17903295 rs10488907 Morbidity-free at 65 -1 table 2 4 2 +17903295 rs17190837 Age at Death -1 table 2 5 2 +17903295 rs17190837 Morbidity-free at 65 -1 table 2 5 2 +17903295 rs4752977 Age at Death -1 table 2 6 2 +17903295 rs4752977 Morbidity-free at 65 -1 table 2 6 2 +17903295 rs10506274 Age at Death -1 table 2 7 2 +17903295 rs10506274 Morbidity-free at 65 -1 table 2 7 2 +17903295 rs2831154 Age at Death -1 table 2 8 2 +17903295 rs2831154 Morbidity-free at 65 -1 table 2 8 2 +17903295 rs243725 Age at Death -1 table 2 9 2 +17903295 rs243725 Morbidity-free at 65 -1 table 2 9 2 +17903295 rs9308261 Age at Death -1 table 2 17 2 +17903295 rs9308261 Morbidity-free at 65 -1 table 2 17 2 +17903295 rs10490518 Age at Death -1 table 2 18 2 +17903295 rs10490518 Morbidity-free at 65 -1 table 2 18 2 +17903295 rs2374983 Age at Death -1 table 2 19 2 +17903295 rs2374983 Morbidity-free at 65 -1 table 2 19 2 +17903295 rs655883 Age at Death -1 table 2 20 2 +17903295 rs655883 Morbidity-free at 65 -1 table 2 20 2 +17903295 rs1368850 Age at Death -1 table 2 21 2 +17903295 rs1368850 Morbidity-free at 65 -1 table 2 21 2 +17903295 rs4943116 Age at Death -1 table 2 22 2 +17903295 rs4943116 Morbidity-free at 65 -1 table 2 22 2 +17903295 rs2254191 Age at Death -1 table 2 23 2 +17903295 rs2254191 Morbidity-free at 65 -1 table 2 23 2 +17903295 rs1620210 Age at Death -1 table 2 24 2 +17903295 rs1620210 Morbidity-free at 65 -1 table 2 24 2 +17903295 rs2823322 Age at Death -1 table 2 25 2 +17903295 rs2823322 Morbidity-free at 65 -1 table 2 25 2 +17903295 rs873348 Biologic age -1 table 2 31 2 +17903295 rs873348 Walking speed -1 table 2 31 2 +17903295 rs10520361 Biologic age -1 table 2 32 2 +17903295 rs10520361 Walking speed -1 table 2 32 2 +17903295 rs31564 Biologic age -1 table 2 33 2 +17903295 rs31564 Walking speed -1 table 2 33 2 +17903295 rs1862345 Biologic age -1 table 2 34 2 +17903295 rs1862345 Walking speed -1 table 2 34 2 +17903295 rs7844834 Biologic age -1 table 2 35 2 +17903295 rs7844834 Walking speed -1 table 2 35 2 +17903295 rs952658 Biologic age -1 table 2 36 2 +17903295 rs952658 Walking speed -1 table 2 36 2 +17903295 rs6487366 Biologic age -1 table 2 37 2 +17903295 rs6487366 Walking speed -1 table 2 37 2 +17903295 rs7135493 Biologic age -1 table 2 38 2 +17903295 rs7135493 Walking speed -1 table 2 38 2 +17903295 rs10492036 Biologic age -1 table 2 39 2 +17903295 rs10492036 Walking speed -1 table 2 39 2 +17903295 rs1978945 Biologic age -1 table 2 40 2 +17903295 rs1978945 Walking speed -1 table 2 40 2 +17903295 rs2165723 Biologic age -1 table 2 41 2 +17903295 rs2165723 Walking speed -1 table 2 41 2 +17903295 rs10492651 Biologic age -1 table 2 42 2 +17903295 rs10492651 Walking speed -1 table 2 42 2 +17903295 rs9301112 Biologic age -1 table 2 43 2 +17903295 rs9301112 Walking speed -1 table 2 43 2 +17903295 rs1474827 Biologic Age -1 table 2 51 2 +17903295 rs1474827 Walking speed -1 table 2 51 2 +17903295 rs10231641 Biologic Age -1 table 2 52 2 +17903295 rs10231641 Walking speed -1 table 2 52 2 +17903295 rs310575 Biologic Age -1 table 2 53 2 +17903295 rs310575 Walking speed -1 table 2 53 2 +17903295 rs10520603 Biologic Age -1 table 2 54 2 +17903295 rs10520603 Walking speed -1 table 2 54 2 +17903295 rs7166323 Biologic Age -1 table 2 55 2 +17903295 rs7166323 Walking speed -1 table 2 55 2 +17903295 rs2215921 Biologic Age -1 table 2 56 2 +17903295 rs2215921 Walking speed -1 table 2 56 2 +17903295 rs4943794 Age at death -1 table 3 1 2 +17903295 rs10507486 Age at death -1 table 3 2 2 +17903295 rs4764600 Age at death -1 table 3 3 2 +17903295 rs683907 Age at death -1 table 3 4 2 +17903295 rs687045 Age at death -1 table 3 5 2 +17903295 rs1475398 Age at death -1 table 3 6 2 +17903295 rs1343981 Age at death -1 table 3 7 2 +17903295 rs10493379 Age at death -1 table 3 8 2 +17903295 rs2154380 Age at death -1 table 3 9 2 +17903295 rs6669117 Age at death -1 table 3 10 2 +17903295 rs2374983 Age at death -1 table 3 11 2 +17903295 rs362356 Age at death -1 table 3 12 2 +17903295 rs911847 Age at death -1 table 3 13 2 +17903295 rs2543600 Age at death 4e-06 table 3 14 2 +17903295 rs719756 Morbidity-free survival at age 65 -1 table 3 15 2 +17903295 rs1171278 Morbidity-free survival at age 65 -1 table 3 16 2 +17903295 rs3790426 Morbidity-free survival at age 65 -1 table 3 17 2 +17903295 rs1383636 Morbidity-free survival at age 65 -1 table 3 18 2 +17903295 rs2374983 Morbidity-free survival at age 65 -1 table 3 19 2 +17903295 rs854523 Morbidity-free survival at age 65 -1 table 3 20 2 +17903295 rs10500784 Morbidity-free survival at age 65 -1 table 3 21 2 +17903295 rs2725369 Morbidity-free survival at age 65 -1 table 3 22 2 +17903295 rs1923249 Biologic Age by OSS -1 table 3 23 2 +17903295 rs4943794 Biologic Age by OSS -1 table 3 24 2 +17903295 rs256014 Biologic Age by OSS -1 table 3 25 2 +17903295 rs1002666 Biologic Age by OSS -1 table 3 26 2 +17903295 rs911847 Biologic Age by OSS -1 table 3 27 2 +17903295 rs1927914 Biologic Age by OSS -1 table 3 28 2 +17903295 rs9322361 Walking speed -1 table 3 29 2 +17903295 rs6433083 Walking speed -1 table 3 30 2 +17903295 rs2918418 Walking speed -1 table 3 31 2 +17903295 rs10515522 Walking speed -1 table 3 32 2 +17903295 rs2833485 Walking speed -1 table 3 33 2 +17903295 rs728546 Walking speed -1 table 3 34 2 +17903295 rs6700734 Walking speed -1 table 3 35 2 +17903296 rs6600671 neck section modulus** 1e-06 table 1 3 1 +17903296 rs2053506 NeckZ1 4e-06 table 1 4 1 +17903296 rs10510628 trochanter bmd** 3e-06 table 1 5 1 +17903296 rs2054989 shaftz1r 1e-06 table 1 6 1 +17903296 rs922948 shaft width** 2e-06 table 1 7 1 +17903296 rs991258 shaft width** 1e-06 table 1 8 1 +17903296 rs9291683 fnbmd 2e-06 table 1 9 1 +17903296 rs2548003 neck section modulus** 0.0 table 1 10 1 +17903296 rs10515148 neck section modulus** 1e-06 table 1 11 1 +17903296 rs10514345 lumbar spine bmd** 2e-06 table 1 12 1 +17903296 rs4715166 shaftz1r 3e-06 table 1 14 1 +17903296 rs2214681 fnbmd 3e-06 table 1 15 1 +17903296 rs10503887 shaft section modulus** 0.0 table 1 16 1 +17903296 rs2165468 femoral bmd** 1e-06 table 1 17 1 +17903296 rs1452928 shaft width** 1e-06 table 1 18 1 +17903296 rs638882 neck section modulus** 3e-06 table 1 19 1 +17903296 rs10492096 shaft section modulus** 3e-06 table 1 20 1 +17903296 rs10506701 trochanter bmd** 1e-06 table 1 21 1 +17903296 rs10506821 shaft width** 0.0 table 1 22 1 +17903296 rs1590305 lsbmd 3e-06 table 1 23 1 +17903296 rs9317284 femoral bmd** 0.0 table 1 24 1 +17903296 rs4087296 trochanter bmd** 0.0 table 1 25 1 +17903296 rs4131805 necklengf 2e-06 table 1 26 1 +17903296 rs4811196 trochanter bmd** 1e-06 table 1 27 1 +17903296 rs1395548 shaftz1r 1e-06 table 1 33 1 +17903296 rs1538173 femoral bmd** 3e-06 table 1 34 1 +17903296 rs3762397 trochanter bmd** 0.0 table 1 35 1 +17903296 rs9287234 shaft section modulus** 8e-06 table 1 36 1 +17903296 rs914951 trochanter bmd** 9e-06 table 1 37 1 +17903296 rs4143244 NeckW1 1e-06 table 1 38 1 +17903296 rs432446 nsa1 5e-06 table 1 42 1 +17903296 rs1552896 nsa1 9e-06 table 1 49 1 +17903296 rs7857590 lsbmd 8e-06 table 1 50 1 +17903296 rs10508076 femoral bmd** 4e-06 table 1 58 1 +17903296 rs1759687 femoral neck length** -1 table 1 67 1 +17903296 rs2320625 shaft width** -1 table 1 68 1 +17903296 rs1304771 nsa1 -1 table 1 69 1 +17903296 rs842288 fnbmd -1 table 1 70 1 +17903296 rs1386389 NeckZ1 -1 table 1 71 1 +17903296 rs2094541 NeckW1 -1 table 1 72 1 +17903296 rs10492028 neckz1rm -1 table 1 73 1 +17903296 rs10518923 ShaftZ1 -1 table 1 74 1 +17903296 rs10492922 fnbmd -1 table 1 76 1 +17903296 rs6502901 NeckZ1 -1 table 1 77 1 +17903296 rs8081154 fnbmd -1 table 1 78 1 +17903296 rs750160 NeckW1 -1 table 1 79 1 +17903296 rs7290139 ShaftZ1 -1 table 1 80 1 +17903296 rs1801133 shaft section modulus** -1 table 3 1 2 +17903296 rs1801133 nsa1 -1 table 3 1 2 +17903296 rs1801133 shaft section modulus** -1 table 3 1 4 +17903296 rs1801133 nsa1 -1 table 3 1 4 +17903296 rs2234693 necklengf -1 table 3 4 2 +17903296 rs2234693 femoral neck length** -1 table 3 4 2 +17903296 rs3866461 necklengf -1 table 3 4 4 +17903296 rs3866461 femoral neck length** -1 table 3 4 4 +17903296 rs1884052 shaft section modulus** -1 table 3 5 4 +17903296 rs1884052 shaftz1r -1 table 3 5 4 +17903296 rs3778099 fnbmd -1 table 3 6 4 +17903296 rs3778099 femoral bmd** -1 table 3 6 4 +17903296 rs9340799 fnbmd -1 table 3 7 2 +17903296 rs9340799 femoral bmd** -1 table 3 7 2 +17903296 rs4988321 shaft section modulus** -1 table 3 8 2 +17903296 rs4988321 femoral bmd** -1 table 3 8 2 +17903296 rs4988300 shaft section modulus** -1 table 3 8 4 +17903296 rs4988300 femoral bmd** -1 table 3 8 4 +17903296 rs627174 shaft section modulus** -1 table 3 9 2 +17903296 rs627174 femoral bmd** -1 table 3 9 2 +17903296 rs4988300 shaft section modulus** -1 table 3 9 4 +17903296 rs4988300 femoral bmd** -1 table 3 9 4 +17903296 rs3736228 shaft section modulus** -1 table 3 10 2 +17903296 rs3736228 femoral bmd** -1 table 3 10 2 +17903296 rs4988300 shaft section modulus** -1 table 3 10 4 +17903296 rs4988300 femoral bmd** -1 table 3 10 4 +17903296 rs11568820 lsbmd -1 table 3 11 2 +17903296 rs11568820 neckz1rm -1 table 3 11 2 +17903296 rs2189480 lsbmd -1 table 3 11 4 +17903296 rs2189480 neckz1rm -1 table 3 11 4 +17903296 rs10735810 lsbmd -1 table 3 12 2 +17903296 rs10735810 neckz1rm -1 table 3 12 2 +17903296 rs2189480 lsbmd -1 table 3 12 4 +17903296 rs2189480 neckz1rm -1 table 3 12 4 +17903296 rs1544410 lsbmd -1 table 3 13 2 +17903296 rs1544410 neckz1rm -1 table 3 13 2 +17903296 rs2189480 lsbmd -1 table 3 13 4 +17903296 rs2189480 neckz1rm -1 table 3 13 4 +17903296 rs7975232 lsbmd -1 table 3 14 2 +17903296 rs7975232 neckz1rm -1 table 3 14 2 +17903296 rs2189480 lsbmd -1 table 3 14 4 +17903296 rs2189480 neckz1rm -1 table 3 14 4 +17903296 rs731236 lsbmd -1 table 3 15 2 +17903296 rs731236 neckz1rm -1 table 3 15 2 +17903296 rs2189480 lsbmd -1 table 3 15 4 +17903296 rs2189480 neckz1rm -1 table 3 15 4 +17903296 rs700518 nsa1 -1 table 3 16 2 +17903296 rs700518 nsa1 -1 table 3 16 2 +17903296 rs10519297 nsa1 -1 table 3 16 4 +17903296 rs10519297 nsa1 -1 table 3 16 4 +17903296 rs2008691 nsa1 -1 table 3 17 4 +17903296 rs2008691 nsa1 -1 table 3 17 4 +17903296 rs4775936 nsa1 -1 table 3 18 2 +17903296 rs4775936 nsa1 -1 table 3 18 2 +17903296 rs10519297 nsa1 -1 table 3 18 4 +17903296 rs10519297 nsa1 -1 table 3 18 4 +17903296 rs10046 nsa1 -1 table 3 19 2 +17903296 rs10046 nsa1 -1 table 3 19 2 +17903296 rs10519297 nsa1 -1 table 3 19 4 +17903296 rs10519297 nsa1 -1 table 3 19 4 +17903296 rs11575899 nsa1 -1 table 3 20 2 +17903296 rs11575899 nsa1 -1 table 3 20 2 +17903296 rs10519297 nsa1 -1 table 3 20 4 +17903296 rs10519297 nsa1 -1 table 3 20 4 +17903296 rs1107946 shaftz1r -1 table 3 21 2 +17903296 rs1107946 neckw1rf -1 table 3 21 2 +17903296 rs2075555 shaftz1r -1 table 3 21 4 +17903296 rs2075555 neckw1rf -1 table 3 21 4 +17903296 rs11327935 shaftz1r -1 table 3 22 2 +17903296 rs11327935 neckw1rf -1 table 3 22 2 +17903296 rs2075555 shaftz1r -1 table 3 22 4 +17903296 rs2075555 neckw1rf -1 table 3 22 4 +17903296 rs1800012 shaftz1r -1 table 3 23 2 +17903296 rs1800012 neckw1rf -1 table 3 23 2 +17903296 rs2075555 shaftz1r -1 table 3 23 4 +17903296 rs2075555 neckw1rf -1 table 3 23 4 +17903297 rs1970546 tcbv 0.0 table 1 3 1 +17903297 rs2179965 f3 1e-06 table 1 4 1 +17903297 rs1155865 boston naming test 2e-06 table 1 5 1 +17903297 rs2832077 f3 2e-06 table 1 6 1 +17903297 rs2352904 factor 2:visual memory and organization 2e-06 table 1 7 1 +17903297 rs6914079 factor 2:visual memory and organization 2e-06 table 1 8 1 +17903297 rs9325032 factor 2:visual memory and organization 3e-06 table 1 9 1 +17903297 rs2847476 ALLV 3e-06 table 1 10 1 +17903297 rs3891355 similarities 3e-06 table 1 11 1 +17903297 rs5028798 temporal brain volume 3e-06 table 1 12 1 +17903297 rs530965 boston naming test 3e-06 table 1 13 1 +17903297 rs9303401 boston naming test 5e-06 table 1 14 1 +17903297 rs952700 tcbv 6e-06 table 1 15 1 +17903297 rs1031381 f3 6e-06 table 1 16 1 +17903297 rs10489896 factor 2:visual memory and organization 6e-06 table 1 17 1 +17903297 rs9300212 wide-range achievement test 8e-06 table 1 18 1 +17903297 rs1831521 boston naming test 8e-06 table 1 19 1 +17903297 rs934299 f3 9e-06 table 1 20 1 +17903297 rs360929 ALTHBV 9e-06 table 1 21 1 +17903297 rs2893363 factor 2:visual memory and organization 1e-05 table 1 22 1 +17903297 rs10502991 wide-range achievement test 1e-05 table 1 23 1 +17903297 rs7124781 ALLV 0.0 table 1 33 1 +17903297 rs1131497 similarities 3e-06 table 1 34 1 +17903297 rs10506065 wide-range achievement test 5e-06 table 1 35 1 +17903297 rs3852286 tcbv 6e-06 table 1 36 1 +17903297 rs2029395 factor 2:visual memory and organization 0.0 table 1 54 1 +17903297 rs1433527 temporal brain volume 0.0 table 1 56 1 +17903297 rs1547275 temporal brain volume -1 table 1 62 1 +17903297 rs2975420 f3 -1 table 1 63 1 +17903297 rs2765241 boston naming test -1 table 1 64 1 +17903297 rs293966 boston naming test -1 table 1 65 1 +17903297 rs10512187 wide-range achievement test -1 table 1 66 1 +17903297 rs1328822 wide-range achievement test -1 table 1 67 1 +17903297 rs1846090 wide-range achievement test -1 table 1 68 1 +17903297 rs10518241 wide-range achievement test -1 table 1 69 1 +17903297 rs4426714 BMRIZLWMHVMV -1 table 1 70 1 +17903297 rs236535 BMRIZLWMHVMV -1 table 1 71 1 +17903297 rs502309 tcbv 5e-06 table 2 23 2 +17903297 rs1131497 similarities 3e-06 table 2 30 2 +17903297 rs2326510 parietal brain volume -1 table 2 46 2 +17903298 rs2722425 28 yr time averaged fpg 0.0 table 1 3 2 +17903298 rs10497721 Incident DM 1e-06 table 1 4 2 +17903298 rs2877832 Fasting Insulin 2e-06 table 1 5 2 +17903298 rs2877832 homeostasis model insulin resistance 3e-06 table 1 6 2 +17903298 rs10510634 28 yr time averaged fpg 5e-06 table 1 7 2 +17903298 rs180730 fasting plasma glucose 5e-06 table 1 8 2 +17903298 rs180730 28 yr time averaged fpg 6e-06 table 1 9 2 +17903298 rs7731657 28 yr time averaged fpg 7e-06 table 1 10 2 +17903298 rs10486607 hemoglobin a1c 8e-06 table 1 11 2 +17903298 rs2722425 fasting plasma glucose 9e-06 table 1 13 2 +17903298 rs1489092 Incident DM -1 table 1 53 2 +17903298 rs1890843 fasting plasma glucose -1 table 1 63 2 +17903298 rs1463697 hemoglobin a1c -1 table 1 64 2 +17903298 rs10513843 homeostasis model insulin resistance -1 table 1 65 2 +17903298 rs4803953 Fasting insulin -1 table 1 66 2 +17903298 rs10510060 hemoglobin a1c -1 table 1 67 2 +17903298 rs10500300 homeostasis model insulin resistance -1 table 1 68 2 +17903298 rs2837076 28 yr time averaged fpg -1 table 1 69 2 +17903298 rs10497392 hemoglobin a1c -1 table 1 70 2 +17903298 rs876362 28 yr time averaged fpg -1 table 1 71 2 +17903298 rs10513860 Fasting insulin -1 table 1 72 2 +17903298 rs1882347 fasting plasma glucose -1 table 1 73 2 +17903298 rs10512296 fasting plasma glucose -1 table 1 74 2 +17903298 rs2444962 28 yr time averaged fpg -1 table 1 76 2 +17903298 rs10494382 hemoglobin a1c -1 table 1 77 2 +17903298 rs757110 Fasting insulin -1 table 3 1 1 +17903298 rs757110 Fasting insulin -1 table 3 1 1 +17903298 rs878208 Fasting insulin -1 table 3 1 3 +17903298 rs878208 Fasting insulin -1 table 3 1 3 +17903298 rs722341 28 yr time averaged fpg -1 table 3 2 3 +17903298 rs722341 hemoglobin a1c -1 table 3 2 3 +17903298 rs916829 Fasting insulin -1 table 3 3 3 +17903298 rs916829 Fasting insulin -1 table 3 3 3 +17903298 rs2299641 Fasting insulin -1 table 3 5 3 +17903298 rs2190454 Fasting insulin -1 table 3 6 3 +17903298 rs1801282 28 yr time averaged fpg -1 table 3 7 1 +17903298 rs10510422 28 yr time averaged fpg -1 table 3 7 3 +17903298 rs3856808 28 yr time averaged fpg -1 table 3 8 3 +17903298 rs10510421 28 yr time averaged fpg -1 table 3 9 3 +17903298 rs2938392 Fasting insulin -1 table 3 10 3 +17903298 rs2938392 Fasting insulin -1 table 3 10 3 +17903298 rs10510418 Fasting insulin -1 table 3 12 3 +17903298 rs1801282 hemoglobin a1c -1 table 3 13 3 +17903298 rs1899951 hemoglobin a1c -1 table 3 14 3 +17903298 rs4135268 28 yr time averaged fpg -1 table 3 15 3 +17903298 rs2292101 28 yr time averaged fpg -1 table 3 17 3 +17903298 rs2292101 Fasting insulin -1 table 3 17 3 +17903298 rs10510419 28 yr time averaged fpg -1 table 3 18 3 +17903298 rs10510410 fasting plasma glucose -1 table 3 19 3 +17903298 rs10510410 Fasting insulin -1 table 3 19 3 +17903298 rs10510411 fasting plasma glucose -1 table 3 20 3 +17903298 rs10510411 Fasting insulin -1 table 3 20 3 +17903298 rs10510412 fasting plasma glucose -1 table 3 21 3 +17903298 rs10510412 Fasting insulin -1 table 3 21 3 +17903298 rs12255372 hemoglobin a1c -1 table 3 22 1 +17903298 rs10509967 hemoglobin a1c -1 table 3 22 3 +17903298 rs7903146 28 yr time averaged fpg -1 table 3 23 1 +17903298 rs7903146 28 yr time averaged fpg -1 table 3 23 1 +17903298 rs7100927 28 yr time averaged fpg -1 table 3 23 3 +17903298 rs7100927 28 yr time averaged fpg -1 table 3 23 3 +17903298 rs10509966 hemoglobin a1c -1 table 3 24 3 +17903298 rs10509969 Fasting insulin -1 table 3 25 3 +17903298 rs10509969 fasting plasma glucose -1 table 3 25 3 +17903298 rs290483 Fasting insulin -1 table 3 26 3 +17903298 rs290483 28 yr time averaged fpg -1 table 3 26 3 +17903298 rs7917983 28 yr time averaged fpg -1 table 3 27 3 +17903298 rs7917983 hemoglobin a1c -1 table 3 27 3 +17903298 rs10509970 28 yr time averaged fpg -1 table 3 28 3 +17903298 rs10509970 28 yr time averaged fpg -1 table 3 28 3 +17903300 rs1106683 Mean body mass index 0.0 table 1 3 1 +17903300 rs4471028 Mean waist circumference 0.0 table 1 4 1 +17903300 rs4469448 Mean waist circumference 0.0 table 1 5 1 +17903300 rs6996971 Mean waist circumference 0.0 table 1 6 1 +17903300 rs10504576 Mean waist circumference 1e-06 table 1 7 1 +17903300 rs1875517 Mean waist circumference 2e-06 table 1 8 1 +17903300 rs1106684 Mean body mass index 2e-06 table 1 9 1 +17903300 rs1333026 Mean body mass index 8e-06 table 1 10 1 +17903300 rs10488165 Mean waist circumference 3e-06 table 1 33 1 +17903300 rs2206682 Mean waist circumference 4e-06 table 1 34 1 +17903300 rs2223662 Mean waist circumference 5e-06 table 1 35 1 +17903300 rs953536 Mean waist circumference 8e-06 table 1 36 1 +17903300 rs9309153 Mean body mass index -1 table 1 63 1 +17903300 rs1992901 Mean waist circumference -1 table 1 64 1 +17903300 rs10518418 Mean body mass index -1 table 1 65 1 +17903301 rs1379659 left ventricular diastolic dimension 0.0 table 1 5 1 +17903301 rs366676 left ventricular fractional shortening 2e-06 table 1 6 1 +17903301 rs666088 left ventricular diastolic dimension 5e-06 table 1 7 1 +17903301 rs10504543 left ventricular systolic dimension 5e-06 table 1 8 1 +17903301 rs1935881 Left atrial diameter 6e-06 table 1 9 1 +17903301 rs10498091 left ventricular mass 6e-06 table 1 10 1 +17903301 rs10493389 Left atrial diameter 7e-06 table 1 11 1 +17903301 rs4920799 left ventricular diastolic dimension 7e-06 table 1 12 1 +17903301 rs10519181 left ventricular wall thickness 1e-05 table 1 13 1 +17903301 rs6847149 Stage 2 Exercise heart rate 3e-06 table 1 23 1 +17903301 rs2819770 Stage 2 Exercise heart rate 4e-06 table 1 24 1 +17903301 rs746463 Post-exercise 3 minute recovery systolic blood pressure 5e-06 table 1 25 1 +17903301 rs2056387 Stage 2 Exercise heart rate 5e-06 table 1 26 1 +17903301 rs2553268 Stage 2 Exercise systolic blood pressure 6e-06 table 1 27 1 +17903301 rs3814219 Baseline brachial artery flow velocity 1e-06 table 1 31 1 +17903301 rs1392284 left ventricular systolic dimension 6e-06 table 1 43 1 +17903301 rs2016718 Post-exercise 3 minute recovery systolic blood pressure 0.0 table 1 61 1 +17903301 rs1029947 Post-exercise 3 minute recovery heart rate 1e-06 table 1 62 1 +17903301 rs1029946 Post-exercise 3 minute recovery heart rate 4e-06 table 1 63 1 +17903301 rs1958055 Stage 2 Exercise heart rate 9e-06 table 1 64 1 +17903301 rs7828552 Post-exercise 3 minute recovery systolic blood pressure 9e-06 table 1 65 1 +17903301 rs10515509 left ventricular mass -1 table 1 81 1 +17903301 rs10513442 Aortic root diameter -1 table 1 82 1 +17903301 rs3813713 left ventricular wall thickness -1 table 1 83 1 +17903301 rs10511550 left ventricular wall thickness -1 table 1 84 1 +17903301 rs2438085 left ventricular wall thickness -1 table 1 86 1 +17903301 rs7327514 Left atrial diameter -1 table 1 87 1 +17903301 rs1719 left ventricular wall thickness -1 table 1 88 1 +17903301 rs10489725 left ventricular mass -1 table 1 89 1 +17903301 rs1989051 left ventricular mass -1 table 1 90 1 +17903301 rs190982 Stage 2 Exercise heart rate -1 table 1 95 1 +17903301 rs7286558 Stage 2 Exercise heart rate -1 table 1 97 1 +17903301 rs10483844 Stage 2 Exercise heart rate -1 table 1 98 1 +17903301 rs1425727 Baseline brachial artery flow velocity -1 table 1 102 1 +17903301 rs3007456 Baseline brachial artery flow velocity -1 table 1 104 1 +17903301 rs4920799 left ventricular diastolic dimension -1 table 2 3 1 +17903301 rs1379659 left ventricular diastolic dimension -1 table 2 4 1 +17903301 rs26438 Aortic root diameter -1 table 2 5 1 +17903301 rs473664 left ventricular mass -1 table 2 6 1 +17903301 rs10488825 Aortic root diameter -1 table 2 7 1 +17903301 rs10498091 left ventricular mass -1 table 2 8 1 +17903301 rs10514431 left ventricular diastolic dimension -1 table 2 9 1 +17903301 rs10505599 left ventricular diastolic dimension -1 table 2 10 1 +17903301 rs10504543 left ventricular systolic dimension -1 table 2 11 1 +17903301 rs2900208 left ventricular diastolic dimension -1 table 2 12 1 +17903301 rs861857 left ventricular mass -1 table 2 13 1 +17903301 rs10501940 left ventricular systolic dimension -1 table 2 14 1 +17903301 rs707025 left ventricular systolic dimension -1 table 2 15 1 +17903301 rs1395204 Aortic root diameter -1 table 2 16 1 +17903301 rs10513272 left ventricular diastolic dimension -1 table 2 17 1 +17903301 rs1379659 Across left ventricular phenotypes -1 table 2 21 1 +17903301 rs10498091 Across left ventricular phenotypes -1 table 2 22 1 +17903301 rs861857 Across left ventricular phenotypes -1 table 2 23 1 +17903301 rs473664 Across left ventricular phenotypes -1 table 2 24 1 +17903301 rs3766377 Across left ventricular phenotypes -1 table 2 25 1 +17903301 rs10504543 Across left ventricular phenotypes -1 table 2 26 1 +17903301 rs10518462 Across left ventricular phenotypes -1 table 2 27 1 +17903301 rs1959289 Across left ventricular phenotypes -1 table 2 28 1 +17903301 rs667269 Across left ventricular phenotypes -1 table 2 29 1 +17903301 rs1959290 Across left ventricular phenotypes -1 table 2 30 1 +17903301 rs1959291 Across left ventricular phenotypes -1 table 2 31 1 +17903301 rs10485104 Across left ventricular phenotypes -1 table 2 32 1 +17903301 rs10491574 Across left ventricular phenotypes -1 table 2 33 1 +17903301 rs707025 Across left ventricular phenotypes -1 table 2 34 1 +17903301 rs525960 Across left ventricular phenotypes -1 table 2 35 1 +17903301 rs1560916 Across phenotypes -1 table 2 39 1 +17903301 rs1432214 Across phenotypes -1 table 2 40 1 +17903301 rs10512056 Across phenotypes -1 table 2 41 1 +17903301 rs2056387 Across phenotypes -1 table 2 42 1 +17903301 rs6560812 Across phenotypes -1 table 2 43 1 +17903301 rs2912991 Across phenotypes -1 table 2 47 1 +17903301 rs10510677 Across phenotypes -1 table 2 48 1 +17903301 rs10493052 Across phenotypes -1 table 2 49 1 +17903301 rs7155941 Across phenotypes -1 table 2 50 1 +17903301 rs1954627 Across phenotypes -1 table 2 51 1 +17903301 rs10510001 left ventricular diastolic dimension -1 table 3 5 1 +17903301 rs10510001 left ventricular systolic dimension -1 table 3 6 1 +17903301 rs10510000 left ventricular diastolic dimension -1 table 3 7 1 +17903301 rs10510000 left ventricular systolic dimension -1 table 3 8 1 +17903301 rs7902873 left ventricular diastolic dimension -1 table 3 9 1 +17903301 rs10509999 left ventricular diastolic dimension -1 table 3 10 1 +17903301 rs180940 left ventricular wall thickness -1 table 3 11 1 +17903301 rs180934 left ventricular wall thickness -1 table 3 12 1 +17903301 rs180935 left ventricular wall thickness -1 table 3 13 1 +17903301 rs998334 left ventricular diastolic dimension -1 table 3 14 1 +17903301 rs7902873 left ventricular systolic dimension -1 table 3 15 1 +17903301 rs10509999 left ventricular systolic dimension -1 table 3 16 1 +17903301 rs180935 left ventricular mass -1 table 3 17 1 +17903301 rs180934 left ventricular mass -1 table 3 18 1 +17903301 rs7902873 left ventricular mass -1 table 3 19 1 +17903301 rs998334 left ventricular systolic dimension -1 table 3 20 1 +17903301 rs10510001 left ventricular fractional shortening -1 table 3 21 1 +17903301 rs10510000 left ventricular fractional shortening -1 table 3 22 1 +17903301 rs180940 left ventricular mass -1 table 3 23 1 +17903301 rs10510001 left ventricular mass -1 table 3 24 1 +17903301 rs6585258 left ventricular mass -1 table 3 25 1 +17903301 rs10510000 left ventricular mass -1 table 3 26 1 +17903301 rs10495300 Left atrial diameter -1 table 3 27 1 +17903301 rs2478518 left ventricular fractional shortening -1 table 3 28 1 +17903301 rs1202585 left ventricular wall thickness -1 table 3 29 1 +17903301 rs2180478 left ventricular diastolic dimension -1 table 3 30 1 +17903301 rs758216 Aortic root diameter -1 table 3 31 1 +17903301 rs1202524 left ventricular diastolic dimension -1 table 3 32 1 +17903301 rs2478518 left ventricular systolic dimension -1 table 3 33 1 +17903301 rs731824 Left atrial diameter -1 table 3 34 1 +17903301 rs1202585 left ventricular mass -1 table 3 35 1 +17903301 rs1059502 Aortic root diameter -1 table 3 36 1 +17903301 rs1357424 left ventricular fractional shortening -1 table 3 37 1 +17903301 rs1357424 left ventricular systolic dimension -1 table 3 38 1 +17903301 rs1059502 left ventricular diastolic dimension -1 table 3 39 1 +17903301 rs2331406 Aortic root diameter -1 table 3 40 1 +17903301 rs10513333 Left atrial diameter -1 table 3 41 1 +17903301 rs729761 left ventricular fractional shortening -1 table 3 42 1 +17903301 rs729761 Left atrial diameter -1 table 3 43 1 +17903301 rs729761 left ventricular systolic dimension -1 table 3 44 1 +17903301 rs2396083 left ventricular fractional shortening -1 table 3 45 1 +17903301 rs2396083 Left atrial diameter -1 table 3 46 1 +17903301 rs2396083 left ventricular systolic dimension -1 table 3 47 1 +17903301 rs10491167 Stage 2 Exercise systolic blood pressure -1 table 3 55 1 +17903301 rs10491168 Stage 2 Exercise systolic blood pressure -1 table 3 56 1 +17903301 rs721575 Post-exercise 3 minute recovery heart rate -1 table 3 57 1 +17903301 rs2419857 Stage 2 Exercise heart rate -1 table 3 58 1 +17903301 rs4345919 Post-exercise 3 minute recovery heart rate -1 table 3 59 1 +17903301 rs1752189 Post-exercise 3 minute recovery systolic blood pressure -1 table 3 60 1 +17903301 rs758216 Post-exercise 3 minute recovery systolic blood pressure -1 table 3 61 1 +17903301 rs10495298 Stage 2 Exercise systolic blood pressure -1 table 3 62 1 +17903301 rs2478516 Stage 2 Exercise systolic blood pressure -1 table 3 63 1 +17903301 rs275678 Post-exercise 3 minute recovery systolic blood pressure -1 table 3 64 1 +17903301 rs427832 Post-exercise 3 minute recovery systolic blood pressure -1 table 3 65 1 +17903301 rs1949350 Stage 2 Exercise heart rate -1 table 3 66 1 +17903301 rs729761 Stage 2 Exercise heart rate -1 table 3 67 1 +17903301 rs2303928 Stage 2 Exercise heart rate -1 table 3 68 1 +17903301 rs180940 brachial artery hyperemic flow velocity -1 table 3 76 1 +17903301 rs180935 brachial artery hyperemic flow velocity -1 table 3 77 1 +17903301 rs180934 brachial artery hyperemic flow velocity -1 table 3 78 1 +17903301 rs10509999 brachial artery hyperemic flow velocity -1 table 3 79 1 +17903301 rs10510000 brachial artery hyperemic flow velocity -1 table 3 80 1 +17903301 rs10510001 brachial artery hyperemic flow velocity -1 table 3 81 1 +17903301 rs758216 Baseline brachial artery flow velocity -1 table 3 82 1 +17903301 rs1202585 Baseline brachial artery diameter -1 table 3 83 1 +17903301 rs1202585 brachial artery hyperemic flow velocity -1 table 3 84 1 +17903301 rs1492090 brachial artery hyperemic flow velocity -1 table 3 85 1 +17903301 rs427832 Baseline brachial artery flow velocity -1 table 3 86 1 +17903301 rs833048 brachial artery hyperemic flow velocity -1 table 3 87 1 +17903301 rs10498756 brachial artery hyperemic flow velocity -1 table 3 88 1 +17903301 rs741067 Baseline brachial artery diameter -1 table 3 89 1 +17903301 rs1006581 Baseline brachial artery diameter -1 table 3 90 1 +17903301 rs2215564 brachial artery hyperemic flow velocity -1 table 3 91 1 +17903302 rs1963982 blood-pressure 3e-06 table 1 5 2 +17903302 rs935334 blood-pressure 3e-06 table 1 6 2 +17903302 rs4370013 blood-pressure 4e-06 table 1 7 2 +17903302 rs10491334 blood-pressure 4e-06 table 1 8 2 +17903302 rs2121070 blood-pressure 5e-06 table 1 9 2 +17903302 rs2509458 blood-pressure 7e-06 table 1 10 2 +17903302 rs10493340 blood-pressure 2e-06 table 1 18 2 +17903302 rs6063312 RW 2e-06 table 1 31 2 +17903302 rs770189 CB-PWV 3e-06 table 1 32 2 +17903302 rs10514688 CB-PWV 6e-06 table 1 33 2 +17903302 rs7042864 CB-PWV 6e-06 table 1 34 2 +17903302 rs1322512 MAP 8e-06 table 1 35 2 +17903302 rs1590919 blood-pressure 1e-06 table 1 50 2 +17903302 rs636864 blood-pressure 2e-06 table 1 51 2 +17903302 rs1588260 blood-pressure 3e-06 table 1 61 2 +17903302 rs1539377 FW 5e-06 table 1 72 2 +17903302 rs792833 RW 6e-06 table 1 73 2 +17903302 rs7591163 blood-pressure 0.0 table 2 3 1 +17903302 rs3096277 blood-pressure 0.0 table 2 16 1 +17903302 rs1721359 blood-pressure 1e-05 table 2 17 1 +17903302 rs3773643 MAP 0.0 table 2 29 1 +17903302 rs3793427 FW 2e-06 table 2 30 1 +17903302 rs6492654 RW 2e-06 table 2 31 1 +17903302 rs1367248 CF-PWV 3e-06 table 2 32 1 +17903302 rs10521232 CF-PWV 4e-06 table 2 33 1 +17903302 rs3766680 FW 4e-06 table 2 34 1 +17903302 rs1371924 RW 4e-06 table 2 35 1 +17903302 rs10488172 RW 8e-06 table 2 36 1 +17903302 rs731824 MAP -1 table 4 23 2 +17903302 rs2478518 FW -1 table 4 24 2 +17903302 rs2478516 FW -1 table 4 25 2 +17903302 rs2478516 RW -1 table 4 26 2 +17903302 rs1059502 MAP -1 table 4 27 2 +17903302 rs427832 FW -1 table 4 28 2 +17903302 rs2717594 CF-PWV -1 table 4 29 2 +17903302 rs3910046 CF-PWV -1 table 4 30 2 +17903302 rs9307847 CB-PWV -1 table 4 31 2 +17903302 rs3910046 CB-PWV -1 table 4 32 2 +17903302 rs10519959 CB-PWV -1 table 4 33 2 +17903302 rs3846317 RW -1 table 4 34 2 +17903302 rs4835136 CB-PWV -1 table 4 35 2 +17903302 rs3846318 RW -1 table 4 36 2 +17903302 rs10519958 RW -1 table 4 37 2 +17903302 rs16776 FW -1 table 4 38 2 +17903302 rs3911890 FW -1 table 4 39 2 +17903303 rs1376877 Internal carotid artery intimal medial thickness 0.0 table 1 3 2 +17903303 rs2390582 Coronary artery calcification 1e-06 table 1 4 2 +17903303 rs3849150 Abdominal aortic calcification 2e-06 table 1 5 2 +17903303 rs2896103 Ankle brachial index 5e-06 table 1 6 2 +17903303 rs10483853 Coronary artery calcification 6e-06 table 1 7 2 +17903303 rs1400544 Common carotid artery intimal medial thickness 6e-06 table 1 8 2 +17903303 rs7715811 Ankle brachial index 6e-06 table 1 9 2 +17903303 rs10507130 Coronary artery calcification 7e-06 table 1 10 2 +17903303 rs1320267 Ankle brachial index 7e-06 table 1 11 2 +17903303 rs1350445 Ankle brachial index 8e-06 table 1 12 2 +17903303 rs1502050 Ankle brachial index 9e-06 table 1 13 2 +17903303 rs4814615 Common carotid artery intimal medial thickness 3e-06 table 1 33 2 +17903303 rs6053733 Common carotid artery intimal medial thickness 4e-06 table 1 34 2 +17903303 rs10499903 Ankle brachial index 4e-06 table 1 35 2 +17903303 rs9302997 Ankle brachial index 5e-06 table 1 36 2 +17903303 rs590183 Ankle brachial index 9e-06 table 1 37 2 +17903303 rs6832344 Ankle brachial index 1e-05 table 1 38 2 +17903303 rs959987 Internal carotid artery intimal medial thickness -1 table 1 64 2 +17903303 rs1180937 Internal carotid artery intimal medial thickness -1 table 1 65 2 +17903303 rs17030524 Abdominal aortic calcification -1 table 1 66 2 +17903303 rs394884 Ankle brachial index -1 table 1 68 2 +17903303 rs300574 Internal carotid artery intimal medial thickness -1 table 1 69 2 +17903303 rs714647 Internal carotid artery intimal medial thickness -1 table 1 70 2 +17903303 rs1106679 Coronary artery calcification -1 table 1 71 2 +17903303 rs1454183 Abdominal aortic calcification -1 table 1 72 2 +17903303 rs7000744 Coronary artery calcification -1 table 1 73 2 +17903303 rs10483084 Ankle brachial index -1 table 1 74 2 +17903303 rs1948685 Internal carotid artery intimal medial thickness -1 table 1 75 2 +17903303 rs10832008 Internal carotid artery intimal medial thickness -1 table 1 76 2 +17903303 rs10483853 Coronary artery calcification 1e-05 table 2 19 2 +17903303 rs3762823 Common carotid artery intimal medial thickness -1 table 3 3 3 +17903303 rs3853250 Ankle brachial index -1 table 3 8 3 +17903303 rs3853251 Ankle brachial index -1 table 3 9 3 +17903303 rs2813563 Abdominal aortic calcification -1 table 3 14 3 +17903303 rs725467 Abdominal aortic calcification -1 table 3 15 3 +17903303 rs10240716 Ankle brachial index -1 table 3 18 3 +17903303 rs10505346 Ankle brachial index -1 table 3 22 3 +17903303 rs4444073 Ankle brachial index -1 table 3 25 3 +17903303 rs1467558 Coronary artery calcification -1 table 3 39 3 +17903304 rs958546 atrial fibrillation 5e-06 table 1 3 1 +17903304 rs499818 Major cardiovascular disease 7e-06 table 1 4 1 +17903304 rs4776472 atrial fibrillation 8e-06 table 1 5 1 +17903304 rs740363 heart failure 9e-06 table 1 6 1 +17903304 rs10501920 atrial fibrillation 9e-06 table 1 7 1 +17903304 rs2549513 Major coronary heart disease 1e-05 table 1 8 1 +17903304 rs7983138 Major coronary heart disease -1 table 3 4 2 +17903304 rs2985183 Major coronary heart disease -1 table 3 5 2 +17903304 rs7984952 Major coronary heart disease -1 table 3 6 2 +17903304 rs117395 Major coronary heart disease -1 table 3 7 2 +17903304 rs4603405 Major coronary heart disease -1 table 3 8 2 +17903304 rs10507391 Major coronary heart disease -1 table 3 9 2 +17903304 rs10507391 Major cardiovascular disease -1 table 3 10 2 +17903304 rs7995384 Major coronary heart disease -1 table 3 11 2 +17903304 rs618675 Major coronary heart disease -1 table 3 12 2 +17903304 rs10489658 Major coronary heart disease -1 table 3 13 2 +17903304 rs618675 Major cardiovascular disease -1 table 3 14 2 +17903304 rs10493062 Major coronary heart disease -1 table 3 15 2 +17903304 rs768586 Major coronary heart disease -1 table 3 16 2 +17903304 rs10489658 Major cardiovascular disease -1 table 3 17 2 +17903304 rs10489656 Major coronary heart disease -1 table 3 18 2 +17903304 rs10489656 Major cardiovascular disease -1 table 3 19 2 +17903304 rs2093185 Major cardiovascular disease -1 table 3 20 2 +17903304 rs6686484 Major coronary heart disease -1 table 3 21 2 +17903304 rs10492225 Major coronary heart disease -1 table 3 24 2 +17903304 rs2033546 Major cardiovascular disease -1 table 3 25 2 +17903304 rs2863274 Major cardiovascular disease -1 table 3 26 2 +17903304 rs2033546 Major coronary heart disease -1 table 3 27 2 +17903304 rs2863274 Major coronary heart disease -1 table 3 28 2 +17903304 rs2096767 Major cardiovascular disease -1 table 3 29 2 +17903304 rs2096767 Major coronary heart disease -1 table 3 30 2 +17903304 rs566125 Major cardiovascular disease -1 table 3 31 2 +17903304 rs2114580 Major coronary heart disease -1 table 3 33 2 +17903304 rs2114580 Major cardiovascular disease -1 table 3 34 2 +17903304 rs2317951 Major cardiovascular disease -1 table 3 35 2 +17903304 rs2317951 Major coronary heart disease -1 table 3 36 2 +17903304 rs2317948 Major coronary heart disease -1 table 3 37 2 +17903304 rs2317948 Major cardiovascular disease -1 table 3 38 2 +17903304 rs911839 Major cardiovascular disease -1 table 3 39 2 +17903304 rs911839 Major coronary heart disease -1 table 3 40 2 +17903304 rs264986 Major coronary heart disease -1 table 3 41 2 +17903304 rs758216 Major coronary heart disease -1 table 3 47 2 +17903304 rs10512574 Major coronary heart disease -1 table 3 51 2 +17903304 rs10488674 Major coronary heart disease -1 table 3 52 2 +17903304 rs7277304 Major coronary heart disease -1 table 3 53 2 +17903304 rs9305551 Major coronary heart disease -1 table 3 54 2 +17903304 rs752876 Major coronary heart disease -1 table 3 59 2 +17903304 rs40949 Major coronary heart disease -1 table 3 61 2 +17903304 rs185021 Major coronary heart disease -1 table 3 62 2 +17903304 rs10484326 Major coronary heart disease -1 table 3 68 2 +17903304 rs3951042 Major coronary heart disease -1 table 3 76 2 +17903304 rs724868 Major coronary heart disease -1 table 3 77 2 +17903304 rs9320660 Major coronary heart disease -1 table 3 78 2 +17903304 rs10484286 Major coronary heart disease -1 table 3 79 2 +17903304 rs1133415 Major coronary heart disease -1 table 3 81 2 +17903304 rs832177 Major coronary heart disease -1 table 3 83 2 +17903304 rs10519186 Major coronary heart disease -1 table 3 84 2 +17903304 rs902027 Major coronary heart disease -1 table 3 85 2 +17903304 rs10497521 Major coronary heart disease -1 table 3 86 2 +17903305 rs7564590 Breast cancer -1 table 2 4 2 +17903305 rs7558615 Breast cancer -1 table 2 5 2 +17903305 rs2410373 Prostate cancer -1 table 2 7 2 +17903306 rs10507380 QT 8e-06 table 2 3 2 +17903306 rs882300 PR 0.0 table 2 25 2 +17903306 rs1395479 LF/HF 7e-06 table 2 36 2 +17903306 rs9315385 TP 8e-06 table 2 47 2 +17903306 rs1011725 PR -1 table 3 3 2 +17903306 rs10512617 QT -1 table 3 4 2 +17903306 rs164462 QT -1 table 3 5 2 +17903306 rs10519165 LF/HF -1 table 3 9 2 +17903306 rs10500600 TP -1 table 3 10 2 +17903306 rs10494365 QT -1 table 4 3 1 +17903306 rs347311 QT -1 table 4 6 1 +17903306 rs10503797 RR -1 table 4 12 1 +17903306 rs10515621 RR -1 table 4 13 1 +17903306 rs520180 PR -1 table 4 17 1 +17903306 rs2195926 TP -1 table 4 25 1 +17903306 rs9325124 TP -1 table 4 26 1 +17903306 rs10503791 SDNN -1 table 4 30 1 +17903306 rs2195926 SDNN -1 table 4 31 1 +17903306 rs10503788 SDNN -1 table 4 32 1 +17903306 rs10503789 SDNN -1 table 4 33 1 +17903306 rs10503790 SDNN -1 table 4 34 1 +17903306 rs10503794 SDNN -1 table 4 35 1 +17903306 rs7000280 SDNN -1 table 4 36 1 +17903307 rs3867498 longitudinal slope of fev 1e-06 table 1 3 1 +17903307 rs441051 mean fvc from two exams 2e-06 table 1 4 1 +17903307 rs2838815 mean fev 3e-06 table 1 5 1 +17903307 rs1455782 percent predicted fvc for latest exam 4e-06 table 1 6 1 +17903307 rs10516541 mean fvc from two exams 4e-06 table 1 7 1 +17903307 rs310558 percent predicted fev 5e-06 table 1 9 1 +17903307 rs3820928 for latest exam 5e-06 table 1 10 1 +17903307 rs730532 for latest exam 6e-06 table 1 11 1 +17903307 rs808225 percent predicted fef 7e-06 table 1 12 1 +17903307 rs4129267 for latest exam 7e-06 table 1 14 1 +17903307 rs2906966 for latest exam 8e-06 table 1 15 1 +17903307 rs357394 percent predicted fvc for latest exam 9e-06 table 1 16 1 +17903307 rs1994169 longitudinal slope of fef 1e-05 table 1 17 1 +17903307 rs2225434 mean fev 1e-05 table 1 18 1 +17903307 rs156697 mean fvc from two exams 1e-05 table 1 19 1 +17903307 rs564425 percent predicted fef 1e-05 table 1 21 1 +17903307 rs10922530 percent predicted fev 1e-06 table 1 36 1 +17903307 rs3753683 percent predicted fef 2e-06 table 1 39 1 +17903307 rs219349 percent predicted fev 6e-06 table 1 42 1 +17903307 rs219391 percent predicted fev 6e-06 table 1 44 1 +17903307 rs219326 percent predicted fev 9e-06 table 1 45 1 +17903307 rs1409149 percent predicted fef 9e-06 table 1 47 1 +17903307 rs2906966 for latest exam 8e-06 table 1 63 1 +17903307 rs2300081 mean fev -1 table 1 74 1 +17903307 rs5909594 longitudinal slope of fef -1 table 1 75 1 +17903307 rs10497042 percent predicted fev -1 table 1 77 1 +17903307 rs10518669 mean fev -1 table 1 78 1 +17903307 rs2974490 for latest exam -1 table 1 79 1 +17903307 rs10488908 mean fvc from two exams -1 table 1 80 1 +17903307 rs10518032 for latest exam -1 table 1 81 1 +17903307 rs10489542 percent predicted fvc for latest exam -1 table 1 82 1 +17903307 rs721411 for latest exam -1 table 1 83 1 +17903307 rs753765 for latest exam -1 table 1 84 1 +17903307 rs4918762 mean fev -1 table 1 85 1 +17903307 rs10517825 percent predicted fvc for latest exam -1 table 1 86 1 +17903307 rs2402446 percent predicted fvc for latest exam longitudinal slope of fev -1 table 3 1 2 +17903307 rs10484042 percent predicted fvc for latest exam longitudinal slope of fev -1 table 3 1 2 +17903307 rs30329 longitudinal slope of fef mean fev -1 table 3 2 2 +17903307 rs9325117 longitudinal slope of fef mean fev -1 table 3 2 2 +17903307 rs213987 mean fvc from two exams percent predicted fev -1 table 3 3 2 +17903307 rs10487367 mean fvc from two exams percent predicted fev -1 table 3 3 2 +17903307 rs3738051 longitudinal slope of fef percent predicted fef -1 table 3 4 2 +17903307 rs423817 percent predicted fef percent predicted fef -1 table 3 5 2 +17903307 rs842873 percent predicted fef percent predicted fef -1 table 3 5 2 +17903307 rs542338 mean fev longitudinal slope of fev -1 table 3 6 2 +17903307 rs156697 mean fvc from two exams 1e-05 table 3 7 2 +17903307 rs688878 percent predicted fef percent predicted fvc for latest exam -1 table 3 8 2 +17903307 rs140289 percent predicted fvc for latest exam for latest exam -1 table 3 9 2 +17903307 rs2267331 longitudinal slope of fev mean fev -1 table 3 10 2 +17903307 rs10483190 longitudinal slope of fev mean fev -1 table 3 10 2 +17903307 rs10494879 longitudinal slope of fef longitudinal slope of fev -1 table 3 11 2 +17903307 rs495366 longitudinal slope of fef for latest exam -1 table 3 12 2 +17903307 rs2903908 percent predicted fef -1 table 3 13 2 +17903307 rs10484047 percent predicted fvc for latest exam longitudinal slope of fev -1 table 3 14 2 +17903307 rs717610 mean fvc from two exams mean fev -1 table 3 15 2 +17903307 rs7577293 mean fev -1 table 3 16 2 +17903307 rs726289 longitudinal slope of fef -1 table 3 17 2 +17903307 rs10489030 for latest exam percent predicted fvc for latest exam -1 table 3 18 2 +17903307 rs3745295 longitudinal slope of fev for latest exam -1 table 3 19 2 +17903307 rs2889529 for latest exam mean fev -1 table 3 20 2 +17903308 rs1823068 Sleepiness 0.0 table 1 3 1 +17903308 rs2218488 Sleepiness 3e-06 table 1 4 1 +17903308 rs2247614 Sleepiness -1 table 1 5 1 +17903308 rs7073579 Sleepiness -1 table 1 6 1 +17903308 rs9298693 Sleepiness -1 table 1 7 1 +17903308 rs949175 Bedtime 1e-05 table 1 8 1 +17903308 rs2288292 Bedtime -1 table 1 9 1 +17903308 rs324981 Bedtime -1 table 1 10 1 +17903308 rs10483871 Bedtime -1 table 1 11 1 +17903308 rs10507551 Bedtime -1 table 1 12 1 +17903308 rs6599077 Sleep duration 0.0 table 1 13 1 +17903308 rs10492604 Sleep duration 4e-06 table 1 14 1 +17903308 rs10489832 Sleep duration -1 table 1 15 1 +17903308 rs2256551 Sleep duration -1 table 1 16 1 +17903308 rs2165207 Sleep duration -1 table 1 17 1 +17903308 rs10510835 Sleepiness -1 table 1 23 1 +17903308 rs2189829 Sleepiness -1 table 1 24 1 +17903308 rs434052 Sleepiness -1 table 1 25 1 +17903308 rs4896580 Sleepiness -1 table 1 26 1 +17903308 rs10520010 Sleepiness -1 table 1 27 1 +17903308 rs1940013 Bedtime 6e-06 table 1 28 1 +17903308 rs2525724 Bedtime -1 table 1 29 1 +17903308 rs1725021 Bedtime -1 table 1 30 1 +17903308 rs932650 Bedtime -1 table 1 31 1 +17903308 rs2985334 Bedtime -1 table 1 32 1 +17903308 rs481233 Sleep duration -1 table 1 33 1 +17903308 rs2359894 Sleep duration -1 table 1 34 1 +17903308 rs2061579 Sleep duration -1 table 1 35 1 +17903308 rs10492507 Sleep duration -1 table 1 36 1 +17903308 rs6974138 Sleep duration -1 table 1 37 1 +17903308 rs28168 Bedtime -1 table 1 43 1 +17903308 rs10498313 Bedtime -1 table 1 44 1 +17903308 rs10503857 Bedtime -1 table 1 45 1 +17903308 rs10512058 Bedtime -1 table 1 46 1 +19043545 rs9309413 rs number -1 table 0 2 1 +19043545 rs992037 rs number -1 table 0 2 2 +19043545 rs1148259 rs number -1 table 0 2 3 +19043545 rs1200826 rs number -1 table 0 2 3 +19043545 rs174548 rs number -1 table 0 2 4 +19043545 rs4775041 rs number -1 table 0 2 5 +19430483 rs17367504 SBP 1e-05 table 1 3 3 +19430483 rs11191548 SBP 0.0 table 1 9 3 +19430483 rs12946454 SBP 4e-06 table 1 16 3 +19430483 rs16998073 DBP 0.0 table 1 28 3 +19430483 rs1530440 DBP 3e-06 table 1 34 3 +19430483 rs653178 DBP 0.0 table 1 42 3 +19430483 rs1378942 DBP 0.0 table 1 47 3 +19430483 rs16948048 DBP 5e-06 table 1 55 3 +19430483 rs17367504 SBP 1e-05 table 2 1 0 +19430483 rs11191548 SBP 0.0 table 2 4 0 +19430483 rs12946454 SBP 4e-06 table 2 7 0 +19430483 rs16998073 DBP 0.0 table 2 10 0 +19430483 rs1530440 DBP 3e-06 table 2 13 0 +19430483 rs653178 DBP 0.0 table 2 16 0 +19430483 rs1378942 DBP 0.0 table 2 19 0 +19430483 rs16948048 DBP 5e-06 table 2 22 0 +19430483 rs17367504 SBP 0.0 table 3 1 0 +19430483 rs11191548 SBP 0.0 table 3 2 0 +19430483 rs16998073 DBP 0.0 table 3 4 0 +19430483 rs653178 DBP 1e-06 table 3 6 0 +19430483 rs1378942 DBP 0.0 table 3 7 0 +19609347 rs9791170 HTN 1e-06 table 5 1 1 +19609347 rs991316 HTN 3e-06 table 5 2 1 +19609347 rs1550576 HTN 3e-06 table 5 5 1 +19609347 rs16877320 SBP 0.0 table 5 6 1 +19609347 rs11160059 SBP 0.0 table 5 7 1 +19609347 rs17365948 SBP 0.0 table 5 8 1 +19609347 rs8039294 SBP 8e-06 table 5 9 1 +19609347 rs10135446 DBP 4e-06 table 5 11 1 +19609347 rs9590141 DBP 1e-06 table 5 12 1 +19609347 rs1867226 DBP 1e-06 table 5 13 1 +19721433 rs17390445 Ziprasidone –Positive 0.0 table 1 4 1 +19721433 rs11722719 Ziprasidone – Positive 1e-06 table 1 5 1 +19721433 rs888219 Risperidone – Negative 0.0 table 1 7 1 +19721433 rs7968606 Olanzapine – Negative 0.0 table 1 8 1 +19721433 rs17727261 Risperidone – Negative 1e-06 table 1 9 1 +19721433 rs10888501 Olanzapine – Negative 1e-06 table 1 10 1 +19721433 rs1040994 Olanzapine – Excitement 2e-06 table 1 12 1 +19721433 rs10484256 Olanzapine – Excitement 3e-06 table 1 13 1 +19721433 rs7635839 Olanzapine – Excitement 3e-06 table 1 15 1 +19721433 rs12526186 Risperidone – Negative 3e-06 table 1 16 1 +19721433 rs17815774 Risperidone – Negative 3e-06 table 1 17 1 +19721433 rs12860002 Quetiapine – Negative -1 table 2 3 1 +19721433 rs12122534 Quetiapine – Emotion -1 table 2 5 1 +19721433 rs12122453 Quetiapine – Emotion -1 table 2 6 1 +19721433 rs6688154 Quetiapine – Emotion -1 table 2 8 1 +19721433 rs12728058 Quetiapine – Emotion -1 table 2 9 1 +19721433 rs2353967 Quetiapine – Emotion -1 table 2 10 1 +19721433 rs2353969 Quetiapine – Emotion -1 table 2 11 1 +19721433 rs11584787 Quetiapine – Emotion -1 table 2 13 1 +19721433 rs2382121 Perphenazine – Disorganiz. -1 table 2 14 1 +19721433 rs3899033 Perphenazine – Negative -1 table 2 15 1 +19721433 rs13174727 Perphenazine– Emotion -1 table 2 16 1 +19721433 rs2036702 Quetiapine– Emotion -1 table 2 17 1 +19721433 rs2684878 Perphenazine– Emotion -1 table 2 18 1 +19721433 rs7829383 Perphenazine– Negative -1 table 2 20 1 +19721433 rs6988339 Perphenazine– Negative -1 table 2 21 1 +19721433 rs7823899 Perphenazine– Negative -1 table 2 23 1 +19721433 rs887829 Perphenazine– Negative -1 table 2 24 1 +19721433 rs2454513 Quetiapine– Emotion -1 table 2 25 1 +19721433 rs2445223 Quetiapine– Emotion -1 table 2 26 1 +19820699 rs1800562 MCV -1 table 0 9 1 +19820699 rs3811647 MCV -1 table 0 16 1 +20066028 rs1532624 HDL-C 1e-06 table 1 3 0 +20066028 rs5400 TC 2e-06 table 1 5 0 +20195266 rs11163585 Perphenazine - HDL 1e-06 table 2 1 1 +20195266 rs17410015 Perphenazine - Triglycerides 2e-06 table 2 2 1 +20195266 rs6735179 Perphenazine - Triglycerides 0.0 table 2 3 1 +20195266 rs6741819 Perphenazine - Triglycerides 0.0 table 2 4 1 +20195266 rs1991126 Risperidone - Hip Circumference 1e-06 table 2 5 1 +20195266 rs1117324 Risperidone - Hip Circumference 0.0 table 2 6 1 +20195266 rs10202231 Perphenazine - Triglycerides 1e-06 table 2 7 1 +20195266 rs399885 Clozapine - Heart Rate 1e-06 table 2 8 1 +20195266 rs7570469 Clozapine - Heart Rate 1e-06 table 2 9 1 +20195266 rs1534238 Clozapine - Triglycerides 3e-06 table 2 10 1 +20195266 rs17385675 Clozapine - Triglycerides 3e-06 table 2 11 1 +20195266 rs13134954 Perphenazine - Triglycerides 2e-06 table 2 12 1 +20195266 rs11735070 Perphenazine - Triglycerides 1e-06 table 2 13 1 +20195266 rs1405687 Ziprasidone - Hip Circumference 0.0 table 2 14 1 +20195266 rs1967256 Olanzapine - Hemoglobin A1c 0.0 table 2 15 1 +20195266 rs11954387 Olanzapine - Hemoglobin A1c 0.0 table 2 16 1 +20195266 rs17100498 Risperidone - Hemoglobin A1c 0.0 table 2 17 1 +20195266 rs17100506 Risperidone - Hemoglobin A1c 1e-06 table 2 18 1 +20195266 rs9658108 Clozapine - Glucose 0.0 table 2 19 1 +20195266 rs1577917 Clozapine - Triglycerides 3e-06 table 2 20 1 +20195266 rs1979096 Clozapine - Total Cholesterol 1e-06 table 2 21 1 +20195266 rs10499504 Clozapine - Total Cholesterol 0.0 table 2 22 1 +20195266 rs13224682 Clozapine - Triglycerides 0.0 table 2 23 1 +20195266 rs977396 Olanzapine - Total Cholesterol 0.0 table 2 24 1 +20195266 rs320209 Clozapine - Glucose 0.0 table 2 25 1 +20195266 rs4838255 Perphenazine - Triglycerides 0.0 table 2 26 1 +20195266 rs17661538 Clozapine - Triglycerides 1e-06 table 2 27 1 +20195266 rs2994684 Clozapine - Triglycerides 0.0 table 2 28 1 +20195266 rs1771628 Clozapine - Triglycerides 1e-06 table 2 29 1 +20195266 rs7119817 Risperidone - Hip Circumference 0.0 table 2 30 1 +20195266 rs7105881 Risperidone - Hip Circumference 0.0 table 2 31 1 +20195266 rs7108821 Risperidone - Hip Circumference 0.0 table 2 32 1 +20195266 rs620875 Clozapine - Triglycerides 3e-06 table 2 33 1 +20195266 rs1464500 Perphenazine - HDL 0.0 table 2 34 1 +20195266 rs518590 Quetiapine - HDL 0.0 table 2 35 1 +20195266 rs1187614 Perphenazine - Total Cholesterol 0.0 table 2 36 1 +20195266 rs1568679 Risperidone - Hip Circumference 0.0 table 2 37 1 +20195266 rs1568679 Risperidone - Waist Circumference 0.0 table 2 38 1 +20195266 rs13335336 Risperidone - Hemoglobin A1c 1e-06 table 2 39 1 +20195266 rs153091 Perphenazine - Triglycerides 2e-06 table 2 40 1 +20195266 rs4783227 Olanzapine - Total Cholesterol 0.0 table 2 41 1 +20195266 rs17216786 Clozapine - Triglycerides 1e-06 table 2 42 1 +20195266 rs17651157 Perphenazine - Triglycerides 0.0 table 2 43 1 +20195266 rs10502661 Perphenazine - Triglycerides 0.0 table 2 44 1 +20195266 rs8092443 Risperidone - Hemoglobin A1c 1e-06 table 2 45 1 +20195266 rs11663206 Risperidone - Hemoglobin A1c 2e-06 table 2 46 1 +20195266 rs6092078 Risperidone - Hip Circumference 3e-06 table 2 47 1 +20395239 rs12571093 Disc -1 table 1 2 3 +20395239 rs3858145 Disc -1 table 1 3 3 +20395239 rs2241970 Disc -1 table 1 4 3 +20395239 rs17231602 Disc -1 table 1 5 3 +20395239 rs7067601 Disc -1 table 1 6 3 +20395239 rs10733843 Disc -1 table 1 7 3 +20395239 rs4517412 Disc -1 table 1 8 3 +20395239 rs690037 Cup -1 table 1 9 3 +20395239 rs6480314 Disc -1 table 1 10 3 +20395239 rs3858145 Cup -1 table 1 11 3 +20395239 rs1192415 Disc -1 table 1 12 3 +20395239 rs491391 Disc -1 table 1 13 3 +20395239 rs6611365 Disc -1 table 1 14 3 +20395239 rs1192404 Disc -1 table 1 15 3 +20395239 rs10762217 Disc -1 table 1 16 3 +20463881 rs3768056 S 0.0 table 1 3 0 +20463881 rs9782955 S 0.0 table 1 4 0 +20463881 rs7219915 C HS1 0.0 table 1 6 0 +20463881 rs9894429 C HS1 0.0 table 1 7 0 +20463881 rs12452184 C HS1 0.0 table 1 8 0 +20463881 rs1003719 C HS1 0.0 table 1 10 0 +20463881 rs2252893 C HS1 0.0 table 1 11 0 +20463881 rs2835621 C HS1 0.0 table 1 12 0 +20463881 rs2835630 C HS1 0.0 table 1 13 0 +20463881 rs7277820 C HS1 0.0 table 1 14 0 +20526338 rs12566888 ADP 3 u M 0.0 table 0 3 0 +20526338 rs12566888 ADP 2 u M 0.0 table 0 3 0 +20526338 rs7940646 ADP 5 u M 0.0 table 0 4 0 +20526338 rs7940646 ADP 10 u M 0.0 table 0 4 0 +20526338 rs2363910 ADP EC50 0.0 table 0 5 0 +20526338 rs2363910 ADP 2 u M 0.0 table 0 5 0 +20526338 rs4311994 Epi EC50 0.0 table 0 9 0 +20526338 rs4311994 Epi 2 u M 0.0 table 0 9 0 +20526338 rs12566888 Epi EC50 0.0 table 0 11 0 +20526338 rs12566888 Epi 2 u M 0.0 table 0 11 0 +20526338 rs342286 Epi EC50 0.0 table 0 13 0 +20526338 rs342286 Epi 2 u M 0.0 table 0 13 0 +20526338 rs10761741 Epi EC50 0.0 table 0 14 0 +20526338 rs10761741 Epi 2 u M 0.0 table 0 14 0 +20526338 rs1671152 Lag 190 u g/mL 0.0 table 0 18 0 +20526338 rs1671152 Lag 2 u g/mL 0.0 table 0 18 0 +20526338 rs12566888 ADP 3 u M 0.0 table 1 3 0 +20526338 rs12566888 ADP 2 u M 0.0 table 1 3 0 +20526338 rs7940646 ADP 5 u M 0.0 table 1 6 0 +20526338 rs7940646 ADP 10 u M 0.0 table 1 6 0 +20526338 rs2363910 ADP EC50 * 0.0 table 1 9 0 +20526338 rs2363910 ADP 2 u M 0.0 table 1 9 0 +20526338 rs4311994 Epi EC50 * 0.0 table 1 13 0 +20526338 rs4311994 Epi 2 u M 0.0 table 1 13 0 +20526338 rs12566888 Epi EC50 * 0.0 table 1 16 0 +20526338 rs12566888 Epi 2 u M 0.0 table 1 16 0 +20526338 rs342286 Epi EC50 * 0.0 table 1 19 0 +20526338 rs342286 Epi 2 u M 0.0 table 1 19 0 +20526338 rs10761741 Epi EC50 * 0.0 table 1 22 0 +20526338 rs10761741 Epi 2 u M 0.0 table 1 22 0 +20526338 rs1671152 Coll. 0.0 table 1 26 0 +20526338 rs1671152 lag 0.0 table 1 26 0 +20526338 rs1671152 Coll. 0.0 table 1 26 0 +20526338 rs1671152 lag 0.0 table 1 26 0 +20548944 rs2278729 NSA 0.0 table 0 3 0 +20548944 rs12808199 FN BMD 1e-06 table 0 4 0 +20548944 rs7227401 NW 0.0 table 0 5 0 +20548944 rs494453 NW 0.0 table 0 7 0 +20548944 rs12151790 FN BMD 0.0 table 0 8 0 +20548944 rs2062375 LS BMD 0.0 table 0 9 0 +20548944 rs17184557 LS BMD 1e-06 table 0 10 0 +20548944 rs6588313 LSBMD, women 5e-06 table 3 5 0 +20548944 rs17463551 LSBMD, women 3e-06 table 3 14 0 +20548944 rs10895656 LSBMD, men 3e-06 table 3 16 0 +20548944 rs3784131 NL, men 3e-06 table 3 17 0 +20548944 rs17201113 NL, men 1e-06 table 3 18 0 +20548944 rs11664087 NSA, women 3e-06 table 3 20 0 +20585627 rs17646946 Hair curl -1 table 1 1 1 +20585627 rs499697 Hair curl -1 table 1 2 1 +20585627 rs7349332 Hair curl -1 table 1 3 1 +20585627 rs4481887 Asparagus -1 table 1 4 1 +20585627 rs4309013 Asparagus -1 table 1 5 1 +20585627 rs4244187 Asparagus -1 table 1 6 1 +20585627 rs10427255 Sneeze -1 table 1 7 1 +20585627 rs12203592 Freckling -1 table 1 8 1 +20585627 rs872071 Freckling -1 table 1 9 1 +20585627 rs3778607 Freckling -1 table 1 10 1 +20585627 rs9328192 Freckling -1 table 1 11 1 +20585627 rs9405675 Freckling -1 table 1 12 1 +20585627 rs12931267 Freckling -1 table 1 13 1 +20585627 rs8049897 Freckling -1 table 1 14 1 +20585627 rs1805008 Freckling -1 table 1 15 1 +20585627 rs1805009 Freckling -1 table 1 16 1 +20585627 rs11547464 Freckling -1 table 1 17 1 +20585627 rs11861084 Freckling -1 table 1 18 1 +20585627 rs7204478 Freckling -1 table 1 19 1 +20585627 rs7195066 Freckling -1 table 1 20 1 +20585627 rs11648785 Freckling -1 table 1 21 1 +20585627 rs8060934 Freckling -1 table 1 22 1 +20585627 rs154659 Freckling -1 table 1 23 1 +20585627 rs619865 Freckling -1 table 1 24 1 +20585627 rs4911442 Freckling -1 table 1 25 1 +20585627 rs291671 Freckling -1 table 1 26 1 +20585627 rs6088316 Freckling -1 table 1 27 1 +20585627 rs761238 Freckling -1 table 1 28 1 +20585627 rs17305657 Freckling -1 table 1 29 1 +20585627 rs4812405 Freckling -1 table 1 30 1 +20585627 rs1474976 Freckling -1 table 1 31 1 +20585627 rs4911414 Freckling -1 table 1 32 1 +20585627 rs2153271 Freckling -1 table 1 33 1 +20585627 rs12913832 Hair color -1 table 2 1 1 +20585627 rs7183877 Hair color -1 table 2 2 1 +20585627 rs4778138 Hair color -1 table 2 3 1 +20585627 rs12203592 Hair color -1 table 2 4 1 +20585627 rs16891982 Hair color -1 table 2 5 1 +20585627 rs12896399 Hair color -1 table 2 6 1 +20585627 rs12931267 Hair color -1 table 2 7 1 +20585627 rs12931267 Red hair -1 table 2 8 1 +20585627 rs4238833 Red hair -1 table 2 9 1 +20585627 rs8049897 Red hair -1 table 2 10 1 +20585627 rs1805008 Red hair -1 table 2 11 1 +20585627 rs4408545 Red hair -1 table 2 12 1 +20585627 rs1805009 Red hair -1 table 2 13 1 +20585627 rs2353033 Red hair -1 table 2 14 1 +20585627 rs2159116 Red hair -1 table 2 15 1 +20585627 rs7196459 Red hair -1 table 2 16 1 +20585627 rs7195066 Red hair -1 table 2 17 1 +20585627 rs447735 Red hair -1 table 2 18 1 +20585627 rs11648785 Red hair -1 table 2 19 1 +20585627 rs4347628 Red hair -1 table 2 20 1 +20585627 rs291671 Red hair -1 table 2 21 1 +20585627 rs17305657 Red hair -1 table 2 22 1 +20585627 rs619865 Red hair -1 table 2 23 1 +20585627 rs12913832 Eye color -1 table 3 1 1 +20585627 rs8039195 Eye color -1 table 3 2 1 +20585627 rs16950987 Eye color -1 table 3 3 1 +20585627 rs2240204 Eye color -1 table 3 4 1 +20585627 rs6497253 Eye color -1 table 3 5 1 +20585627 rs1470608 Eye color -1 table 3 6 1 +20585627 rs4778232 Eye color -1 table 3 7 1 +20585627 rs1597196 Eye color -1 table 3 8 1 +20585627 rs7170451 Eye color -1 table 3 9 1 +20585627 rs1800407 Eye color -1 table 3 10 1 +20585627 rs4778220 Eye color -1 table 3 11 1 +20585627 rs728405 Eye color -1 table 3 12 1 +20585627 rs1800404 Eye color -1 table 3 13 1 +20585627 rs1107267 Eye color -1 table 3 14 1 +20585627 rs3930739 Eye color -1 table 3 15 1 +20585627 rs17565953 Eye color -1 table 3 16 1 +20585627 rs977588 Eye color -1 table 3 17 1 +20585627 rs12896399 Eye color -1 table 3 18 1 +20585627 rs4904868 Eye color -1 table 3 19 1 +20585627 rs12203592 Eye color -1 table 3 20 1 +20585627 rs16891982 Eye color -1 table 3 21 1 +20585627 rs1393350 Eye color -1 table 3 22 1 +20585627 rs12913832 Green eyes -1 table 3 23 1 +20585627 rs7183877 Green eyes -1 table 3 24 1 +20585627 rs12896399 Green eyes -1 table 3 25 1 +20585627 rs1847134 Green eyes -1 table 3 26 1 +20585627 rs1827430 Green eyes -1 table 3 27 1 +20585627 rs11018528 Green eyes -1 table 3 28 1 +20585627 rs7120151 Green eyes -1 table 3 29 1 +20585627 rs1806319 Green eyes -1 table 3 30 1 +20585627 rs1556547 Haircurl -1 table 4 1 1 +20585627 rs10960751 Eye color -1 table 4 2 1 +20585627 rs1042602 Freckle -1 table 4 3 1 +20585627 rs11856995 Sneeze -1 table 4 4 1 +20694148 rs3764261 Log HDL-C (mmol/l) 0.0 table 1 2 1 +20694148 rs9989419 “ 0.0 table 1 3 1 +20694148 rs2083637 “ 0.0 table 1 4 1 +20694148 rs4523270 “ 0.0 table 1 5 1 +20694148 rs496300 “ 0.0 table 1 6 1 +20694148 rs174546 “ 0.0 table 1 7 1 +20694148 rs1535 “ 1e-06 table 1 8 1 +20694148 rs7903146 T2D 0.0 table 1 9 1 +20694148 rs7865146 DBP (mmHg) 1e-06 table 1 10 1 +20838585 rs7704530 diastolic BP 0.0 table 0 1 3 +20838585 rs709595 diastolic BP 1e-06 table 0 2 3 +20838585 rs853773 glucose 1e-06 table 0 3 3 +20838585 rs781718 glucose 1e-06 table 0 4 3 +20838585 rs247616 HDL-cholesterol 1e-06 table 0 5 3 +20838585 rs3793275 insulin 0.0 table 0 6 3 +20838585 rs6052399 insulin 0.0 table 0 7 3 +20838585 rs16892328 insulin 0.0 table 0 8 3 +20838585 rs1613695 insulin 0.0 table 0 9 3 +20838585 rs10498337 insulin 1e-06 table 0 10 3 +20838585 rs8131349 LDL-cholesterol 0.0 table 0 11 3 +20838585 rs7412 LDL-cholesterol 0.0 table 0 12 3 +20838585 rs7738656 LDL-cholesterol 0.0 table 0 13 3 +20838585 rs10044666 LDL-cholesterol 0.0 table 0 14 3 +20838585 rs11822822 systolic BP 1e-06 table 0 15 3 +20838585 rs726914 systolic BP 1e-06 table 0 16 3 +20838585 rs8131349 total cholesterol 0.0 table 0 17 3 +20838585 rs6829649 total cholesterol 0.0 table 0 18 3 +20838585 rs7738656 total cholesterol 0.0 table 0 19 3 +20838585 rs4897695 total cholesterol 0.0 table 0 20 3 +20838585 rs891541 waist circumference 1e-06 table 0 21 3 +20838585 rs17104804 distolic BP 1e-06 table 1 1 3 +20838585 rs4783595 glucose 0.0 table 1 2 3 +20838585 rs3793275 glucose 0.0 table 1 3 3 +20838585 rs5979903 glucose 0.0 table 1 4 3 +20838585 rs12807555 glucose 0.0 table 1 5 3 +20838585 rs9909931 glucose 0.0 table 1 6 3 +20838585 rs12069004 glucose 1e-06 table 1 7 3 +20838585 rs12548494 glucose 1e-06 table 1 8 3 +20838585 rs10260737 glucose 1e-06 table 1 9 3 +20838585 rs3019325 glucose 1e-06 table 1 10 3 +20838585 rs6440031 heart rate 0.0 table 1 11 3 +20838585 rs1449460 heart rate 1e-06 table 1 12 3 +20838585 rs1144036 height 0.0 table 1 13 3 +20838585 rs8103264 height 1e-06 table 1 14 3 +20838585 rs1552257 insulin 1e-06 table 1 15 3 +20838585 rs8073909 LDL 0.0 table 1 16 3 +20838585 rs11258628 LDL 0.0 table 1 17 3 +20838585 rs1046391 systolic BP 0.0 table 1 18 3 +20838585 rs17104804 systolic BP 1e-06 table 1 19 3 +20838585 rs8073909 total cholesterol 0.0 table 1 20 3 +20838585 rs7890572 triglycerides 0.0 table 1 21 3 +20838585 rs12280753 triglycerides 0.0 table 1 22 3 +20838585 rs13290397 triglycerides 0.0 table 1 23 3 +20838585 rs6726786 triglycerides 0.0 table 1 24 3 +20838585 rs12330441 triglycerides 0.0 table 1 25 3 +20838585 rs127430 waist circumference 0.0 table 1 26 3 +20838585 rs7121446 waist circumference 0.0 table 1 27 3 +20838585 rs7210277 waist circumference 1e-06 table 1 28 3 +20838585 rs17568778 waist circumference 1e-06 table 1 29 3 +20838585 rs6552560 weight 0.0 table 1 30 3 +20838585 rs7704530 diastolic BP 0.0 table 2 2 1 +20838585 rs709595 diastolic BP 1e-06 table 2 3 1 +20838585 rs853773 glucose 1e-06 table 2 4 1 +20838585 rs781718 glucose 1e-06 table 2 5 1 +20838585 rs247616 HDL-cholesterol 0.0 table 2 6 1 +20838585 rs3793275 insulin 0.0 table 2 7 1 +20838585 rs6052399 insulin 0.0 table 2 8 1 +20838585 rs16892328 insulin 0.0 table 2 9 1 +20838585 rs1613695 insulin 0.0 table 2 10 1 +20838585 rs10498337 insulin 1e-06 table 2 11 1 +20838585 rs8131349 LDL-cholesterol 0.0 table 2 12 1 +20838585 rs445925 LDL-cholesterol 0.0 table 2 13 1 +20838585 rs7738656 LDL-cholesterol 0.0 table 2 14 1 +20838585 rs10044666 LDL-cholesterol 0.0 table 2 15 1 +20838585 rs11822822 systolic BP 1e-06 table 2 16 1 +20838585 rs726914 systolic BP 1e-06 table 2 17 1 +20838585 rs8131349 total cholesterol 0.0 table 2 18 1 +20838585 rs6829649 total cholesterol 0.0 table 2 19 1 +20838585 rs7738656 total cholesterol 0.0 table 2 20 1 +20838585 rs4897695 total cholesterol 0.0 table 2 21 1 +20838585 rs891541 waist circumference 1e-06 table 2 22 1 +20838585 rs17104804 distolic BP 1e-06 table 2 23 1 +20838585 rs4783595 glucose 0.0 table 2 24 1 +20838585 rs3793275 glucose 0.0 table 2 25 1 +20838585 rs5979903 glucose 0.0 table 2 26 1 +20838585 rs12807555 glucose 0.0 table 2 27 1 +20838585 rs9909931 glucose 0.0 table 2 28 1 +20838585 rs12069004 glucose 1e-06 table 2 29 1 +20838585 rs12548494 glucose 1e-06 table 2 30 1 +20838585 rs10260737 glucose 1e-06 table 2 31 1 +20838585 rs3019325 glucose 1e-06 table 2 32 1 +20838585 rs6440031 heart rate 0.0 table 2 33 1 +20838585 rs1449460 heart rate 1e-06 table 2 34 1 +20838585 rs1144036 height 0.0 table 2 35 1 +20838585 rs8103264 height 1e-06 table 2 36 1 +20838585 rs1552257 insulin 1e-06 table 2 37 1 +20838585 rs8073909 LDL 0.0 table 2 38 1 +20838585 rs11258628 LDL 0.0 table 2 39 1 +20838585 rs1046391 systolic BP 0.0 table 2 40 1 +20838585 rs17104804 systolic BP 1e-06 table 2 41 1 +20838585 rs8073909 total cholesterol 0.0 table 2 42 1 +20838585 rs7890572 triglycerides 0.0 table 2 43 1 +20838585 rs12280753 triglycerides 0.0 table 2 44 1 +20838585 rs13290397 triglycerides 0.0 table 2 45 1 +20838585 rs6726786 triglycerides 0.0 table 2 46 1 +20838585 rs12330441 triglycerides 0.0 table 2 47 1 +20838585 rs127430 waist circumference 0.0 table 2 48 1 +20838585 rs7121446 waist circumference 0.0 table 2 49 1 +20838585 rs7210277 waist circumference 1e-06 table 2 50 1 +20838585 rs17568778 waist circumference 1e-06 table 2 51 1 +20838585 rs6552560 weight 0.0 table 2 52 1 +20838585 rs7704530 diastolic BP -1 table 3 1 1 +20838585 rs709595 diastolic BP -1 table 3 2 1 +20838585 rs853773 glucose -1 table 3 3 1 +20838585 rs781718 glucose -1 table 3 4 1 +20838585 rs3793275 insulin -1 table 3 6 1 +20838585 rs6052399 insulin -1 table 3 7 1 +20838585 rs16892328 insulin -1 table 3 8 1 +20838585 rs1613695 insulin -1 table 3 9 1 +20838585 rs10498337 insulin -1 table 3 10 1 +20838585 rs8131349 LDL-cholesterol -1 table 3 11 1 +20838585 rs445925 LDL-cholesterol 2e-06 table 3 12 1 +20838585 rs7738656 LDL-cholesterol -1 table 3 13 1 +20838585 rs10044666 LDL-cholesterol -1 table 3 14 1 +20838585 rs11822822 systolic BP -1 table 3 15 1 +20838585 rs726914 systolic BP -1 table 3 16 1 +20838585 rs8131349 total cholesterol -1 table 3 17 1 +20838585 rs6829649 total cholesterol -1 table 3 18 1 +20838585 rs7738656 total cholesterol -1 table 3 19 1 +20838585 rs4897695 total cholesterol -1 table 3 20 1 +20838585 rs891541 waist circumference -1 table 3 21 1 +20838585 rs4783595 glucose 0.0 table 3 23 1 +20838585 rs3793275 glucose 1e-06 table 3 24 1 +20838585 rs12807555 glucose 0.0 table 3 26 1 +20838585 rs9909931 glucose 0.0 table 3 27 1 +20838585 rs12548494 glucose 3e-06 table 3 29 1 +20838585 rs1449460 heart rate -1 table 3 33 1 +20838585 rs1144036 height -1 table 3 34 1 +20838585 rs8103264 height -1 table 3 35 1 +20838585 rs8073909 LDL 1e-06 table 3 37 1 +20838585 rs11258628 LDL 7e-06 table 3 38 1 +20838585 rs17104804 systolic BP -1 table 3 40 1 +20838585 rs8073909 total cholesterol 0.0 table 3 41 1 +20838585 rs7890572 triglycerides 4e-06 table 3 42 1 +20838585 rs12280753 triglycerides 0.0 table 3 43 1 +20838585 rs13290397 triglycerides 1e-06 table 3 44 1 +20838585 rs6726786 triglycerides 4e-06 table 3 45 1 +20838585 rs127430 waist circumference 0.0 table 3 47 1 +20838585 rs7121446 waist circumference 2e-06 table 3 48 1 +20838585 rs7210277 waist circumference 1e-06 table 3 49 1 +20838585 rs17568778 waist circumference 1e-06 table 3 50 1 +20838585 rs653178 diastolic BP -1 table 5 1 1 +20838585 rs560887 glucose -1 table 5 2 1 +20838585 rs1532624 HDL-cholesterol -1 table 5 3 1 +20838585 rs964184 HDL-cholesterol -1 table 5 4 1 +20838585 rs157580 HDL-cholesterol -1 table 5 5 1 +20838585 rs7395662 HDL-cholesterol -1 table 5 6 1 +20838585 rs471364 HDL-cholesterol -1 table 5 7 1 +20838585 rs185819 height -1 table 5 8 1 +20838585 rs3748069 height -1 table 5 9 1 +20838585 rs710841 height -1 table 5 10 1 +20838585 rs4896582 height -1 table 5 11 1 +20838585 rs967417 height -1 table 5 12 1 +20838585 rs757608 height -1 table 5 13 1 +20838585 rs3760318 height -1 table 5 14 1 +20838585 rs16896068 height -1 table 5 15 1 +20838585 rs6060373 height -1 table 5 16 1 +20838585 rs12740374 LDL-cholesterol -1 table 5 17 1 +20838585 rs12272004 LDL-cholesterol -1 table 5 18 1 +20838585 rs3184504 systolic BP -1 table 5 19 1 +20838585 rs693 total cholesterol -1 table 5 20 1 +20838585 rs2304130 total cholesterol -1 table 5 21 1 +20838585 rs964184 triglycerides 2e-06 table 5 22 1 +20838585 rs780094 triglycerides -1 table 5 23 1 +20838585 rs7819412 triglycerides -1 table 5 24 1 +20838585 rs7138803 weight -1 table 5 25 1 +20921969 rs10458561 risperidone/QTc 0.0 table 3 1 1 +20921969 rs4959235 quetiapine/QTc 0.0 table 3 2 1 +20921969 rs16895513 risperidone/QTc 1e-06 table 3 3 1 +20921969 rs6468544 risperidone/QTc 1e-06 table 3 4 1 +20927387 rs7775698 RBC count 0.0 table 1 1 2 +20927387 rs4895441 RBC count 0.0 table 1 2 2 +20927387 rs9376092 RBC count 0.0 table 1 3 2 +20927387 rs9494145 RBC count 0.0 table 1 4 2 +20927387 rs6569992 RBC count 0.0 table 1 5 2 +20927387 rs7775698 MCV 0.0 table 1 6 2 +20927387 rs4895441 MCV 0.0 table 1 7 2 +20927387 rs9376092 MCV 0.0 table 1 8 2 +20927387 rs9494145 MCV 0.0 table 1 9 2 +20927387 rs6569992 MCV 0.0 table 1 10 2 +20927387 rs17064262 MCV 0.0 table 1 11 2 +20927387 rs855791 MCV 0.0 table 1 12 2 +20927387 rs7775698 MCH 0.0 table 1 13 2 +20927387 rs4895441 MCH 0.0 table 1 14 2 +20927387 rs9376092 MCH 0.0 table 1 15 2 +20927387 rs9494145 MCH 0.0 table 1 16 2 +20927387 rs6569992 MCH 0.0 table 1 17 2 +20927387 rs17064262 MCH 0.0 table 1 18 2 +20927387 rs17342717 MCH 0.0 table 1 19 2 +20927387 rs1800562 MCH 0.0 table 1 20 2 +20927387 rs855791 MCH 0.0 table 1 21 2 +20927387 rs5756504 MCH 0.0 table 1 22 2 +20927387 rs4820268 MCH 0.0 table 1 23 2 +20927387 rs855791 MCHC 0.0 table 1 24 2 +20927387 rs4820268 MCHC 0.0 table 1 25 2 +20927387 rs4895441 MCV 0.0 table 2 2 2 +20927387 rs4895441 MCV 0.0 table 2 2 7 +20927387 rs4895441 MCV 0.0 table 2 3 2 +20927387 rs9402686 MCV 0.0 table 2 3 7 +20927387 rs4895441 RBC count 0.0 table 2 4 2 +20927387 rs9483788 RBC count 0.0 table 2 4 7 +20927387 rs855791 MCV 0.0 table 2 5 2 +20927387 rs855791 MCV 0.0 table 2 5 7 +20927387 rs855791 MCV 0.0 table 2 6 2 +20927387 rs2413450 MCV 0.0 table 2 6 7 +20927387 rs855791 MCH 0.0 table 2 7 2 +20927387 rs855791 MCH 0.0 table 2 7 7 +20927387 rs855791 MCH 0.0 table 2 8 2 +20927387 rs5756506 MCH 0.0 table 2 8 7 +20927387 rs1800562 MCV 1e-06 table 2 9 2 +20927387 rs1800562 MCV 1e-06 table 2 9 7 +20927387 rs1800562 MCV 1e-06 table 2 10 2 +20927387 rs1800562 MCV 1e-06 table 2 10 7 +20927387 rs1800562 MCV 1e-06 table 2 11 2 +20927387 rs1800562 MCV 1e-06 table 2 11 7 +20927387 rs1800562 MCV 1e-06 table 2 12 2 +20927387 rs198846 MCV 1e-06 table 2 12 7 +20927387 rs1800562 MCH 0.0 table 2 13 2 +20927387 rs198846 MCH 0.0 table 2 13 7 +21203500 rs7159888 DG1 0.0 table 0 1 3 +21203500 rs10483776 DG6 0.0 table 0 2 3 +21203500 rs7953249 DG7 0.0 table 0 3 3 +21203500 rs3760776 DG7 0.0 table 0 4 3 +21203500 rs3760776 DG9 0.0 table 0 5 3 +21203500 rs735396 DG11 0.0 table 0 6 3 +21203500 rs3760776 DG12 0.0 table 0 7 3 +21203500 rs3760776 FUCA 0.0 table 0 8 3 +21347282 rs7323893 HDL-C 0.0 table 1 2 1 +21347282 rs937254 HDL-C 1e-06 table 1 3 1 +21347282 rs7801190 Hypertension 0.0 table 1 4 1 +21347282 rs13161895 LDL-C 1e-06 table 1 5 1 +21347282 rs4977574 Coronary heart disease -1 table 2 1 3 +21347282 rs7903146 Type-2 diabetes 0.0 table 2 3 3 +21347282 rs2144300 HDL-C -1 table 2 4 3 +21347282 rs10096633 HDL-C 0.0 table 2 7 3 +21347282 rs3905000 HDL-C -1 table 2 8 3 +21347282 rs13284054 HDL-C -1 table 2 9 3 +21347282 rs174547 HDL-C -1 table 2 10 3 +21347282 rs1800588 HDL-C 0.0 table 2 12 3 +21347282 rs8034802 HDL-C 0.0 table 2 13 3 +21347282 rs3764261 HDL-C 0.0 table 2 14 3 +21347282 rs247617 HDL-C 0.0 table 2 15 3 +21347282 rs255052 HDL-C 0.0 table 2 16 3 +21347282 rs7679 HDL-C -1 table 2 17 3 +21347282 rs10889353 LDL-C -1 table 2 19 3 +21347282 rs12740374 LDL-C 0.0 table 2 21 3 +21347282 rs10493178 LDL-C 0.0 table 2 22 3 +21347282 rs562338 LDL-C 0.0 table 2 23 3 +21347282 rs503662 LDL-C 0.0 table 2 24 3 +21347282 rs6511720 LDL-C 0.0 table 2 25 3 +21347282 rs1160985 LDL-C 0.0 table 2 26 3 +21347282 rs6674681 Coronary heart disease 0.0 table 3 2 1 +21347282 rs6753112 Coronary heart disease 1e-06 table 3 3 1 +21347282 rs8078633 HDL-C 0.0 table 3 4 1 +21347282 rs10218356 Hypertension 1e-06 table 3 5 1 +21347282 rs17441606 LDL-C 0.0 table 3 6 1 +21347282 rs9306885 LDL-C 0.0 table 3 7 1 +21347282 rs6728440 LDL-C 0.0 table 3 8 1 +21347282 rs7560236 LDL-C 0.0 table 3 9 1 +21347282 rs6748157 LDL-C 0.0 table 3 10 1 +21347282 rs7075036 Smoking 1e-06 table 3 11 1 +21347282 rs11088655 Smoking 0.0 table 3 12 1 +21347282 rs16982414 Smoking 1e-06 table 3 13 1 +21386085 rs780093 TG-BP 0.0 table 1 1 1 +21386085 rs780093 WC-TG 0.0 table 1 2 1 +21386085 rs1919128 WC-TG 0.0 table 1 3 1 +21386085 rs13022873 WC-TG 0.0 table 1 4 1 +21386085 rs3749147 WC-TG 0.0 table 1 5 1 +21386085 rs569805 HDLC-GLUC 0.0 table 1 6 1 +21386085 rs2206277 WC-GLUC 0.0 table 1 7 1 +21386085 rs9987289 HDLC-TG 0.0 table 1 8 1 +21386085 rs9987289 HDLC-WC 0.0 table 1 9 1 +21386085 rs295 MetS 0.0 table 1 10 1 +21386085 rs301 HDLC-WC 0.0 table 1 11 1 +21386085 rs13702 HDLC-TG 0.0 table 1 12 1 +21386085 rs15285 TG-BP 0.0 table 1 13 1 +21386085 rs2197089 TG-GLUC 0.0 table 1 14 1 +21386085 rs1441756 BP-HDLC 0.0 table 1 15 1 +21386085 rs2954026 HDLC-TG 0.0 table 1 16 1 +21386085 rs2954033 TG-BP 0.0 table 1 17 1 +21386085 rs1387153 BP-GLUC 0.0 table 1 18 1 +21386085 rs1387153 HDLC-GLUC 0.0 table 1 19 1 +21386085 rs10830956 TG-GLUC 0.0 table 1 20 1 +21386085 rs11825181 TG-BP 0.0 table 1 21 1 +21386085 rs11820589 TG-GLUC 0.0 table 1 22 1 +21386085 rs10790162 HDLC-TG 0.0 table 1 23 1 +21386085 rs10790162 MetS 0.0 table 1 24 1 +21386085 rs10790162 WC-TG 0.0 table 1 25 1 +21386085 rs11823543 TG-BP 0.0 table 1 26 1 +21386085 rs12286037 TG-GLUC 0.0 table 1 27 1 +21386085 rs2075290 HDLC-TG 0.0 table 1 28 1 +21386085 rs2075290 MetS 0.0 table 1 29 1 +21386085 rs2075290 WC-TG 0.0 table 1 30 1 +21386085 rs2266788 HDLC-TG 0.0 table 1 31 1 +21386085 rs2266788 MetS 0.0 table 1 32 1 +21386085 rs2266788 TG-BP 0.0 table 1 33 1 +21386085 rs2266788 WC-TG 0.0 table 1 34 1 +21386085 rs10468017 HDLC-WC 0.0 table 1 35 1 +21386085 rs2043085 HDLC-GLUC 0.0 table 1 36 1 +21386085 rs173539 HDLC-TG 0.0 table 1 37 1 +21386085 rs173539 HDLC-WC 0.0 table 1 38 1 +21386085 rs173539 MetS 0.0 table 1 39 1 +21386085 rs3764261 BP-HDLC 0.0 table 1 40 1 +21386085 rs9939224 HDLC-GLUC 0.0 table 1 41 1 +21386085 rs439401 HDLC-TG 0.0 table 1 42 1 +21483845 rs3811647 Case-Control -1 table 1 11 1 +21483845 rs1800562 Case-Control -1 table 1 19 1 +21483845 rs987710 Case-Control 0.0 table 1 35 1 +21552555 rs17126232 BMI 0.0 table 4 1 2 +21552555 rs17126237 BMI 1e-06 table 4 2 2 +21552555 rs10953454 HIP 1e-06 table 4 3 2 +21552555 rs10216243 HIP 1e-06 table 4 4 2 +21552555 rs17126232 HIP 0.0 table 4 5 2 +21552555 rs17126237 HIP 0.0 table 4 6 2 +21552555 rs9923451 HIP 1e-06 table 4 7 2 +21552555 rs5762430 HIP 1e-06 table 4 8 2 +21552555 rs11088859 Waist 0.0 table 4 9 2 +21552555 rs17126232 Weight 0.0 table 4 10 2 +21552555 rs17126237 Weight 0.0 table 4 11 2 +21552555 rs17081231 Weight 1e-06 table 4 12 2 +21552555 rs7581710 WHR 0.0 table 4 13 2 +21552555 rs2807278 WHR 0.0 table 4 14 2 +21552555 rs11624704 WHR 0.0 table 4 15 2 +21738479 rs17609240 WBC 0.0 table 3 2 4 +21738479 rs4065321 WBC 0.0 table 3 3 4 +21738479 rs4895441 WBC 0.0 table 3 4 4 +21738479 rs3094212 WBC 0.0 table 3 5 4 +21738479 rs445 WBC 0.0 table 3 6 4 +21738479 rs12313946 WBC 0.0 table 3 7 4 +21738479 rs4794822 Neutrophils 0.0 table 3 8 4 +21738479 rs2072910 Neutrophils 0.0 table 3 9 4 +21738479 rs1420101 Eosinophils 0.0 table 3 10 4 +21738479 rs12619285 Eosinophils 0.0 table 3 11 4 +21738479 rs4857855 Eosinophils 0.0 table 3 12 4 +21738479 rs4143832 Eosinophils 0.0 table 3 13 4 +21738479 rs3184504 Eosinophils 0.0 table 3 14 4 +21738480 rs2517524 WBC 0.0 table 2 2 1 +21738480 rs4794822 WBC 0.0 table 2 3 1 +21738480 rs8078723 Neutrophils 0.0 table 2 4 1 +21738480 rs4328821 Basophils 0.0 table 2 5 1 +21738480 rs2524079 Lymphocytes 0.0 table 2 6 1 +21738480 rs11878602 Lymphocytes 0.0 table 2 7 1 +21738480 rs1449263 Monocytes 0.0 table 2 8 1 +21738480 rs9880192 Monocytes 0.0 table 2 9 1 +21738480 rs1991866 Monocytes 0.0 table 2 10 1 +21738480 rs10980800 Monocytes 0.0 table 2 11 1 +21738480 rs2517524 WBC 0.0 table 3 2 1 +21738480 rs4794822 WBC 0.0 table 3 3 1 +21738480 rs8078723 Neutrophils 0.0 table 3 4 1 +21738480 rs4328821 Basophils 0.0 table 3 5 1 +21738480 rs2524079 Lymphocytes 0.0 table 3 6 1 +21738480 rs11878602 Lymphocytes 0.0 table 3 7 1 +21738480 rs1449263 Monocytes 0.0 table 3 8 1 +21738480 rs9880192 Monocytes 0.0 table 3 9 1 +21738480 rs1991866 Monocytes 0.0 table 3 10 1 +21738480 rs10980800 Monocytes 0.0 table 3 11 1 +21738491 rs4687718 QRS -1 table 1 1 2 +21738491 rs4687718 â’0.63 -1 table 1 1 2 +21738491 rs11153730 QRS -1 table 1 2 2 +21738491 rs12143842 QT -1 table 1 3 2 +21738491 rs11970286 QT -1 table 1 4 2 +21738491 rs12296050 QT -1 table 1 5 2 +21931564 rs7072216 TMAu -1 table 3 2 3 +21931564 rs9309473 N-ACu -1 table 3 3 3 +21931564 rs37369 BAIBu -1 table 3 4 3 +21931564 rs6584194 DMAp -1 table 3 5 3 +21931564 rs174547 PC aa C36:3/PC aa C36:4 -1 table 3 6 3 +21931564 rs2014355 C3/C4 -1 table 3 7 3 +21931564 rs9393903 PC aa C40:3/PC aa C42:5 -1 table 3 10 3 +21931564 rs2216405 Gly–PTC/PC ae C38:2 -1 table 3 11 3 +21931564 rs7156144 PC ae C32:1/PC ae C34:1 -1 table 3 12 3 +21931564 rs11158519 PC ae C38:1/PC aa C28:1 -1 table 3 13 3 +21931564 rs168622 SM (OH) C24:1/SM C16:0 -1 table 3 14 3 +21931564 rs7094971 C0 -1 table 3 16 3 +21931564 rs2046813 PC ae C44:5/PC ae C42:5 -1 table 3 17 3 +21931564 rs272889 Val-PTC/C5 -1 table 3 19 3 +21931564 rs541503 Orn-PTC/Ser-PTC -1 table 3 20 3 +21931564 rs174547 PC aa C36:3/PC aa C36:4 0.0 table 4 2 0 +21931564 rs2014355 C3/C4 0.0 table 4 3 0 +21931564 rs9393903 PC aa C40:3/PC aa C42:5 0.0 table 4 6 0 +21931564 rs2216405 Gly-PTC/PC ae C38:2 0.0 table 4 7 0 +21931564 rs7156144 PC ae C32:1/PC ae C34:1 0.0 table 4 8 0 +21931564 rs11158519 PC ae C38:1/PC aa C28:1 0.0 table 4 9 0 +21931564 rs168622 SM (OH) C24:1/SM C16:0 0.0 table 4 10 0 +21931564 rs7094971 C0 0.0 table 4 12 0 +21931564 rs2046813 PC ae C44:5/PC ae C42:5 0.0 table 4 13 0 +21931564 rs272889 Val-PTC/C5 0.0 table 4 15 0 +21931564 rs541503 Orn-PTC/Ser-PTC 0.0 table 4 16 0 +22216198 rs867186 PC 0.0 table 0 1 1 +22216198 rs8119351 PC 0.0 table 0 2 1 +22216198 rs11906160 PC 1e-06 table 0 3 1 +22216198 rs13230047 PC 8e-06 table 0 4 1 +22216198 rs1006973 PC 8e-06 table 0 5 1 +22216198 rs1413885 fPS 0.0 table 0 11 1 +22216198 rs1570868 fPS 0.0 table 0 12 1 +22216198 rs12086738 fPS 3e-06 table 0 13 1 +22216198 rs2137111 fPS 7e-06 table 0 14 1 +22216198 rs13130255 funcPS 3e-06 table 0 21 1 +22216198 rs1401543 Total PS 8e-06 table 0 31 1 +22216198 rs1607504 Total PS 8e-06 table 0 32 1 +22216198 rs2523674 Total PS 1e-05 table 0 33 1 +22291609 rs643434 IL-6 0.0 table 0 2 2 +22291609 rs12034598 ESR 0.0 table 0 3 2 +22291609 rs4910742 ESR 0.0 table 0 4 2 +22291609 rs12075 MCP-1 0.0 table 0 5 2 +22291609 rs3026968 MCP-1 0.0 table 0 6 2 +22291609 rs1341665 hsCRP 0.0 table 0 7 2 +22291609 rs3845624 hsCRP 0.0 table 0 8 2 +22291609 rs657152 IL-6 0.0 table 1 1 2 +22291609 rs643434 IL-6 0.0 table 1 1 9 +22291609 rs4129267 IL-6 0.0 table 1 2 2 +22291609 rs12567990 ESR 0.0 table 1 3 2 +22291609 rs12034598 ESR 0.0 table 1 3 9 +22291609 rs4910742 ESR 0.0 table 1 4 2 +22291609 rs10903129 ESR 0.0 table 1 5 2 +22291609 rs11829037 ESR 0.0 table 1 6 2 +22291609 rs12075 MCP-1 0.0 table 1 7 2 +22291609 rs17141006 MCP-1 0.0 table 1 8 2 +22291609 rs3918357 MCP-1 0.0 table 1 8 9 +22291609 rs1205 hsCRP 0.0 table 1 9 2 +22291609 rs1341665 hsCRP 0.0 table 1 9 9 +22291609 rs3093077 hsCRP 0.0 table 1 10 2 +22291609 rs3845624 hsCRP 0.0 table 1 10 9 +22291609 rs11829037 hsCRP 0.0 table 1 11 2 +22291609 rs2259816 hsCRP 5e-06 table 1 12 2 +22291609 rs4420638 hsCRP 0.0 table 1 13 2 +22291609 rs113459440 hsCRP 0.0 table 1 14 2 +22509378 rs13202860 Arousal 0.0 table 0 1 1 +22509378 rs1876525 Arousal 0.0 table 0 2 1 +22509378 rs13209281 Arousal 1e-06 table 0 3 1 +22509378 rs4820255 Overall FSD 2e-06 table 0 4 1 +22509378 rs4821535 Overall FSD 2e-06 table 0 5 1 +22509378 rs2284024 Overall FSD 2e-06 table 0 6 1 +22509378 rs5750311 Overall FSD 2e-06 table 0 7 1 +22509378 rs739031 Overall FSD 2e-06 table 0 8 1 +22509378 rs4821536 Overall FSD 3e-06 table 0 9 1 +22509378 rs2370759 Lubrication 2e-06 table 0 10 1 +22509378 rs11594963 Lubrication 2e-06 table 0 11 1 +22509378 rs11599044 Lubrication 2e-06 table 0 12 1 +22509378 rs10508773 Lubrication 2e-06 table 0 13 1 +22509378 rs16933243 Lubrication 3e-06 table 0 14 1 +22509378 rs11008865 Lubrication 3e-06 table 0 15 1 +22558069 rs4985726 TP 0.0 table 1 2 1 +22558069 rs1260326 ALB 0.0 table 1 3 1 +22558069 rs4985726 NAP 0.0 table 1 4 1 +22558069 rs3803800 NAP 0.0 table 1 5 1 +22558069 rs11552708 NAP 0.0 table 1 6 1 +22558069 rs10007186 NAP 0.0 table 1 7 1 +22589738 rs984222 Men -1 table 2 2 1 +22589738 rs1011731 Men -1 table 2 3 1 +22589738 rs4846567 Men -1 table 2 4 1 +22589738 rs10195252 Men -1 table 2 5 1 +22589738 rs6784615 Men -1 table 2 6 1 +22589738 rs6795735 Men -1 table 2 7 1 +22589738 rs6861681 Men -1 table 2 8 1 +22589738 rs1294421 Men -1 table 2 9 1 +22589738 rs6905288 Men -1 table 2 10 1 +22589738 rs9491696 Men -1 table 2 11 1 +22589738 rs1055144 Men -1 table 2 12 1 +22589738 rs718314 Men -1 table 2 13 1 +22589738 rs1443512 Men -1 table 2 14 1 +22589738 rs4823006 Men -1 table 2 15 1 +22589738 rs984222 Women -1 table 2 16 1 +22589738 rs1011731 Women -1 table 2 17 1 +22589738 rs4846567 Women -1 table 2 18 1 +22589738 rs10195252 Women -1 table 2 19 1 +22589738 rs6784615 Women -1 table 2 20 1 +22589738 rs6795735 Women -1 table 2 21 1 +22589738 rs6861681 Women -1 table 2 22 1 +22589738 rs1294421 Women -1 table 2 23 1 +22589738 rs6905288 Women -1 table 2 24 1 +22589738 rs9491696 Women -1 table 2 25 1 +22589738 rs1055144 Women -1 table 2 26 1 +22589738 rs718314 Women -1 table 2 27 1 +22589738 rs1443512 Women -1 table 2 28 1 +22589738 rs4823006 Women -1 table 2 29 1 +22589738 rs984222 Overall -1 table 2 30 1 +22589738 rs1011731 Overall -1 table 2 31 1 +22589738 rs4846567 Overall -1 table 2 32 1 +22589738 rs10195252 Overall -1 table 2 33 1 +22589738 rs6784615 Overall -1 table 2 34 1 +22589738 rs6795735 Overall -1 table 2 35 1 +22589738 rs6861681 Overall -1 table 2 36 1 +22589738 rs1294421 Overall -1 table 2 37 1 +22589738 rs6905288 Overall -1 table 2 38 1 +22589738 rs9491696 Overall -1 table 2 39 1 +22589738 rs1055144 Overall -1 table 2 40 1 +22589738 rs718314 Overall -1 table 2 41 1 +22589738 rs1443512 Overall -1 table 2 42 1 +22589738 rs4823006 Overall -1 table 2 43 1 +22832964 rs2036527 CPD 0.0 table 1 1 1 +22832964 rs667282 CPD 0.0 table 1 2 1 +22832964 rs3101457 CPD 0.0 table 1 3 1 +22832964 rs938682 CPD 0.0 table 1 4 1 +22832964 rs547843 CPD 1e-06 table 1 5 1 +22832964 rs3813570 CPD 1e-06 table 1 6 1 +22832964 rs1678618 AOI 1e-06 table 1 7 1 +22832964 rs1245577 AOI 1e-06 table 1 8 1 +22832964 rs1612028 AOI 1e-06 table 1 9 1 +23028342 rs12437854 ESRD 0.0 table 1 2 0 +23028342 rs7583877 ESRD 0.0 table 1 3 0 +23028342 rs7588550 T1DN 0.0 table 1 4 0 +23118974 rs1667394 Eye C' 0.0 table 1 2 1 +23118974 rs702477 Eye C' 0.0 table 1 3 1 +23118974 rs8039195 Eye C' 0.0 table 1 4 1 +23118974 rs886890 Eye C' 6e-06 table 1 5 1 +23118974 rs1635168 Eye C' 0.0 table 1 6 1 +23118974 rs9809315 Skin M 0.0 table 1 7 1 +23118974 rs2033739 Skin M 5e-06 table 1 8 1 +23118974 rs262825 Hair M 8e-06 table 1 9 1 +23251661 rs1056513 Weight (kg) 0.0 table 0 1 0 +23251661 rs1056513 BMI (kg/m 2 ) 8e-06 table 0 2 0 +23251661 rs1056513 Fat mass (kg) 0.0 table 0 3 0 +23251661 rs1056513 Trunk fat mass (kg) 0.0 table 0 4 0 +23251661 rs1056513 Fat free mass (kg) 0.0 table 0 5 0 +23251661 rs1056513 Hip circumference (cm) 2e-06 table 0 6 0 +23251661 rs494558 Weight z-score change (SD/y) 0.0 table 0 7 0 +23251661 rs40357 Height change (cm/y) 0.0 table 0 8 0 +23251661 rs3733402 IGF-1 free (ng/mL) -1 table 1 1 0 +23251661 rs11974269 Urinary creatinine(mmol/d) 0.0 table 1 2 0 +23251661 rs7030241 TSH (µIU/mL) 0.0 table 1 3 0 +23251661 rs10830963 Glucose (mg/dL) 0.0 table 1 4 0 +23251661 rs3741298 Triglycerides(mg/dL) 0.0 table 1 5 0 +23251661 rs2266788 Triglycerides(mg/dL) 0.0 table 1 6 0 +23251661 rs10131141 Urinary nitrogen (g/d) 0.0 table 1 7 0 +23251661 rs3783637 Urinary freedopamine:creatinine 0.0 table 1 8 0 +23251661 rs61744862 IGFBP-3 (ng/mL) 0.0 table 1 9 0 +23251661 rs6044834 Total antioxidants(mM) 0.0 table 1 10 0 +23251661 rs863002 MCP-1 (pg/mL) 0.0 table 2 1 0 +23251661 rs12075 MCP-1 (pg/mL) 0.0 table 2 2 0 +23251661 rs73175262 MCP-1 (pg/mL) 0.0 table 2 3 0 +23251661 rs7645716 MCP-1 (pg/mL) 0.0 table 2 4 0 +23251661 rs79509430 MCP-1 (pg/mL) 0.0 table 2 5 0 +23251661 rs657152 IL-6 (pg/mL) 0.0 table 2 6 0 +23251661 rs28461806 MCP-1 (pg/mL) 0.0 table 2 7 0 +23251661 rs16933006 Light activity (min/d) 0.0 table 3 1 0 +23251661 rs17104363 Dinner intake, adjEER (kcal) 0.0 table 3 2 0 +23251661 rs8037818 Sleep duration (min/d) 0.0 table 3 3 0 +23251661 rs8040868 Sleep energyexpenditure adjweight (kcal/d) 0.0 table 3 4 0 +23251661 rs12104221 Total energyexpenditure adjweight (kcal/d) 0.0 table 3 5 0 +23251661 rs6025590 Sedentary&lightactivity (min/d) 0.0 table 3 6 0 +23251661 rs2823615 Sleep RQ 0.0 table 3 7 0 +23408906 rs753760 TSH -1 table 5 1 0 +23408906 rs2983521 TSH -1 table 5 1 5 +23408906 rs9347083 TSH -1 table 5 1 5 +23408906 rs9472138 TSH/FT4 -1 table 5 2 0 +23408906 rs11755845 TSH/FT4 -1 table 5 2 0 +23408906 rs9472138 TSH/FT4 -1 table 5 2 5 +23408906 rs11755845 TSH/FT4 -1 table 5 2 5 +23408906 rs13015993 TSH -1 table 5 3 0 +23408906 rs737308 TSH -1 table 5 3 5 +23408906 rs9915657 TSH -1 table 5 4 0 +23408906 rs334699 TSH -1 table 5 5 0 +23408906 rs334725 TSH -1 table 5 5 5 +23408906 rs10519227 TSH -1 table 5 6 0 +23408906 rs4338740 TSH -1 table 5 6 5 +23408906 rs17723470 TSH -1 table 5 7 0 +23408906 rs7128207 TSH -1 table 5 7 5 +23408906 rs17776563 TSH -1 table 5 8 0 +23408906 rs4804416 TSH -1 table 5 9 0 +23408906 rs10420008 TSH -1 table 5 9 5 +23408906 rs657152 TSH -1 table 5 10 0 +23408906 rs11624776 TSH -1 table 5 11 0 +23408906 rs7825175 TSH -1 table 5 12 0 +23408906 rs2439302 TSH -1 table 5 12 5 +23408906 rs1537424 TSH -1 table 5 13 0 +23408906 rs944289 TSH -1 table 5 13 5 +23408906 rs9497965 TSH -1 table 5 14 0 +23408906 rs1571583 TSH -1 table 5 15 0 +23408906 rs7860634 FT4/TSH -1 table 5 16 0 +23408906 rs7045138 FT4 -1 table 5 17 0 +23408906 rs1443434 FT4 -1 table 5 17 5 +23408906 rs965513 FT4 -1 table 5 17 5 +23408906 rs7850258 FT4 -1 table 5 17 5 +23408906 rs716822 FT4 -1 table 5 18 0 +23408906 rs7240777 FT4 -1 table 5 19 0 +23408906 rs6499766 FT4 -1 table 5 20 0 +23696099 rs7120391 MCHC 0.0 table 1 2 2 +23696099 rs9924561 MCV 0.0 table 1 3 2 +23696099 rs9924561 MCH 0.0 table 1 4 2 +23696099 rs9924561 MCHC 0.0 table 1 5 2 +23696099 rs1050828 RBC count 0.0 table 1 6 2 +23696099 rs1050828 MCV 0.0 table 1 7 2 +23696099 rs1050828 MCH 0.0 table 1 8 2 +23704328 rs17101923 psL-psR: left-to-right palpebrale superius distance -1 table 1 2 1 +23704328 rs17101923 piL-piR: left-to-right palpebrale inferius distance -1 table 1 3 1 +23704328 rs17101923 exR.yz: distance of the right exocanthion from the YZ plane -1 table 1 4 1 +23704328 rs17101923 enL.yz: distance of the left endocanthion from the YZ plane -1 table 1 5 1 +23704328 rs17101923 enL-enR: left-to-right endocanthion distance -1 table 1 6 1 +23704328 rs17101923 exL-exR: left-to-right exocanthion distance -1 table 1 7 1 +23704328 rs17101923 prn-alL: pronasale to left alare distance -1 table 1 9 1 +23704328 rs7924176 sn-alL: subnasale to left alare -1 table 1 10 1 +23704328 rs17101923 alL-alR: left-to-right alare distance -1 table 1 11 1 +23704328 rs997154 g-men: glabella to mid-endocanthion distance -1 table 1 13 1 +23754948 rs6717858 WHRadjBMI 0.0 table 0 3 0 +23754948 rs2820443 WHRadjBMI 0.0 table 0 4 0 +23754948 rs1358980 WHRadjBMI 0.0 table 0 5 0 +23754948 rs11743303 WCadjBMI 0.0 table 0 6 0 +23754948 rs2371767 WHRadjBMI 0.0 table 0 7 0 +23754948 rs10478424 WHRadjBMI 0.0 table 0 8 0 +23754948 rs4684854 WHRadjBMI 0.0 table 0 9 0 +23754948 rs6717858 WHRADJ [31] 0.0 table 1 1 0 +23754948 rs10195252 WHRADJ [31] 0.0 table 1 1 8 +23754948 rs2820443 HEIGHT [25] ; WHRADJ [31] 0.0 table 1 2 0 +23754948 rs11118346 HEIGHT [25] ; WHRADJ [31] 0.0 table 1 2 8 +23754948 rs4846567 HEIGHT [25] ; WHRADJ [31] 0.0 table 1 2 8 +23754948 rs1358980 WHRADJ [31] 0.0 table 1 3 0 +23754948 rs6905288 WHRADJ [31] 0.0 table 1 3 8 +23754948 rs2371767 WHRADJ [31] 2e-06 table 1 5 0 +23754948 rs6795735 WHRADJ [31] 2e-06 table 1 5 8 +23836780 rs4656461 Glaucoma -1 table 0 1 1 +23836780 rs3213787 Glaucoma -1 table 0 3 1 +23836780 rs735860 Glaucoma -1 table 0 4 1 +23836780 rs4977756 Glaucoma -1 table 0 6 1 +23836780 rs3825942 Glaucoma (exfoliation) -1 table 0 7 1 +23836780 rs11656696 IOP -1 table 0 8 1 +23935956 rs1155865 MCHC 0.0 table 0 1 1 +23935956 rs1887582 MCHC 0.0 table 0 2 1 +23966867 rs2075064 WC_BMI_pooled 0.0 table 1 2 1 +23966867 rs6931262 WHR_BMI_pooled 0.0 table 1 3 1 +23966867 rs6867983 WC_men 0.0 table 1 4 1 +23966867 rs7601155 WC_pooled 0.0 table 1 5 1 +23966867 rs10894604 WHR_BMI_pooled 0.0 table 1 6 1 +23966867 rs17213965 WHR_BMI_Men 0.0 table 1 7 1 +23966867 rs2570467 WC_Men 0.0 table 1 8 1 +23966867 rs11777345 WHR_BMI_men 0.0 table 1 9 1 +23966867 rs4730779 WC_BMI_men 0.0 table 1 10 1 +23966867 rs6739392 WHR_BMI_women 1e-06 table 1 11 1 +23966867 rs1345301 WC_Men 0.0 table 1 12 1 +23966867 rs16830366 WC_women 0.0 table 1 13 1 +23966867 rs11961438 WC_women 1e-06 table 1 14 1 +23966867 rs7672174 WC_pooled 0.0 table 1 15 1 +23966867 rs4292018 WHR_pooled 1e-06 table 1 16 1 +23966867 rs1355187 WC_pooled 0.0 table 1 17 1 +23966867 rs2907512 WC_men 1e-06 table 1 18 1 +23966867 rs12777819 WC_BMI_pooled 0.0 table 1 19 1 +23966867 rs11197515 WHR_men 2e-06 table 1 20 1 +23966867 rs214679 WHR_pooled 1e-06 table 1 21 1 +23966867 rs17134146 WHR_pooled 0.0 table 1 22 1 +23966867 rs2881189 WC_BMI_pooled 0.0 table 1 23 1 +23966867 rs2548774 WC_BMI_men 1e-06 table 1 24 1 +23966867 rs2958759 WC_pooled 1e-06 table 1 25 1 +23966867 rs7296740 WHR_men 4e-06 table 1 26 1 +24324551 rs4149018 Cardio 0.0 table 0 1 2 +24324551 rs12582717 Cardio 0.0 table 0 2 2 +24324551 rs2645430 EF 0.0 table 0 3 2 +24324551 rs1497042 EF 0.0 table 0 4 2 +24324551 rs2252567 EF 1e-06 table 0 5 2 +24324551 rs111981433 EF 1e-06 table 0 6 2 +24324551 rs807029 EF 0.0 table 0 7 2 +24324551 rs13078828 EIA 0.0 table 0 8 2 +24324551 rs57302454 PCR 1e-06 table 0 9 2 +24324551 rs7013781 PCR 1e-06 table 0 10 2 +24324551 rs2054148 PCR 1e-06 table 0 11 2 +24324551 rs10955961 PCR 0.0 table 0 12 2 +24324551 rs10955962 PCR 0.0 table 0 13 2 +24324551 rs2034842 PCR 1e-06 table 0 14 2 +24324551 rs10808508 PCR 0.0 table 0 15 2 +24324551 rs7387094 PCR 0.0 table 0 16 2 +24324551 rs7387373 PCR 1e-06 table 0 17 2 +24324551 rs56159702 PCR 0.0 table 0 18 2 +24324551 rs58829748 PCR 1e-06 table 0 19 2 +24324551 rs6989074 PCR 0.0 table 0 20 2 +24324551 rs4408325 PCR 0.0 table 0 21 2 +24324551 rs116303449 PCR 1e-06 table 0 22 2 +24324551 rs56988800 PR 0.0 table 0 23 2 +24324551 rs79523511 PR 0.0 table 0 24 2 +24324551 rs76090503 PR 0.0 table 0 25 2 +24324551 rs9815195 PR 1e-06 table 0 26 2 +24324551 rs114133078 PR 0.0 table 0 27 2 +24324551 rs61018535 PR 0.0 table 0 28 2 +24324551 rs59623110 PR 0.0 table 0 29 2 +24324551 rs73276602 PR 0.0 table 0 30 2 +24324551 rs114137957 PR 1e-06 table 0 31 2 +24324551 rs115744676 PR 0.0 table 0 32 2 +24324551 rs116187617 PR 0.0 table 0 33 2 +24324551 rs75609241 PR 0.0 table 0 34 2 +24324551 rs78852656 PR 0.0 table 0 35 2 +24324551 rs59403466 PR 1e-06 table 0 36 2 +24324551 rs117364231 PR 0.0 table 0 37 2 +24324551 rs75041531 PR 1e-06 table 0 38 2 +24324551 rs191392302 PR 0.0 table 0 39 2 +24324551 rs11664027 PR 0.0 table 0 40 2 +24324551 rs8087073 PR 0.0 table 0 41 2 +24324551 rs3176130 PR 0.0 table 0 42 2 +24324551 rs182503338 QRS 1e-06 table 0 43 2 +24324551 rs72786268 QRS 0.0 table 0 44 2 +24324551 rs10769783 QRS 0.0 table 0 45 2 +24324551 rs2274511 QRS 1e-06 table 0 46 2 +24347629 rs733048 PD1 1e-06 table 0 1 2 +24347629 rs11713199 PD2 7e-06 table 0 11 2 +24347629 rs12630254 PD2 7e-06 table 0 12 1 +24347629 rs12630931 PD2 6e-06 table 0 13 1 +24376456 rs648425 SBP 1e-06 table 2 2 2 +24376456 rs17669622 MAP 1e-06 table 2 3 2 +24376456 rs16849553 MAP 1e-06 table 2 4 2 +24376456 rs13008299 DBP 0.0 table 2 5 2 +24376456 rs4953404 PP 1e-06 table 2 6 2 +24376456 rs9874923 MAP 0.0 table 2 8 2 +24376456 rs3852160 MAP 0.0 table 2 9 2 +24376456 rs4537030 MAP 1e-06 table 2 10 2 +24376456 rs7791745 MAP 1e-06 table 2 11 2 +24376456 rs11766519 PP 0.0 table 2 12 2 +24376456 rs10826334 MAP 1e-06 table 2 13 2 +24376456 rs12773465 MAP 0.0 table 2 16 2 +24376456 rs7902871 DBP 1e-06 table 2 17 2 +24376456 rs7116456 SBP 0.0 table 2 18 2 +24376456 rs12292796 PP 0.0 table 2 19 2 +24376456 rs10841530 SBP 1e-06 table 2 20 2 +24376456 rs991427 SBP 0.0 table 2 21 2 +24376456 rs4494364 SBP 0.0 table 2 22 2 +24376456 rs9318552 DBP 0.0 table 2 23 2 +24376456 rs2735413 SBP 1e-06 table 2 24 2 +24376456 rs16963349 SBP 0.0 table 2 25 2 +24376456 rs1943940 DBP 1e-06 table 2 26 2 +24376456 rs2410182 SBP 1e-06 table 2 28 2 +24376456 rs2837253 SBP 1e-06 table 2 29 2 +24376456 rs648425 Blood pressure -1 table 3 2 2 +24376456 rs669733 Blood pressure -1 table 3 2 4 +24376456 rs10518590 Blood pressure 3e-06 table 3 3 4 +24376456 rs17669622 Cardiac hypertrophy 0.0 table 3 4 2 +24376456 rs12757165 Cardiac hypertrophy 0.0 table 3 4 4 +24376456 rs4953404 Coronary heart disease 2e-06 table 3 8 2 +24376456 rs2346177 Coronary heart disease 2e-06 table 3 8 4 +24376456 rs1523351 Coronary artery disease 1e-06 table 3 10 4 +24376456 rs3852160 QT interval 1e-06 table 3 11 2 +24376456 rs7728043 QT interval 1e-06 table 3 11 4 +24376456 rs2937785 Hypertension 9e-06 table 3 12 4 +24376456 rs10486744 Blood pressure -1 table 3 14 4 +24376456 rs10826334 Blood pressure 4e-06 table 3 15 2 +24376456 rs10509096 Blood pressure 4e-06 table 3 15 4 +24376456 rs12356193 Uric acid levels 0.0 table 3 16 4 +24376456 rs7094971 Carnitine 0.0 table 3 17 4 +24376456 rs6479671 Alcohol drinking -1 table 3 18 4 +24376456 rs1171614 Urate levels 0.0 table 3 19 4 +24376456 rs12773465 Cystathionine 6e-06 table 3 20 2 +24376456 rs3824789 Cystathionine 6e-06 table 3 20 4 +24376456 rs7902871 Total cysteine 7e-06 table 3 21 2 +24376456 rs12767760 Total cysteine 7e-06 table 3 21 4 +24376456 rs2275588 Blood pressure 0.0 table 3 22 4 +24376456 rs10500968 Echocardiography 1e-06 table 3 24 4 +24376456 rs10841530 Baseline blood pressure 9e-06 table 3 25 2 +24376456 rs10841397 Baseline blood pressure 9e-06 table 3 25 4 +24376456 rs10770612 Aortic root size 0.0 table 3 26 4 +24376456 rs1348582 QT interval 1e-06 table 3 27 4 +24376456 rs991427 Sudden cardiac arrest 5e-06 table 3 28 2 +24376456 rs10777317 Sudden cardiac arrest 5e-06 table 3 28 4 +24376456 rs4494364 Sudden cardiac arrest -1 table 3 29 2 +24376456 rs2735413 Folate 7e-06 table 3 30 2 +24376456 rs4888671 Folate 7e-06 table 3 30 4 +24376456 rs2059238 Cardiac structure and function 3e-06 table 3 31 4 +24376456 rs2278075 Cardiovascular disease 0.0 table 3 32 4 +24376456 rs16963349 Blood pressure 0.0 table 3 33 2 +24376456 rs3096277 Blood pressure 0.0 table 3 33 4 +24376456 rs1943940 Hypertension 1e-05 table 3 34 2 +24376456 rs4892138 Hypertension 1e-05 table 3 34 4 +24376456 rs2410182 Coronary heart disease 9e-06 table 3 36 2 +24376456 rs1735151 Coronary heart disease 9e-06 table 3 36 4 +24379826 rs938553 Body weight 5e-06 table 2 1 1 +24379826 rs6832439 Total antioxidant status 1e-06 table 2 12 1 +24379826 rs737267 Total antioxidant status 1e-06 table 2 13 1 +24386095 rs11207995 TC 0.0 table 1 2 1 +24386095 rs10045497 TC 0.0 table 1 3 1 +24386095 rs10045497 LDL 0.0 table 1 4 1 +24386095 rs328 TG 0.0 table 1 5 1 +24386095 rs328 HDL 0.0 table 1 6 1 +24386095 rs507666 TC 0.0 table 1 7 1 +24386095 rs507666 LDL 0.0 table 1 8 1 +24386095 rs651821 TG 0.0 table 1 9 1 +24386095 rs2043085 HDL 0.0 table 1 10 1 +24386095 rs1160985 LDL 0.0 table 1 11 1 +24386095 rs3764261 HDL 0.0 table 1 12 1 +24386095 rs599839 LDL 0.0 table 2 2 2 +24386095 rs646776 LDL 0.0 table 2 3 2 +24386095 rs12740374 LDL 0.0 table 2 4 2 +24386095 rs673548 HDL 1e-06 table 2 5 2 +24386095 rs693 HDL 0.0 table 2 6 2 +24386095 rs6754295 HDL 0.0 table 2 7 2 +24586186 rs11884776 N-acetylated compounds 0.0 table 0 2 1 +24586186 rs3764913 Unknown 0.0 table 0 3 1 +24586186 rs37370 3-Aminoisobutyrate 0.0 table 0 4 1 +24586186 rs4921914 Unknown 0.0 table 0 5 1 +24586186 rs579459 Unknown 0.0 table 0 6 1 +24586186 rs2147896 Trimethylamine 0.0 table 0 7 1 +24586186 rs4345897 Unknown 0.0 table 0 8 1 +24586186 rs3916 Unknown 0.0 table 0 9 1 +24586186 rs7314056 2-Hydroxyisobutyrate 0.0 table 0 10 1 +24586186 rs8101881 Lysine 0.0 table 0 11 1 +24586186 rs492602 Fucose 0.0 table 0 12 1 +24892410 rs6556114 Daytime PP -1 table 1 1 1 +24892410 rs897669 Daytime PP -1 table 1 2 1 +24892410 rs2527083 Daytime PP -1 table 1 3 1 +24892410 rs505299 Daytime PP -1 table 1 4 1 +24892410 rs9564376 Daytime PP -1 table 1 5 1 +24892410 rs6696698 Nighttime PP -1 table 1 6 1 +24892410 rs17039365 Nighttime PP -1 table 1 7 1 +24892410 rs17338512 Nighttime PP -1 table 1 8 1 +24892410 rs7596980 Nighttime PP -1 table 1 9 1 +24892410 rs897876 Nighttime PP -1 table 1 10 1 +24892410 rs1019102 Nighttime PP -1 table 1 11 1 +24892410 rs17513926 Nighttime PP -1 table 1 12 1 +24903457 rs13390641 SBP -1 table 1 2 2 +24945404 rs3765350 TBLH-BMD 0.0 table 1 2 1 +24945404 rs6726821 TBLH-BMD 0.0 table 1 3 1 +24945404 rs7776725 TBLH-BMD 0.0 table 1 4 1 +24945404 rs7466269 TBLH-BMD 0.0 table 1 5 1 +24945404 rs4420311 TBLH-BMD 0.0 table 1 6 1 +24945404 rs17536328 TBLH-BMD 0.0 table 1 7 1 +24945404 rs754388 TBLH-BMD 0.0 table 1 8 1 +24945404 rs3765350 LL-BMD 0.0 table 1 9 1 +24945404 rs2908004 LL-BMD 0.0 table 1 10 1 +24945404 rs7466269 LL-BMD 0.0 table 1 11 1 +24945404 rs4420311 LL-BMD 0.0 table 1 12 1 +24945404 rs754388 LL-BMD 0.0 table 1 13 1 +24945404 rs2235529 UL-BMD 0.0 table 1 14 1 +24945404 rs6726821 UL-BMD 0.0 table 1 15 1 +24945404 rs1262476 UL-BMD 0.0 table 1 16 1 +24945404 rs798943 UL-BMD 0.0 table 1 17 1 +24945404 rs9525638 UL-BMD 0.0 table 1 18 1 +24945404 rs3920498 SK-BMD 0.0 table 1 19 1 +24945404 rs2130604 SK-BMD 0.0 table 1 20 1 +24945404 rs3012465 SK-BMD 0.0 table 1 21 1 +24945404 rs13223036 SK-BMD 0.0 table 1 22 1 +24945404 rs2450083 SK-BMD 0.0 table 1 23 1 +24945404 rs10835187 SK-BMD 0.0 table 1 24 1 +24945404 rs12272917 SK-BMD 0.0 table 1 25 1 +24945404 rs884205 SK-BMD 0.0 table 1 26 1 +25087078 rs6732655 All epilepsy 0.0 table 1 1 0 +25087078 rs28498976 All epilepsy 0.0 table 1 2 0 +25087078 rs111577701 All epilepsy 0.0 table 1 3 0 +25087078 rs535066 All epilepsy 0.0 table 1 4 0 +25087078 rs2947349 GGE 0.0 table 1 5 0 +25087078 rs1939012 GGE 0.0 table 1 6 0 +25087078 rs1044352 GGE 0.0 table 1 7 0 +25087078 rs55670112 GGE 0.0 table 1 8 0 +25087078 rs12987787 Focal epilepsy 0.0 table 1 9 0 +25133637 rs955423 BMI -1 table 0 1 3 +25133637 rs3096490 BMI -1 table 0 2 3 +25133637 rs1392280 BMI -1 table 0 3 3 +25133637 rs1426654 BMI -1 table 0 4 3 +25133637 rs794149 BMI -1 table 0 5 3 +25133637 rs3096483 BMI -1 table 0 6 3 +25133637 rs10041997 Change in BMI -1 table 0 7 3 +25133637 rs1347155 Change in BMI -1 table 0 8 3 +25133637 rs7565158 Change in BMI -1 table 0 9 3 +25133637 rs8042988 Height -1 table 0 10 3 +25133637 rs4898878 Height -1 table 0 11 3 +25133637 rs12882679 Underweight -1 table 0 12 3 +25133637 rs1475010 Overweight -1 table 0 13 3 +25133637 rs8181969 Overweight -1 table 0 14 3 +25133637 rs1426654 BMI: Female -1 table 1 2 3 +25133637 rs1331623 Height: Female -1 table 1 4 3 +25133637 rs6833159 Underweight: Male -1 table 1 5 3 +25133637 rs12101726 Overweight: Male -1 table 1 7 3 +25133637 rs1161397 Overweight: Male -1 table 1 8 3 +25133637 rs280325 Overweight: Male -1 table 1 9 3 +25133637 rs6447650 Change in BMI: Male -1 table 1 11 3 +25133637 rs347313 Change in BMI: Female -1 table 1 12 3 +25133637 rs347306 Change in BMI: Female -1 table 1 13 3 +25133637 rs1347155 Change in BMI: Female -1 table 1 14 3 +25133637 rs347282 Change in BMI: Female -1 table 1 15 3 +25188341 rs6857 Primary (Case-Control) 0.0 table 1 1 1 +25188341 rs6857 Complete (Case-Control) 0.0 table 1 3 1 +25188341 rs6857 NFT Braak (Ordinal I) 0.0 table 1 5 1 +25188341 rs6857 NFT Braak (Ordinal II) 0.0 table 1 6 1 +25188341 rs6857 Neuritic Plaque (Ordinal) 0.0 table 1 7 1 +25188341 rs6857 Neuritic Plaque (Case-Control) 0.0 table 1 8 1 +25188341 rs62341097 Neuritic Plaque (Case-Control) 0.0 table 1 9 1 +25188341 rs429358 Lewy Body (Ordinal I) 0.0 table 1 12 1 +25188341 rs429358 Lewy Body (Case-Control) 0.0 table 1 13 1 +25188341 rs429358 Lewy Body (Ordinal II) 0.0 table 1 14 1 +25188341 rs6857 CAA (Case-Control) 0.0 table 1 16 1 +25340798 rs4968782 ACE 0.0 table 1 1 1 +25340798 rs4459609 ACE 0.0 table 1 2 1 +25340798 rs4316 ACE 0.0 table 1 3 1 +25340798 rs4343 ACE 0.0 table 1 4 1 +25340798 rs2228467 CCL2 0.0 table 1 5 1 +25340798 rs6808835 CCL4 0.0 table 1 6 1 +25340798 rs6762266 CCL4 0.0 table 1 7 1 +25340798 rs11575821 CCL4 0.0 table 1 8 1 +25340798 rs113263161 CCL4 0.0 table 1 9 1 +25340798 rs11574428 CCL4 0.0 table 1 10 1 +25340798 rs3092960 CCL4 0.0 table 1 11 1 +25340798 rs6441977 CCL4 0.0 table 1 12 1 +25340798 rs61812598 IL6R 0.0 table 1 13 1 +25340798 rs4845622 IL6R 0.0 table 1 14 1 +25340798 rs2228145 IL6R 0.0 table 1 15 1 +25340798 rs4129267 IL6R 0.0 table 1 16 1 +25340798 rs3811448 IL6R 0.0 table 1 17 1 +25340798 rs2229238 IL6R 0.0 table 1 18 1 +25340798 rs573521 MMP3 0.0 table 1 19 1 +25340798 rs645419 MMP3 0.0 table 1 20 1 +25340798 rs679620 MMP3 0.0 table 1 21 1 +25340798 rs7926920 MMP3 0.0 table 1 22 1 +25340798 rs11225434 MMP3 0.0 table 1 23 1 +25340798 rs948399 MMP3 0.0 table 1 24 1 +25340798 rs495366 MMP3 0.0 table 1 25 1 +25340798 rs650108 MMP3 0.0 table 1 26 1 +25340798 rs603050 MMP3 0.0 table 1 27 1 +25340798 rs4845622 IL6R 0.0 table 2 1 1 +25340798 rs61812598 IL6R 0.0 table 2 2 1 +25340798 rs4129267 IL6R 0.0 table 2 3 1 +25340798 rs2228145 IL6R 0.0 table 2 4 1 +25340798 rs2229238 IL6R 0.0 table 2 5 1 +25340798 rs3811448 IL6R 0.0 table 2 6 1 +25340798 rs2228467 CCL2 0.0 table 2 7 1 +25340798 rs3092960 CCL4 1e-06 table 2 8 1 +25340798 rs11575821 CCL4 0.0 table 2 9 1 +25340798 rs113263161 CCL4 1e-06 table 2 10 1 +25340798 rs11574428 CCL4 0.0 table 2 11 1 +25340798 rs6808835 CCL4 0.0 table 2 12 1 +25340798 rs6441977 CCL4 1e-06 table 2 13 1 +25340798 rs6762266 CCL4 0.0 table 2 14 1 +25340798 rs603050 MMP3 0.0 table 2 15 1 +25340798 rs11225434 MMP3 0.0 table 2 16 1 +25340798 rs495366 MMP3 0.0 table 2 17 1 +25340798 rs7926920 MMP3 0.0 table 2 18 1 +25340798 rs650108 MMP3 0.0 table 2 19 1 +25340798 rs679620 MMP3 0.0 table 2 20 1 +25340798 rs645419 MMP3 0.0 table 2 21 1 +25340798 rs573521 MMP3 0.0 table 2 22 1 +25340798 rs948399 MMP3 0.0 table 2 23 1 +25340798 rs4968782 ACE 0.0 table 2 24 1 +25340798 rs4459609 ACE 0.0 table 2 25 1 +25340798 rs4316 ACE 1e-05 table 2 26 1 +25367360 rs10226930 RA -1 table 3 4 1 +17903295 rs1528753 Age at death 0.0 table 1 4 1 +17903295 rs2371208 Age at death 3e-06 table 1 5 1 +17903295 rs10493513 Age at death 2e-06 table 1 40 1 +17903295 rs10493514 Age at death 3e-06 table 1 41 1 +19197348 rs6560749 BMI 2e-06 table 2 2 3 +19197348 rs10486715 Height 3e-06 table 2 4 3 +19197348 rs17718077 Height 3e-06 table 2 5 3 +19197348 rs2222328 Waist Circumference 1e-06 table 2 7 3 +19197348 rs613391 Waist Circumference 5e-06 table 2 8 3 +19197348 rs527485 Waist Circumference 7e-06 table 2 9 3 +19197348 rs976731 Waist Circumference 7e-06 table 2 10 3 +19197348 rs976730 Waist Circumference 8e-06 table 2 11 3 +19197348 rs2225614 Weight 3e-06 table 2 13 3 +19197348 rs10928195 Weight 4e-06 table 2 14 3 +19197348 rs1874326 Weight 9e-06 table 2 15 3 +19197348 rs755109 Thyroid Stimulating Hormone 1e-06 table 2 63 3 +19197348 rs6462411 Thyroid Stimulating Hormone 1e-06 table 2 64 3 +19197348 rs10983893 Thyroid Stimulating Hormone 2e-06 table 2 65 3 +19197348 rs10848704 Thyroid Stimulating Hormone 2e-06 table 2 66 3 +19197348 rs4743136 Thyroid Stimulating Hormone 2e-06 table 2 67 3 +19197348 rs10241703 Thyroid Stimulating Hormone 2e-06 table 2 68 3 +19197348 rs6958535 Thyroid Stimulating Hormone 3e-06 table 2 69 3 +19197348 rs925488 Thyroid Stimulating Hormone 3e-06 table 2 70 3 +19197348 rs10983932 Thyroid Stimulating Hormone 3e-06 table 2 71 3 +19197348 rs6959674 Thyroid Stimulating Hormone 3e-06 table 2 72 3 +19197348 rs11514766 Thyroid Stimulating Hormone 3e-06 table 2 73 3 +19197348 rs7804166 Thyroid Stimulating Hormone 3e-06 table 2 74 3 +19197348 rs1877431 Thyroid Stimulating Hormone 3e-06 table 2 75 3 +19197348 rs1588635 Thyroid Stimulating Hormone 4e-06 table 2 76 3 +19197348 rs10984516 Thyroid Stimulating Hormone 4e-06 table 2 77 3 +19197348 rs1962785 Thyroid Stimulating Hormone 4e-06 table 2 78 3 +19197348 rs2805809 Thyroid Stimulating Hormone 4e-06 table 2 79 3 +19197348 rs12531984 Thyroid Stimulating Hormone 5e-06 table 2 80 3 +19197348 rs10243770 Thyroid Stimulating Hormone 5e-06 table 2 81 3 +19197348 rs10119795 Thyroid Stimulating Hormone 5e-06 table 2 82 3 +19197348 rs12539695 Thyroid Stimulating Hormone 6e-06 table 2 83 3 +19197348 rs2805810 Thyroid Stimulating Hormone 6e-06 table 2 84 3 +19197348 rs6956479 Thyroid Stimulating Hormone 6e-06 table 2 85 3 +19197348 rs2668804 Thyroid Stimulating Hormone 6e-06 table 2 86 3 +19197348 rs7036589 Thyroid Stimulating Hormone 7e-06 table 2 87 3 +19197348 rs6909430 Thyroid Stimulating Hormone 8e-06 table 2 88 3 +19197348 rs2808693 Thyroid Stimulating Hormone 1e-05 table 2 89 3 +19197348 rs10245389 Thyroid Stimulating Hormone 1e-05 table 2 90 3 +19197348 rs9939609 BMI 0.0 table 3 3 0 +19197348 rs17782313 BMI 0.0 table 3 4 0 +19197348 rs6763931 Height 0.0 table 3 6 0 +19197348 rs6440003 Height 0.0 table 3 6 7 +19197348 rs724016 Height 0.0 table 3 7 0 +19197348 rs6440003 Height 0.0 table 3 7 7 +19197348 rs1042725 Height 0.0 table 3 8 0 +19197348 rs6060369 Height 0.0 table 3 9 0 +19197348 rs798544 Height 0.0 table 3 10 0 +19197348 rs3748069 Height 0.0 table 3 11 0 +19197348 rs7755109 Height 0.0 table 3 11 7 +19197348 rs1812175 Height 0.0 table 3 12 0 +19197348 rs7153027 Height 0.0 table 3 13 0 +19197348 rs6830062 Height 0.0 table 3 14 0 +19197348 rs3760318 Height 0.0 table 3 15 0 +19197348 rs7225461 Height 0.0 table 3 15 7 +19197348 rs2282978 Height 0.0 table 3 16 0 +19197348 rs967417 Height 0.0 table 3 17 0 +19197348 rs4743034 Height 0.0 table 3 18 0 +19197348 rs678962 Height 0.0 table 3 19 0 +19197348 rs12411264 Height 0.0 table 3 19 7 +19197348 rs4533267 Height 0.0 table 3 20 0 +19197348 rs7846385 Height 0.0 table 3 21 0 +19197348 rs2562784 Height 0.0 table 3 22 0 +19197348 rs4794665 Height 0.0 table 3 23 0 +19197348 rs563694 Fasting plasma glucose 0.0 table 3 45 0 +19197348 rs1799884 Fasting plasma glucose 0.0 table 3 46 0 +19197348 rs4704397 Thyroid Stimulating Hormone 0.0 table 3 48 0 +19448621 rs314277 Age at Menarche 0.0 table 0 3 0 +19448621 rs314263 Age at Menarche 0.0 table 0 4 0 +19448621 rs369065 Age at Menarche 0.0 table 0 5 0 +19448621 rs7861820 Age at Menarche 0.0 table 0 6 0 +19448621 rs314280 Age at Menarche 0.0 table 0 7 0 +19448621 rs4946651 Age at Menarche 0.0 table 0 8 0 +19448621 rs12684013 Age at Menarche 0.0 table 0 9 0 +19448621 rs4452860 Age at Menarche 0.0 table 0 10 0 +19448621 rs7028916 Age at Menarche 0.0 table 0 11 0 +19448621 rs314262 Age at Menarche 0.0 table 0 12 0 +22911880 rs7624327 BULIMIA 3e-06 table 2 6 0 +24886709 rs6027281 BMI 0.0 table 1 16 0 diff --git a/notebooks/results/nb-output/phenotypes.extracted.tsv b/notebooks/results/nb-output/phenotypes.extracted.tsv new file mode 100644 index 0000000..877692b --- /dev/null +++ b/notebooks/results/nb-output/phenotypes.extracted.tsv @@ -0,0 +1,589 @@ +25086665 Pancreatic Cancer +23349640 Malignancies +20436471 Paget’s Disease Bone +24714607 Chronic Mucus Hypersecretion +22174851 Viral Set Point|Hiv-1 +22993228 Lumbar Disc Degeneration +24204828 Diabetes-Related Traits +19812673 Autism +20011104 Adiponectin Levels +23128233 Inflammatory Bowel Disease +17903297 Brain|Cognitive Test +23358160 Schizophrenia|Cytomegalovirus Infection|Infection Suggests +24223155 Torsades De Pointes +22044751 Chronic Kidney Disease +25105248 Colorectal Cancer +21801394 Stevens-Johnson Syndrome|Toxic Epidermal Necrolysis +17903305 Prostate Cancer|Breast +22116950 Ovarian Reserve +17658951 Obesity-Related Traits +24651765 Homocysteine|Methionine|Metabolism +22144915 Corneal Astigmatism +24489884 Aggression +18604267 Antigen|Icam-1 +21424380 Breast Cancer +23378610 Type 2 Diabetes|Metabolism|Glycine +23844046 C-Reactive Protein +17903294 Hematological Phenotypes +23300701 Colorectal Cancer +22763110 Osteoarthritis +20522523 Partial Epilepsies +21909108 Intima Media Thickness|Plaque +20041166 Hiv-1 +17903308 Circadian Phenotypes|Sleep +18262040 LDL-cholesterol +24023788 Lung Function +23118916 Serum IgM +19936222 Cholesterol|Plasma Lipoprotein Size +25352737 Cataract +21242260 Colon Cancer +22028671 Ratio|Total Cholesterol +22792071 Bone Mineral Density|Bone|Osteoporotic Fracture +25133637 Body Mass Index +19820699 Erythrocyte +25569183 Marginal Zone Lymphoma +25705158 Metabolic Syndrome +24101674 Type 2 Diabetes +23646285 Hypersomnia +21878437 Vitamin A +19116933 Juvenile Idiopathic Arthritis +19056611 Type 2 Diabetes +20173748 Chronic Obstructive Pulmonary Disease +25625606 Hippocampal Volume|Dementia +24778558 Coronary Heart Disease +23829686 Childhood|Childhood Asthma +19668339 Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease +25628645 Homoharringtonine +23593202 Age Menarche|Femoral Neck Bone Geometry +23793025 Migraine +23666240 Testicular Cancer +23350875 Colorectal Cancer +20062060 Pr Interval +22719876 Non-Alcoholic Fatty Liver Disease|Liver Disease +23326517 Age-Related Macular Degeneration +22792082 Asthma|Bronchodilator Response +25038754 Breast Cancer +24908248 Telomere Length|Glioma +23508266 Asthmatics|Bronchodilator Response +25350695 Ldl Cholesterol Response|Response Statins +21573128 Osteoporosis +21533074 Diffuse Large B-cell Lymphoma|Follicular Lymphoma|Diffuse +23967269 Mite-Specific IgEs|Asthma +24586186 Metabolic Traits|Metabolite-Disease +24586183 Thyroid Peroxidase Antibodies|Thyroid Disease +17903296 Association Bone +22511988 Cell-Free Dna|Cardiovascular +21573004 Telomere Length +21901158 Insulin Resistance|Copy Number Variation +21909115 Cardiovascular Disease|Blood Pressure +24816252 Blood Metabolites +25017104 Allergic Disease|Eosinophilic Esophagitis +24941225 Serum Carcinoembryonic Antigen Levels|Lymph Nodes|Colorectal Cancer +25372704 Sickle Cell Anemia|Fetal Hemoglobin|Sickle Cell +17903300 Waist Circumference|Body Mass Index +21448238 Migraine +19305408 Qt Interval Duration +25526632 Breast Cancer +24920014 Hodgkin Lymphoma +22737229 Chronic Hepatitis B +24379826 Serum Uric Acid Levels +21386085 Metabolic Syndrome +19454037 Left Ventricular Mass +23535730 Ovarian Cancer +21502949 Brain +17903303 Atherosclerosis +17903298 Diabetes-Related Traits +22076464 Acute Lymphoblastic Leukemia +21750679 Systemic Sclerosis +21779181 Systemic Sclerosis +21602798 Prostate Cancer|Prostate +20862305 Type 2 Diabetes +20661308 Serum Calcium +23979607 Borderline Personality +25140149 Neurodegeneration|Biomarker +21390209 Late-Onset Alzheimer's Disease +23341777 Lung Squamous Cell Carcinoma +21775986 Recombination +22430674 Alzheimer's Disease +19448621 Age Menarche|Menopause +23698163 Serum Selenium +25317112 Gastritis|Gastric Ulcer +21082022 Hypertension|Blood Pressure +20072603 Osteoporosis +22941191 Neuroblastoma +23535967 Glomerular Filtration Rate|Quantitative Trait +24324551 Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive +24244560 Diabetic Retinopathy|Chronic Kidney Disease|Hemoglobin A +21602797 Cystic Fibrosis|Lung Disease +23307926 Menopause +20861866 Age-Related Macular Degeneration +17447842 Crohn Disease +22247754 Arrhythmias +21060863 Cardiovascular Diseases +21980494 Venous Thrombosis +20200953 Osteoporosis-Related Phenotypes +20858683 Hemoglobin A +21810271 Factor Viii +25533491 Sepsis|Due Pneumonia +23886662 Psoriasis|Atopic Dermatitis|Asthma +19609347 Hypertension|Blood Pressure +19503597 Uric Acid +19587794 Sudden Cardiac Death +25705159 Hepatitis +25056061 Schizophrenia +23958962 Cocaine Dependence +25129146 Esophageal Squamous Cell Carcinoma +21339755 Galactose|Mutarotase|Serotonin Transporter +21483845 Iron Deficiency +21533175 Dehydroepiandrosterone Sulphate +22589738 Adipose +22675492 Sex Hormone-Binding Globulin|Testosterone|Estradiol +21779176 Restless Legs Syndrome +24068947 Brain +22479419 Treatment Refractory Schizophrenia +21700879 Adiponectin Levels +19557197 Distribution|Adiposity|Waist Circumference +25705162 Platelet Count +22961080 Type 2 Diabetes +23770605 Chronic Lymphocytic Leukemia +23459443 Qt Interval +25310821 Hirschsprung Disease +20634892 Neuroticism +20081856 Major Mood Disorders +21983785 Melanoma +23536807 Primary Open Angle Glaucoma|Macular Degeneration +24324648 Serum IgE +24348519 Body Mass Index +20686651 Chronic Kidney Disease|Kidney Stones|Comorbid Diseases +24121790 Barrett’s Esophagus|Esophageal Adenocarcinoma +19421330 Onset|Hypertension +20169177 Systemic Lupus Erythematosus +24892410 Onset|Hypertension|Cardiovascular Events +23509613 Antiphospholipid Antibodies +19343178 Stature +20038947 Major Depression +24740154 Prostate Cancer|Early-Onset +20421936 Onset|Obesity-Related Traits|Body-Weight +21399635 Primary Biliary Cirrhosis +22087292 Femoral Neck Bone Geometry +24023777 Adolescent Idiopathic Scoliosis +24743840 Colorectal Cancer +19430480 Type 1 Diabetes +21738484 Bipolar Disorder|Disorder Suggests +22666496 Cardiovascular Event +21552555 Obesity|Obesity-Related Traits +24836286 Colorectal Cancer +21844884 Treatment +22001756 Dengue Shock Syndrome +20526338 Platelet Aggregation +23565137 Late-Onset Alzheimer’s Disease +22792070 Bone Mineral Density|Bone|Osteoporotic Fracture +22807686 Chronic Hepatitis B|Hepatitis B Virus|Carriers +18483556 Hair Color|Skin Pigmentation +24964207 Suicidal Ideation|Attempts Suicidal|Suicide Attempts +20927387 Cell Traits|Red Blood Cell +19714249 Obesity|Osteoporosis Phenotypes +22493691 Hypothyroidism +21804549 Asthma +18455228 Bone Mineral Density|Osteoporosis +23708191 Congenital Heart Disease|Atrial Septal Defect +19412175 Neuroblastoma +20548946 Optic Disc +19961619 Respiratory|Atopy +20663923 Autism +20932310 Τ Protein Levels +22952603 -Amphetamine Response +19304780 Blood Pressure +20395239 Optic Disc Size +25064009 Parkinson’s Disease +24133439 Autistic-Like Traits +20081858 Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis +23727862 Osteosarcoma +17903292 Kidney|Endocrine-Related Traits +25241763 Optic Nerve +23118974 Pigmentation|Skin +23049750 Smoking|Cyp2A6 +23419831 Cerebral Amyloid Deposition +21876539 Cyp1A2 +24068962 Serum Calcium +21347282 Coronary Heart Disease +21423719 Metabolic Traits|Nonalcoholic Fatty Liver Disease +23300278 Type 2 Diabetes +23028483 Asthma +24280982 Schizophrenia|Bipolar Disorder|Disorder +23936387 Celiac Disease +22359512 Sphingolipids +23259602 Dental Caries +23183491 Sensitivity +20953189 Psoriasis +25310577 Acute Lymphoblastic Leukemia|Childhood +20174558 Type 2 Diabetes +24166486 Schizophrenia +22479309 Brachial Circumference +22504420 Bone Mineral Density +23717212 Malaria +22570617 Optic Nerve|Glaucoma +22558069 Immunoglobulin Isotypes|Non-Albumin Protein +22452962 Breast Cancer +23381943 Ischemic Stroke +25364816 Diabetic Retinopathy +23297363 Tetralogy Fallot +21729881 Vitamin E Levels +20694148 Metabolic Syndrome +20585626 Breast Cancer +22832961 Alzheimer's Disease +24047820 Social Communication +21998595 Height +21060860 Breast Cancer +24880342 Lung Cancer|Lung +22368281 LDL-c Response|Lp(a) +23006423 Lung Cancer|Overall Survival +22085899 Bilirubin Levels +20485516 Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease +22205951 Bipolar Disorder +23028342 Type 1 Diabetes|Kidney Disease|Diabetic Nephropathy +23966867 Body Fat Distribution +22197932 Atopic Dermatitis +24709693 Methotrexate Response|Juvenile Idiopathic Arthritis +20622878 Behçet's Disease +21827660 Increased Disease Risk +25009551 Peripheral Arterial Disease +24253340 Schizophrenia|Bipolar Disorder +19132087 Kawasaki Disease +24999842 Celiac Disease|Celiac +21627779 Alzheimer's Disease +21665990 Age-Related Macular Degeneration +19779542 Pathological Myopia +21490707 Caffeine Consumption|Cyp1A2 +25340798 Proteins Involved|Inflammation|Alzheimer's Disease +20548944 Osteoporosis-Related Traits|Gene Expression Profiling +23326239 Antibodies|Epstein-Barr Virus Nuclear Antigen +21483430 Neurocognitive Phenotypes +24518671 Pressure +20305777 Osteoarthritis +20885792 Dementia|Late-Onset Alzheimer Disease +23001122 Male Breast Cancer +23001564 Homeostasis +20195514 Primary Tooth Development +23028356 Rheumatoid Arthritis +22344219 Body Mass Index +21873549 Type 2 Diabetes|Proinsulin Levels +23776548 Arterioles +22916037 Atherosclerosis +22238593 Type 2 Diabetes +22479202 Metabolic Traits|Type 2 Diabetes|Adiponectin Levels +23209189 Type 2 Diabetes +22286170 Asthma|Gene Expression|Lymphocyte Count +22589742 Pericardial +20686608 Pancreatic Cancer +24465473 Telomere Length +23284291 Pulmonary Function|Lung Function +21685912 Progressive Supranuclear Palsy +23636237 Analysis +21738478 White Blood Cell Count|Cell Phenotypes|White Blood Cell +22570627 Primary Open-Angle Glaucoma|Intraocular Pressure +20801717 Sporadic Amyotrophic Lateral Sclerosis +22383894 Toxicity Phenotypes|Metabolism +23408906 Thyroid|Thyroid-Related Traits|Differences +17997608 Serum Uric Acid Levels +21931564 Metabolite Quantitative Trait +21738487 Parkinson's Disease +24392092 Memory +23666239 Testicular Germ Cell Tumor +20802479 Migraine +24564958 Social-Communication|Spectrum Phenotypes +25008200 Chronic Periodontitis +21490949 Type 2 Diabetes|Transferability +24058526 Systolic Blood Pressure|Sickle Cell Disease +22745674 Coronary Artery Stenosis|Coronary Artery +24483146 Biomarkers +22747683 Breast Cancer|Breast Size +22561518 Generalized Vitiligo +22792221 Normal Tension Glaucoma +17903302 Arterial Stiffness|Blood Pressure +22760553 Global Disease|Depression|Citalopram-Induced Side Effects +17903307 Pulmonary Function +23966204 Bitter Taste|Bitter Taste Perception +20372150 Birth Weight|Fetal Growth +20339536 Lipid-Lowering Response|Response Statins +18464913 Protein Quantitative Trait|Genome|Association +25241909 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis +21383967 Rheumatoid Arthritis|Celiac Disease +17903293 Biomarker Traits +19300499 Cyp2C9|Warfarin +25162662 Serum Ferritin +23533358 Opiates Addiction|African-Origin +23874384 Behavior +22412388 Crohn's Disease +24009623 Biomarker +21829377 Plasma Phospholipid|Fatty Acids +22911880 Behaviors|Personality Traits|Eating +25087078 Epilepsies +23532257 Type 2 Diabetes +23738518 Reading|Language +18159244 Onset|Obesity|Obesity Associated +22423221 Platelet Count|Mean Platelet Volume +18776929 Hip Bone Size|Females +19300482 Chronic Obstructive Pulmonary Disease (Copd)|Pulmonary Function +18282107 Schizophrenia +20418485 Vitamin D Levels +24688116 Longevity|Analysis|Population +20639881 Follicular Lymphoma +20675712 Quinine +22216198 Protein C +21347284 Pr Interval +24390342 Rheumatoid Arthritis|Biology +22843504 Autism Spectrum +23755828 Warfarin +23382809 Schizophrenia +22685421 Ocular Axial Length|High Myopia +19801982 Bone Mineral Density +19874204 Femoral Neck Bone|Bone Mineral Density +19597492 Atrial Fibrillation +19219042 Breast Cancer +19096518 Glycated Hemoglobin +23974872 Schizophrenia +24603532 Primary Angle Closure Glaucoma|Anterior Chamber Depth +23903356 Pregnancy|Glycemic Traits +21771975 Adiponectin|Quantitative Trait|Cardiometabolic Outcomes +24465431 Onset|Cardiovascular Disease|Diabetes +19197348 Complex Disease +23041239 Ischaemic Stroke +23459936 Chronic Periodontitis +23386860 Iron Intake|Type 2 Diabetes +23583978 Body Mass Index +23437003 Volumetric Bone Mineral Densities +24871463 Systemic Lupus Erythematosus (Sle) +23989986 Hip|Osteoarthritis +21124946 Bone Mineral Density +19169254 Psoriasis +24449572 Rheumatoid Arthritis +18823527 Late-Onset Alzheimer's Disease +25742292 Parity +22693459 Onset|Androgenetic Alopecia|Common Diseases +20881960 Height +24940741 Infection +22504421 Hippocampal Volume +23423138 Mathematical Abilities|Dyslexia|Myosin +25760438 Type 2 Diabetes|Body Mass Index +23468962 Breast Cancer +23785401 Oligoclonal Bands|Multiple Sclerosis +23667675 Age Menarche +21042317 Major Depressive Disorder +21244703 Multiple Sclerosis +21326860 Kawasaki Disease +22428042 Glaucoma|Optic-Nerve +22479191 Kidney|Follow-Up +19651812 Melatonin|Plasma Glucose|Type 2 Diabetes +23761726 Corneal Astigmatism|Platelet-Derived Growth Factor +24509480 Type 2 Diabetes +19570815 C-type Natriuretic Peptide|Height +23555300 Rheumatoid Arthritis|Response Etanercept +17903295 Age-Related Phenotypes|Longevity +23028341 Complement C3 +19122664 Ulcerative Colitis +25147783 Ischemic Stroke|Vitamin|Folate Levels +21946350 Lung Function|Follow-Up +22403646 Haptoglobin Levels +21935397 Extremely|Overweight|Body Mass Index +21460841 Late-Onset Alzheimer’s Disease +23696099 Cell Traits|Red Blood Cell|Resistance +19043545 Metabolite +20463881 Eye Color +23754948 Anthropometric Traits|Sexual +25226531 Suggest|Associated|Linguistic Phenotype +21156761 Rheumatoid Arthritis +25003214 Reading|Mathematics Ability +24800985 Birth +21151130 Endometriosis +23472185 Multiple Sclerosis|Oligoclonal Band +19081515 Creutzfeldt–Jakob Disease +22005930 Alzheimer’s Disease|Psychotic Symptoms +24938310 Exfoliation Glaucoma +24124408 Standing|Blood Pressure Changes|Orthostatic Hypotension +24097068 Lipid Levels +24403052 Basal Cell Carcinoma +19503088 Rheumatoid Arthritis +24376456 Blood Pressure +22291604 Lupus +25436638 Serum Thyroid Stimulating Hormone +21418511 Longevity +18941528 Multiple Sclerosis +25378659 Long-Chain Saturated Fatty Acids +24386095 Lipid Levels +20585627 Common Traits +24886709 Lipid +22832964 Smoking Behaviors +19772629 Parkinson Disease|Onset +22384028 Pressure Traits|Hypertension|Blood Pressure +22233651 Gestational Diabetes Mellitus +22306652 Ischemic Stroke +23263487 Colorectal Cancer +25085501 Allergic Rhinitis +21983787 Melanoma +25102180 Type 2 Diabetes +19412176 Narcolepsy +19247474 Smoking Behaviors|Cigarette Smoking +23817569 Allergy +21364930 Hiv-1 +19359265 Telomere Length +20066028 Serum Cholesterol Levels +24511991 Parkinson’s Disease +23291585 Visceral Leishmaniasis +22267201 Age Menopause +21738491 Sudden Cardiac Death +22961001 Barrett’s Esophagus +25188341 Dementias|Alzheimer's Disease +20364137 Intracranial Aneurysm +23401653 Platelet-Derived Growth Factor|Quantitative Trait|Corneal +19714205 Asthma +19401414 Type 2 Diabetes +21931568 Eruption +21980299 Type 1 Diabetes +21943158 Cardiovascular-Related Traits +23104006 Endometriosis +19430483 Blood Pressure +21998597 Serum Testosterone +22693455 Obese|Type 2 Diabetes +24903457 Blood Pressure +23544013 Breast Cancer|Breast Ovarian Cancer|Carriers +21298047 European-Origin|Substance Dependence +24478790 Telomere Length +24143190 Breast Cancer|Breast +20442857 Phospholipase A +21124955 Serum Amyloid A|Type 2 Diabetes +21829393 Type 1 Diabetes|Autoantibody +22470424 Amyotrophic Lateral Sclerosis +18846228 Serum IgE Levels +24376798 Chronic Hepatitis C +22509378 Sexual Dysfunction +21799836 Type 2 Diabetes +18840781 Type 1 Diabetes +19915575 Parkinson’s Disease +17903306 Heart Rate|Variability Traits +25187353 Agranulocytosis +21379329 Late-Onset Alzheimer's Disease +21533022 Bone Mineral Density +22544364 Wilms Tumor +21738479 White Blood Cell Count|Cell Phenotypes|White Blood Cell +21186350 Glycemic Response|Type 2 Diabetes|Response Metformin +23382691 Immunoglobulin G|Human Immunoglobulin|-Glycosylation +21044948 Parkinson's Disease +19557161 Distribution|Adiposity|Waist Circumference +22899653 Lung Cancer +22832960 Temperament Character Inventory +24571439 Specific Language Impairment|Genotype Effects +24014518 Epilepsy|Febrile Seizures +23984888 Airway Responsiveness +23870195 Coronary Artery|Coronary Artery Calcification +21273288 NT-proBNP +17684544 Ibd Disease +23509962 Venous Thrombosis +21909110 Mean Arterial Pressure|Pulse Pressure +24625756 Intermediate Phenotypes +23326512 Elated|Mania|Irritable +21833088 Immune Mechanisms|Multiple Sclerosis +17903304 Cardiovascular Disease +21738480 Cell Phenotypes|White Blood Cell +23935489 Hiv-1 +23209447 I Antigen|Nasopharyngeal Carcinoma +21437268 Cancers|Conducted|Upper Aerodigestive Tract +19798445 Sphingolipid +22291609 Inflammation +19734902 Alzheimer's Disease +23092984 Bipolar Disorder +20921969 Cardiac Arrhythmias +23563607 Anthropometric Traits +23400010 Metabolic Response|Response Hctz +20686565 Lipids +21460840 Alzheimer’s Disease +21423239 Attempted Suicide +21294900 Serum Uric Acid +19578366 High Grade|Glioma +19721433 Response Treatment|Antipsychotics +21298027 Celiac Disease|Crohn's Disease +24516586 Tobacco Smoke|Chromosome 4|Cleft Palate +19571809 Schizophrenia +21297633 Ulcerative Colitis +21812969 Parkinson's Disease +22484627 Childhood Obesity +20711177 Parkinson’s Disease +21076409 Conduction|Qrs Duration +24513273 Serum Uric Acid +19300500 Chronic Obstructive Pulmonary Disease (Copd)|Pulmonary Function +25390645 Anxiety +20953186 Psoriasis|Psoriatic Arthritis +23900074 Telomere Length|Cancer +25060954 Kinase|Hearing +23935956 Red Blood Cell +21278746 Mammographic Density|Breast Cancer +23251661 Childhood Obesity|Childhood +19966805 Type 1 Diabetes +22438815 Parkinson's Disease +23704328 Tooth Eruption|Height +20190752 Celiac Disease +25044758 Height-Adjusted Bmi +20729852 Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma +23291587 Behçet's Disease +24124411 Liver Enzymes +23834954 Sensory Disturbances|Split +22383897 Breast Cancer +21408207 Systemic Lupus Erythematosus|Autoantibody +20700443 Potassium|Serum Magnesium|Serum Magnesium Levels +22570697 Multiple Sclerosis +21223598 Aortic Root +20700438 Lung Adenocarcinoma|Lung +20838585 Cardiovascular Disease +25551457 Fibrinogen|Alcohol Consumption|Body Mass Index +21779381 Migraine|Cardiovascular Events|Cardiovascular +23143602 Pancreatitis +24204295 Narcolepsy|Influenza|Changes +21533024 Icam-1 +23393555 Retinopathy|Diabetes +24847357 Staphylococcus Aureus +24945404 Bone Mineral Density|Bone +22170493 Psoriatic Arthritis +23670970 Cystic Fibrosis|Diabetes +22396660 Nephrolithiasis +21658281 Coronary Artery Disease|Sudden Cardiac Arrest +17903301 Exercise Responses|Artery +25297839 Herpes Zoster +24755620 Glutamate|Alzheimer's Disease +24025145 Chemotherapy-Induced Alopecia|Breast Cancer +24347629 Periodontal +21051773 Handedness|Dyslexia +24763700 C-Reactive Protein Levels +21079607 Anorexia Nervosa +23703922 Uric Acid Levels +23678272 Vitiligo +20195266 Antipsychotic Drugs|Metabolic Side Effects +24086445 Schizophrenia|Quantitative Phenotype|Matter Volume +25233373 Myopia|Hyperopia +24096698 Cancer +25367360 Astigmatism|Refractive Error +20972438 Bladder Cancer|Bladder +21814517 Asthma +23593239 Self-Employment +20852633 Ovarian Cancer +23583980 Pulmonary Fibrosis +25383866 General Cognitive Ability +21203500 Master|Plasma Protein +25317111 Chronic Diseases|Medication Adherence +23455636 Age-Related Macular Degeneration +20173747 Lone Atrial Fibrillation +18369459 Psoriasis|Psoriatic Arthritis|New Disease +20834067 Longevity +24952745 Qt Interval|Calcium +23836780 Intraocular Pressure|Glaucoma +24094242 Serum Alkaline Phosphatase 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+25378659 0 0 0 +25378659 1 0 0 +25383866 0 0 0 +25390645 0 0 0 +25390645 1 0 0 +25390645 2 0 0 +25390645 3 0 0 +25436638 0 0 0 +25436638 1 1 0 +25436638 2 1 0 +25526632 0 0 0 +25526632 1 0 0 +25526632 2 1 0 +25526632 3 1 0 +25526632 4 1 0 +25533491 0 0 0 +25551457 0 0 0 +25551457 1 1 0 +25551457 2 1 0 +25569183 0 1 0 +25625606 0 0 0 +25625606 1 1 0 +25625606 2 1 0 +25625606 3 1 0 +25628645 0 0 0 +25628645 1 0 0 +25628645 2 0 0 +25628645 3 0 0 +25629512 0 0 0 +25629512 1 0 0 +25629512 2 1 0 +25629512 3 0 0 +25629512 4 1 0 +25729143 0 0 0 +25729143 1 1 0 +25729143 2 0 0 +25742292 0 0 0 +25742292 1 1 0 +25760438 0 0 0 +25760438 1 0 0 diff --git a/notebooks/results/rels.discovered.annotated.txt b/notebooks/results/rels.discovered.annotated.txt deleted file mode 100644 index 2b18394..0000000 --- a/notebooks/results/rels.discovered.annotated.txt +++ /dev/null @@ -1 +0,0 @@ -17903305 rs7329659 prostate cancer|breast 2 unsure MAF<0.1; why not in main table? 18483556 rs164741 Hair Color|Skin Pigmentation 2 repeat 19197348 rs2849176 complex disease 0 TRUE Other gold SNPs in the same table 19197348 rs328 complex disease 0 repeat 19247474 rs1400363 Smoking Behaviors|Cigarette Smoking 2 TRUE only in combined study 19300500 rs1877252 Chronic Obstructive Pulmonary Disease COPD|Pulmonary Function 2 unsure rounding error 19343178 rs6817306 Stature 3 TRUE "In the text and it says that it's ""one of the strongest""" 19412175 rs17487792 neuroblastoma 3 TRUE neighbor is reported 19448621 rs402511 age menarche|menopause 2 TRUE confirmed in text 19503597 rs780093 Uric Acid 3 unsure significant in men but not not women 19503597 rs942379 Uric Acid 3 TRUE significant in both men and women 19557197 rs6714750 Distribution|Adiposity|Waist Circumference 3 not_in_combined significant in own dataset but not in combined; all reported snps are significant in both 19798445 rs12889954 Sphingolipid 3 TRUE "species range of pvalues for various lipids, but at least one is significant; reported snps are not significant in entire range either" 19874204 rs2036417 Bone Mineral Density|Femoral Neck Bone 2 TRUE its listed in text as significant 20169177 rs9271366 Systemic Lupus Erythematosus 3 TRUE test says this is the most significant snp 20395239 rs4517412 optic disc size Disc 3 TRUE other reported snps have worse pvalues 20686608 rs11242674 Pancreatic Cancer 3 TRUE "not significant in one model, but there are gold snps not significant in >2 models" 20838585 rs11258628 Cardiovascular Disease LDL 3 not_in_combined can be detected via column name 20838585 rs12069004 Cardiovascular Disease glucose 3 not_in_combined can be detected via column name 20838585 rs6726786 Cardiovascular Disease triglycerides 3 not_in_combined can be detected via column name 20838585 rs781718 Cardiovascular Disease glucose 3 not_in_combined can be detected via column name 20861866 rs3750848 age-related macular degeneration 3 TRUE in the text and meta-analysis 20881960 rs2280470 height 3 unsure "it is labeled as ""second signal SNP""" 20953186 rs13190932 psoriasis|psoriatic arthritis 3 TRUE confirmed in text 20953186 rs13210247 psoriasis|psoriatic arthritis 3 TRUE confirmed in text 20972438 rs798766 bladder cancer|bladder 3 TRUE confirmed in text 21297633 rs6556412 ulcerative colitis 3 TRUE shared association; one disease is just above 1e-5 21297633 rs7554511 ulcerative colitis 3 TRUE shared association 21390209 rs624225 Late-Onset Alzheimer's Disease 3 not_in_combined "Only two SNPs are replicated and it's in the text; the title of our snp's column says ""combined""" 21502949 rs4752194 brain 0 not_in_combined not significant in pooled analysis; can be detected via column name 21738487 rs1079597 Parkinson's Disease 3 FALSE "gets reported as singleton because pvalue column is labeled just ""p"" (an image) and all siginificant snp pvalues are images" 21829393 rs478582 Type 1 Diabetes|Autoantibody 2 TRUE "not significant for some subdiseases, but other snps with same profile are in gold set" 21931564 rs2014355 nuclear magnetic resonance C3/C4 3 TRUE "Table that indicates that SNP is ""identified by this study""" 21935397 rs2798311 body mass index 2 not_in_combined can be detected via column name 21935397 rs4771122 body mass index 2 not_in_combined can be detected via column name 22087292 rs13299777 Appendicular Lean Mass|Femoral Neck Bone Geometry 2 not_in_combined "column is named ""replication p"" but the significant values there are ~0.01" 22087292 rs1368998 Appendicular Lean Mass|Femoral Neck Bone Geometry 2 not_in_combined 22087292 rs3849874 Appendicular Lean Mass|Femoral Neck Bone Geometry 2 not_in_combined 22291609 rs11829037 Inflammation ESR 2 TRUE confirmed in text 22291609 rs12034598 Inflammation ESR 2 TRUE confirmed in text 22368281 rs1985096 LDL-c response|Lpa 3 TRUE The paper seems to use a more stringent threshold but it seems to refer to the right column for gold standard p-values 22412388 rs2076756 Crohn's Disease 3 TRUE "confirmed in text, but they mention its old, but they report it as new" 22430674 rs744373 Alzheimer's disease 2 FALSE "haplotype and snp in same line; hap is significant, snp is not" 22452962 rs10995190 breast cancer|Breast Cancer 3 repeat 22479419 rs4699030 Treatment Refractory Schizophrenia 3 TRUE confirmed in text 22509378 rs4821536 Sexual Dysfunction Overall FSD 3 TRUE gold snps from gwas catalog are in the same table 22719876 rs738407 Non-Alcoholic Fatty Liver Disease|Liver Disease 3 TRUE "confirmed in text as 1e-7, which is enough for us (paper is stricter)" 22792070 rs2536182 "Bone Mineral Density,|Bone|Osteoporotic Fracture" 3 TRUE its numbers look just like the top hit 22832964 rs1245577 smoking behaviors AOI 2 TRUE its in the same table as top hit and pvalue is ok for us 22843504 rs6653872 autism spectrum FALSE the pvalue associated with this snp is from another study 22843504 rs9302952 autism spectrum TRUE same table as best hit with good enough pvalue 23028483 rs1564606 Asthma 23251661 rs2266788 Childhood Obesity|Childhood Triglycerides(mg/dL) 23259602 rs505982 dental caries 23300701 rs7136702 Colorectal Cancer 23326239 rs3115663 Antibodies|Epstein-Barr Virus Nuclear Antigen 23326239 rs7754768 Antibodies|Epstein-Barr Virus Nuclear Antigen 23382691 rs10276619 Human Immunoglobulin|Cancers|-Glycosylation 23509613 rs2857597 Antiphospholipid Antibodies 23509613 rs2894254 Antiphospholipid Antibodies 23509613 rs3129934 Antiphospholipid Antibodies 23509962 rs12880735 venous thrombosis 23509962 rs3780293 venous thrombosis 23667675 rs6438424 Age Menarche 23703922 rs6832439 uric acid levels 23738518 rs11666805 reading|language 23844046 rs11265260 C-Reactive Protein 23979607 rs6888413 borderline personality 23979607 rs6894288 borderline personality 23984888 rs11683662 airway responsiveness 24025145 rs7318267 chemotherapy-induced alopecia|breast cancer 24086445 rs10770359 Schizophrenia|Matter Volume 24133439 rs10778511 Autistic-Like Traits 24166486 rs34706883 Schizophrenia 24376456 rs13008299 blood pressure DBP 24376456 rs3852160 blood pressure QT interval 24376456 rs9874923 blood pressure MAP 24386095 rs1160985 Lipid Levels LDL 24390342 rs678347 rheumatoid arthritis|biology 24483146 rs11636687 biomarkers 24483146 rs13171512 biomarkers 24513273 rs1394125 serum uric acid 24513273 rs3114018 serum uric acid 24586186 rs37370 Metabolic Traits 3-Aminoisobutyrate 24586186 rs4921914 Metabolic Traits Unknown 24709693 rs66861122 Methotrexate Response|Juvenile Idiopathic Arthritis 24714607 rs4760851 "Chronic Mucus Hypersecretion," 24892410 rs17338512 Hypertension|Pulse Pressure Nighttime PP 24945404 rs10835187 Bone Mineral Density|Bone 24945404 rs2908004 Bone Mineral Density|Bone 25060954 rs6472312 kinase|hearing 25064009 rs11158026 Parkinson‰ŰŞs disease 25064009 rs11724635 Parkinson‰ŰŞs disease 25147783 rs1801222 Stroke|Vitamin|Folate Levels 25162662 rs4666783 Serum Ferritin 25340798 rs7926920 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 25364816 rs9362054 Diabetic Retinopathy 25378659 rs2100944 long-chain saturated fatty acids 25436638 rs12138950 Serum Thyroid Stimulating Hormone \ No newline at end of file diff --git a/notebooks/table-extraction.ipynb b/notebooks/table-extraction.ipynb index d3582d3..d3f88a2 100644 --- a/notebooks/table-extraction.ipynb +++ b/notebooks/table-extraction.ipynb @@ -4,7 +4,28 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# SNP/Phenotype detection from raw text" + "# Extracting SNP/P-value relations from tables" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This module parses XML tables and extracts relations between SNPs and the p-values at which they are deemed to be significant." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Preparations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We start by configuring Jupyter and setting up our environment." ] }, { @@ -18,56 +39,55 @@ "%load_ext autoreload\n", "%autoreload 2\n", "\n", + "import sys\n", + "import cPickle\n", "import numpy as np\n", - "import cPickle, os, sys\n", - "np.random.seed(seed=1701)\n", + "import sqlalchemy\n", + "\n", + "# set the paths to snorkel and gwasdb\n", + "sys.path.append('../snorkel-tables')\n", + "sys.path.append('../src')\n", + "sys.path.append('../src/crawler')\n", + "\n", + "# set up the directory with the input papers\n", + "abstract_dir = '../data/db/papers'\n", + "\n", + "# set up matplotlib\n", "import matplotlib\n", "%matplotlib inline\n", - "matplotlib.rcParams['figure.figsize'] = (18,6)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "# import snorkel and gwasdb\n", - "sys.path.append('../snorkel')\n", - "sys.path.append('../src')\n", + "matplotlib.rcParams['figure.figsize'] = (12,4)\n", "\n", - "# set up paths\n", - "abstract_dir = '../data/db/papers'" + "# create a Snorkel session\n", + "from snorkel import SnorkelSession\n", + "session = SnorkelSession()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Assemble a corpus" + "### Load corpus" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Collect all the tables in our dataset" + "We load our usual corpus of GWAS papers." ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "from snorkel.parser import XMLDocParser\n", + "from snorkel.parser import XMLMultiDocParser\n", "from extractor.parser import UnicodeXMLTableDocParser\n", "\n", - "xml_parser = UnicodeXMLTableDocParser(\n", + "xml_parser = XMLMultiDocParser(\n", " path=abstract_dir,\n", " doc='./*',\n", " text='.//table',\n", @@ -77,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "collapsed": false }, @@ -86,132 +106,135 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 16min 35s, sys: 49.8 s, total: 17min 25s\n", - "Wall time: 24min 36s\n" + "Loaded corpus of 589 documents\n" ] } ], "source": [ - "from snorkel.parser import HTMLParser\n", - "from extractor.parser import UnicodeTableParser\n", - "from snorkel.parser import CorpusParser\n", - "import cPickle\n", + "from snorkel.parser import CorpusParser, OmniParser\n", + "from snorkel.models import Corpus\n", "\n", - "table_parser = UnicodeTableParser()\n", - "html_parser = HTMLParser(path='../data/db/papers/')\n", - "\n", - "corpus_name = 'gwas-table-corpus.pkl'\n", + "# parses tables into rows, cols, cells...\n", + "table_parser = OmniParser(timeout=1000000)\n", "\n", "try:\n", - " with open(corpus_name,\"r\") as pkl:\n", - " corpus = cPickle.load(pkl)\n", + " corpus = session.query(Corpus).filter(Corpus.name == 'GWAS Table Corpus').one()\n", "except:\n", " cp = CorpusParser(xml_parser, table_parser)\n", - " %time corpus = cp.parse_corpus(name='GWAS Corpus')\n", - " # pickling currently doesn't work...\n", - "# with open(corpus_name,\"w\") as pkl:\n", - "# corpus = cPickle.dump(corpus, pkl)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "# pickling currently doesn't work...\n", - "# import cPickle\n", - "# with open(corpus_name,\"w\") as pkl:\n", - "# corpus = cPickle.dump(corpus, pkl)" + " %time corpus = cp.parse_corpus(name='GWAS Table Corpus', session=session)\n", + " session.add(corpus)\n", + " session.commit()\n", + "\n", + "print 'Loaded corpus of %d documents' % len(corpus)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Try extracting rs-ids first" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "# add new paths\n", - "sys.path.append('../src/crawler')\n", - "sys.path.append('../src/crawler/db')\n", - "\n", - "# import new libs\n", - "from kb import KnowledgeBase\n", - "from extractor.util import gold_rsid_stats, gold_rsid_precision\n", - "\n", - "from snorkel.candidates import Ngrams\n", - "from snorkel.matchers import DictionaryMatch, RegexMatchSpan, Union\n", - "from snorkel.candidates import EntityExtractor\n", - "\n", - "# from snorkel.candidates import Candidates" + "## Candidate Extraction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Create a gold set" + "### Defining candidate matchers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Get a list of all the rs-ids we know." + "We genereate RSid candidates from all spans that match the following regular expression." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "kb = KnowledgeBase()" + "from snorkel.matchers import RegexMatchSpan\n", + "rsid_matcher = RegexMatchSpan(rgx=r'rs\\d+(/[ATCG]{1,2})*$')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Get a gold set:" + "Similarly, p-value candidates are all spans that match the following regular expression." ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "gold_set = frozenset( [ (doc.name, rs_id) for doc in corpus.documents for rs_id in kb.rsids_by_pmid(int(doc.name)) ] )\n", - "gold_set_rsids = [rs_id for doc_id, rs_id in gold_set]" + "from snorkel.candidates import TableNgrams\n", + "from snorkel.matchers import RegexMatchSpan, Union\n", + "\n", + "# 1: p-value matcher\n", + "\n", + "rgx1 = u'[1-9]\\d?[\\xb7\\.]?\\d*[\\s\\u2009]*[\\xd7\\xb7\\*][\\s\\u2009]*10[\\s\\u2009]*[-\\u2212\\u2013\\u2012][\\s\\u2009]*\\d+'\n", + "pval_rgx_matcher1 = RegexMatchSpan(rgx=rgx1)\n", + "rgx2 = u'[1-9]\\d?[\\xb7\\.]?\\d*[\\s\\u2009]*[eE][\\s\\u2009]*[-\\u2212\\u2013\\u2012][\\s\\u2009]*\\d+'\n", + "pval_rgx_matcher2 = RegexMatchSpan(rgx=rgx2)\n", + "rgx3 = u'0\\.0000+\\d+'\n", + "pval_rgx_matcher3 = RegexMatchSpan(rgx=rgx3)\n", + "pval_rgx_matcher = Union(pval_rgx_matcher1, pval_rgx_matcher2, pval_rgx_matcher3)\n", + "\n", + "# 2: column-based matcher (currently not used)\n", + "\n", + "from snorkel.matchers import CellNameRegexMatcher\n", + "\n", + "pval_rgx = 'p\\s?.?\\s?value'\n", + "pval_rgxname_matcher = CellNameRegexMatcher(axis='col', rgx=pval_rgx, n_max=3, ignore_case=True, header_only=True, max_chars=20)\n", + "\n", + "# 3: combine the two\n", + "\n", + "pval_matcher = Union(pval_rgx_matcher, pval_rgxname_matcher)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Extract candidate relations between SNPs and p-values" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 6, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ - "gold_rsid_dict = {doc_id : set() for doc_id, rs_id in gold_set}\n", - "for docid, rsid in gold_set:\n", - " gold_rsid_dict[docid].add(rsid)" + "# create a Snorkel class for the relation we will extract\n", + "from snorkel.models import candidate_subclass\n", + "RsidPhenRel = candidate_subclass('RsidPvalRel', ['rsid','pval'])\n", + "\n", + "# define our candidate spaces\n", + "from snorkel.candidates import TableNgrams\n", + "unigrams = TableNgrams(n_max=1)\n", + "heptagrams = TableNgrams(n_max=7)\n", + "\n", + "# we will be looking only at aligned cells\n", + "from snorkel.throttlers import AlignmentThrottler\n", + "row_align_filter = AlignmentThrottler(axis='row', infer=False)\n", + "\n", + "# the first extractor looks at phenotype names in columns with a header indicating it's a phenotype\n", + "from snorkel.candidates import CandidateExtractor\n", + "ce = CandidateExtractor(RsidPhenRel, [unigrams, heptagrams], [rsid_matcher, pval_rgx_matcher], throttler=row_align_filter)\n", + "\n", + "# collect that cells that will be searched for candidates\n", + "tables = [table for doc in corpus.documents for table in doc.tables]" ] }, { @@ -225,247 +248,158 @@ "name": "stdout", "output_type": "stream", "text": [ - "10073\n" + "22536 relations extracted, e.g.\n", + "RsidPvalRel(Span(\"rs12722489\", parent=416148, chars=[0,9], words=[0,0]), Span(\"2.16E-07\", parent=416156, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs1736916\", parent=416112, chars=[0,8], words=[0,0]), Span(\"1.22E-07\", parent=416120, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs2857439\", parent=416028, chars=[0,8], words=[0,0]), Span(\"1.86E-10\", parent=416036, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs17421624\", parent=415992, chars=[0,9], words=[0,0]), Span(\"9.72E-15\", parent=416000, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs3094157\", parent=416124, chars=[0,8], words=[0,0]), Span(\"1.24E-07\", parent=416132, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs7382297\", parent=415980, chars=[0,8], words=[0,0]), Span(\"2.01E-15\", parent=415988, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs2647046\", parent=415968, chars=[0,8], words=[0,0]), Span(\"1.43E-17\", parent=415976, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs3905495\", parent=416100, chars=[0,8], words=[0,0]), Span(\"4.76E-08\", parent=416108, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs4959093\", parent=415956, chars=[0,8], words=[0,0]), Span(\"8.18E-34\", parent=415964, chars=[0,7], words=[0,0]))\n", + "RsidPvalRel(Span(\"rs2517646\", parent=416004, chars=[0,8], words=[0,0]), Span(\"1.95E-11\", parent=416012, chars=[0,7], words=[0,0]))\n" ] } ], "source": [ - "print len(gold_set)" + "from snorkel.models import CandidateSet\n", + " \n", + "try:\n", + " rels = session.query(CandidateSet).filter(CandidateSet.name == 'RsidPvalRel Relations').one()\n", + "except:\n", + " %time rels = ce.extract(tables, 'RsidPvalRel Relations', session)\n", + " session.add(rels)\n", + " session.commit()\n", + "\n", + "print \"%s relations extracted, e.g.\" % len(rels)\n", + "for cand in rels[:10]:\n", + " print cand" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Extract candidates:" + "#### Save this for now" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 29, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "from snorkel.candidates import EntityExtractor\n", - "from snorkel.candidates import TableNgrams\n", - "\n", - "# Define a candidate space\n", - "ngrams = TableNgrams(n_max=1)\n", - "\n", - "# Define matchers\n", - "gold_rsid_matcher = DictionaryMatch(d=gold_set_rsids, longest_match_only=False)\n", - "regx_rsid_matcher = RegexMatchSpan(rgx=r'rs\\d+(/[^s]+)?')\n", - "# dict_rsid_matcher = DictionaryMatch(d=rs_ids, longest_match_only=False)\n", - "# rsid_matcher = Union(dict_rsid_matcher, regx_rsid_matcher)\n", + "import re\n", + "from extractor.util import pvalue_to_float\n", "\n", - "rsid_extractor = EntityExtractor(ngrams, regx_rsid_matcher)\n", - "# %time rs_candidates = rsid_extractor.extract(corpus.get_tables(), name='all')" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs1992662\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs1992660\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs1793004\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs10521209\", context=None, chars=[0,9], words=[0,0])\n", - "Span(\"rs2631372\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs2925757\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs6947579\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs1553575\", context=None, chars=[0,8], words=[0,0])\n", - "Span(\"rs10484545\", context=None, chars=[0,9], words=[0,0])\n", - "15330 candidates extracted\n", - "Phrase('17684544', 1, 20, 0, u'rs2076756')\n", - "Cell('17684544', 1, 20, u'rs2076756')\n", - "rs10490924/T 1\n", - "rs10737680/A 1\n", - "rs429608/G 1\n", - "rs2230199/C 1\n", - "rs5749482/G 1\n", - "rs4420638/A 1\n", - "rs1864163/G 1\n", - "rs943080/T 1\n", - "rs13278062/T 1\n", - "rs920915/C 1\n", - "rs4698775/G 1\n", - "rs3812111/T 1\n", - "rs13081855/T 1\n", - "rs3130783/A 1\n", - "rs8135665/T 1\n", - "rs334353/T 1\n", - "rs8017304/A 1\n", - "rs6795735/T 1\n", - "rs9542236/C 1\n" - ] - } - ], - "source": [ - "for cand in rs_candidates[:10]: \n", - " print cand\n", - "print \"%s candidates extracted\" % len(rs_candidates)\n", - "print rs_candidates[0].context\n", - "print rs_candidates[0].context.cell\n", + "def clean_rsid(rsid):\n", + " return re.sub('/.+', '', rsid)\n", "\n", - "for cand in rs_candidates:\n", - " if cand.context.document.name == '23455636':\n", - " print cand.get_span(), cand.context.table.position" + "with open('pval-rsid.raw.cols.tsv', 'w') as f:\n", + " for rel in rels:\n", + " pmid = rel[0].parent.document.name\n", + " table_id = rel[0].parent.table.position\n", + " row_id = rel[0].parent.cell.row.position\n", + " col_id = rel[0].parent.cell.col.position\n", + " rsid = rel[0].get_span()\n", + " pval = pvalue_to_float(rel[1].get_span())\n", + " \n", + " try:\n", + " out_str = '%s\\t%s\\t%d\\t%d\\t%d\\t%f\\n' % (pmid, clean_rsid(rsid), table_id, row_id, col_id, pval)\n", + " except:\n", + " print pmid, clean_rsid(rsid), table_id, row_id, col_id, pval\n", + " f.write(out_str)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Statistics" + "## Extracting singleton SNPs" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Statistics on all the rsid candidates:" + "There also exist many papers that don't report p-values. To handle these, we also report certain rsids that have *not* been associated with a p-value.\n", + "\n", + "Here, we extract these entites. Later on, we will filter them." ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 48, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "# of gold annotations\t= 10537\n", - "# of candidates\t\t= 12005\n", - "Candidate recall\t= 0.427\n", - "Candidate precision\t= 0.375\n" - ] - } - ], + "outputs": [], "source": [ - "gold_rsid_stats(rs_candidates, gold_set)" + "# Define the extractor\n", + "from snorkel.models import candidate_subclass\n", + "from snorkel.matchers import RegexMatchSpan\n", + "from snorkel.candidates import CandidateExtractor\n", + "\n", + "RSID = candidate_subclass('SnorkelRsid2', ['rsid'])\n", + "\n", + "unigrams = TableNgrams(n_max=1)\n", + "rsid_singleton_matcher = RegexMatchSpan(rgx=r'rs\\d+(/[^s]+)?')\n", + "rsid_singleton_extractor = CandidateExtractor(RSID, unigrams, rsid_singleton_matcher)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Interesting: some SNPs seem to be never mentioned (e.g. rs12122100) while others (rs727153) appear only in the text.\n", - "\n", - "Sometimes, it's not picked up for a different, strange reason: see rs13314993." + "Perform the extraction process." ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 1, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "('24945404', 'rs13204965')\n", - "('24386095', 'rs10158897')\n", - "('23251661', 'rs10514310')\n", - "('23382691', 'rs10822136')\n", - "('20686565', 'rs6065906')\n", - "('20395239', 'rs10483727')\n", - "('23251661', 'rs9997524')\n", - "('20858683', 'rs853789')\n", - "('22005930', 'rs9811423')\n", - "('22589738', 'rs1498095')\n" - ] - } - ], + "outputs": [], "source": [ - "from extractor.util import gold_rsid_recall\n", + "from snorkel.models import CandidateSet\n", "\n", - "incorrect_rsids = list(gold_rsid_recall(rs_candidates, gold_set))\n", - "for ngram in incorrect_rsids[:10]:\n", - " print ngram" + "try:\n", + " rsid_c = session.query(CandidateSet).filter(CandidateSet.name == 'Rsid Candidates2').one()\n", + "except:\n", + " tables = [table for doc in corpus.documents for table in doc.tables]\n", + " print '%d tables loaded' % len(tables)\n", + " %time rsid_c = rsid_extractor.rsid_singleton_extractor(tables, 'Rsid Candidates2', session)\n", + " session.add(rsid_c)\n", + " session.commit()\n", + "\n", + "print '%d candidates extracted' % len(rsid_c)" ] }, { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Phrase('17903294', 6, 127, 0, u'rs10514919')\n", - "Phrase('17903294', 6, 136, 0, u'rs10514919')\n", - "Phrase('17903294', 6, 145, 0, u'rs2015729')\n", - "Phrase('17903294', 6, 154, 0, u'rs2015729')\n", - "Phrase('17903294', 6, 163, 0, u'rs2015729')\n", - "Phrase('17903294', 6, 199, 0, u'rs6956010')\n", - "Phrase('17903294', 6, 208, 0, u'rs6956010')\n", - "Phrase('17903294', 6, 217, 0, u'rs6956010')\n", - "Phrase('17903294', 6, 226, 0, u'rs917858')\n", - "Phrase('17903294', 6, 235, 0, u'rs917859')\n", - "Phrase('17903294', 6, 244, 0, u'rs2239138')\n", - "Phrase('17903294', 6, 253, 0, u'rs216901')\n", - "Phrase('17903294', 6, 262, 0, u'rs216903')\n", - "Phrase('17903294', 6, 271, 0, u'rs216904')\n", - "Phrase('17903294', 7, 29, 0, u'rs7741731')\n", - "Phrase('17903294', 7, 77, 0, u'rs4075265')\n", - "Phrase('17903294', 7, 89, 0, u'rs915171')\n", - "Phrase('17903294', 7, 113, 0, u'rs6938586')\n", - "Phrase('17903294', 7, 125, 0, u'rs3777442')\n", - "Phrase('17903294', 7, 185, 0, u'rs2105250')\n", - "Phrase('17903294', 7, 197, 0, u'rs9321263')\n", - "Phrase('17903294', 7, 209, 0, u'rs1811949')\n", - "Phrase('17903294', 7, 221, 0, u'rs9321265')\n", - "Phrase('17903294', 7, 233, 0, u'rs7761311')\n", - "Phrase('17903294', 7, 281, 0, u'rs4128714')\n", - "Phrase('17903294', 7, 293, 0, u'rs2105819')\n", - "Phrase('17903294', 7, 341, 0, u'rs3898916')\n", - "Phrase('17903294', 7, 353, 0, u'rs10499199')\n", - "Phrase('17903294', 7, 365, 0, u'rs10499200')\n", - "Phrase('17903294', 7, 377, 0, u'rs10499201')\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "from extractor.util import gold_rsid_precision\n", - "\n", - "strange_ngrams = list(gold_rsid_precision(rs_candidates, gold_set))\n", - "for ngram in strange_ngrams[70:100]:\n", - " print ngram.context" + "We store candidates that occur in sufficiently large tables:" ] }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 41, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# store candidates that occur in sufficiently large tables:\n", "rsid_by_table = dict()\n", - "for cand in rs_candidates:\n", - " rsid = cand.get_span()\n", - " key = cand.context.document.name, cand.context.table.position\n", + "for cand in rsid_c:\n", + " rsid = cand[0].get_span()\n", + " key = cand[0].parent.document.name, cand[0].parent.table.position\n", " if key not in rsid_by_table: rsid_by_table[key] = set()\n", - " rsid_by_table[key].add((rsid, cand.context.cell.row_num, cand.context.cell.col_num))\n", + " rsid_by_table[key].add((rsid, cand[0].parent.cell.row.position, cand[0].parent.cell.col.position))\n", " \n", "with open('rsids.singletons.all.tsv', 'w') as f:\n", " for (pmid, table_id), rsids in rsid_by_table.items():\n", @@ -475,96 +409,57 @@ ] }, { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "set([u'rs6577648', u'rs254315', u'rs10520880', u'rs38276', u'rs986831', u'rs10520246', u'rs7610584', u'rs3751832', u'rs3794889', u'rs10492797', u'rs9327886', u'rs10505624', u'rs208354', u'rs4418248', u'rs10514443', u'rs10486031', u'rs10513681', u'rs216666', u'rs10515347', u'rs10487577', u'rs2253319', u'rs7989050', u'rs4801149', u'rs10512920', u'rs3017183', u'rs2371438', u'rs6555491', u'rs10520247', u'rs10256504', u'rs7329659', u'rs392715', u'rs2834645', u'rs10497958', u'rs1261256', u'rs6102912', u'rs4782742'])\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "print rsid_by_table[('17903305', 4)]" + "Here, we store certain table features that will be used to select which singelton rsid's to report." ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 43, "metadata": { - "collapsed": true + "collapsed": false }, + "outputs": [], "source": [ - "## Get candidate p-values" + "import re\n", + "pval_rgx = 'p\\s?.?\\s?value'\n", + "lod_rgx = 'LOD'\n", + "\n", + "with open('table-annotations.tsv', 'w') as f:\n", + " for doc in corpus.documents:\n", + " for table in doc.tables:\n", + " lod_found = 0\n", + " pval_found = 0\n", + " for cell in table.cells:\n", + " if not pval_found and len(cell.text) < 30 and (re.search(pval_rgx, cell.text, re.IGNORECASE) or cell.text.lower() == 'p'):\n", + " pval_found = 1\n", + " if not lod_found and re.search(lod_rgx, cell.text):\n", + " lod_found = 1\n", + " if pval_found and lod_found: break\n", + " \n", + " out_str = '%s\\t%s\\t%s\\t%s\\n' % (doc.name, table.position, pval_found, lod_found)\n", + " f.write(out_str) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Need to use regular expressions for this." + "## Filtering relations" ] }, { - "cell_type": "code", - "execution_count": 64, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 3min 7s, sys: 18.9 s, total: 3min 26s\n", - "Wall time: 4min 34s\n" - ] - } - ], + "cell_type": "markdown", + "metadata": {}, "source": [ - "from extractor.matcher import PvalMatcher\n", - "from snorkel.candidates import EntityExtractor, TableNgrams\n", - "from snorkel.matchers import RegexMatchSpan, Union\n", - "\n", - "# 1: p-value matcher\n", - "\n", - "rgx1 = u'[1-9]\\d?[\\xb7\\.]?\\d*[\\s\\u2009]*[\\xd7\\*][\\s\\u2009]*10[\\s\\u2009]*[-\\u2212\\u2013\\u2012][\\s\\u2009]*\\d+'\n", - "pval_rgx_matcher1 = RegexMatchSpan(rgx=rgx1)\n", - "rgx2 = u'[1-9]\\d?[\\xb7\\.]?\\d*[\\s\\u2009]*[eE][\\s\\u2009]*[-\\u2212\\u2013\\u2012][\\s\\u2009]*\\d+'\n", - "pval_rgx_matcher2 = RegexMatchSpan(rgx=rgx2)\n", - "rgx3 = u'0\\.0000+\\d+'\n", - "pval_rgx_matcher3 = RegexMatchSpan(rgx=rgx3)\n", - "pval_rgx_matcher = Union(pval_rgx_matcher1, pval_rgx_matcher2, pval_rgx_matcher3)\n", - "# pval_matcher = PvalMatcher()\n", - "ngrams = TableNgrams(n_max=7)\n", - "pval_rgx_extractor = EntityExtractor(ngrams, pval_rgx_matcher)\n", - "# %time pval_c = pval_extractor.extract(corpus.get_tables(), name='all')\n", - "\n", - "# 2: column-based matcher\n", - "\n", - "from snorkel.candidates import CellSpace\n", - "from snorkel.matchers import CellNameRegexMatcher\n", - "\n", - "cells = CellSpace()\n", - "pval_rgx = 'p\\s?.?\\s?value'\n", - "pval_rgxname_matcher = CellNameRegexMatcher(axis='col', rgx=pval_rgx, n_max=3, ignore_case=True, header_only=True, max_chars=20)\n", - "pval_rgxname_extractor = EntityExtractor(cells, pval_rgxname_matcher)\n", - "\n", - "# %time pval_regex_candidates = pval_rgxname_extractor.extract(corpus.get_tables(), name='all')\n", - "\n", - "# 3: combine the two\n", - "\n", - "from snorkel.candidates import UnionExtractor\n", - "pval_extractor = UnionExtractor([pval_rgx_extractor, pval_rgxname_extractor])" + "Here, we perform a bit of filtering in post-processing." ] }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 44, "metadata": { "collapsed": false }, @@ -573,985 +468,33 @@ "name": "stdout", "output_type": "stream", "text": [ - " 28\n", - "2 8 1.44 E â’ 06 3 8 6.08 E â’ 06 4 8 1.09 E â’ 05 5 8 1.11 E â’ 05 6 8 2.61 E â’ 05\n" + "22536 20258\n" ] } ], "source": [ - "special_doc = [doc for doc in corpus.documents if doc.name == '23509613'][0]\n", - "special_table = special_doc.tables[4]\n", - "\n", - "pval_regex_candidates = pval_rgx_extractor.extract([special_table])\n", - "# pval_regex_canidates = pval_rgxname_extractor.extract(corpus.get_tables())\n", - "print len(pval_regex_candidates)\n", - "for c in pval_regex_candidates[:5]:\n", - " print c.context.cell.row_num, c.context.cell.col_num, c.get_span(), #c.context.cell.head_cell('col').text" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'pval_c' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mngrams\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTableNgrams\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m7\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mprint\u001b[0m \u001b[0;34m'Got %d candidates, e.g.:'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpval_c\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mcandidate\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mpval_c\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0municode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcandidate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'pval_c' is not defined" - ] - } - ], - "source": [ - "ngrams = TableNgrams(n_max=7)\n", - "\n", - "print 'Got %d candidates, e.g.:' % len(pval_c)\n", - "for candidate in pval_c[:10]:\n", - " print unicode(candidate)\n", - " print candidate.context\n", - "# for t in ngrams.apply(candidate.context):\n", - "# print unicode(t.get_span())\n", - "# print re.match(rgx, t.get_span())\n", - "# print [unicode(t.get_span()) for t in ngrams.apply(candidate.context)]\n", - "# print\n", - "# print candidate.get_attrib_span('words')\n", - " print" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Filter nested p-value estimates e.g. 1.2\\*10^-7 and 2*10^-7" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1246 1246\n" - ] - } - ], - "source": [ - "# load existing candidates into a dict\n", - "span_dict = { str(span.context.cell) : list() for span in pval_c }\n", - "for span in pval_c:\n", - " span_dict[str(span.context.cell)].append( (span.char_start, span.char_end) )\n", - "\n", - "def nested(ivl1, ivl2):\n", - " if ivl1 != ivl2 and ivl2[0] <= ivl1[0] <= ivl1[1] <= ivl2[1]:\n", - " return True\n", - " else:\n", - " return False\n", - "\n", - "new_pval_c = list()\n", - "for span in pval_c:\n", - " span_ivl = span.char_start, span.char_end\n", - " span_name = str(span.context.cell)\n", - " if all([not nested(span_ivl, other_ivl) for other_ivl in span_dict[span_name]]):\n", - " new_pval_c.append(span)\n", - "# else:\n", - "# print span_ivl, span_dict[span_name]\n", - "# print unicode(span)\n", - "# print unicode(span.context.cell.text)\n", - "# print span.uid\n", - "# print span.context.row_num, span.context.col_num\n", - "# print unicode(span)\n", - "# print\n", - "# print [(cell, cell.row_num, cell.col_num) for cell in span.context.table.cells]\n", - "# break\n", - "\n", - "print len(new_pval_c), len(pval_c)\n", - "pval_c = new_pval_c" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Statistics" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First, how many p-values that should be present do we extract?" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6.2e-05\n", - "1.85e-20\n" - ] - } - ], - "source": [ - "# we need to define a p-value -> float converter\n", - "from extractor.util import pvalue_to_float, gold_pval_stats, gold_pval_precision\n", - "\n", - "print pvalue_to_float(u\"6.2Ă—10 â’5\")\n", - "print pvalue_to_float(u\"1.85Ă—10 â’20\")" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from kb import KnowledgeBase\n", - "kb = KnowledgeBase()\n", - "gold_set_pvals = frozenset([ (doc.name, pval) for doc in corpus.documents for pval in kb.pvals_by_pmid(int(doc.name)) ])\n", - "gold_set_dict = {doc.name: kb.assoc_by_pmid(int(doc.name)) for doc in corpus.documents }" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will be looking at precision/recall over p-values that are known to be associated with a SNP, and the rsid of that SNP occurs somewhere in the document (as determined above)." - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Found 107 gold mentions, e.g.:\n", - "[('17903300', 1e-07), ('17903300', 2e-07), ('17903294', 2e-06), ('17903296', 2e-07), ('17903303', 4.9999999999999996e-06)]\n", - "\n", - "p-value candidate extraction statistics:\n", - "[('17684544', 1e-21), ('17684544', 4e-07), ('17684544', 3e-06), ('17903292', 9.000000000000001e-09), ('17903292', 2e-06), ('17903292', 4e-06), ('17903292', 7e-06), ('17903292', 8e-06), ('17903293', 1e-14), ('17903293', 4e-12)]\n", - "[('17684544', -21.0), ('17684544', -7.0), ('17684544', -6.0), ('17903292', -9.0), ('17903292', -6.0), ('17903293', -14.0), ('17903293', -12.0), ('17903293', -8.0), ('17903293', -7.0), ('17903293', -6.0)]\n", - "[('17684544', -49.0), ('17684544', -41.0), ('17684544', -34.0), ('17684544', -28.0), ('17684544', -22.0), ('17684544', -21.0), ('17684544', -20.0), ('17684544', -18.0), ('17684544', -17.0), ('17684544', -14.0)]\n", - "# of gold annotations\t= 35\n", - "# of candidates\t\t= 78\n", - "Candidate recall\t= 0.886\n", - "Candidate precision\t= 0.397\n", - "None\n" - ] - } - ], - "source": [ - "from extractor.util import gold_pval_stats, gold_pval_stats_limited\n", - "\n", - "print 'Found %d gold mentions, e.g.:' % len(gold_set_pvals)\n", - "print list(gold_set_pvals)[:5]\n", - "print\n", - "\n", - "print 'p-value candidate extraction statistics:'\n", - "# print gold_pval_stats(pval_c, gold_set_pvals, gold_set_dict)\n", - "print gold_pval_stats_limited(pval_c, gold_set_dict, rs_candidates)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Some debugging... We will print the papers and their pvalues that are not found in the paper. Below, is the list of all SNPs associated with the paper, so we can find the SNP that is missing." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from extractor.util import gold_pval_recall, gold_pval_precision\n", - "missing = list(gold_pval_recall(pval_c, gold_set_dict, rs_candidates))\n", - "# print gold_pval_precision(pval_c, gold_set_pvals)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17903298 -8.0\n", - "[(2e-06, u'Diabetes related insulin traits', -6.0, u'rs2877832'), (3e-06, u'Diabetes related insulin traits', -6.0, u'rs2877832'), (2e-08, u'Fasting plasma glucose', -8.0, u'rs2722425'), (4.9999999999999996e-06, u'Fasting plasma glucose', -6.0, u'rs10510634'), (7e-07, u'Diabetes (incident)', -7.0, u'rs10497721'), (8e-06, u'Diabetes related insulin traits', -6.0, u'rs10486607'), (9e-06, u'Diabetes related insulin traits', -6.0, u'rs2066219'), (4.9999999999999996e-06, u'Fasting plasma glucose', -6.0, u'rs180730'), (6e-06, u'Fasting plasma glucose', -6.0, u'rs180730'), (9e-06, u'Fasting plasma glucose', -6.0, u'rs2722425'), (7e-06, u'Fasting plasma glucose', -6.0, u'rs7731657')]\n", - "\n", - "17903302 -9.0\n", - "[(2e-06, u'Blood pressure', -6.0, u'rs10493340'), (3e-06, u'Blood pressure', -6.0, u'rs1963982'), (3e-06, u'Blood pressure', -6.0, u'rs935334'), (2e-06, u'Tonometry', -6.0, u'rs6063312'), (3e-06, u'Tonometry', -6.0, u'rs770189'), (6e-06, u'Tonometry', -6.0, u'rs10514688'), (6e-06, u'Tonometry', -6.0, u'rs7042864'), (8e-06, u'Tonometry', -6.0, u'rs1322512'), (2e-07, u'Tonometry', -7.0, u'rs3773643'), (2e-06, u'Tonometry', -6.0, u'rs3793427'), (2e-06, u'Tonometry', -6.0, u'rs6492654'), (3e-06, u'Tonometry', -6.0, u'rs1367248'), (4e-06, u'Tonometry', -6.0, u'rs10521232'), (4e-06, u'Tonometry', -6.0, u'rs3766680'), (4e-06, u'Tonometry', -6.0, u'rs1371924'), (8e-06, u'Tonometry', -6.0, u'rs10488172'), (4e-06, u'Blood pressure', -6.0, u'rs4370013'), (4e-06, u'Blood pressure', -6.0, u'rs10491334'), (4.9999999999999996e-06, u'Blood pressure', -6.0, u'rs2121070'), (7e-06, u'Blood pressure', -6.0, u'rs2509458'), (3e-07, u'Blood pressure', -7.0, u'rs7591163'), (1e-09, u'Blood pressure', -9.0, u'rs3096277')]\n", - "\n", - "17903298 -6.0\n", - "[(2e-06, u'Diabetes related insulin traits', -6.0, u'rs2877832'), (3e-06, u'Diabetes related insulin traits', -6.0, u'rs2877832'), (2e-08, u'Fasting plasma glucose', -8.0, u'rs2722425'), (4.9999999999999996e-06, u'Fasting plasma glucose', -6.0, u'rs10510634'), (7e-07, u'Diabetes (incident)', -7.0, u'rs10497721'), (8e-06, u'Diabetes related insulin traits', -6.0, u'rs10486607'), (9e-06, u'Diabetes related insulin traits', -6.0, u'rs2066219'), (4.9999999999999996e-06, u'Fasting plasma glucose', -6.0, u'rs180730'), (6e-06, u'Fasting plasma glucose', -6.0, u'rs180730'), (9e-06, u'Fasting plasma glucose', -6.0, u'rs2722425'), (7e-06, u'Fasting plasma glucose', -6.0, u'rs7731657')]\n", - "\n", - "17903298 -7.0\n", - "[(2e-06, u'Diabetes related insulin traits', -6.0, u'rs2877832'), (3e-06, u'Diabetes related insulin traits', -6.0, u'rs2877832'), (2e-08, u'Fasting plasma glucose', -8.0, u'rs2722425'), (4.9999999999999996e-06, u'Fasting plasma glucose', -6.0, u'rs10510634'), (7e-07, u'Diabetes (incident)', -7.0, u'rs10497721'), (8e-06, u'Diabetes related insulin traits', -6.0, u'rs10486607'), (9e-06, u'Diabetes related insulin traits', -6.0, u'rs2066219'), (4.9999999999999996e-06, u'Fasting plasma glucose', -6.0, u'rs180730'), (6e-06, u'Fasting plasma glucose', -6.0, u'rs180730'), (9e-06, u'Fasting plasma glucose', -6.0, u'rs2722425'), (7e-06, u'Fasting plasma glucose', -6.0, u'rs7731657')]\n", - "\n" - ] - } - ], - "source": [ - "from math import log10, floor\n", - "\n", - "for pmid, pval in missing[:5]:\n", - " print pmid, pval\n", - " print [(a.pvalue, a.phenotype.name, floor(log10(a.pvalue)), a.snp.rs_id) for a in gold_set_dict[pmid]]\n", - " print" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The SNPs above are either labeled incorrectly (most of the time), or could also not occur in tables." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Extract candidate relations between SNPs and p-values" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from snorkel.candidates import AlignedTableRelationExtractor\n", - "# Relation Extractor:\n", - "relation_extractor = AlignedTableRelationExtractor(rsid_extractor, pval_rgx_extractor, axis='row')" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 8min 13s, sys: 7min 49s, total: 16min 3s\n", - "Wall time: 49min 45s\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"1.93E-13\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"2.04E-12\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"6.80E-20\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"1.39E-21\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"5.90E-08\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs1992662\", context=None, chars=[0,8], words=[0,0]), Span(\"7.59E-05\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs1992660\", context=None, chars=[0,8], words=[0,0]), Span(\"4.53E-05\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs10521209\", context=None, chars=[0,9], words=[0,0]), Span(\"8.65E-05\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs10521209\", context=None, chars=[0,9], words=[0,0]), Span(\"8.68E-05\", context=None, chars=[0,7], words=[0,0]))\n", - "SpanPair(Span(\"rs1553575\", context=None, chars=[0,8], words=[0,0]), Span(\"1.68E-06\", context=None, chars=[0,7], words=[0,0]))\n", - "22077 relations extracted\n" - ] - } - ], - "source": [ - "%time candidates = relation_extractor.extract(corpus.get_tables(), name='all')\n", - "\n", - "for cand in candidates[:10]: \n", - " print cand\n", - "print \"%s relations extracted\" % len(candidates)" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "63\n", - "63\n" - ] - } - ], - "source": [ - "print candidates[1000].span0.context.cell.row_num\n", - "print candidates[1000].span1.context.cell.row_num" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Statistics" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's consider the subset of gold SNPs that have been found to match somewhere with a table." - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[u'rs9932186', u'rs6880595', u'rs12989701', u'rs6606686', u'rs12470505']\n" - ] - } - ], - "source": [ - "rs_subset = set([span_pair.span0.get_span().lower() for span_pair in candidates])\n", - "print list(rs_subset)[:5]" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[(u'rs1883025', 3e-27), (u'rs10811661', 7e-07), (u'rs1532085', 7e-47), (u'rs174546', 6e-07), (u'rs163879', 2e-11)]\n", - "5304\n" - ] - } - ], - "source": [ - "gold_relations = set([(assoc.snp.rs_id, assoc.pvalue) for doc in corpus.documents for assoc in kb.assoc_by_pmid(doc.name) if assoc.snp.rs_id.lower() in rs_subset])\n", - "print list(gold_relations)[:5]\n", - "print len(gold_relations)" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "2e-24" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "kb.assoc_by_pmid(18483556)[10].pvalue" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "# of gold annotations\t= 4853\n", - "# of candidates\t\t= 16645\n", - "Candidate recall\t= 0.792\n", - "Candidate precision\t= 0.231\n" - ] - } - ], - "source": [ - "from extractor.util import gold_rspval_stats\n", - "\n", - "gold_rspval_stats(candidates, gold_relations)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Why low precision?" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"1.93E-13\", context=None, chars=[0,7], words=[0,0]))\n", - "Table('17684544', 1) 2 1\n", - "\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"2.04E-12\", context=None, chars=[0,7], words=[0,0]))\n", - "Table('17684544', 1) 2 1\n", - "\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"6.80E-20\", context=None, chars=[0,7], words=[0,0]))\n", - "Table('17684544', 1) 2 1\n", - "\n", - "SpanPair(Span(\"rs2076756\", context=None, chars=[0,8], words=[0,0]), Span(\"5.90E-08\", context=None, chars=[0,7], words=[0,0]))\n", - "Table('17684544', 1) 2 1\n", - "\n", - "SpanPair(Span(\"rs1992662\", context=None, chars=[0,8], words=[0,0]), Span(\"7.59E-05\", context=None, chars=[0,7], words=[0,0]))\n", - "Table('17684544', 1) 3 1\n", - "\n" - ] - } - ], - "source": [ - "from extractor.util import gold_rspval_precision\n", - "\n", - "strange_rels = gold_rspval_precision(candidates, gold_relations)\n", - "for rel in strange_rels[:5]:\n", - " print rel\n", - " print rel.span0.context.table, rel.span0.context.cell.row_num, rel.span0.context.cell.col_num\n", - " print" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It seems like there are many pvalues for the same span and only one of them is actually correct." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Save this for now" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "import re\n", - "from extractor.util import pvalue_to_float\n", - "\n", - "def clean_rsid(rsid):\n", - " return re.sub('/.+', '', rsid)\n", - "\n", - "with open('pval-rsid.raw.cols.tsv', 'w') as f:\n", - " for rel in candidates:\n", - " pmid = rel.span0.context.document.name\n", - " table_id = rel.span0.context.table.position\n", - " row_id = rel.span0.context.cell.row_num\n", - " col_id = rel.span0.context.cell.col_num\n", - " rsid = rel.span0.get_span()\n", - " pval = pvalue_to_float(rel.span1.get_span())\n", - "\n", - " out_str = '%s\\t%s\\t%d\\t%d\\t%d\\t%f\\n' % (pmid, clean_rsid(rsid), table_id, row_id, col_id, pval)\n", - " f.write(out_str)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Store tables that have pvalue columns" - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "import re\n", - "pval_rgx = 'p\\s?.?\\s?value'\n", - "lod_rgx = 'LOD'\n", - "\n", - "with open('table-annotations.tsv', 'w') as f:\n", - " for doc in corpus.documents:\n", - " for table in doc.tables:\n", - " lod_found = 0\n", - " pval_found = 0\n", - " for cell in table.cells:\n", - " if not pval_found and len(cell.text) < 30 and re.search(pval_rgx, cell.text, re.IGNORECASE):\n", - " pval_found = 1\n", - " if not lod_found and re.search(lod_rgx, cell.text):\n", - " lod_found = 1\n", - " if pval_found and lod_found: break\n", - " \n", - " out_str = '%s\\t%s\\t%s\\t%s\\n' % (doc.name, table.position, pval_found, lod_found)\n", - " f.write(out_str) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Learning the rsid/pvalue relation" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Load the gold set" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from extractor.util import get_exponent, pvalue_to_float\n", - "\n", - "gold_relations = set([(assoc.snp.rs_id, assoc.pvalue) for doc in corpus.documents for assoc in kb.assoc_by_pmid(doc.name) if assoc.snp.rs_id.lower() in rs_subset])\n", - "gold_relations = set([ (rs_id, get_exponent(pval)) for rs_id, pval in gold_relations ])" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4614 16280\n" - ] - } - ], - "source": [ - "def spair2uid(span_pair):\n", - " doc_id = span_pair.span0.context.document.name\n", - " table_id = str(span_pair.span0.context.table.position)\n", - " str1 = span_pair.span0.get_span()\n", - " str2 = span_pair.span1.get_span()\n", - " return (doc_id, table_id, str1, str2)\n", - "\n", - "gt_dict_pos = dict()\n", - "gt_dict_neg = dict()\n", - "for crel in candidates:\n", - " uid = spair2uid(crel)\n", - " if (crel.span0.get_span(), get_exponent(pvalue_to_float(crel.span1.get_span()))) in gold_relations:\n", - " gt_dict_pos[uid] = +1\n", - " else:\n", - " gt_dict_neg[uid] = -1\n", - "\n", - "print len(gt_dict_pos), len(gt_dict_neg)\n", - "gt_dict = dict(gt_dict_pos.items() + gt_dict_neg.items())" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "20894" - ] - }, - "execution_count": 40, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(gt_dict)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Load the features" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Extract features, and store them to a file." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Building feature index...\n" - ] - } - ], - "source": [ - "from snorkel.features import TableNgramPairFeaturizer\n", - "\n", - "# pkl_f = 'phenotype_feats.pkl'\n", - "# try:\n", - "# with open(pkl_f, 'rb') as f:\n", - "# featurizer = cPickle.load(f)\n", - "# except:\n", - "featurizer = TableNgramPairFeaturizer()\n", - "featurizer.fit_transform(candidates)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "for f in featurizer.get_features_by_candidate(candidates[0])[:10]: print f" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "pkl_f = 'rsid_pval_feats.pkl'\n", - "with open(pkl_f, 'w+') as f:\n", - " cPickle.dump(featurizer, f)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Split into training and test sets" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "# Split into train and test set\n", - "training_candidates = []\n", - "gold_candidates = []\n", - "gold_labels = []\n", - "n_half = len(candidates)/2\n", - "for c in candidates[:n_half]:\n", - " uid = spair2uid(c)\n", - " if uid in gt_dict:\n", - " gold_candidates.append(c)\n", - " gold_labels.append(gt_dict[uid])\n", - " else:\n", - " training_candidates.append(c)\n", - "training_candidates.extend(candidates[n_half:])\n", - "gold_labels = np.array(gold_labels)\n", - "print \"Training set size: %s\" % len(training_candidates)\n", - "print \"Gold set size: %s\" % len(gold_candidates)\n", - "print \"Positive labels in training set: %s\" % len([c for c in training_candidates if gt_dict.get(spair2uid(c),0)==1])\n", - "print \"Negative labels in training set: %s\" % len([c for c in training_candidates if gt_dict.get(spair2uid(c),0)==-1])\n", - "print \"Positive labels in gold set: %s\" % len([c for c in gold_candidates if gt_dict[spair2uid(c)]==1])\n", - "print \"Negative labels in gold set: %s\" % len([c for c in gold_candidates if gt_dict[spair2uid(c)]==-1])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Create the model." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Labeling functions" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "rsid_keywords = [\"id\", \"rsid\", \"snp\"]\n", - "pval_keywords = [\"value\", \"p-value\", \"p-val\", \"p_value\", \"pvalue\"]\n", - "\n", - "# positive LFs\n", - "def LF_pval_header(m):\n", - " # if \"pvalue\" is mentioned in first or last row, it's probably correct\n", - " pass\n", - "def LF_pval_aligned(m):\n", - " # if \"pvalue\" is mentioned in aligned cells, it's probably correct\n", - " return +1 if any(kw in m.span1.aligned_ngrams('words') for kw in pval_keywords) else 0\n", - "def LF_id_aligned(m):\n", - " # if \"id\" is mentioned in aligned cells, it's probably correct \n", - " return +1 if any(kw in m.span0.aligned_ngrams('words') for kw in rsid_keywords) else 0\n", - "def LF_phen_aligned(m):\n", - " # if there is an aligned phenotype, then it is probably correct\n", - " pass\n", - "\n", - "# negative LFs\n", - "def LF_align(m):\n", - " # if the two spans don't align in the table, then they're clearly wrong \n", - " return -1 if m.span0.context.row_num != m.span1.context.row_num and \\\n", - " m.span0.context.col_num != m.span1.context.col_num \\\n", - " else 0\n", - "def LF_diff_col(m):\n", - " return -1 if m.span0.context.col_num != m.span1.context.col_num else 0\n", - "\n", - "pos_LFs = [LF_pval_aligned, LF_id_aligned]\n", - "neg_LFs = [LF_align]\n", - "LFs = pos_LFs + neg_LFs" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "ename": "TypeError", - "evalue": "__init__() got an unexpected keyword argument 'featurizer'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0msnorkel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeatures\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mNgramFeaturizer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mtraining_set\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTrainingSet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtraining_candidates\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLFs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeaturizer\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTableNgramPairFeaturizer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m: __init__() got an unexpected keyword argument 'featurizer'" - ] - } - ], - "source": [ - "from snorkel.snorkel import TrainingSet\n", - "from snorkel.features import NgramFeaturizer\n", - "\n", - "training_set = TrainingSet(training_candidates, LFs, featurizer=TableNgramPairFeaturizer())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Results" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "lf_stats = training_set.lf_stats()\n", - "lf_stats[:5]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "lf_stats.hist(\"coverage\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from snorkel.snorkel import Learner\n", - "import snorkel.learning\n", - "from snorkel.learning import LogReg\n", - "print snorkel.learning.__dict__\n", - "\n", - "learner = Learner(training_set, model=snorkel.learning.LogRegSKLearn())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Splitting into CV and test set\n", - "n_half = len(gold_candidates)/2\n", - "test_candidates = gold_candidates[:n_half]\n", - "test_labels = gold_labels[:n_half]\n", - "cv_candidates = gold_candidates[n_half:]\n", - "cv_labels = gold_labels[n_half:]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "from snorkel.learning_utils import GridSearch\n", - "\n", - "gs = GridSearch(learner, ['mu', 'lf_w0'], [[1e-5, 1e-7],[1.0,2.0]])\n", - "gs_stats = gs.fit(cv_candidates, cv_labels)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "gs_stats" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "learner.test(test_candidates, test_labels)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "learner.feature_stats(n_max=10)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "mislabeled_cand = learner.mislabeled_test_candidates(test_candidates, test_labels)\n", - "for (c,p,g) in mislabeled_cand[50:500]:\n", - " snp_name = c.span0.get_span()\n", - " if snp_name not in gold_rel_dict: continue\n", - " print c.span0.context.document.name\n", - " print c.span0.context \n", - " print c.span1.context\n", - " print" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "gold_rel_dict = dict(gold_relations)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "gold_rel_dict" + "rels = []\n", + "loc2rsid = dict()\n", + "with open('pval-rsid.raw.cols.tsv') as f:\n", + " for line in f:\n", + " pmid, rsid, table_id, row_id, col_id, pval = line.strip().split('\\t')\n", + " loc = pmid, table_id, row_id\n", + " rels.append((pmid, rsid, table_id, row_id, col_id, pval))\n", + " if loc not in loc2rsid: loc2rsid[loc] = set()\n", + " loc2rsid[loc].add(rsid)\n", + "\n", + "n = 0\n", + "with open('pval-rsid.raw.cols.filtered.tsv', 'w') as f:\n", + " for rel in rels:\n", + " pmid, rsid, table_id, row_id, col_id, pval = rel\n", + " loc = pmid, table_id, row_id\n", + " if len(loc2rsid[loc]) > 1: continue\n", + " \n", + " out_str = '%s\\t%s\\t%s\\t%s\\t%s\\t%s\\n' % (pmid, rsid, table_id, row_id, col_id, pval)\n", + " f.write(out_str)\n", + " n += 1\n", + " \n", + "print len(rels), n" ] }, { diff --git a/notebooks/util/phenotype.mapping.annotated.txt b/notebooks/util/phenotype.mapping.annotated.txt index 8bd93b6..de31d2f 100644 --- a/notebooks/util/phenotype.mapping.annotated.txt +++ b/notebooks/util/phenotype.mapping.annotated.txt @@ -1 +1 @@ -Systolic blood pressure Hypertension|Blood Pressure 2 "Systemic sclerosis, dcSSc" Systemic Sclerosis 3 Waist circumference Body Fat Distribution WC_BMI_pooled 2 Primary tooth development tooth eruption|height g-men: glabella to mid-endocanthion distance 2 Waist circumference Body Fat Distribution WC_BMI_men 2 Body mass index body mass index 3 "Hip geometry, neck width, gender differentiated in females" association bone shaftz1r 2 Systolic blood pressure Hypertension|Blood Pressure SBP 2 Systolic blood pressure Cardiovascular Disease|Blood Pressure 2 "Systemic sclerosis, IcSSc" Systemic Sclerosis 2 Non-word repetition reading|language 2 Primary tooth development tooth eruption|height exL-exR: left-to-right exocanthion distance 3 Corneal astigmatism corneal astigmatism|platelet-derived growth factor 3 "Cardiovascular disease risk factors, migraineurs with aura - ischemic stroke" Migraine|Cardiovascular Events|Cardiovascular 3 Factor VII hematological phenotypes "FVII, exam 5" 3 IgM levels Serum IgM 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG1" Master|Plasma Protein DG1 2 Diastolic blood pressure Hypertension|Blood Pressure DBP 2 Substance dependence European-Origin|Substance Dependence 3 "White blood cell types, neutrophil count" White Blood Cell Count|White Blood Cell 3 "Schizophrenia, schizoaffective disorder or bipolar disorder" Schizophrenia 3 Distal colon cancer colon cancer 3 Red blood cell traits Red Blood Cell|Resistance|Malaria MCH 2 Ankle brachial index atherosclerosis Ankle brachial index 3 "Hip geometry, neck section modulus, gender differentiated in males" association bone lsbmd 2 Glycated hemoglobin levels Glycated Hemoglobin 3 Serum IgE levels Serum IgE Levels 3 Disc degeneration lumbar disc degeneration 3 Cortical thickness "Bone Mineral Density,|Bone|Osteoporotic Fracture" 2 Handedness in dyslexia handedness|dyslexia 3 Tetralogy of Fallot Tetralogy Fallot 3 Usual bedtime circadian phenotypes|sleep Bedtime 3 Sensory disturbances after bilateral sagittal split ramus osteotomy sensory disturbances|split 2 Atopic dermatitis ATOPIC DERMATITIS 3 Serum hemoglobin levels erythrocyte MCV 2 "Liver function test: alkaline phosphatase, AST, ALT, GGT" biomarker traits Liver function: Alkaline phosphatase; AST; ALT; gamma-glutamyl transferase 3 Cardiac repolarisation "sudden cardiac death," 0 Systolic blood pressure blood pressure SBP 2 Migraine without aura migraine 3 Parkinson's disease Parkinson’s disease 3 Kawasaki disease Kawasaki Disease 3 Intracellular adhesion molecule-1 biomarker traits Intercellular adhesion molecule-1 3 Case-only systemic lupus erythematosus Systemic Lupus Erythematosus|Autoantibody 3 "Obesity, weight" Obesity|Obesity-Related Traits Weight 3 "Platelet aggregation, epinephrine" platelet aggregation Epi 2 u M 3 Breast cancer Breast Cancer 3 Age-related macular degeneration Age-Related Macular Degeneration 3 Telomere length homeostasis 0 Eating disorders "Eating|Behaviors,|Symptoms, Behaviors" BULIMIA 3 Inflammatory bowel disease inflammatory bowel disease 3 "HIV-1 control, setpoint" HIV-1 3 Sphingomyelin 16:1 Sphingolipid 2 Obesity-related traits Childhood Obesity|Childhood Urinary creatinine(mmol/d) 3 Early onset extreme obesity Onset|Obesity|Obesity Associated 3 Ovarian reserve ovarian reserve 3 Sexual dysfunction Sexual Dysfunction Arousal 3 Obesity-related traits Childhood Obesity|Childhood Triglycerides(mg/dL) 3 Rheumatoid arthritis rheumatoid arthritis 3 Ulcerative colitis inflammatory bowel disease 2 Temperament Temperament Character Inventory 3 Heart failure cardiovascular disease heart failure 3 "Type II diabetes, Indian" Type 2 Diabetes|Transferability 2 Mean body mass index waist circumference|body mass index Mean body mass index 3 Multiple sclerosis Multiple Sclerosis|Oligoclonal Band 3 White blood cell count White Blood Cell Count|White Blood Cell Basophils 3 Hepatitis B Chronic Hepatitis B 3 Menopause menopause 3 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome TG-BP 2 Obesity body mass index 2 "Bone mineral density, femoral neck" Bone Mineral Density 2 "Obesity, weight" Obesity|Obesity-Related Traits HIP 3 Behcet's disease Behçet's disease 3 Adverse response to chemotherapy in breast cancer chemotherapy-induced alopecia|breast cancer 3 Monocyte chemoattractant protein-1 biomarker traits Monocyte chemoattractant protein-1 3 "Systemic sclerosis, ATA positive" Systemic Sclerosis 3 Response to the antipsychotic treatment olanzapine Response Treatment|Antipsychotics Olanzapine – Excitement 3 Plasma CD40 ligand biomarker traits CD40 Ligand plasma 3 Waist-hip ratio Body Fat Distribution WHR_BMI_women 3 Glucosylceramide Sphingolipid 2 Morbidity-free survival at age 65 longevity|age-related phenotypes Morbidity-free survival at age 65 3 "Vitamin D, Vitamin K phylloquinone, Vitamin K % undercaboxylated osteocalcin" biomarker traits "Vitamin D, Vitamin K phylloquinone & Vitamin K % undercarboxylated osteocalcin" 3 Glioma increased disease risk 0 Anticoagulant levels Protein C funcPS 1 Obesity-related traits Childhood Obesity|Childhood Sedentary&lightactivity (min/d) 3 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein DG12 0 Tourette syndrome Tourette Syndrome 3 Cigarettes smoked per day Smoking Behaviors|Cigarette Smoking 2 Carotid-brachial pulse wave velocity arterial stiffness|blood pressure CB-PWV 1 Calcium levels Serum Calcium 3 "T-tau, Alzheimer's disease" Ď„ protein levels 2 Fasting plasma glucose diabetes-related traits 28 yr time averaged fpg 3 Smoking intensity Smoking Behaviors|Cigarette Smoking 2 Plasma vitamin K biomarker traits Vitamin K plasma phylloquinone 3 C-reactive protein biomarker traits C-reactive protein exam 7 3 Fasting glucose-related: homeostatic model assessment of insulin resistance fasting glucose|type 2 diabetes|glucose homeostasis 3 Time to first tooth eruption Primary Tooth Development 2 Ulcerative colitis Ulcerative colitis 3 Aortic root diameter aortic root 2 Testicular germ cell tumor "testicular cancer," 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome WC-TG 2 Sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual WCadjBMI 3 Hair curl Common Traits Hair curl 3 "Platelet aggregation, adenosine diphosphate" platelet aggregation Epi EC50 2 Word reading reading|language 3 Obesity-related traits Childhood Obesity|Childhood Weight z-score change (SD/y) 3 Stage 2 exercise heart rate exercise responses|artery Across phenotypes 2 Red blood cell count Cell Traits|Red Blood Cell MCV 2 Waist circumference complex disease Waist Circumference 3 Sexual dysfunction Sexual Dysfunction Lubrication 3 Smokers who quit versus those who did not Smoking Behaviors|Cigarette Smoking 2 Eye color "Skin,|Pigmentation" Eye C' 3 Body mass index complex disease BMI 3 "Brain MRI, lateral ventricular volume" brain|cognitive test ALLV 3 Femoral neck and bone mineral density in women Osteoporosis-Related Traits|Gene Expression Profiling FN BMD 2 "Platelet aggregation, collagen" platelet aggregation lag 2 Systolic blood pressure arterial stiffness|blood pressure blood-pressure 2 Obesity-related traits Childhood Obesity|Childhood "Dinner intake, adjEER (kcal)" 3 Risperidone-induced change in hip circumference antipsychotic drugs|metabolic side effects Risperidone - Waist Circumference 3 Major depressive disorder major depression 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein FUCA 0 Osteoarthritis hip|osteoarthritis 3 Warfarin maintenance dose warfarin 2 Fasting plasma glucose diabetes-related traits fasting plasma glucose 3 Freckling Common Traits Red hair 0 Lymphoma Malignancies 2 Serum bilirubin levels bilirubin levels 3 "Hip geometry, neck section modulus, gender differentiated in females" association bone neck section modulus** 3 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein FUCA 2 Red blood cell traits Red Blood Cell|Resistance|Malaria MCV 2 Age at smoking initiation Smoking Behaviors|Cigarette Smoking 2 Soluble ICAM-1 ICAM-1 3 Atrial fibrillation Lone Atrial Fibrillation 3 28-yr time-averaged fasting plasma glucose diabetes-related traits 28 yr time averaged fpg 3 Red hair color Common Traits Freckling 0 Ovarian cancer in BRCA1 mutation carriers Breast Cancer|Breast Ovarian Cancer|Carriers 3 Cholesterol Serum Cholesterol Levels HDL-C 3 Breast Cancer in BRCA1 mutation carriers Breast Cancer|Breast Ovarian Cancer|Carriers 3 Neck shaft angle in men Osteoporosis-Related Traits|Gene Expression Profiling NSA 2 Reflected wave amplitude arterial stiffness|blood pressure RW 3 Type II diabetes Metabolic Syndrome T2D 2 Viscosity hematological phenotypes Viscosity 3 Prostate cancer prostate cancer|breast 3 Collagen-induced platelet aggregation hematological phenotypes platelet aggregation (collagen-induced) 3 Nonalcoholic fatty liver disease Metabolic Traits|Nonalcoholic Fatty Liver Disease 3 Upper aerodigestive tract cancers Cancers|Conducted|Upper Aerodigestive Tract 3 Primary tooth development tooth eruption|height alL-alR: left-to-right alare distance 3 "Platelet aggregation, epinephrine" platelet aggregation Epi EC50 3 Adiponectin levels Adiponectin Levels 3 "HIV-1 control, progression" HIV-1 3 "Type I diabetes autoantibodies, T1D" Type 1 Diabetes|Autoantibody 3 Alzheimer's disease Alzheimer’s disease 3 Plasma C-reactive protein complex disease 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein DG12 2 "Plasma Phospholipid levels, EPA" Plasma Phospholipid|Fatty Acids 3 Obesity childhood obesity 3 Femoral neck bone geometry Appendicular Lean Mass|Femoral Neck Bone Geometry 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein DG12 2 "Breast cancer, all races" Breast Cancer 3 Post-exercise 3 minute recovery: heart rate exercise responses|artery Post-exercise 3 minute recovery heart rate 3 Glycated hemoglobin diabetes-related traits hemoglobin a1c 2 Serum metabolites Metabolite rs number 2 B-type natriuretic peptide biomarker traits B-type natriuretic peptide 3 Bone mineral density Bone Mineral Density 3 Eye color Common Traits Green eyes 3 Migraine migraine 3 Left ventricular systolic dimension exercise responses|artery Across left ventricular phenotypes 2 Asthma Asthma 3 Natriuretic peptide levels NT-proBNP 1 Ceramide 24:0 Sphingolipid 2 Intraocular pressure Primary Open-Angle Glaucoma|Intraocular Pressure 3 Late onset Alzheimer's disease Late-Onset Alzheimer's Disease 3 Height Height 3 "Coronary heart disease risk factor, LDL-C" Coronary Heart Disease LDL-C 3 Hemoglobin hematological phenotypes hemoglobin 3 Olanzapine-induced change in total cholesterol antipsychotic drugs|metabolic side effects Olanzapine - Total Cholesterol 3 "Cardiovascular disease risk factors, migraineurs with aura - major CVD" Migraine|Cardiovascular Events|Cardiovascular 3 "Platelet aggregation, epinephrine" platelet aggregation ADP 2 u M 3 Hair color: black versus blond Hair Color|Skin Pigmentation 2 Serum dehydroepiandrosterone sulphate levels steroid 0 Follicular lymphoma Diffuse Large B-cell Lymphoma|Follicular Lymphoma|Diffuse 3 "Hip geometery, neck shaft angle, gender differentiated in males" association bone necklengf 2 Hair color Common Traits Red hair 3 "Brain MRI, temporal brain volume" brain|cognitive test temporal brain volume 3 Pulmonary function Pulmonary Function|Lung Function 3 Mean corpuscular volume Cell Traits|Red Blood Cell MCHC 2 Anticoagulant levels Protein C fPS 1 Left ventricular mass exercise responses|artery left ventricular mass 3 Type I diabetes Type 1 Diabetes 3 "Lipoprotein-associated phospholipase A2 activity and mass, activity" phospholipase A 2 IgG glycosylation Human Immunoglobulin|Cancers|-Glycosylation 3 Gray matter volume Schizophrenia|Matter Volume 3 Ovarian cancer ovarian cancer 3 Red blood cell count Cell Traits|Red Blood Cell RBC count 3 Longevity longevity 3 Schizophrenia Schizophrenia 3 Left ventricular diastolic dimension exercise responses|artery left ventricular diastolic dimension 3 Glaucoma Normal Tension Glaucoma 3 "Eye color traits, 1st principal component on transformed hue and saturation values" Eye Color C HS1 2 "Coronary heart disease risk factor, hypertension" Coronary Heart Disease Hypertension 3 Neck width in men Osteoporosis-Related Traits|Gene Expression Profiling NW 2 Type 1 diabetes nephropathy Type 1 Diabetes|Diabetic Nephropathy ESRD 3 "Obesity, hip" Obesity|Obesity-Related Traits BMI 2 Mean artierial pressure arterial stiffness|blood pressure MAP 2 HDL cholesterol Cardiovascular Disease HDL-cholesterol 3 Uric acid levels uric acid levels 3 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein DG9 2 Borderline personality disorder features borderline personality 3 Intracranial aneurysm intracranial aneurysm 3 Osteoarthritis osteoarthritis 3 "Metabolic syndrome bivariate trait, waist circumference and fasting glucose" Metabolic Syndrome WC-GLUC 2 Vertical cup-disc ratio Optic Disc 3 Total plasma cholesterol complex disease 0 Left ventricular mass exercise responses|artery Across left ventricular phenotypes 2 Systolic blood pressure complex disease 0 Schizophrenia schizophrenia|cytomegalovirus infection|infection suggests 3 HDL cholesterol complex disease 0 Femoral neck bone mineral density Osteoporosis-Related Phenotypes 2 Metabolic syndrome Metabolic Syndrome HDLC-WC 3 Green eyes Common Traits Eye color 2 Bipolar disorder psychiatric disorder 2 Obesity-related traits Childhood Obesity|Childhood BMI (kg/m 2 ) 3 Dengue shock syndrome Dengue shock syndrome 3 Progressive supranuclear palsy Progressive Supranuclear Palsy 3 C-reactive protein biomarker traits C-reactive protein exam 6 3 Thyroid stimulating hormone complex disease Thyroid Stimulating Hormone 3 Hypertension Cardiovascular Disease|Blood Pressure 2 Fasting insulin-related: homeostatic model assessment of insulin resistance fasting glucose|type 2 diabetes|glucose homeostasis 3 Cocaine dependence cocaine dependence 3 Retinal arteriolar caliber resistance 0 "Obesity and osteoporosis, body mass index and bone mineral density, males" Obesity|Osteoporosis Phenotypes 2 "White blood cell types, eosinophil count" White Blood Cell Count|White Blood Cell 3 Digestive system disease Barrett’s Esophagus|Esophageal Adenocarcinoma 3 "Obesity, hip" Obesity|Obesity-Related Traits HIP 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell MCHC 2 "Antipsychotic-induced QTc interval prolongation, quetiapine" cardiac arrhythmias quetiapine/QTc 3 Pack-years Smoking Behaviors|Cigarette Smoking 2 Waist circumference Cardiovascular Disease waist circumference 3 Paget's disease of bone Paget’s disease bone 3 Percent predicted forced expiratory flow pulmonary function for latest exam 2 Adiponectin levels Type 2 Diabetes|Adiponectin Levels 3 Mean corpuscular hemoglobin concentration Cell Traits|Red Blood Cell MCHC 2 Cardiovascular disease risk factors cardiovascular-related traits 3 Insulin resistance/response Insulin Resistance|Copy Number Variation 3 Waist-hip ratio Body Fat Distribution WHR_BMI_pooled 2 Sudden cardiac arrest Sudden Cardiac Death 3 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome HDLC-TG 2 HDL Metabolic Syndrome Log HDL-C (mmol/l) 2 Hypertension Hypertension|Blood Pressure 2 Thyroid hormone levels Thyroid|Differences|Thyroid Function FT4 3 "Platelet aggregation, epinephrine" platelet aggregation ADP 3 u M 3 Mean corpuscular volume Cell Traits|Red Blood Cell MCH 3 Airway hyperresponsiveness airway responsiveness 3 Non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein ALB 3 "Esophageal cancer, total gastric" esophageal squamous cell carcinoma|gastric adenocarcinoma 3 Eye color Common Traits Hair color 0 Urinary albumin excretion endocrine-related traits|kidney urinary albumin excretion 3 Common carotid artery intimal medial thickness atherosclerosis Common carotid artery intimal medial thickness 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell MCH 2 Green eyes Common Traits Green eyes 3 "Obesity, body mass index" Obesity|Obesity-Related Traits BMI 3 Protein quantitative trait loci Protein Quantitative Trait 3 White blood cell count White Blood Cell Count|White Blood Cell Neutrophils 2 "Sudden cardiac arrest, dominant" coronary artery disease|sudden cardiac arrest 3 Alzheimer's disease Late-Onset Alzheimer’s Disease 3 Crohn's disease IBD Disease 2 "Bone mineral density, hip" bone mineral density 2 Height anthropometric traits 2 Renal sinus fat chronic kidney disease 2 Mean corpuscular hemoglobin hematological phenotypes hemoglobin 2 Obesity-related traits Childhood Obesity|Childhood Light activity (min/d) 3 "Brain MRI, frontal brain volume" brain|cognitive test tcbv 2 Alzheimer's disease "Alzheimer's disease," 3 Red blood cell traits Red Blood Cell|Resistance|Malaria MCHC 2 Dietary macronutrient intake body mass index 0 "Combined bone mineral density phenotypes, femoral neck bone mineral density, trochanater bone mineral density, lumbar spine bone mineral density, gender differentiated in females" association bone 2 Autism AUTISM 3 Waist circumference Distribution|Adiposity|Waist Circumference 3 "Cognitive performance, Boston naming test" brain|cognitive test boston naming test 3 Type 2 diabetes iron intake|type 2 diabetes 3 Vitiligo generalized vitiligo 3 Usual sleep duration circadian phenotypes|sleep Sleep duration 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein DG9 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and waist circumference" Metabolic Syndrome HDLC-TG 2 Percent body fat complex disease BMI 3 "Hip geometry, neck width" association bone NeckW1 1 "Cognitive performance, wide-range achievement test" brain|cognitive test wide-range achievement test 3 Restless legs syndrome Restless Legs Syndrome 3 Primary tooth development tooth eruption|height sn-alL: subnasale to left alare 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein DG9 2 Obesity-related traits Childhood Obesity|Childhood Trunk fat mass (kg) 3 Wilms tumor Wilms tumor 3 QT interval length heart rate|variability traits QT 3 "Insulin resistance/response, HOMA-IR" Insulin Resistance|Copy Number Variation 3 Corneal astigmatism Corneal Astigmatism 3 Hair color Common Traits Green eyes 0 "White blood cell types, monocyte count" White Blood Cell Count|White Blood Cell 3 Hair color Common Traits Eye color 0 Height Stature 3 Relative content of sphingomyelin 14:0 Sphingolipid 2 Age at natural menopause longevity|age-related phenotypes Age at natural menopause‡ 3 Type 1 diabetes nephropathy Type 1 Diabetes|Diabetic Nephropathy T1DN 3 Pancreatitis pancreatitis 3 Optic disc parameters Optic Disc 3 Mean corpuscular hemoglobin hematological phenotypes mean corpuscular hemoglobin 3 "AB1-42, normal" Ď„ protein levels 2 Obesity obesity 3 "Platelet aggregation, epinephrine" platelet aggregation 3 "White blood cell types, basophil count" White Blood Cell Count|White Blood Cell 3 Reading and spelling reading|language 2 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein DG7 2 Serum LDL cholesterol levels LDL-cholesterol 3 Esophageal adenocarcinoma Barrett’s Esophagus|Esophageal Adenocarcinoma 3 Femoral neck and bone mineral density in men Osteoporosis-Related Traits|Gene Expression Profiling FN BMD 2 "Blood pressure, pulse pressure" mean arterial pressure|pulse pressure 3 Fasting plasma glucose Type 2 Diabetes|Plasma Glucose|Melatonin 2 Clozapine-induced change in triglycerides antipsychotic drugs|metabolic side effects Clozapine - Triglycerides 3 "Platelet aggregation, adenosine diphosphate" platelet aggregation ADP 5 u M 2 Chronic obstructive pulmonary disease Chronic Obstructive Pulmonary Disease COPD|Pulmonary Function 3 Non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein TP 2 LDL cholesterol Cardiovascular Disease LDL-cholesterol 3 Serum selenium levels Serum Selenium 3 "Obesity, body mass index" Obesity|Obesity-Related Traits HIP 3 Biologic age by osseographic scoring system longevity|age-related phenotypes Biologic age by osseographic scoring system 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein DG7 2 Percent predicted FEV1/FVC ratio Chronic Obstructive Pulmonary Disease COPD|Pulmonary Function 2 "Optic disc size, cup" optic disc size Disc 3 Clozapine-induced change in total cholesterol antipsychotic drugs|metabolic side effects Clozapine - Total Cholesterol 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome HDLC-TG 2 Quetiapine-induced change in HDL antipsychotic drugs|metabolic side effects Quetiapine - HDL 3 Estradiol levels "Testosterone,|Sex Hormone-Binding Globulin|Testosterone" 0 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome TG-BP 2 Young-onset hypertension Hypertension 2 "Plasma Phospholipid levels, lower docosahexaenoic acid" Plasma Phospholipid|Fatty Acids 3 Primary tooth development tooth eruption|height exR.yz: distance of the right exocanthion from the YZ plane 3 Chronic kidney disease Follow-Up|Kidney 2 Systemic sclerosis Systemic Sclerosis 3 Complement C3 and C4 levels Complement C3 3 Triglycerides Cardiovascular Disease triglycerides 3 Atopic dermatitis psoriasis|atopic dermatitis|asthma 3 Urinary isoprostanes/creatinine biomarker traits Urinary isoprostanes/creatinine 3 Thyroid stimulating hormone endocrine-related traits|kidney thyroid stimulating hormone 3 Telomere length telomere length 3 Forced expiratory volume in one second slope pulmonary function longitudinal slope of fev 3 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome WC-TG 2 Trochanter bone mineral density association bone trochanter bmd** 3 Childhood onset asthma Asthma 2 "Plasma Phospholipid levels, eicosapentaenoic acid" Plasma Phospholipid|Fatty Acids 3 Duration of smoking Smoking Behaviors|Cigarette Smoking 2 "Bone mineral density, spine" bone mineral density 3 Ziprasidone-induced change in hip circumference antipsychotic drugs|metabolic side effects Ziprasidone - Hip Circumference 3 "Statin-mediated cholesterol level, difference trait" Lipid-Lowering Response|Response Statins 2 Obesity-related traits Childhood Obesity|Childhood Sleep RQ 3 Age at onset of menarche and menopause age menarche|menopause 3 Olanzapine-induced change in hemoglobin A1c antipsychotic drugs|metabolic side effects Olanzapine - Hemoglobin A1c 3 Combined Crohn's disease and celiac disease Celiac Disease|Crohn's Disease 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein FUCA 2 Obesity-related traits Childhood Obesity|Childhood IGFBP-3 (ng/mL) 3 Intraocular pressure intraocular pressure|glaucoma 3 Atrial fibrillation cardiovascular disease atrial fibrillation 3 Left ventricular systolic dimension exercise responses|artery left ventricular systolic dimension 3 "Cognitive performance, similarities" brain|cognitive test similarities 3 Obesity-related traits Childhood Obesity|Childhood Weight (kg) 3 Atopy Respiratory|atopy 3 "Cardiovascular disease risk factors, migraineurs with aura - CVD death" Migraine|Cardiovascular Events|Cardiovascular 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein DG12 2 Colorectal cancer Colorectal Cancer 3 Mean corpuscular volume Cell Traits|Red Blood Cell MCV 2 Relative hand skill in reading disability handedness 2 Proinsulin levels Type 2 Diabetes|Proinsulin Levels 2 Drug-induced torsades de pointes Torsades de Pointes 3 Amyloid A Levels "serum amyloid A|amyloidosis|type 2 diabetes," 3 Creutzfeldt-Jakob disease Creutzfeldt–Jakob disease 3 Myopia Ocular Axial Length|High Myopia 3 Internal carotid artery intimal medial thickness atherosclerosis Internal carotid artery intimal medial thickness 3 Metabolic syndrome Metabolic Syndrome HDLC-TG 3 Sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual WHRadjBMI 3 Iron status biomarkers Iron Deficiency Case-Control 3 Waist circumference Body Fat Distribution WC_Men 2 Quantitative broadband ultrasound attentuation of the calcaneus association bone fnbmd 2 Response to statin therapy Cardiovascular Event 2 LDL cholesterol complex disease 0 Thyroid hormone levels Thyroid|Differences|Thyroid Function TSH/FT4 2 "Esophageal cancer, ESCC" esophageal squamous cell carcinoma|gastric adenocarcinoma 3 Obesity-related traits Childhood Obesity|Childhood Fat mass (kg) 3 Mean FEV1/FVC ratio pulmonary function mean fev 3 Ever versus never smoking status Smoking Behaviors|Cigarette Smoking 2 Colorectal cancer colorectal cancer 3 Sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual WHRADJ [31] 3 Eye color Common Traits Freckling 0 Adolescent idiopathic scoliosis Adolescent Idiopathic Scoliosis 3 Hippocampal volume hippocampal volume 3 Metabolic syndrome Metabolic Syndrome MetS 3 "Caudate nucleus volume, Right caudate" brain 2 Alanine aminotransferase biomarker traits Alanine aminotransferase exam 2 3 Red hair color Common Traits Red hair 3 Freckling Common Traits Hair color 0 "Cardiovascular disease risk factors, any migraine - CVD death" Migraine|Cardiovascular Events|Cardiovascular 3 Primary tooth development tooth eruption|height prn-alL: pronasale to left alare distance 3 Diastolic blood pressure Hypertension|Blood Pressure SBP 2 Late onset Alzheimer's disease late-onset Alzheimer’s disease 3 "Cardiovascular disease including myocardial infarction, coronary insufficiency, CHD death, atherothrombotic stroke" cardiovascular disease Major cardiovascular disease 3 "T-tau, mild cognitive impairment" Ď„ protein levels 3 Serum mean cell volume erythrocyte MCV 2 Hair color: black versus red Hair Color|Skin Pigmentation 2 Response to the antipsychotic treatment ziprasidone Response Treatment|Antipsychotics Ziprasidone –Positive 3 0- to 120-min insulin sensitivity index diabetes-related traits 2 "P-tau181p, normal" Ď„ protein levels 2 N-terminal pro-atrial natriuretic peptide biomarker traits Atrial natriuretic peptide exam 6 3 White blood cell count White Blood Cell Count|White Blood Cell Monocytes 3 Baseline brachial artery flow velocity exercise responses|artery Baseline brachial artery flow velocity 3 Obesity-related traits Childhood Obesity|Childhood Sleep duration (min/d) 3 Late onset Alzheimer's disease Dementia|Late-Onset Alzheimer Disease 3 Plasma vitamin D biomarker traits Vitamin D plasma 25(OH)-D 3 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome HDLC-TG 2 Bone mineral density bone mineral density 3 C-reactive protein C-Reactive Protein 3 Osteoporosis Osteoporosis 3 Sneezing Common Traits Sneeze 3 Epworth sleepiness scale score circadian phenotypes|sleep Sleepiness 2 "Plasma Phospholipid levels, ALA" Plasma Phospholipid|Fatty Acids 3 Callous-unemotional behaviour Behavior 0 Percent predicted forced expiratory volume/forced vital capacity ratio pulmonary function percent predicted fev 3 "Hip geometry, shaft section modulus, gender differentiated in females" association bone shaft section modulus** 3 C-reactive protein biomarker traits "C-reactive protein average exams 2,6,7" 3 Glaucoma Optic Nerve|Glaucoma 3 Bone mineral density Bone Mineral Density|Femoral Neck Bone 3 Stage 2 exercise systolic blood pressure exercise responses|artery Stage 2 Exercise systolic blood pressure 3 Anticoagulant levels Protein C PC 0 Carotid-femoral pulse wave velocity arterial stiffness|blood pressure CF-PWV 2 Anticoagulant levels Protein C Total PS 2 "Cognitive performance, visual memory and organization" brain|cognitive test factor 2:visual memory and organization 3 Alzheimer's disease Alzheimer's disease 3 Diastolic blood pressure blood pressure DBP 2 "Obesity, waist" Obesity|Obesity-Related Traits Waist 3 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome MetS 2 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein DG7 3 Walking speed at advanced age longevity|age-related phenotypes Walking speed exam 7 3 Celiac disease and rheumatoid arthritis Rheumatoid Arthritis|Celiac Disease 3 Primary tooth development tooth eruption|height enL.yz: distance of the left endocanthion from the YZ plane 3 Height C-type natriuretic peptide|height 3 Obesity-related traits Childhood Obesity|Childhood Urinary nitrogen (g/d) 3 Type 2 diabetes Obese|Type 2 Diabetes 3 Stage 2 exercise heart rate exercise responses|artery Stage 2 Exercise heart rate 3 Serum magnesium levels "Potassium,|Sodium|Serum Magnesium Levels" 3 Femoral neck bone mineral density association bone femoral bmd** 3 "Hip geometry, neck section modulus" association bone lumbar spine bmd** 2 "Obesity, waist-hip ratio" Obesity|Obesity-Related Traits WHR 2 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein FUCA 2 Presence of antiphospholipid antibodies Antiphospholipid Antibodies 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein DG9 2 Green eyes Common Traits Hair color 0 "Obesity, weight" Obesity|Obesity-Related Traits BMI 3 Obesity-related traits Childhood Obesity|Childhood IL-6 (pg/mL) 3 "Statin-mediated cholesterol level, sum trait" Lipid-Lowering Response|Response Statins 2 Psoriasis Psoriasis 3 Diastolic blood pressure Hypertension|Blood Pressure 2 Asthma Asthma|Bronchodilator Response 3 Autism autism spectrum 3 Dental caries dental caries 3 "Brain MRI, temporal horn volume" brain|cognitive test ALTHBV 2 Systemic lupus erythematosus Systemic Lupus Erythematosus 3 Response to the antipsychotic treatment olanzapine Response Treatment|Antipsychotics Olanzapine – Negative 3 Obesity-related traits Childhood Obesity|Childhood Fat free mass (kg) 3 Menarche Age Menarche 3 Breast cancer prostate cancer|breast 2 Neuroblastoma neuroblastoma 3 Cholelithiasis-related traits in sickle cell anemia Cholelithiasis|Sickle Cell Anemia|Sickle Cell 3 Number of teeth Primary Tooth Development 2 "Platelet aggregation, adenosine diphosphate" platelet aggregation ADP 2 u M 2 "Type II diabetes, Chinese, Malay, Indian" Type 2 Diabetes|Transferability 2 Red blood cell traits Red Blood Cell|Resistance|Malaria RBC count 3 Bone mineral density Volumetric Bone Mineral Densities 3 Left ventricular mass left ventricular mass 3 Primary tooth development tooth eruption|height piL-piR: left-to-right palpebrale inferius distance 3 Smoking behavior smoking behaviors CPD 2 Obesity-related traits Childhood Obesity|Childhood Glucose (mg/dL) 3 Social autistic-like traits Autistic-Like Traits 3 Clozapine-induced change in heart rate antipsychotic drugs|metabolic side effects Clozapine - Heart Rate 3 Telomere length Telomere Length 3 "Femoral neck bone mineral density, gender differentiated in males" association bone femoral bmd** 3 Diastolic blood pressure Metabolic Syndrome DBP (mmHg) 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and fasting glucose" Metabolic Syndrome HDLC-GLUC 2 Breast cancer Breast Cancer|Breast 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and waist circumference" Metabolic Syndrome MetS 3 Thyroid hormone levels Thyroid|Differences|Thyroid Function TSH 2 Mean corpuscular hemoglobin concentration Cell Traits|Red Blood Cell MCH 2 Waist-hip ratio Body Fat Distribution WHR_BMI_men 2 Sex hormone-binding globulin levels "Testosterone,|Sex Hormone-Binding Globulin|Testosterone" 2 Percent body fat complex disease 0 Type I diabetes type 1 diabetes 3 Left ventricular diastolic dimension exercise responses|artery Across left ventricular phenotypes 2 Nonalcoholic fatty liver disease Non-Alcoholic Fatty Liver Disease|Liver Disease 3 Obesity-related traits Childhood Obesity|Childhood Urinary freedopamine:creatinine 3 Percent predicted forced vital capacity pulmonary function percent predicted fvc for latest exam 3 Iron deficiency Iron Deficiency Case-Control 3 Rheumatoid arthritis Rheumatoid Arthritis 3 Barrett's esophagus Barrett’s esophagus 3 Self-reported allergy allergy 3 "Metabolic syndrome bivariate trait, blood pressure and fasting glucose" Metabolic Syndrome HDLC-GLUC 2 "Obesity, extreme" Distribution|Adiposity|Obesity 3 Post-exercise 3 minute recovery: systolic blood pressure exercise responses|artery Post-exercise 3 minute recovery systolic blood pressure 3 Diastolic blood pressure complex disease 0 Migraine - clinic-based migraine 3 Partial epilepsies partial epilepsies 3 Testosterone levels "Testosterone,|Sex Hormone-Binding Globulin|Testosterone" 3 Parkinson's disease Parkinson's disease 3 Risperidone-induced change in hemoglobin A1c antipsychotic drugs|metabolic side effects Risperidone - Hemoglobin A1c 3 Serum testosterone Serum Testosterone 3 Endometriosis endometriosis 3 Tissue plasminogen activator hematological phenotypes tissue plasminogen activator 3 White blood cell count White Blood Cell Count|White Blood Cell WBC 3 Response to taxane treatment lung cancer|overall survival 2 Obesity-related traits Childhood Obesity|Childhood Sleep energyexpenditure adjweight (kcal/d) 3 Triglycerides complex disease 0 Psoriasis Psoriasis|Psoriatic Arthritis 3 pathological myopia Pathological Myopia 3 "Platelet aggregation, epinephrine" platelet aggregation Epi EC50 * 3 HIV-1 replication HIV-1 3 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome WC-TG 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome TG-BP 3 Waist-hip ratio Body Fat Distribution WHR_BMI_Men 2 Suicide attempts in bipolar disorder attempted suicide 3 Celiac disease Celiac Disease 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome HDLC-WC 2 "Platelet aggregation, adenosine diphosphate" platelet aggregation Epi EC50 * 3 Response to the antipsychotic treatment risperidone Response Treatment|Antipsychotics Risperidone – Negative 3 Waist circumference Body Fat Distribution WC_pooled 2 Serum alkaline phosphatase levels serum alkaline phosphatase levels 3 Age at death longevity|age-related phenotypes Age at death 3 Obesity-related traits Childhood Obesity|Childhood Hip circumference (cm) 3 Social communication problems social communication 3 Hippocampal atrophy Hippocampal Atrophy|Alzheimer's Disease 3 Sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual HEIGHT [25] ; WHRADJ [31] 2 Hypertension Hypertension|Blood Pressure HTN 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and fasting glucose" Metabolic Syndrome BP-GLUC 2 Type II diabetes Type 2 Diabetes 3 Cystatin C endocrine-related traits|kidney cst3 2 Bone mineral density "osteoporosis,|osteoporotic fractures|Bone mineral density," 3 Vitamin K % undercarboxylated osteocalcin biomarker traits Vitamin K % undercarboxylated osteocalcin 3 "AB1-42, Alzheimer's disease" Ď„ protein levels 2 "Platelet aggregation, collagen" platelet aggregation Lag 190 u g/mL 2 Sexual dysfunction Sexual Dysfunction Overall FSD 3 Protein biomarker lectin 0 Red hair color Common Traits Hair color 2 Systolic blood pressure in sickle cell anemia Systolic Blood Pressure|Sickle Cell Disease 3 "Hip geometry, shaft width, gender differentiated in females" association bone shaft width** 3 Pancreatic cancer Pancreatic Cancer 3 "Metabolic syndrome bivariate trait, blood pressure and high-density lipoprotein cholesterol" Metabolic Syndrome BP-HDLC 2 "Caudate nucleus volume, Left caudate" brain 2 Interstitial lung disease pulmonary fibrosis 2 Metabolite levels Atherosclerosis 2 "P-tau181p, mild cognitive impairment" Ď„ protein levels 2 Periodontitis chronic periodontitis 3 Red blood cell count Cell Traits|Red Blood Cell MCH 2 Anti-dsDNA + systemic lupus erythematosus Systemic Lupus Erythematosus|Autoantibody 3 Warfarin maintenance dose CYP2C9|Warfarin 3 Response to citalopram treatment global disease|depression|citalopram-induced side effects 3 Weight complex disease Weight 3 Stroke ischaemic stroke 3 Relative content of sphingomyelin 18:1 Sphingolipid 2 "Optic disc size, cup" optic disc size Cup 3 Serum CD40 ligand biomarker traits CD40 Ligand serum 3 Waist-hip ratio Body Fat Distribution 2 Tumor necrosis factor alpha biomarker traits Tumor necrosis factor alpha 3 Mean corpuscular volume Cell Traits|Red Blood Cell RBC count 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome MetS 2 "Cognitive performance, attention and executive function" brain|cognitive test f3 3 Lumbar spine and bone moneral denisty in women Osteoporosis-Related Traits|Gene Expression Profiling LS BMD 2 "Systemic sclerosis, ACA positive" Systemic Sclerosis 3 Obesity anthropometric traits 0 Psoriatic arthritis psoriasis|psoriatic arthritis 3 "Platelet aggregation, adenosine diphosphate" platelet aggregation ADP 10 u M 2 PR interval length heart rate|variability traits PR 2 Soluble ICAM-1 Antigen|ICAM-1 3 "Trochanter bone mineral density, gender differentiated in males" association bone trochanter bmd** 3 Serum uric acid concentration Uric Acid 3 Narcolepsy Narcolepsy 3 Age-related macular degeneration age-related macular degeneration 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG11" Master|Plasma Protein DG11 2 "Platelet aggregation, adenosine diphosphate" platelet aggregation 2 Glycated hemoglobin levels Hemoglobin A 2 Psoriasis psoriasis 3 Risperidone-induced change in hip circumference antipsychotic drugs|metabolic side effects Risperidone - Hip Circumference 3 Hypersomnia hypersomnia 3 "Hip geometery, neck shaft angle" association bone nsa1 2 Serum calcium Serum Calcium 3 Hip bone size Hip Bone Size|Females 3 Perphenazine-induced change in total cholesterol antipsychotic drugs|metabolic side effects Perphenazine - Total Cholesterol 3 Primary biliary cirrhosis primary biliary cirrhosis 3 "Antipsychotic-induced QTc interval prolongation, risperidone" cardiac arrhythmias risperidone/QTc 3 "Obesity, hip" Obesity|Obesity-Related Traits Weight 2 "Plasma Phospholipid levels, DPA" Plasma Phospholipid|Fatty Acids 3 "Platelet aggregation, adenosine diphosphate" platelet aggregation Epi 2 u M 2 Plasma vWF and FVIII levels von Willebrand Factor vWF 2 Red hair color Common Traits Eye color 0 Retinal vascular caliber cardiovascular diseases 2 Hodgkin's lymphoma Hodgkin Lymphoma 3 Left ventricular fractional shortening exercise responses|artery left ventricular fractional shortening 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG6" Master|Plasma Protein DG6 2 PR interval PR interval 3 Mesial temporal lobe epilepsy with hippocampal sclerosis "febrile seizures|Epilepsy," 3 "Metabolic syndrome bivariate trait, blood pressure and fasting glucose" Metabolic Syndrome BP-GLUC 2 Male-pattern baldness Androgenetic Alopecia|Common Diseases 3 Caffeine consumption Caffeine Consumption|CYP1A2 3 Multiple sclerosis Multiple Sclerosis 3 Percent predicted forced expiratory volume pulmonary function for latest exam 2 Diastolic blood pressure arterial stiffness|blood pressure blood-pressure 3 Multiple sclerosis multiple sclerosis 3 "Adiponectin levels, Second stage" Quantitative Trait|Cardiometabolic Outcomes|Adiponectin 3 Parkinson's disease Parkinson's Disease 3 Epstein-Barr virus immune response Antibodies|Epstein-Barr Virus Nuclear Antigen 3 Celiac disease celiac disease 3 C-reactive protein biomarker traits C-reactive protein exam 2 3 Psoriatic arthritis Psoriatic Arthritis 3 Venous thromboembolism Venous Thrombosis 3 Obesity Obesity|Obesity-Related Traits 3 "Type I diabetes autoantibodies, I-A2A" Type 1 Diabetes|Autoantibody 3 Red blood cell count hematological phenotypes red blood cell count 3 Sex hormone-binding globulin levels Globulin|Hormone|Steroid Hormone 2 Heart rate variability: low frequency/high frequency power heart rate|variability traits LF/HF 2 Response to mTOR inhibitor biomarker 0 Diastolic blood pressure Cardiovascular Disease|Blood Pressure 3 Height complex disease Height 3 Juvenile idiopathic arthritis juvenile idiopathic arthritis 3 Alanine aminotransferase biomarker traits Alanine aminotransferase 3 Mathematical ability in children with dyslexia mathematical abilities|dyslexia|Myosin 3 "P-tau181p, Alzheimer's disease" Ď„ protein levels 2 ADP-induced platelet aggregation hematological phenotypes platelet aggregation (ADP-induced) 3 Metabolic syndrome Metabolic Syndrome WC-TG 3 Central corneal thickness Central Corneal Thickness|Brittle Cornea Syndrome 3 Perphenazine-induced change in HDL antipsychotic drugs|metabolic side effects Perphenazine - HDL 3 Age of onset of Parkinson's disease onset|Parkinson disease 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein DG7 2 Femoral neck bone geometry and menarche Age Menarche|Femoral Neck Bone Geometry 3 Obesity-related traits Childhood Obesity|Childhood Total antioxidants(mM) 3 Atrial fibrillation atrial fibrillation 3 Heart rate variability: total power heart rate|variability traits TP 2 Asparagus anosmia Common Traits Asparagus 2 "Coronary heart disease risk factor, HDL-C" Coronary Heart Disease HDL-C 3 "Lipoprotein-associated phospholipase A2 activity and mass, mass" phospholipase A 2 Non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein NAP 3 Coronary heart disease Coronary Artery Stenosis|Coronary Artery 3 "Sudden cardiac arrest, recessive" coronary artery disease|sudden cardiac arrest 3 Thyroid hormone levels Thyroid|Differences|Thyroid Function 2 HDL Metabolic Syndrome “ 3 Smoking behavior smoking behaviors AOI 2 Osteoprotegerin biomarker traits Osteoprotegerin 3 Breast cancer breast cancer 3 Mean waist circumference waist circumference|body mass index Mean waist circumference 3 Forward wave amplitude arterial stiffness|blood pressure FW 2 "Platelet aggregation, collagen" platelet aggregation Coll. 2 "Hip geometry, neck section modulus" association bone NeckZ1 2 "Progressive supranuclear palsy, controlling for rs8070723" Progressive Supranuclear Palsy 3 Mean forced vital capacity pulmonary function mean fvc from two exams 3 Cystic fibrosis severity p.Phe508del/p.Phe508del only cystic fibrosis|lung disease 3 Waist circumference Body Fat Distribution WC_women 2 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome MetS 3 Clozapine-induced change in glucose antipsychotic drugs|metabolic side effects Clozapine - Glucose 3 "Hip geometry, shaft section modulus" association bone shaft section modulus** 3 Asthma asthmatics|bronchodilator response 3 Melanoma melanoma 3 Fasting glucose-related: fasting plasma glucose fasting glucose|type 2 diabetes|glucose homeostasis 3 High-risk neuroblastoma neuroblastoma 3 "T-tau, normal" Ď„ protein levels 3 Fasting insulin-related: fasting insulin fasting glucose|type 2 diabetes|glucose homeostasis 2 Fasting glucose-related: homeostatic model assessment of beta-cell function fasting glucose|type 2 diabetes|glucose homeostasis 3 Perphenazine-induced change in triglycerides antipsychotic drugs|metabolic side effects Perphenazine - Triglycerides 3 "Carotid intima media thickness, plaque" intima media thickness|plaque 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and waist circumference" Metabolic Syndrome HDLC-WC 2 Metabolic syndrome Metabolic Syndrome TG-BP 3 Primary tooth development tooth eruption|height 2 Bipolar disorder bipolar disorder 3 Type 2 diabetes type 2 diabetes 3 Lung cancer lung cancer 3 Eating disorders "Eating|Behaviors,|Symptoms, Behaviors" 2 Waist circumference Body Fat Distribution WC_men 2 Bone mineral density "Bone Mineral Density,|Bone|Osteoporotic Fracture" 3 Alkaline phosphatase biomarker traits Alkaline phosphatase 3 "Platelet aggregation, adenosine diphosphate" platelet aggregation ADP 3 u M 2 "Platelet aggregation, collagen" platelet aggregation Lag 2 u g/mL 2 PR interval PR Interval 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell RBC count 2 Freckling Common Traits Eye color 0 Coronary artery calcification atherosclerosis Coronary artery calcification 3 "Trochanter bone mineral density, gender differentiated in females" association bone trochanter bmd** 3 Hair color Common Traits Hair color 3 "Hip geometry, shaft width" association bone shaft width** 3 Neuranatomic and neurocognitive phenotypes neurocognitive phenotypes 3 Hair color Common Traits Freckling 0 Obesity-related traits Childhood Obesity|Childhood IGF-1 free (ng/mL) 3 Factor VII hematological phenotypes factor vii 3 "Brain MRI, total cerebral brain volume" brain|cognitive test tcbv 2 Primary tooth development tooth eruption|height psL-psR: left-to-right palpebrale superius distance 3 Self-employment Self-Employment 3 Fasting glucose-related: fasting insulin fasting glucose|type 2 diabetes|glucose homeostasis 2 "Obesity, body mass index" Obesity|Obesity-Related Traits Weight 3 Congenital heart disease congenital heart disease|atrial septal defect 3 Ulcerative colitis ulcerative colitis 3 Cystic fibrosis severity cystic fibrosis|lung disease 3 Age at onset of menarche and menopause age menarche|menopause Age at Menarche 3 Ventricular conduction conduction|QRS duration 2 Height height 3 Obesity-related traits Childhood Obesity|Childhood MCP-1 (pg/mL) 3 IgE levels in asthmatics Mite-Specific IgEs|Asthma 3 Coffee consumption addictive behavior 0 Primary tooth development tooth eruption|height enL-enR: left-to-right endocanthion distance 3 Left atrial diameter exercise responses|artery Left atrial diameter 3 Eye color Common Traits Eye color 3 Freckling Common Traits Freckling 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell MCV 2 Obesity-related traits Childhood Obesity|Childhood Total energyexpenditure adjweight (kcal/d) 3 "Carotid intima media thickness, cIMT" intima media thickness|plaque 3 Circulating cell-free DNA Cell-Free DNA|Cardiovascular 3 Crohn's disease inflammatory bowel disease 2 Chronic obstructive pulmonary disease chronic obstructive pulmonary disease 3 Thyroid hormone levels Thyroid|Differences|Thyroid Function FT4/TSH 2 White blood cell count White Blood Cell Count|White Blood Cell Lymphocytes 3 QT interval QT interval duration 3 Percent predicted forced expiratory flow/forced vital capacity ratio pulmonary function percent predicted fef 3 Neck width in men and women Osteoporosis-Related Traits|Gene Expression Profiling NW 2 Anti-dsDNA - systemic lupus erythematosus Systemic Lupus Erythematosus|Autoantibody 3 Abdominal aortic calcification atherosclerosis Abdominal aortic calcification 3 Schizophrenia schizophrenia 3 "Metabolic syndrome bivariate trait, triglycerides and fasting glucose" Metabolic Syndrome TG-GLUC 3 \ No newline at end of file +Systolic blood pressure Hypertension|Blood Pressure 2 "Systemic sclerosis, dcSSc" Systemic Sclerosis 3 Waist circumference Body Fat Distribution WC_BMI_men 2 "Hip geometry, neck width, gender differentiated in females" association bone shaftz1r 2 Systolic blood pressure Hypertension|Blood Pressure SBP 2 Percent body fat complex disease BMI 3 "Systemic sclerosis, IcSSc" Systemic Sclerosis 2 Non-word repetition reading|language 2 Temperament Temperament Character Inventory 3 Factor VII hematological phenotypes "FVII, exam 5" 3 IgM levels Serum IgM 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG1" Master|Plasma Protein DG1 2 Diastolic blood pressure Hypertension|Blood Pressure DBP 2 Substance dependence European-Origin|Substance Dependence 3 Percent predicted forced expiratory flow pulmonary function for latest exam 2 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein FUCA 2 Cholesterol Serum Cholesterol Levels 3 Ankle brachial index atherosclerosis Ankle brachial index 3 "Hip geometry, neck section modulus, gender differentiated in males" association bone lsbmd 2 Glycated hemoglobin levels Glycated Hemoglobin 3 Serum IgE levels Serum IgE Levels 3 Disc degeneration lumbar disc degeneration 3 Cortical thickness "Bone Mineral Density,|Bone|Osteoporotic Fracture" 2 Handedness in dyslexia handedness|dyslexia 3 Tetralogy of Fallot Tetralogy Fallot 3 Usual bedtime circadian phenotypes|sleep Bedtime 3 Sensory disturbances after bilateral sagittal split ramus osteotomy sensory disturbances|split 2 Atopic dermatitis ATOPIC DERMATITIS 3 Serum hemoglobin levels erythrocyte MCV 2 "Liver function test: alkaline phosphatase, AST, ALT, GGT" biomarker traits Liver function: Alkaline phosphatase; AST; ALT; gamma-glutamyl transferase 3 Freckling Common Traits Freckling 3 Femoral neck bone geometry Femoral Neck Bone Geometry 3 Systolic blood pressure blood pressure SBP 2 Chronic kidney disease Kidney|Follow-Up 2 Parkinson's disease Parkinson‰ŰŞs disease 3 Kawasaki disease Kawasaki Disease 3 Intracellular adhesion molecule-1 biomarker traits Intercellular adhesion molecule-1 3 Case-only systemic lupus erythematosus Systemic Lupus Erythematosus|Autoantibody 3 "Obesity, weight" Obesity|Obesity-Related Traits Weight 3 Left ventricular diastolic dimension exercise responses|artery left ventricular diastolic dimension 3 "Lipoprotein-associated phospholipase A2 activity and mass, activity" phospholipase A 2 Breast cancer Breast Cancer 3 Age-related macular degeneration Age-Related Macular Degeneration 3 Telomere length homeostasis 0 Hippocampal volume hippocampal volume 3 Inflammatory bowel disease inflammatory bowel disease 3 "HIV-1 control, setpoint" HIV-1 3 Protein quantitative trait loci Protein Quantitative Trait|genome|Association 3 Obesity-related traits Childhood Obesity|Childhood Urinary creatinine(mmol/d) 3 Mean forced vital capacity pulmonary function 2 Gray matter volume Quantitative Phenotype|Matter Volume 0 Total plasma cholesterol complex disease 0 LDL cholesterol complex disease 0 Obesity-related traits Childhood Obesity|Childhood Triglycerides(mg/dL) 3 Rheumatoid arthritis rheumatoid arthritis 3 Ulcerative colitis inflammatory bowel disease 2 Red blood cell traits Cell Traits|Red Blood Cell|Resistance 3 "Lipoprotein-associated phospholipase A2 activity and mass, mass" phospholipase A 2 Heart failure cardiovascular disease heart failure 3 "Type II diabetes, Indian" Type 2 Diabetes|Transferability 2 Mean body mass index waist circumference|body mass index Mean body mass index 3 Multiple sclerosis Multiple Sclerosis|Oligoclonal Band 3 Hepatitis B Chronic Hepatitis B 3 Menopause menopause 3 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome TG-BP 2 "Bone mineral density, femoral neck" Bone Mineral Density 2 "Obesity, weight" Obesity|Obesity-Related Traits HIP 3 "Optic disc size, disc" optic disc size Cup 3 Behcet's disease Beh̤et's disease 3 Adverse response to chemotherapy in breast cancer chemotherapy-induced alopecia|breast cancer 3 Monocyte chemoattractant protein-1 biomarker traits Monocyte chemoattractant protein-1 3 "Systemic sclerosis, ATA positive" Systemic Sclerosis 3 Cholelithiasis-related traits in sickle cell anemia Total Bilirubin|Sickle Cell Anemia|Sickle Cell 3 Serum selenium levels Serum Selenium 3 Cholesterol Serum Cholesterol Levels HDL-C 3 Protein biomarker lectin 0 Waist-hip ratio Body Fat Distribution WHR_BMI_women 3 Glucosylceramide Sphingolipid 2 Obesity-related traits Childhood Obesity|Childhood Glucose (mg/dL) 3 Diastolic blood pressure Metabolic Syndrome DBP (mmHg) 2 Glioma increased disease risk 0 Anticoagulant levels Protein C funcPS 1 Cardiac repolarisation "sudden cardiac death," 0 Obesity-related traits Childhood Obesity|Childhood Sedentary&lightactivity (min/d) 3 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein DG12 0 Tourette syndrome Tourette Syndrome 3 Cigarettes smoked per day Smoking Behaviors|Cigarette Smoking 2 Carotid-brachial pulse wave velocity arterial stiffness|blood pressure CB-PWV 1 Calcium levels Serum Calcium 3 "T-tau, Alzheimer's disease" ěă protein levels 2 Fasting plasma glucose diabetes-related traits 28 yr time averaged fpg 3 Smoking intensity Smoking Behaviors|Cigarette Smoking 2 Plasma vitamin K biomarker traits Vitamin K plasma phylloquinone 3 C-reactive protein biomarker traits C-reactive protein exam 7 3 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome 2 Time to first tooth eruption Primary Tooth Development 2 Thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences FT4 3 Aortic root diameter aortic root 2 Testicular germ cell tumor "testicular cancer," 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome WC-TG 2 Sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual WCadjBMI 3 Hair curl Common Traits Hair curl 3 Walking speed at advanced age age-related phenotypes|longevity Walking speed exam 7 3 Obesity-related traits Childhood Obesity|Childhood Weight z-score change (SD/y) 3 Red blood cell count Cell Traits|Red Blood Cell MCV 2 Non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein NAP 3 Sexual dysfunction Sexual Dysfunction Lubrication 3 Breast cancer breast cancer 3 Thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences FT4/TSH 3 Eye color "Skin,|Pigmentation" Eye C' 3 Metabolic syndrome Metabolic Syndrome TG-BP 3 "Brain MRI, lateral ventricular volume" brain|cognitive test ALLV 3 Femoral neck and bone mineral density in women Osteoporosis-Related Traits|Gene Expression Profiling FN BMD 2 "Platelet aggregation, collagen" platelet aggregation lag 2 Obesity-related traits Childhood Obesity|Childhood Fat mass (kg) 3 Systolic blood pressure arterial stiffness|blood pressure blood-pressure 2 Obesity-related traits Childhood Obesity|Childhood "Dinner intake, adjEER (kcal)" 3 Risperidone-induced change in hip circumference antipsychotic drugs|metabolic side effects Risperidone - Waist Circumference 3 Major depressive disorder major depression 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein FUCA 0 Osteoarthritis hip|osteoarthritis 3 Warfarin maintenance dose warfarin 2 Fasting plasma glucose diabetes-related traits fasting plasma glucose 3 Freckling Common Traits Red hair 0 Lymphoma Malignancies 2 Mean FEV1/FVC ratio pulmonary function mean fev 3 "Hip geometry, neck section modulus, gender differentiated in females" association bone neck section modulus** 3 Distal colon cancer colon cancer 3 Age at smoking initiation Smoking Behaviors|Cigarette Smoking 2 Atrial fibrillation Lone Atrial Fibrillation 3 Ovarian reserve ovarian reserve 3 Wilms tumor Wilms tumor 3 Red hair color Common Traits Freckling 0 Ovarian cancer in BRCA1 mutation carriers Breast Cancer|Breast Ovarian Cancer|Carriers 3 Plasma CD40 ligand biomarker traits CD40 Ligand plasma 3 Breast Cancer in BRCA1 mutation carriers Breast Cancer|Breast Ovarian Cancer|Carriers 3 Neck shaft angle in men Osteoporosis-Related Traits|Gene Expression Profiling NSA 2 Reflected wave amplitude arterial stiffness|blood pressure RW 3 Viscosity hematological phenotypes Viscosity 3 Prostate cancer prostate cancer|breast 3 Collagen-induced platelet aggregation hematological phenotypes platelet aggregation (collagen-induced) 3 Nonalcoholic fatty liver disease Metabolic Traits|Nonalcoholic Fatty Liver Disease 3 Upper aerodigestive tract cancers Cancers|Conducted|Upper Aerodigestive Tract 3 Psoriatic arthritis Psoriatic Arthritis 3 28-yr time-averaged fasting plasma glucose diabetes-related traits 28 yr time averaged fpg 3 Adiponectin levels Adiponectin Levels 3 "HIV-1 control, progression" HIV-1 3 "Type I diabetes autoantibodies, T1D" Type 1 Diabetes|Autoantibody 3 Alzheimer's disease Alzheimer‰ŰŞs disease 3 "AB1-42, Alzheimer's disease" ěă protein levels 2 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein DG12 2 Obesity childhood obesity 3 Anticoagulant levels Protein C fPS 1 "Breast cancer, all races" Breast Cancer 3 Post-exercise 3 minute recovery: heart rate exercise responses|artery Post-exercise 3 minute recovery heart rate 3 Glycated hemoglobin diabetes-related traits hemoglobin a1c 2 Serum metabolites Metabolite rs number 2 "Obesity, waist" Obesity|Obesity-Related Traits Waist 3 Red blood cell traits Cell Traits|Red Blood Cell|Resistance MCHC 3 Sex hormone-binding globulin levels Globulin|Hormone|Steroid Hormone 2 Bone mineral density Bone Mineral Density 3 Eye color Common Traits Green eyes 3 Migraine migraine 3 Crohn's disease IBD Disease 2 Asthma Asthma 3 Natriuretic peptide levels NT-proBNP 1 "Platelet aggregation, epinephrine" platelet aggregation Epi 2 u M 3 Intraocular pressure Primary Open-Angle Glaucoma|Intraocular Pressure 3 Late onset Alzheimer's disease Late-Onset Alzheimer's Disease 3 Height Height 3 "Coronary heart disease risk factor, LDL-C" Coronary Heart Disease LDL-C 3 Hemoglobin hematological phenotypes hemoglobin 3 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein DG7 3 Olanzapine-induced change in total cholesterol antipsychotic drugs|metabolic side effects Olanzapine - Total Cholesterol 3 "Platelet aggregation, epinephrine" platelet aggregation ADP 2 u M 3 Hair color: black versus blond Hair Color|Skin Pigmentation 2 Follicular lymphoma Diffuse Large B-cell Lymphoma|Follicular Lymphoma|Diffuse 3 "Hip geometery, neck shaft angle, gender differentiated in males" association bone necklengf 2 Hair color Common Traits Red hair 3 "Cognitive performance, visual memory and organization" brain|cognitive test 2 "Brain MRI, temporal brain volume" brain|cognitive test temporal brain volume 3 Pulmonary function Pulmonary Function|Lung Function 3 Mean corpuscular volume Cell Traits|Red Blood Cell MCHC 2 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein DG12 2 Left ventricular mass exercise responses|artery left ventricular mass 3 Type I diabetes Type 1 Diabetes 3 Serum alkaline phosphatase levels serum alkaline phosphatase levels 3 IgG glycosylation Immunoglobulin G|Human Immunoglobulin|-Glycosylation 3 Red blood cell count Cell Traits|Red Blood Cell RBC count 3 "White blood cell types, neutrophil count" White Blood Cell Count|Cell Phenotypes|White Blood Cell 3 White blood cell count Cell Phenotypes|White Blood Cell Neutrophils 3 Schizophrenia Schizophrenia 3 Urinary albumin excretion kidney|endocrine-related traits urinary albumin excretion 3 Dental caries dental caries 3 B-type natriuretic peptide biomarker traits B-type natriuretic peptide 3 "White blood cell types, basophil count" White Blood Cell Count|Cell Phenotypes|White Blood Cell 3 "Eye color traits, 1st principal component on transformed hue and saturation values" Eye Color C HS1 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome 2 Neck width in men Osteoporosis-Related Traits|Gene Expression Profiling NW 2 "Platelet aggregation, collagen" platelet aggregation 2 Bone mineral density "osteoporosis,|Bone mineral density,|osteoporosis" 3 Esophageal adenocarcinoma Barrett‰ŰŞs Esophagus|Esophageal Adenocarcinoma 3 Mean artierial pressure arterial stiffness|blood pressure MAP 2 Mean FEV1/FVC ratio pulmonary function 3 HDL cholesterol Cardiovascular Disease HDL-cholesterol 3 Uric acid levels uric acid levels 3 Obesity-related traits Childhood Obesity|Childhood Total antioxidants(mM) 3 Borderline personality disorder features borderline personality 3 Myopia Ocular Axial Length|High Myopia 3 Osteoarthritis osteoarthritis 3 Testosterone levels "Testosterone,|Estradiol,|Sex Hormone-Binding Globulin" 3 "Metabolic syndrome bivariate trait, waist circumference and fasting glucose" Metabolic Syndrome WC-GLUC 2 Vertical cup-disc ratio Optic Disc 3 Retinal vascular caliber cardiovascular diseases 2 Schizophrenia schizophrenia|cytomegalovirus infection|infection suggests 3 PR interval PR interval 3 Femoral neck bone mineral density Osteoporosis-Related Phenotypes 2 Metabolic syndrome Metabolic Syndrome HDLC-WC 3 Green eyes Common Traits Eye color 2 "Obesity, extreme" Obesity-Related Traits|Body-Weight 3 Migraine - clinic-based migraine 3 Progressive supranuclear palsy Progressive Supranuclear Palsy 3 "T-tau, normal" ěă protein levels 3 Hypertension Cardiovascular Disease|Blood Pressure 2 Cocaine dependence cocaine dependence 3 "Obesity and osteoporosis, body mass index and bone mineral density, males" Obesity|Osteoporosis Phenotypes 2 Digestive system disease Barrett‰ŰŞs Esophagus|Esophageal Adenocarcinoma 3 "Obesity, hip" Obesity|Obesity-Related Traits HIP 3 Height complex disease Height 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell MCHC 2 Pack-years Smoking Behaviors|Cigarette Smoking 2 Waist circumference Cardiovascular Disease waist circumference 3 Paget's disease of bone Paget‰ŰŞs disease bone 3 "Schizophrenia, schizoaffective disorder or bipolar disorder" Schizophrenia 3 Mean corpuscular hemoglobin concentration Cell Traits|Red Blood Cell MCHC 2 Sphingomyelin 16:1 Sphingolipid 2 Cardiovascular disease risk factors cardiovascular-related traits 3 Insulin resistance/response Insulin Resistance|Copy Number Variation 3 Waist-hip ratio Body Fat Distribution WHR_BMI_pooled 2 Sudden cardiac arrest Sudden Cardiac Death 3 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome HDLC-TG 2 HDL Metabolic Syndrome Log HDL-C (mmol/l) 2 Hypertension Hypertension|Blood Pressure 2 Metabolic syndrome Metabolic Syndrome 3 Mean corpuscular volume Cell Traits|Red Blood Cell MCH 3 Airway hyperresponsiveness airway responsiveness 3 Non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein ALB 3 Obesity Extremely|Overweight|body mass index 3 Systolic blood pressure complex disease 0 "Esophageal cancer, total gastric" esophageal squamous cell carcinoma|gastric adenocarcinoma 3 Atrial fibrillation atrial fibrillation 3 Common carotid artery intimal medial thickness atherosclerosis Common carotid artery intimal medial thickness 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell MCH 2 Hair color: black versus red Hair Color|Skin Pigmentation 2 "Obesity, body mass index" Obesity|Obesity-Related Traits BMI 3 Type II diabetes Metabolic Syndrome T2D 2 Waist circumference Body Fat Distribution WC_BMI_pooled 2 "Sudden cardiac arrest, dominant" coronary artery disease|sudden cardiac arrest 3 Alzheimer's disease Late-Onset Alzheimer‰ŰŞs Disease 3 "Adiponectin levels, Second stage" Quantitative Trait|Cardiometabolic Outcomes 2 "Bone mineral density, hip" bone mineral density 2 Height anthropometric traits 2 Ceramide 24:0 Sphingolipid 2 "Brain MRI, frontal brain volume" brain|cognitive test tcbv 2 Alzheimer's disease "Alzheimer's disease," 3 "Combined bone mineral density phenotypes, femoral neck bone mineral density, trochanater bone mineral density, lumbar spine bone mineral density, gender differentiated in females" association bone 2 Autism AUTISM 3 Waist circumference Distribution|Adiposity|Waist Circumference 3 "Cognitive performance, Boston naming test" brain|cognitive test boston naming test 3 "Sudden cardiac arrest, recessive" coronary artery disease|sudden cardiac arrest 3 Vitiligo generalized vitiligo 3 Usual sleep duration circadian phenotypes|sleep Sleep duration 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein DG9 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and waist circumference" Metabolic Syndrome HDLC-TG 2 "Hip geometry, neck width" association bone NeckW1 1 "Cognitive performance, wide-range achievement test" brain|cognitive test wide-range achievement test 3 Restless legs syndrome Restless Legs Syndrome 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein DG9 2 Obesity-related traits Childhood Obesity|Childhood Trunk fat mass (kg) 3 Metabolite levels Atherosclerosis 2 QT interval length heart rate|variability traits QT 3 "Insulin resistance/response, HOMA-IR" Insulin Resistance|Copy Number Variation 3 Age at death age-related phenotypes|longevity Age at death 3 Hair color Common Traits Green eyes 0 Hair color Common Traits Eye color 0 Height Stature 3 Relative content of sphingomyelin 14:0 Sphingolipid 2 Duration of smoking Smoking Behaviors|Cigarette Smoking 2 Pancreatitis pancreatitis 3 Optic disc parameters Optic Disc 3 Mean corpuscular hemoglobin hematological phenotypes mean corpuscular hemoglobin 3 "AB1-42, normal" ěă protein levels 2 Obesity obesity 3 Baseline brachial artery flow velocity exercise responses|artery Baseline brachial artery flow velocity 3 Reading and spelling reading|language 2 Serum LDL cholesterol levels LDL-cholesterol 3 Sexual dysfunction Sexual Dysfunction Arousal 3 Femoral neck and bone mineral density in men Osteoporosis-Related Traits|Gene Expression Profiling FN BMD 2 Anticoagulant levels Protein C Total PS 2 Clozapine-induced change in triglycerides antipsychotic drugs|metabolic side effects Clozapine - Triglycerides 3 Chronic obstructive pulmonary disease Chronic Obstructive Pulmonary Disease COPD|Pulmonary Function 3 Non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein TP 2 Percent predicted forced expiratory volume/forced vital capacity ratio pulmonary function percent predicted fev 3 "Obesity, body mass index" Obesity|Obesity-Related Traits HIP 3 Celiac disease and rheumatoid arthritis Rheumatoid Arthritis|Celiac Disease 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein DG7 2 Percent predicted FEV1/FVC ratio Chronic Obstructive Pulmonary Disease COPD|Pulmonary Function 2 "Optic disc size, cup" optic disc size Disc 3 Clozapine-induced change in total cholesterol antipsychotic drugs|metabolic side effects Clozapine - Total Cholesterol 3 Quetiapine-induced change in HDL antipsychotic drugs|metabolic side effects Quetiapine - HDL 3 "Hip geometry, neck section modulus" association bone NeckZ1 2 "Plasma Phospholipid levels, lower docosahexaenoic acid" Plasma Phospholipid|Fatty Acids 3 Complement C3 and C4 levels Complement C3 3 Coronary artery calcification atherosclerosis Coronary artery calcification 3 Multiple sclerosis Multiple Sclerosis 3 Atopic dermatitis psoriasis|atopic dermatitis|asthma 3 Urinary isoprostanes/creatinine biomarker traits Urinary isoprostanes/creatinine 3 Age of onset of Parkinson's disease Parkinson disease|onset 3 Telomere length telomere length 3 Forced expiratory volume in one second slope pulmonary function longitudinal slope of fev 3 "White blood cell types, eosinophil count" White Blood Cell Count|Cell Phenotypes|White Blood Cell 2 Childhood onset asthma Asthma 2 "Plasma Phospholipid levels, eicosapentaenoic acid" Plasma Phospholipid|Fatty Acids 3 Response to the antipsychotic treatment risperidone Response Treatment|Antipsychotics Risperidone ‰ŰŇ Negative 3 "Bone mineral density, spine" bone mineral density 3 Retinal arteriolar caliber arterioles 2 Ziprasidone-induced change in hip circumference antipsychotic drugs|metabolic side effects Ziprasidone - Hip Circumference 3 "Platelet aggregation, adenosine diphosphate" platelet aggregation Epi 2 u M 2 Obesity-related traits Childhood Obesity|Childhood Sleep RQ 3 Usual bedtime circadian phenotypes|sleep 2 Age at onset of menarche and menopause age menarche|menopause 3 Olanzapine-induced change in hemoglobin A1c antipsychotic drugs|metabolic side effects Olanzapine - Hemoglobin A1c 3 Combined Crohn's disease and celiac disease Celiac Disease|Crohn's Disease 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein FUCA 2 Obesity-related traits Childhood Obesity|Childhood IGFBP-3 (ng/mL) 3 Waist circumference Body Fat Distribution WC_women 2 Renal sinus fat chronic kidney disease 2 Atrial fibrillation cardiovascular disease atrial fibrillation 3 Perphenazine-induced change in triglycerides antipsychotic drugs|metabolic side effects Perphenazine - Triglycerides 3 Psoriasis Psoriasis|New Disease 3 Left ventricular systolic dimension exercise responses|artery left ventricular systolic dimension 3 "Cognitive performance, similarities" brain|cognitive test similarities 3 Obesity-related traits Childhood Obesity|Childhood Weight (kg) 3 Atopy Respiratory|atopy 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein DG12 2 Colorectal cancer Colorectal Cancer 3 Mean corpuscular volume Cell Traits|Red Blood Cell MCV 2 Proinsulin levels Type 2 Diabetes|Proinsulin Levels 2 Triglycerides Cardiovascular Disease triglycerides 3 Drug-induced torsades de pointes Torsades de Pointes 3 Creutzfeldt-Jakob disease Creutzfeldt‰ŰŇJakob disease 3 Internal carotid artery intimal medial thickness atherosclerosis Internal carotid artery intimal medial thickness 3 Metabolic syndrome Metabolic Syndrome HDLC-TG 3 Iron status biomarkers Iron Deficiency Case-Control 3 Waist circumference Body Fat Distribution WC_Men 2 Waist circumference complex disease Waist Circumference 3 Quantitative broadband ultrasound attentuation of the calcaneus association bone fnbmd 2 "Antipsychotic-induced QTc interval prolongation, risperidone" cardiac arrhythmias risperidone/QTc 3 Systolic blood pressure Cardiovascular Disease|Blood Pressure 2 "Esophageal cancer, ESCC" esophageal squamous cell carcinoma|gastric adenocarcinoma 3 Response to citalopram treatment global disease|citalopram-induced side effects 3 Serum bilirubin levels bilirubin levels 3 Ever versus never smoking status Smoking Behaviors|Cigarette Smoking 2 Colorectal cancer colorectal cancer 3 Eye color Common Traits Freckling 0 Thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences 3 Adolescent idiopathic scoliosis Adolescent Idiopathic Scoliosis 3 "White blood cell types, monocyte count" White Blood Cell Count|Cell Phenotypes|White Blood Cell 3 Metabolic syndrome Metabolic Syndrome MetS 3 "Caudate nucleus volume, Right caudate" brain 2 Alanine aminotransferase biomarker traits Alanine aminotransferase exam 2 3 "Coronary heart disease risk factor, hypertension" Coronary Heart Disease Hypertension 3 Freckling Common Traits Hair color 0 Diastolic blood pressure Hypertension|Blood Pressure SBP 2 Late onset Alzheimer's disease late-onset Alzheimer‰ŰŞs disease 3 "Cardiovascular disease including myocardial infarction, coronary insufficiency, CHD death, atherothrombotic stroke" cardiovascular disease Major cardiovascular disease 3 Mean body mass index waist circumference|body mass index 3 "T-tau, mild cognitive impairment" ěă protein levels 3 Serum mean cell volume erythrocyte MCV 2 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome WC-TG 2 Response to the antipsychotic treatment ziprasidone Response Treatment|Antipsychotics Ziprasidone ‰ŰŇPositive 3 Eating disorders Personality Traits|Eating 3 Longevity longevity 3 Mean waist circumference waist circumference|body mass index Mean waist circumference 3 "P-tau181p, normal" ěă protein levels 2 Corneal astigmatism Corneal Astigmatism 3 "Blood pressure, pulse pressure" mean arterial pressure|pulse pressure 3 Obesity-related traits Childhood Obesity|Childhood Sleep duration (min/d) 3 Thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences TSH/FT4 3 Trochanter bone mineral density association bone trochanter bmd** 3 Red blood cell count hematological phenotypes red blood cell count 3 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome HDLC-TG 2 Bone mineral density bone mineral density 3 Relative hand skill in reading disability brain 0 C-reactive protein C-Reactive Protein 3 HDL cholesterol complex disease 0 Osteoporosis Osteoporosis 3 Sneezing Common Traits Sneeze 3 Epworth sleepiness scale score circadian phenotypes|sleep Sleepiness 2 "Plasma Phospholipid levels, ALA" Plasma Phospholipid|Fatty Acids 3 Callous-unemotional behaviour Behavior 0 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and waist circumference" Metabolic Syndrome 2 LDL cholesterol Cardiovascular Disease LDL-cholesterol 3 "Hip geometry, shaft section modulus, gender differentiated in females" association bone shaft section modulus** 3 Serum dehydroepiandrosterone sulphate levels Dehydroepiandrosterone sulphate 3 "Cardiovascular disease risk factors, migraineurs with aura - major CVD" Cardiovascular Events|Cardiovascular 2 "Optic disc size, disc" optic disc size Disc 3 C-reactive protein biomarker traits "C-reactive protein average exams 2,6,7" 3 Plasma vitamin D biomarker traits Vitamin D plasma 25(OH)-D 3 Glaucoma Optic Nerve|Glaucoma 3 Bipolar disorder bipolar disorder 3 Soluble ICAM-1 ICAM-1 3 Anticoagulant levels Protein C PC 0 Bipolar disorder Bipolar disorder 3 Asthma Asthma|Bronchodilator Response 3 Alzheimer's disease Alzheimer's disease 3 Diastolic blood pressure blood pressure DBP 2 Serum magnesium levels "Serum Magnesium,|Potassium,|Serum Magnesium Levels" 3 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome MetS 2 Green eyes Common Traits Green eyes 3 Stage 2 exercise systolic blood pressure exercise responses|artery Stage 2 Exercise systolic blood pressure 3 Dengue shock syndrome Dengue shock syndrome 3 Height C-type natriuretic peptide|height 3 Obesity-related traits Childhood Obesity|Childhood Urinary nitrogen (g/d) 3 "Coronary heart disease including myocardial infarction, coronary insufficiency, CHD death" cardiovascular disease 3 Type 2 diabetes Obese|Type 2 Diabetes 3 Parkinson's disease Parkinson's disease 3 Stage 2 exercise heart rate exercise responses|artery Stage 2 Exercise heart rate 3 Carotid-femoral pulse wave velocity arterial stiffness|blood pressure CF-PWV 2 Femoral neck bone mineral density association bone femoral bmd** 3 "Hip geometry, neck section modulus" association bone lumbar spine bmd** 2 "Obesity, waist-hip ratio" Obesity|Obesity-Related Traits WHR 2 Bone mineral density Femoral Neck Bone|Bone Mineral Density 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein FUCA 2 Eye color Common Traits Hair color 0 Presence of antiphospholipid antibodies Antiphospholipid Antibodies 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG7" Master|Plasma Protein DG9 2 Green eyes Common Traits Hair color 0 "Obesity, weight" Obesity|Obesity-Related Traits BMI 3 Response to the antipsychotic treatment olanzapine Response Treatment|Antipsychotics Olanzapine ‰ŰŇ Excitement 3 "Statin-mediated cholesterol level, sum trait" Lipid-Lowering Response|Response Statins 2 Psoriasis Psoriasis 3 Diastolic blood pressure Hypertension|Blood Pressure 2 "Cognitive performance, visual memory and organization" brain|cognitive test factor 2:visual memory and organization 3 Autism autism spectrum 3 Central corneal thickness Brittle Cornea Syndrome|Blinding Disease 2 "Brain MRI, temporal horn volume" brain|cognitive test ALTHBV 2 Systemic lupus erythematosus Systemic Lupus Erythematosus 3 Response to the antipsychotic treatment olanzapine Response Treatment|Antipsychotics Olanzapine ‰ŰŇ Negative 3 Type 1 diabetes nephropathy Type 1 Diabetes|Kidney Disease|Diabetic Nephropathy T1DN 3 Obesity-related traits Childhood Obesity|Childhood Fat free mass (kg) 3 Menarche Age Menarche 3 Breast cancer prostate cancer|breast 2 Neuroblastoma neuroblastoma 3 Number of teeth Primary Tooth Development 2 "Platelet aggregation, adenosine diphosphate" platelet aggregation ADP 2 u M 2 "Cardiovascular disease risk factors, migraineurs with aura - ischemic stroke" Cardiovascular Events|Cardiovascular 2 "Type II diabetes, Chinese, Malay, Indian" Type 2 Diabetes|Transferability 2 Bone mineral density Volumetric Bone Mineral Densities 3 Left ventricular mass left ventricular mass 3 Smoking behavior smoking behaviors CPD 2 Forced expiratory flow between 25th and 75th percentile slope pulmonary function 2 Migraine without aura migraine 3 Thyroid stimulating hormone complex disease Thyroid Stimulating Hormone 3 Social autistic-like traits Autistic-Like Traits 3 Clozapine-induced change in heart rate antipsychotic drugs|metabolic side effects Clozapine - Heart Rate 3 Telomere length Telomere Length 3 "Femoral neck bone mineral density, gender differentiated in males" association bone femoral bmd** 3 "Vitamin D, Vitamin K phylloquinone, Vitamin K % undercaboxylated osteocalcin" biomarker traits "Vitamin D, Vitamin K phylloquinone & Vitamin K % undercarboxylated osteocalcin" 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and fasting glucose" Metabolic Syndrome HDLC-GLUC 2 Breast cancer Breast Cancer|Breast 3 PR interval PR Interval 3 0- to 120-min insulin sensitivity index diabetes-related traits 2 Mean corpuscular hemoglobin concentration Cell Traits|Red Blood Cell MCH 2 Waist-hip ratio Body Fat Distribution WHR_BMI_men 2 Word reading reading|language 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG9" Master|Plasma Protein DG7 2 Type I diabetes type 1 diabetes 3 Nonalcoholic fatty liver disease Non-Alcoholic Fatty Liver Disease|Liver Disease 3 Percent predicted forced vital capacity pulmonary function percent predicted fvc for latest exam 3 Iron deficiency Iron Deficiency Case-Control 3 Rheumatoid arthritis Rheumatoid Arthritis 3 Barrett's esophagus Barrett‰ŰŞs esophagus 3 Self-reported allergy allergy 3 "Metabolic syndrome bivariate trait, blood pressure and fasting glucose" Metabolic Syndrome HDLC-GLUC 2 Post-exercise 3 minute recovery: systolic blood pressure exercise responses|artery Post-exercise 3 minute recovery systolic blood pressure 3 Ovarian cancer ovarian cancer 3 Triglycerides complex disease 0 Sex hormone-binding globulin levels "Testosterone,|Estradiol,|Sex Hormone-Binding Globulin" 3 "Obesity, hip" Obesity|Obesity-Related Traits BMI 2 Serum testosterone Serum Testosterone 3 Endometriosis endometriosis 3 Tissue plasminogen activator hematological phenotypes tissue plasminogen activator 3 Response to taxane treatment lung cancer|overall survival 2 Obesity-related traits Childhood Obesity|Childhood Sleep energyexpenditure adjweight (kcal/d) 3 Red blood cell traits Cell Traits|Red Blood Cell|Resistance RBC count 3 Adiponectin levels Metabolic Traits|Type 2 Diabetes|Adiponectin Levels 3 pathological myopia Pathological Myopia 3 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome WC-TG 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome TG-BP 3 Waist-hip ratio Body Fat Distribution WHR_BMI_Men 2 Suicide attempts in bipolar disorder attempted suicide 3 Celiac disease Celiac Disease 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome HDLC-WC 2 Age at natural menopause age-related phenotypes|longevity Age at natural menopause‰ŰÁ 3 Waist circumference Body Fat Distribution WC_pooled 2 Waist-hip ratio Body Fat Distribution 2 Obesity-related traits Childhood Obesity|Childhood Hip circumference (cm) 3 Social communication problems social communication 3 "Antennary fucosylated glycans, FUC-A" Master|Plasma Protein DG9 2 Eating disorders Personality Traits|Eating BULIMIA 3 "Plasma Phospholipid levels, EPA" Plasma Phospholipid|Fatty Acids 3 Hypertension Hypertension|Blood Pressure HTN 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and fasting glucose" Metabolic Syndrome BP-GLUC 2 Type II diabetes Type 2 Diabetes 3 QT interval QT interval duration 3 "Antipsychotic-induced QTc interval prolongation, quetiapine" cardiac arrhythmias quetiapine/QTc 3 Intracranial aneurysm intracranial aneurysm 3 Vitamin K % undercarboxylated osteocalcin biomarker traits Vitamin K % undercarboxylated osteocalcin 3 "Carotid intima media thickness, cIMT" intima media thickness|plaque 3 Sexual dysfunction Sexual Dysfunction Overall FSD 3 Hippocampal atrophy Hippocampal Atrophy|Quantitative Trait 3 Red hair color Common Traits Red hair 3 Red hair color Common Traits Hair color 2 "Hip geometry, shaft width, gender differentiated in females" association bone shaft width** 3 Pancreatic cancer Pancreatic Cancer 3 "Metabolic syndrome bivariate trait, blood pressure and high-density lipoprotein cholesterol" Metabolic Syndrome BP-HDLC 2 "Caudate nucleus volume, Left caudate" brain 2 Amyloid A Levels "serum amyloid A|type 2 diabetes|type 2 diabetes," 3 Interstitial lung disease pulmonary fibrosis 2 "P-tau181p, mild cognitive impairment" ěă protein levels 2 Diastolic blood pressure complex disease 0 Periodontitis chronic periodontitis 3 Red blood cell count Cell Traits|Red Blood Cell MCH 2 Anti-dsDNA + systemic lupus erythematosus Systemic Lupus Erythematosus|Autoantibody 3 Warfarin maintenance dose CYP2C9|Warfarin 3 Obesity-related traits Childhood Obesity|Childhood Urinary freedopamine:creatinine 3 Stroke ischaemic stroke 3 Relative content of sphingomyelin 18:1 Sphingolipid 2 "Optic disc size, cup" optic disc size Cup 3 Serum CD40 ligand biomarker traits CD40 Ligand serum 3 Factor VII hematological phenotypes 2 Tumor necrosis factor alpha biomarker traits Tumor necrosis factor alpha 3 Mean corpuscular volume Cell Traits|Red Blood Cell RBC count 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome MetS 2 "Cognitive performance, attention and executive function" brain|cognitive test f3 3 Lumbar spine and bone moneral denisty in women Osteoporosis-Related Traits|Gene Expression Profiling LS BMD 2 PR interval length heart rate|variability traits PR 2 Systolic blood pressure blood pressure 2 Psoriatic arthritis psoriasis|psoriatic arthritis 3 Ulcerative colitis ulcerative colitis 3 "Platelet aggregation, adenosine diphosphate" platelet aggregation ADP 10 u M 2 "Systemic sclerosis, ACA positive" Systemic Sclerosis 3 Soluble ICAM-1 Antigen|ICAM-1 3 "Trochanter bone mineral density, gender differentiated in males" association bone trochanter bmd** 3 White blood cell count Cell Phenotypes|White Blood Cell Basophils 3 "Cardiovascular disease risk factors, migraineurs with aura - CVD death" Cardiovascular Events|Cardiovascular 2 Serum uric acid concentration Uric Acid 3 Narcolepsy Narcolepsy 3 Age-related macular degeneration age-related macular degeneration 3 Estradiol levels "Testosterone,|Estradiol,|Sex Hormone-Binding Globulin" 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG11" Master|Plasma Protein DG11 2 Venous thromboembolism Venous Thrombosis 3 Psoriasis psoriasis 3 Risperidone-induced change in hip circumference antipsychotic drugs|metabolic side effects Risperidone - Hip Circumference 3 C-reactive protein biomarker traits 0 Hypersomnia hypersomnia 3 "Hip geometery, neck shaft angle" association bone nsa1 2 Serum calcium Serum Calcium 3 Dietary macronutrient intake analysis 0 Alkaline phosphatase biomarker traits Alkaline phosphatase 3 Perphenazine-induced change in total cholesterol antipsychotic drugs|metabolic side effects Perphenazine - Total Cholesterol 3 Primary biliary cirrhosis primary biliary cirrhosis 3 "Hip geometry, shaft width" association bone shaft width** 3 Coronary artery calcification atherosclerosis 3 Ulcerative colitis Ulcerative colitis 3 "Obesity, hip" Obesity|Obesity-Related Traits Weight 2 "Plasma Phospholipid levels, DPA" Plasma Phospholipid|Fatty Acids 3 "Statin-mediated cholesterol level, difference trait" Lipid-Lowering Response|Response Statins 2 Corneal astigmatism corneal astigmatism|platelet-derived growth factor 3 Red hair color Common Traits Eye color 0 Hodgkin's lymphoma Hodgkin Lymphoma 3 Left ventricular fractional shortening exercise responses|artery left ventricular fractional shortening 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG6" Master|Plasma Protein DG6 2 Mesial temporal lobe epilepsy with hippocampal sclerosis "febrile seizures|Epilepsy," 3 White blood cell count Cell Phenotypes|White Blood Cell Monocytes 2 "Metabolic syndrome bivariate trait, blood pressure and fasting glucose" Metabolic Syndrome BP-GLUC 2 Fasting plasma glucose Melatonin|Plasma Glucose|Type 2 Diabetes 3 Obesity-related traits Childhood Obesity|Childhood IL-6 (pg/mL) 3 Caffeine consumption Caffeine Consumption|CYP1A2 3 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome 2 Percent body fat complex disease 0 Percent predicted forced expiratory volume pulmonary function for latest exam 2 Diastolic blood pressure arterial stiffness|blood pressure blood-pressure 3 Parkinson's disease Parkinson's Disease 3 Epstein-Barr virus immune response Antibodies|Epstein-Barr Virus Nuclear Antigen 3 Celiac disease celiac disease 3 C-reactive protein biomarker traits C-reactive protein exam 2 3 Red blood cell traits Cell Traits|Red Blood Cell|Resistance MCV 3 Obesity anthropometric traits 0 Obesity Obesity|Obesity-Related Traits 3 "Type I diabetes autoantibodies, I-A2A" Type 1 Diabetes|Autoantibody 3 Obesity-related traits Childhood Obesity|Childhood BMI (kg/m 2 ) 3 Morbidity-free survival at age 65 age-related phenotypes|longevity Morbidity-free survival at age 65 3 Heart rate variability: low frequency/high frequency power heart rate|variability traits LF/HF 2 Response to mTOR inhibitor biomarker 0 Diastolic blood pressure Cardiovascular Disease|Blood Pressure 3 Juvenile idiopathic arthritis juvenile idiopathic arthritis 3 Alanine aminotransferase biomarker traits Alanine aminotransferase 3 Mathematical ability in children with dyslexia mathematical abilities|dyslexia|Myosin 3 "P-tau181p, Alzheimer's disease" ěă protein levels 2 ADP-induced platelet aggregation hematological phenotypes platelet aggregation (ADP-induced) 3 Body mass index complex disease 0 Male-pattern baldness Onset|Common Diseases 0 Perphenazine-induced change in HDL antipsychotic drugs|metabolic side effects Perphenazine - HDL 3 "Desialylated 2AB-labelled human plasma N-glycans groups, DG12" Master|Plasma Protein DG7 2 Femoral neck bone geometry and menarche Age Menarche|Femoral Neck Bone Geometry 3 Type 1 diabetes nephropathy Type 1 Diabetes|Kidney Disease|Diabetic Nephropathy ESRD 3 Mean forced vital capacity pulmonary function mean fvc from two exams 3 Heart rate variability: total power heart rate|variability traits TP 2 Biologic age by osseographic scoring system age-related phenotypes|longevity Biologic age by osseographic scoring system 3 Asparagus anosmia Common Traits Asparagus 2 "Coronary heart disease risk factor, HDL-C" Coronary Heart Disease HDL-C 3 Coronary heart disease Coronary Artery Stenosis|Coronary Artery 3 Type 2 diabetes iron intake|type 2 diabetes 3 Thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences TSH 3 HDL Metabolic Syndrome ‰ŰĎ 3 Smoking behavior smoking behaviors AOI 2 Osteoprotegerin biomarker traits Osteoprotegerin 3 Smokers who quit versus those who did not Smoking Behaviors|Cigarette Smoking 2 Forward wave amplitude arterial stiffness|blood pressure FW 2 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and triglycerides" Metabolic Syndrome HDLC-TG 2 "Metabolic syndrome bivariate trait, waist circumference and triglycerides" Metabolic Syndrome TG-BP 2 "Progressive supranuclear palsy, controlling for rs8070723" Progressive Supranuclear Palsy 3 Systemic sclerosis Systemic Sclerosis 3 Cystic fibrosis severity p.Phe508del/p.Phe508del only cystic fibrosis|lung disease 3 Intraocular pressure intraocular pressure|glaucoma 3 "Metabolic syndrome bivariate trait, triglycerides and blood pressure" Metabolic Syndrome MetS 3 Clozapine-induced change in glucose antipsychotic drugs|metabolic side effects Clozapine - Glucose 3 "Hip geometry, shaft section modulus" association bone shaft section modulus** 3 Asthma asthmatics|bronchodilator response 3 Melanoma melanoma 3 Thyroid stimulating hormone kidney|endocrine-related traits thyroid stimulating hormone 3 Response to statin therapy Cardiovascular Event 2 High-risk neuroblastoma neuroblastoma 3 C-reactive protein biomarker traits C-reactive protein exam 6 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and fasting glucose" Metabolic Syndrome 2 N-terminal pro-atrial natriuretic peptide biomarker traits Atrial natriuretic peptide exam 6 3 "Carotid intima media thickness, plaque" intima media thickness|plaque 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and waist circumference" Metabolic Syndrome HDLC-WC 2 Congenital heart disease congenital heart disease|atrial septal defect 3 Primary tooth development tooth eruption|height 2 Hair color Common Traits Freckling 0 Type 2 diabetes type 2 diabetes 3 Lung cancer lung cancer 3 Obesity-related traits Childhood Obesity|Childhood Light activity (min/d) 3 Red blood cell traits Cell Traits|Red Blood Cell|Resistance MCH 3 Waist circumference Body Fat Distribution WC_men 2 Bone mineral density "Bone Mineral Density,|Bone|Osteoporotic Fracture" 3 Plasma C-reactive protein complex disease 3 Hip bone size Hip Bone Size|Females 3 White blood cell count White Blood Cell Count|Cell Phenotypes WBC 3 "Platelet aggregation, collagen" platelet aggregation Lag 2 u g/mL 2 Weight complex disease Weight 3 "Metabolic syndrome bivariate trait, high-density lipoprotein cholesterol and waist circumference" Metabolic Syndrome MetS 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell RBC count 2 Freckling Common Traits Eye color 0 White blood cell count Cell Phenotypes|White Blood Cell Lymphocytes 3 "Trochanter bone mineral density, gender differentiated in females" association bone trochanter bmd** 3 Hair color Common Traits Hair color 3 Sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual WHRadjBMI 3 Neuranatomic and neurocognitive phenotypes neurocognitive phenotypes 3 Coffee consumption CYP1A2 0 Factor VII hematological phenotypes factor vii 3 "Brain MRI, total cerebral brain volume" brain|cognitive test tcbv 2 White blood cell count Cell Phenotypes|White Blood Cell WBC 2 Self-employment Self-Employment 3 "Obesity, body mass index" Obesity|Obesity-Related Traits Weight 3 Cystatin C kidney|endocrine-related traits cst3 2 Cystic fibrosis severity cystic fibrosis|lung disease 3 Age at onset of menarche and menopause age menarche|menopause Age at Menarche 3 Ventricular conduction conduction|QRS duration 2 Obesity-related traits Childhood Obesity|Childhood MCP-1 (pg/mL) 3 IgE levels in asthmatics Mite-Specific IgEs|Asthma 3 Risperidone-induced change in hemoglobin A1c antipsychotic drugs|metabolic side effects Risperidone - Hemoglobin A1c 3 Body mass index complex disease BMI 3 Left atrial diameter exercise responses|artery Left atrial diameter 3 Eye color Common Traits Eye color 3 Metabolic syndrome Metabolic Syndrome WC-TG 3 Mean corpuscular hemoglobin Cell Traits|Red Blood Cell MCV 2 Obesity-related traits Childhood Obesity|Childhood Total energyexpenditure adjweight (kcal/d) 3 "Cardiovascular disease risk factors, any migraine - CVD death" Cardiovascular Events|Cardiovascular 3 Circulating cell-free DNA Cell-Free DNA|Cardiovascular 3 Crohn's disease inflammatory bowel disease 2 Chronic obstructive pulmonary disease chronic obstructive pulmonary disease 3 Percent predicted forced expiratory flow/forced vital capacity ratio pulmonary function percent predicted fef 3 Neck width in men and women Osteoporosis-Related Traits|Gene Expression Profiling NW 2 Anti-dsDNA - systemic lupus erythematosus Systemic Lupus Erythematosus|Autoantibody 3 Abdominal aortic calcification atherosclerosis Abdominal aortic calcification 3 Schizophrenia schizophrenia 3 "Metabolic syndrome bivariate trait, triglycerides and fasting glucose" Metabolic Syndrome TG-GLUC 3 \ No newline at end of file diff --git a/notebooks/util/phenotype.mapping.gwascat.annotated.tsv b/notebooks/util/phenotype.mapping.gwascat.annotated.tsv new file mode 100644 index 0000000..a230c64 --- /dev/null +++ b/notebooks/util/phenotype.mapping.gwascat.annotated.tsv @@ -0,0 +1,767 @@ +hemostatic factors and hematological phenotypes Hematological Phenotypes mean corpuscular hemoglobin 3 +neuritic plaque Dementias|Alzheimer's Disease Complete (Case-Control) 2 +eye color traits Eye Color C HS1 3 +eosinophilic esophagitis Allergic Disease|Eosinophilic Esophagitis 3 +response to antipsychotic treatment Response Treatment|Antipsychotics Ziprasidone –Positive 3 +testosterone levels Serum Testosterone 3 +systemic lupus erythematosus Systemic Lupus Erythematosus 3 +partial epilepsies Partial Epilepsies 3 +bone mineral density (paediatric, skull) Bone Mineral Density|Bone SK-BMD 3 +cerebral amyloid angiopathy Dementias|Alzheimer's Disease Primary (Case-Control) 2 +glycated hemoglobin levels Glycated Hemoglobin 3 +phospholipid levels (plasma) Sphingolipids 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Clozapine - Glucose 3 +metabolic syndrome Metabolic Syndrome TG-BP 3 +alzheimer's disease Alzheimer’s Disease 3 +antipsychotic-induced qtc interval prolongation Cardiac Arrhythmias risperidone/QTc 3 +qt interval Sudden Cardiac Death 0 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease Complete (Case-Control) 3 +handedness in dyslexia Handedness|Dyslexia 3 +obesity Anthropometric Traits 2 +cognitive test performance Brain|Cognitive Test wide-range achievement test 3 +anger Aggression 3 +n-glycan levels Master|Plasma Protein DG6 2 +iron status biomarkers Erythrocyte MCV 2 +select biomarker traits Biomarker Traits CD40 Ligand serum 3 +obesity-related traits Childhood Obesity|Childhood BMI (kg/m 2 ) 3 +tonometry Arterial Stiffness|Blood Pressure MAP 3 +hdl cholesterol Lipid 2 +waist circumference Body Fat Distribution WC_BMI_pooled 2 +body mass index Body Mass Index 3 +sudden cardiac arrest Coronary Artery Disease|Sudden Cardiac Arrest 3 +select biomarker traits Biomarker Traits Monocyte chemoattractant protein-1 3 +echocardiographic traits Exercise Responses|Artery Left atrial diameter 3 +response to statin therapy LDL-c Response|Lpa 3 +schizophrenia (treatment resistant) Treatment Refractory Schizophrenia 3 +progressive supranuclear palsy Progressive Supranuclear Palsy 3 +hippocampal atrophy Hippocampal Atrophy|Quantitative Trait|Alzheimer's Disease 3 +colorectal cancer (diet interaction) Colorectal Cancer 3 +blood pressure (anthropometric measures interaction) Blood Pressure SBP 2 +hemostatic factors and hematological phenotypes Hematological Phenotypes platelet aggregation (collagen-induced) 3 +longevity (90 years and older) Longevity|Analysis|Population 3 +fasting insulin-related traits Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis 3 +hip geometry Association Bone neck section modulus** 2 +bone mineral density (spine) Bone Mineral Density 2 +complement c3 and c4 levels Complement C3 3 +eating disorders Behaviors|Personality Traits|Eating 3 +cholesterol, total Lipid Levels 3 +n-glycan levels Master|Plasma Protein DG12 2 +pulmonary function (interaction) Pulmonary Function|Lung Function 3 +white blood cell count Cell Phenotypes|White Blood Cell Basophils 2 +hair color Common Traits Freckling 3 +select biomarker traits Biomarker Traits Alanine aminotransferase 3 +obesity-related traits Childhood Obesity|Childhood IL-6 (pg/mL) 3 +platelet aggregation Platelet Aggregation ADP 10 u M 3 +social communication problems Social Communication 3 +select biomarker traits Biomarker Traits Tumor necrosis factor alpha 3 +drug-induced torsades de pointes Torsades De Pointes 3 +smoking behavior Smoking Behaviors|Cigarette Smoking 3 +cerebrospinal ab1-42 levels Τ Protein Levels 0 +triglycerides-blood pressure (tg-bp) Metabolic Syndrome TG-BP 3 +qrs duration Conduction|Qrs Duration 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Perphenazine - HDL 3 +nonalcoholic fatty liver disease Metabolic Traits|Nonalcoholic Fatty Liver Disease 3 +thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences 2 +asthma Asthma 3 +cerebrospinal fluid levels of alzheimer's disease-related proteins Proteins Involved|Inflammation|Alzheimer's Disease MMP3 3 +gray matter volume (schizophrenia interaction) Schizophrenia|Quantitative Phenotype|Matter Volume 2 +bone mineral density Association Bone trochanter bmd** 2 +breast cancer in brca2 mutation carriers Breast Cancer 2 +mesial temporal lobe epilepsy with hippocampal sclerosis Epilepsy|Febrile Seizures 2 +systemic lupus erythematosus Systemic Lupus Erythematosus|Autoantibody 3 +neuritic plaque Dementias|Alzheimer's Disease NFT Braak (Ordinal II) 2 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Quetiapine - HDL 3 +metabolite levels Metabolite rs number 3 +autism Autism Spectrum 3 +quantitative traits Complex Disease BMI 3 +very long-chain saturated fatty acid levels (fatty acid 20:0) Long-Chain Saturated Fatty Acids 3 +hyperopia Myopia|Hyperopia 3 +retinal vascular caliber Cardiovascular Diseases 2 +obesity Obesity|Obesity-Related Traits 3 +narcolepsy Narcolepsy 3 +thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences FT4/TSH 2 +bone mineral density (paediatric, lower limb) Bone Mineral Density|Bone 2 +echocardiographic traits Exercise Responses|Artery left ventricular diastolic dimension 3 +lung cancer Lung Cancer 3 +mean forced vital capacity from 2 exams Pulmonary Function mean fvc from two exams 3 +waist-hip ratio Body Fat Distribution WHR_BMI_pooled 2 +underweight status Body Mass Index Underweight 3 +body mass index Body Mass Index BMI: Female 3 +sudden cardiac arrest Sudden Cardiac Death 3 +cerebrospinal t-tau levels Τ Protein Levels 2 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease 3 +morbidity-free survival Age-Related Phenotypes|Longevity Morbidity-free survival at age 65 3 +sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual WCadjBMI 3 +paget's disease Paget’s Disease Bone 3 +behcet's disease Behçet's Disease 3 +platelet aggregation Platelet Aggregation 3 +triglycerides-blood pressure (tg-bp) Metabolic Syndrome 2 +obesity-related traits Childhood Obesity|Childhood Fat mass (kg) 3 +dengue shock syndrome Dengue Shock Syndrome 3 +glycated hemoglobin levels Diabetic Retinopathy|Chronic Kidney Disease|Hemoglobin A 3 +acute lymphoblastic leukemia (childhood) Acute Lymphoblastic Leukemia|Childhood 3 +follicular lymphoma Diffuse Large B-cell Lymphoma|Follicular Lymphoma|Diffuse 3 +sexual dimorphism in anthropometric traits Anthropometric Traits|Sexual WHRadjBMI 3 +aging traits Age-Related Phenotypes|Longevity Walking speed exam 7 3 +white blood cell count Cell Phenotypes|White Blood Cell Neutrophils 2 +insulin resistance/response Insulin Resistance|Copy Number Variation 3 +qt interval Qt Interval Duration 3 +serum ferritin levels Serum Ferritin 3 +obesity-related traits Childhood Obesity|Childhood Sleep duration (min/d) 3 +waist-hip ratio Body Fat Distribution WHR_BMI_men 2 +number of children (6+ vs. 0 or 1) Parity 2 +nephrolithiasis Nephrolithiasis 3 +barrett's esophagus Barrett’s Esophagus 3 +parkinson's disease Parkinson’s Disease 3 +lipid traits Lipid Levels TG 3 +parasitemia in tripanosoma cruzi seropositivity Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PCR 2 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Olanzapine - Hemoglobin A1c 3 +hypertension Hypertension|Blood Pressure 3 +intracranial aneurysm Intracranial Aneurysm 3 +select biomarker traits Biomarker Traits C-reactive protein exam 6 3 +cocaine dependence Cocaine Dependence 3 +select biomarker traits Biomarker Traits Alanine aminotransferase exam 2 3 +inflammatory bowel disease Inflammatory Bowel Disease 3 +obesity-related traits Childhood Obesity|Childhood IGFBP-3 (ng/mL) 3 +height Height 3 +type 2 diabetes Type 2 Diabetes|Transferability 3 +type 1 diabetes Type 1 Diabetes 3 +hip geometry Association Bone shaft width** 2 +tonometry Arterial Stiffness|Blood Pressure RW 2 +obesity-related traits Childhood Obesity|Childhood Glucose (mg/dL) 3 +obesity Childhood Obesity 3 +basal cell carcinoma Basal Cell Carcinoma 3 +hepatitis b (viral clearance) Chronic Hepatitis B 3 +ige levels Serum IgE Levels 3 +aging traits Age-Related Phenotypes|Longevity Age at natural menopause‡ 3 +alzheimer's disease (late onset) Late-Onset Alzheimer's Disease 3 +airway hyperresponsiveness Airway Responsiveness 3 +coronary heart disease Coronary Heart Disease 3 +n-glycan levels Master|Plasma Protein DG7 2 +platelet aggregation Platelet Aggregation ADP 2 u M 3 +obesity-related traits Childhood Obesity|Childhood Triglycerides(mg/dL) 3 +epilepsy Epilepsies All epilepsy 3 +pr interval in tripanosoma cruzi seropositivity Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive PR 2 +hepatocellular carcinoma Chronic Hepatitis B|Hepatitis B Virus|Carriers 0 +electrocardiographic traits Heart Rate|Variability Traits QT 2 +response to citalopram treatment Global Disease|Depression|Citalopram-Induced Side Effects 3 +coffee consumption Cyp1A2 0 +social autistic-like traits Autistic-Like Traits 3 +optic nerve measurement (disc area) Optic Disc Size Cup 3 +obesity Obesity|Obesity-Related Traits WHR 3 +primary tooth development (number of teeth) Primary Tooth Development 3 +uric acid levels Uric Acid Levels 3 +common traits (other) Common Traits Hair curl 3 +age-related macular degeneration Age-Related Macular Degeneration 3 +type 2 diabetes Type 2 Diabetes|Body Mass Index 3 +height Body Mass Index Height: Female 3 +chagas cardiomyopathy in tripanosoma cruzi seropositivity Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive Cardio 3 +breast cancer Breast Cancer|Breast 3 +bone mineral density Bone Mineral Density|Osteoporosis 3 +addiction Opiates Addiction|African-Origin 3 +neurofibrillary tangles Dementias|Alzheimer's Disease NFT Braak (Ordinal I) 2 +number of children Parity 2 +pulmonary function Lung Function|Follow-Up 3 +bone mineral density Association Bone femoral bmd** 3 +antipsychotic-induced qtc interval prolongation Cardiac Arrhythmias quetiapine/QTc 2 +obesity-related traits Childhood Obesity|Childhood Sedentary&lightactivity (min/d) 3 +pulmonary function Pulmonary Function longitudinal slope of fev 3 +red blood cell traits Cell Traits|Red Blood Cell MCV 3 +presence of antiphospholipid antibodies Antiphospholipid Antibodies 3 +hip geometry Association Bone shaft section modulus** 3 +bilirubin levels Bilirubin Levels 3 +bone mineral density (paediatric, total body less head) Bone Mineral Density|Bone 2 +intraocular pressure Intraocular Pressure|Glaucoma 3 +serum thyroid-stimulating hormone levels Serum Thyroid Stimulating Hormone 3 +diabetes related insulin traits Diabetes-Related Traits Fasting Insulin 3 +ovarian cancer Ovarian Cancer 3 +longevity Longevity 3 +amyotrophic lateral sclerosis Amyotrophic Lateral Sclerosis 3 +response to cytidine analogues (gemcitabine) Biomarkers 0 +venous thromboembolism Venous Thrombosis 3 +neurofibrillary tangles Dementias|Alzheimer's Disease Primary (Case-Control) 2 +hemostatic factors and hematological phenotypes Hematological Phenotypes hemoglobin 3 +upper aerodigestive tract cancers Cancers|Conducted|Upper Aerodigestive Tract 3 +response to antipsychotic treatment Response Treatment|Antipsychotics Olanzapine – Negative 3 +longevity (85 years and older) Longevity|Analysis|Population 3 +non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein ALB 3 +hiv-1 control Hiv-1 3 +refractive astigmatism Astigmatism|Refractive Error 3 +qt interval Qt Interval|Calcium 3 +urinary metabolites (h-nmr features) Metabolic Traits|Metabolite-Disease Unknown 2 +response to methotrexate in juvenile idiopathic arthritis Methotrexate Response|Juvenile Idiopathic Arthritis 3 +obesity-related traits Childhood Obesity|Childhood MCP-1 (pg/mL) 3 +cerebrospinal fluid levels of alzheimer's disease-related proteins Proteins Involved|Inflammation|Alzheimer's Disease IL6R 3 +smoking behavior Smoking Behaviors CPD 3 +cholesterol Serum Cholesterol Levels 3 +tetralogy of fallot Tetralogy Fallot 3 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease Neuritic Plaque (Case-Control) 3 +warfarin maintenance dose Warfarin 2 +response to cytadine analogues (cytosine arabinoside) Biomarkers 0 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Ziprasidone - Hip Circumference 3 +neuranatomic and neurocognitive phenotypes Neurocognitive Phenotypes 3 +cognitive test performance Brain|Cognitive Test f3 3 +atrial fibrillation Lone Atrial Fibrillation 3 +quantitative traits Complex Disease Waist Circumference 3 +bone mineral density Volumetric Bone Mineral Densities 3 +suicide attempts in depression or bipolar disorder Suicidal Ideation|Attempts Suicidal|Suicide Attempts 3 +platelet aggregation Platelet Aggregation Lag 2 u g/mL 3 +arthritis (juvenile idiopathic) Juvenile Idiopathic Arthritis 3 +dental caries Dental Caries 3 +systolic blood pressure (alcohol consumption interaction) Blood Pressure MAP 3 +parkinson's disease Parkinson's Disease 3 +adolescent idiopathic scoliosis (severe) Adolescent Idiopathic Scoliosis 3 +sexual dysfunction (female) Sexual Dysfunction Arousal 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Clozapine - Heart Rate 3 +systolic blood pressure Cardiovascular Disease|Blood Pressure 2 +age-related cataracts (age at onset) Cataract 2 +metabolite levels Metabolite Quantitative Trait TMAu 3 +diabetes related insulin traits Diabetes-Related Traits 3 +freckling Common Traits Hair color 3 +red blood cell traits Cell Traits|Red Blood Cell MCH 3 +pulmonary function Pulmonary Function mean fev 3 +breast cancer (survival) Breast Cancer 3 +word reading Reading|Language 3 +corneal astigmatism Corneal Astigmatism 3 +lewy body disease Dementias|Alzheimer's Disease Lewy Body (Case-Control) 3 +glioma Increased Disease Risk 0 +esophageal cancer and gastric cancer Esophageal Squamous Cell Carcinoma|Gastric Adenocarcinoma 3 +bone mineral density (paediatric, total body less head) Bone Mineral Density|Bone UL-BMD 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Risperidone - Waist Circumference 3 +age-related cataracts Cataract 3 +red blood cell traits Cell Traits|Red Blood Cell|Resistance MCHC 3 +cystatin c Kidney|Endocrine-Related Traits cst3 2 +hdl cholesterol - triglycerides (hdlc-tg) Metabolic Syndrome TG-BP 2 +testosterone levels Sex Hormone-Binding Globulin|Testosterone|Estradiol 3 +cerebrospinal fluid levels of alzheimer's disease-related proteins Proteins Involved|Inflammation|Alzheimer's Disease 3 +neuritic plaque Dementias|Alzheimer's Disease CAA (Case-Control) 2 +sex hormone-binding globulin levels Globulin|Hormone|Steroid Hormone 2 +bone mineral density (paediatric, total body less head) Bone Mineral Density|Bone TBLH-BMD 2 +parkinson's disease (age of onset) Parkinson Disease|Onset 3 +bone mineral density Association Bone fnbmd 3 +ulcerative colitis Ulcerative Colitis 3 +neurofibrillary tangles Dementias|Alzheimer's Disease Complete (Case-Control) 2 +mean arterial pressure (alcohol consumption interaction) Blood Pressure MAP 2 +obesity Obesity|Obesity-Related Traits Weight 3 +cerebrospinal fluid levels of alzheimer's disease-related proteins Proteins Involved|Inflammation|Alzheimer's Disease CCL2 2 +cerebral amyloid angiopathy Dementias|Alzheimer's Disease Neuritic Plaque (Case-Control) 2 +urinary metabolites (h-nmr features) Metabolic Traits|Metabolite-Disease Lysine 3 +quantitative traits Complex Disease Weight 3 +sleep-related phenotypes Circadian Phenotypes|Sleep Sleep duration 3 +heart rate variability traits Heart Rate|Variability Traits TP 3 +metabolic syndrome Metabolic Syndrome MetS 3 +heart rate variability traits Heart Rate|Variability Traits LF/HF 3 +systemic lupus erythematosus Systemic Lupus Erythematosus Sle 3 +triglycerides-blood pressure (tg-bp) Metabolic Syndrome MetS 2 +hemostatic factors and hematological phenotypes Hematological Phenotypes platelet aggregation (ADP-induced) 3 +bone mineral density Bone Mineral Density|Bone|Osteoporotic Fracture 3 +systolic blood pressure Blood Pressure 2 +quantitative traits Complex Disease 0 +response to antipsychotic treatment Response Treatment|Antipsychotics Risperidone – Negative 3 +quantitative traits Complex Disease Thyroid Stimulating Hormone 3 +cognitive test performance Brain|Cognitive Test boston naming test 3 +vitamin d levels Vitamin D Levels 3 +periodontal disease-related phenotypes Periodontal 3 +fasting plasma glucose Diabetes-Related Traits fasting plasma glucose 3 +soluble icam-1 Icam-1 3 +waist circumference Body Fat Distribution WC_pooled 2 +stroke Ischemic Stroke 3 +diastolic blood pressure Cardiovascular Disease|Blood Pressure 2 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Olanzapine - Total Cholesterol 3 +bladder cancer Bladder Cancer|Bladder 3 +eye color Pigmentation|Skin Eye C' 3 +body mass index Waist Circumference|Body Mass Index Mean body mass index 3 +vitamin b levels in ischemic stroke Ischemic Stroke|Vitamin|Folate Levels 2 +lewy body disease Dementias|Alzheimer's Disease Lewy Body (Ordinal II) 3 +periodontal disease-related phenotypes Periodontal PD1 3 +hypertension Hypertension|Blood Pressure HTN 3 +osteoarthritis Osteoarthritis 3 +nonalcoholic fatty liver disease Non-Alcoholic Fatty Liver Disease|Liver Disease 3 +osteoporosis-related phenotypes Osteoporosis-Related Traits|Gene Expression Profiling LS BMD 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome BP-HDLC 3 +adiponectin levels Metabolic Traits|Type 2 Diabetes|Adiponectin Levels 3 +lipid traits Lipid Levels HDL 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome TG-GLUC 3 +anticoagulant levels Protein C Total PS 0 +glycated hemoglobin levels Hemoglobin A 3 +natriuretic peptide levels NT-proBNP 0 +optic nerve measurement (cup area) Optic Disc Size Cup 3 +triglycerides Lipid Levels 2 +urinary metabolites (h-nmr features) Metabolic Traits|Metabolite-Disease N-acetylated compounds 3 +body mass index Type 2 Diabetes|Body Mass Index 3 +obesity and osteoporosis Obesity|Osteoporosis Phenotypes 3 +femoral neck bone geometry Femoral Neck Bone Geometry 3 +estradiol levels Sex Hormone-Binding Globulin|Testosterone|Estradiol 3 +height Body Mass Index Height 3 +neurofibrillary tangles Dementias|Alzheimer's Disease Neuritic Plaque (Ordinal) 2 +endometrial cancer Cancer 2 +menarche (age at onset) Age Menarche 3 +body mass index Body Mass Index BMI 3 +exudative age-related macular degeneration Age-Related Macular Degeneration 3 +response to antipsychotic treatment Response Treatment|Antipsychotics Olanzapine – Excitement 3 +systolic blood pressure (alcohol consumption interaction) Blood Pressure SBP 2 +serum selenium levels Serum Selenium 3 +vitiligo Generalized Vitiligo 3 +urinary albumin excretion Kidney|Endocrine-Related Traits urinary albumin excretion 3 +disc degeneration (lumbar) Lumbar Disc Degeneration 3 +menarche and menopause (age at onset) Age Menarche|Menopause 3 +hip geometry Association Bone lsbmd 2 +multiple sclerosis (ocb status) Multiple Sclerosis|Oligoclonal Band 3 +red blood cell traits Cell Traits|Red Blood Cell MCHC 3 +obesity-related traits Childhood Obesity|Childhood Hip circumference (cm) 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome WC-GLUC 2 +dietary macronutrient intake Analysis 0 +thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences TSH 2 +igg glycosylation Immunoglobulin G|Human Immunoglobulin|-Glycosylation 3 +eye color Common Traits Green eyes 3 +hdl cholesterol - triglycerides (hdlc-tg) Metabolic Syndrome HDLC-WC 2 +periodontitis Chronic Periodontitis 3 +neuroblastoma (high-risk) Neuroblastoma 3 +tourette syndrome Tourette Syndrome 3 +multiple sclerosis Multiple Sclerosis 3 +wilms tumor Wilms Tumor 3 +fibrinogen levels (smoking status, alcohol consumption or body mass index interaction) Fibrinogen|Alcohol Consumption|Body Mass Index 3 +waist circumference Body Fat Distribution WC_BMI_men 2 +very long-chain saturated fatty acid levels (fatty acid 24:0) Long-Chain Saturated Fatty Acids 3 +select biomarker traits Biomarker Traits Vitamin D plasma 25(OH)-D 3 +esophageal adenocarcinoma Barrett’s Esophagus|Esophageal Adenocarcinoma 3 +conotruncal heart defects Birth 0 +response to statin therapy Lipid-Lowering Response|Response Statins 3 +response to taxane treatment (placlitaxel) Lung Cancer|Overall Survival 0 +n-glycan levels Master|Plasma Protein DG9 2 +iron deficiency Iron Deficiency Case-Control 3 +self-reported allergy Allergy 3 +cardiovascular disease risk factors Migraine|Cardiovascular Events|Cardiovascular 3 +hip geometry Association Bone NeckZ1 2 +body mass index (change over time) Body Mass Index Change in BMI: Male 3 +pulmonary function Pulmonary Function percent predicted fef 3 +hirschsprung disease Hirschsprung Disease 3 +platelet aggregation Platelet Aggregation lag 3 +expressive vocabulary in infants Suggest|Associated|Linguistic Phenotype 2 +diabetic retinopathy in type 2 diabetes Diabetic Retinopathy 3 +ldl cholesterol LDL-cholesterol 3 +crohn's disease and celiac disease Celiac Disease|Crohn's Disease 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hemoglobin A1c 3 +factor vii Hematological Phenotypes factor vii 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Clozapine - Total Cholesterol 3 +cerebral amyloid angiopathy Dementias|Alzheimer's Disease Complete (Case-Control) 2 +myopia Myopia|Hyperopia 3 +electrocardiographic traits Heart Rate|Variability Traits PR 2 +lymphoma Malignancies 2 +thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences TSH/FT4 2 +anticoagulant levels Protein C funcPS 0 +subclinical atherosclerosis traits (other) Atherosclerosis Ankle brachial index 3 +retinal arteriolar caliber Arterioles 2 +hdl cholesterol - triglycerides (hdlc-tg) Metabolic Syndrome HDLC-TG 2 +sensory disturbances after bilateral sagittal split ramus osteotomy Sensory Disturbances|Split 2 +primary tooth development (time to first tooth eruption) Tooth Eruption|Height 2 +anticoagulant levels Protein C fPS 0 +white blood cell types White Blood Cell Count|Cell Phenotypes|White Blood Cell 3 +protein biomarker Lectin 3 +glioma (high-grade) Telomere Length|Glioma 3 +height Anthropometric Traits 2 +cholelithiasis-related traits in sickle cell anemia Total Bilirubin|Sickle Cell Anemia|Sickle Cell 2 +hemostatic factors and hematological phenotypes Hematological Phenotypes tissue plasminogen activator 3 +breast cancer in brca1 mutation carriers Breast Cancer|Breast Ovarian Cancer|Carriers 2 +crohn's disease Inflammatory Bowel Disease 2 +obesity Obesity|Obesity-Related Traits HIP 3 +blood pressure Arterial Stiffness|Blood Pressure blood-pressure 3 +echocardiographic traits Exercise Responses|Artery left ventricular systolic dimension 3 +interstitial lung disease Pulmonary Fibrosis 3 +major cvd Cardiovascular Disease Major cardiovascular disease 3 +neuritic plaque Dementias|Alzheimer's Disease Neuritic Plaque (Ordinal) 3 +select biomarker traits Biomarker Traits Bilirubin 3 +chagas cardiomyopathy in tripanosoma cruzi seropositivity Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive QRS 3 +neuroblastoma Neuroblastoma 3 +migraine - clinic-based Migraine 3 +subclinical atherosclerosis traits (other) Atherosclerosis Abdominal aortic calcification 3 +hemostatic factors and hematological phenotypes Hematological Phenotypes red blood cell count 3 +cardiovascular disease risk factors Cardiovascular Disease LDL-cholesterol 3 +metabolite levels Atherosclerosis 3 +optic nerve measurement (cup area) Optic Disc Size Disc 3 +lipid traits Lipid Levels TC 3 +type 2 diabetes Type 2 Diabetes 3 +serum uric acid levels Serum Uric Acid Levels Total antioxidant status 3 +cystic fibrosis severity Cystic Fibrosis|Lung Disease 3 +factor vii Hematological Phenotypes FVII, exam 5 3 +circulating cell-free dna Cell-Free Dna|Cardiovascular 3 +periodontal disease-related phenotypes Periodontal PD2 3 +obesity-related traits Childhood Obesity|Childhood Urinary creatinine(mmol/d) 3 +select biomarker traits Biomarker Traits Alkaline phosphatase 3 +bone mineral density Femoral Neck Bone|Bone Mineral Density 3 +myopia (pathological) Ocular Axial Length|High Myopia 3 +optic disc parameters Optic Disc 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome HDLC-WC 2 +lewy body disease Dementias|Alzheimer's Disease Lewy Body (Ordinal I) 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome MetS 3 +osteoporosis-related phenotypes Osteoporosis-Related Traits|Gene Expression Profiling FN BMD 3 +serum uric acid levels Serum Uric Acid Levels 3 +migraine Migraine 3 +platelet aggregation Platelet Aggregation Epi 2 u M 3 +pulse pressure (alcohol consumption interaction) Blood Pressure PP 2 +serum alkaline phosphatase levels Serum Alkaline Phosphatase Levels 3 +ovarian reserve Ovarian Reserve 3 +parent of origin effect on language impairment (paternal) Specific Language Impairment|Genotype Effects 2 +menopause (age at onset) Menopause 3 +epilepsy Epilepsies Focal epilepsy 3 +metabolic syndrome Metabolic Syndrome Log HDL-C (mmol/l) 3 +fasting plasma glucose Melatonin|Plasma Glucose|Type 2 Diabetes 2 +underweight status Body Mass Index Underweight: Male 3 +hair color Common Traits Eye color 0 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease NFT Braak (Ordinal II) 3 +obesity-related traits Childhood Obesity|Childhood Urinary freedopamine:creatinine 3 +renal sinus fat Chronic Kidney Disease 2 +white blood cell count Cell Phenotypes|White Blood Cell Monocytes 2 +body mass index (change over time) Body Mass Index Change in BMI 3 +soluble icam-1 Antigen|Icam-1 3 +obesity-related traits Childhood Obesity|Childhood Total antioxidants(mM) 3 +waist circumference - triglycerides (wc-tg) Metabolic Syndrome WC-TG 2 +freckling Common Traits Eye color 3 +cognitive test performance Brain|Cognitive Test similarities 3 +rheumatoid arthritis Rheumatoid Arthritis 3 +schizophrenia (negative symptoms) Schizophrenia 3 +iron status biomarkers Iron Deficiency Case-Control 3 +inflammatory biomarkers Inflammation ESR 3 +type 1 diabetes autoantibodies Type 1 Diabetes|Autoantibody 3 +atrial fibrillation Atrial Fibrillation 3 +neuritic plaque Dementias|Alzheimer's Disease Primary (Case-Control) 2 +white blood cell count Cell Phenotypes|White Blood Cell WBC 2 +pulse pressure in young-onset hypertension Onset|Hypertension|Cardiovascular Events Nighttime PP 2 +corneal astigmatism Corneal Astigmatism|Platelet-Derived Growth Factor 3 +heart failure Cardiovascular Disease heart failure 3 +serum uric acid levels Serum Uric Acid 3 +autism Autism 3 +non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein TP 3 +breast cancer Breast Cancer 3 +thyroid peroxidase antibody positivity Thyroid Peroxidase Antibodies|Thyroid Disease 2 +brachial circumference Brachial Circumference 3 +hemostatic factors and hematological phenotypes Hematological Phenotypes PAI1 3 +shingles Herpes Zoster 0 +relative hand skill in reading disability Brain 0 +phospholipid levels (plasma) Plasma Phospholipid|Fatty Acids 3 +obesity-related traits Childhood Obesity|Childhood Sleep energyexpenditure adjweight (kcal/d) 3 +freckling Common Traits Red hair 3 +schizophrenia Schizophrenia|Cytomegalovirus Infection|Infection Suggests 3 +pr interval Pr Interval 3 +mean arterial pressure (alcohol consumption interaction) Blood Pressure DBP 3 +borderline personality disorder features Borderline Personality 3 +eye color Common Traits Eye color 3 +sphingolipid levels Sphingolipid 3 +neuritic plaque Dementias|Alzheimer's Disease Neuritic Plaque (Case-Control) 3 +ige levels in asthmatics Mite-Specific IgEs|Asthma 3 +cholesterol, total Lipid 2 +asthma (bronchodilator response) Asthma|Bronchodilator Response 3 +cerebral amyloid angiopathy Dementias|Alzheimer's Disease NFT Braak (Ordinal II) 2 +chronic obstructive pulmonary disease Chronic Obstructive Pulmonary Disease 3 +sleep-related phenotypes Circadian Phenotypes|Sleep Sleepiness 3 +hip geometry Association Bone shaftz1r 2 +chronic lymphocytic leukemia Chronic Lymphocytic Leukemia 3 +anxiety disorder Anxiety 3 +prostate cancer (early onset) Prostate Cancer|Early-Onset 3 +type 2 diabetes (dietary heme iron intake interaction) Iron Intake|Type 2 Diabetes 3 +epilepsy Epilepsies GGE 3 +bone mineral density (paediatric, lower limb) Bone Mineral Density|Bone LL-BMD 3 +tonometry Arterial Stiffness|Blood Pressure FW 3 +coronary artery calcification Atherosclerosis Coronary artery calcification 3 +migraine without aura Migraine 3 +response to statins (ldl cholesterol change) Ldl Cholesterol Response|Response Statins 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Risperidone - Hip Circumference 3 +epstein-barr virus immune response (ebna-1) Antibodies|Epstein-Barr Virus Nuclear Antigen 3 +select biomarker traits Biomarker Traits C-reactive protein average exams 2,6,7 3 +urinary metabolites (h-nmr features) Metabolic Traits|Metabolite-Disease Trimethylamine 3 +waist-hip ratio Body Fat Distribution 2 +neurofibrillary tangles Dementias|Alzheimer's Disease Neuritic Plaque (Case-Control) 3 +male-pattern baldness Onset|Androgenetic Alopecia|Common Diseases 3 +waist circumference - triglycerides (wc-tg) Metabolic Syndrome MetS 0 +ejection fraction in tripanosoma cruzi seropositivity Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive EF 2 +pulmonary function Pulmonary Function percent predicted fvc for latest exam 3 +body mass index (change over time) Body Mass Index Change in BMI: Female 3 +hdl cholesterol - triglycerides (hdlc-tg) Metabolic Syndrome MetS 2 +tonometry Arterial Stiffness|Blood Pressure CF-PWV 3 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease NFT Braak (Ordinal I) 3 +reading and spelling Reading|Language 3 +osteoarthritis (hip) Hip|Osteoarthritis 3 +atopic dermatitis Atopic Dermatitis 3 +waist circumference - triglycerides (wc-tg) Metabolic Syndrome TG-BP 2 +schizophrenia, schizoaffective disorder or bipolar disorder Schizophrenia 3 +hip geometry Association Bone lumbar spine bmd** 0 +metabolic syndrome Metabolic Syndrome “ 3 +sex hormone-binding globulin levels Sex Hormone-Binding Globulin|Testosterone|Estradiol 3 +type 1 diabetes nephropathy Type 1 Diabetes|Kidney Disease|Diabetic Nephropathy T1DN 3 +ulcerative colitis Inflammatory Bowel Disease 2 +obesity-related traits Childhood Obesity|Childhood Light activity (min/d) 3 +igm levels Serum IgM 3 +aortic root size Aortic Root 3 +obesity-related traits Childhood Obesity|Childhood Total energyexpenditure adjweight (kcal/d) 3 +urinary metabolites (h-nmr features) Metabolic Traits|Metabolite-Disease 2-Hydroxyisobutyrate 3 +obesity Obesity|Obesity-Related Traits BMI 3 +chronic hepatitis c infection Chronic Hepatitis C 3 +chronic mucus hypersecretion Chronic Mucus Hypersecretion 3 +hypertension Cardiovascular Disease|Blood Pressure 3 +waist circumference Distribution|Adiposity|Waist Circumference 3 +exercise treadmill test traits Exercise Responses|Artery Post-exercise 3 minute recovery systolic blood pressure 3 +adiponectin levels Adiponectin|Quantitative Trait|Cardiometabolic Outcomes 3 +chronic periodontitis Chronic Periodontitis 3 +blood pressure Mean Arterial Pressure|Pulse Pressure 3 +waist-hip ratio Body Fat Distribution WHR_BMI_women 2 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Triglycerides 3 +obesity-related traits Childhood Obesity|Childhood Weight z-score change (SD/y) 3 +c-reactive protein C-Reactive Protein 3 +hdl cholesterol Coronary Heart Disease HDL-C 2 +social communication problems Social-Communication|Spectrum Phenotypes 3 +obesity Obesity|Obesity-Related Traits Waist 3 +life threatening arrhythmia Arrhythmias 3 +hair color Common Traits Green eyes 0 +volumetric brain mri Brain|Cognitive Test temporal brain volume 3 +subclinical atherosclerosis traits (other) Atherosclerosis Common carotid artery intimal medial thickness 3 +sexual dysfunction (female) Sexual Dysfunction Lubrication 3 +uric acid levels Uric Acid 3 +bone mineral density (paediatric, upper limb) Bone Mineral Density|Bone TBLH-BMD 3 +subclinical atherosclerosis traits (other) Atherosclerosis Internal carotid artery intimal medial thickness 3 +left inferior lateral ventricle volume (cerebrospinal fluid biomarker status interaction) Neurodegeneration|Biomarker 0 +chronic obstructive pulmonary disease Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function 3 +lipoprotein-associated phospholipase a2 activity and mass Phospholipase A 2 +height C-type Natriuretic Peptide|Height 3 +thyroid hormone levels Thyroid|Thyroid-Related Traits|Differences FT4 2 +schizophrenia or bipolar disorder Schizophrenia|Bipolar Disorder|Disorder 3 +cleft plate (environmental tobacco smoke interaction) Tobacco Smoke|Chromosome 4|Cleft Palate 3 +obesity-related traits Childhood Obesity|Childhood Weight (kg) 3 +suicide attempts in bipolar disorder Attempted Suicide 3 +prostate cancer Prostate Cancer|Breast 3 +endothelial function traits Exercise Responses|Artery Baseline brachial artery flow velocity 3 +fasting plasma glucose Diabetes-Related Traits 28 yr time averaged fpg 3 +atopic dermatitis Psoriasis|Atopic Dermatitis|Asthma 3 +select biomarker traits Biomarker Traits C-reactive protein exam 2 3 +type 2 diabetes (young onset) and obesity Onset|Cardiovascular Disease|Diabetes 2 +hdl cholesterol Lipid Levels 2 +hodgkin's lymphoma Hodgkin Lymphoma 3 +eating disorders Behaviors|Personality Traits|Eating BULIMIA 3 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease Primary (Case-Control) 2 +number of pregnancies Parity 2 +psoriatic arthritis Psoriasis|Psoriatic Arthritis 3 +volumetric brain mri Brain|Cognitive Test tcbv 2 +obesity-related traits Childhood Obesity|Childhood Dinner intake, adjEER (kcal) 3 +amyloid a serum levels Serum Amyloid A|Type 2 Diabetes 3 +bone mineral density (paediatric, upper limb) Bone Mineral Density|Bone 2 +alzheimer's disease Glutamate|Alzheimer's Disease 3 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Perphenazine - Total Cholesterol 3 +menarche and menopause (age at onset) Age Menarche|Menopause Age at Menarche 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome HDLC-GLUC 3 +glaucoma (primary open-angle) Optic Nerve|Glaucoma 3 +waist circumference Waist Circumference|Body Mass Index Mean waist circumference 3 +thyroid stimulating hormone Kidney|Endocrine-Related Traits thyroid stimulating hormone 3 +diabetes (incident) Diabetes-Related Traits Incident DM 3 +temperament Temperament Character Inventory 3 +dehydroepiandrosterone sulphate levels Dehydroepiandrosterone Sulphate 3 +thyroid peroxidase antibody levels Thyroid Peroxidase Antibodies|Thyroid Disease 3 +breast cancer Prostate Cancer|Breast 3 +waist circumference Body Fat Distribution WC_Men 2 +inflammatory biomarkers Inflammation IL-6 3 +hypersomnia (hla-dqb1*06:02 negative) Hypersomnia 2 +red blood cell traits Cell Traits|Red Blood Cell|Resistance MCV 3 +telomere length Homeostasis 0 +cerebrospinal p-tau181p levels Τ Protein Levels 3 +femoral neck bone geometry and menarche (age at onset) Age Menarche|Femoral Neck Bone Geometry 3 +melanoma Melanoma 3 +staphylococcus aureus infection Staphylococcus Aureus 3 +lipid traits Lipid Levels LDL 3 +coronary heart disease event reduction in response to statin therapy (interaction) Cardiovascular Event 2 +asthma (bronchodilator response) Asthmatics|Bronchodilator Response 3 +non-word repetition Reading|Language 2 +volumetric brain mri Brain|Cognitive Test ALTHBV 0 +caudate nucleus volume Brain 0 +adverse response to chemotherapy in breast cancer (alopecia) Chemotherapy-Induced Alopecia|Breast Cancer 2 +cerebral amyloid angiopathy Dementias|Alzheimer's Disease CAA (Case-Control) 2 +warfarin maintenance dose Cyp2C9|Warfarin 2 +psoriasis Psoriasis|Psoriatic Arthritis|New Disease 3 +esophageal squamous cell carcinoma Esophageal Squamous Cell Carcinoma 3 +cognitive test performance Brain|Cognitive Test factor 2:visual memory and organization 3 +inflammatory biomarkers Inflammation MCP-1 3 +overweight status Body Mass Index Overweight 3 +antibody status in tripanosoma cruzi seropositivity Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive EIA 3 +black vs. blond hair color Hair Color|Skin Pigmentation 3 +pancreatic cancer Pancreatic Cancer 3 +pulmonary function Chronic Obstructive Pulmonary Disease Copd|Pulmonary Function 3 +metabolite levels Metabolite Quantitative Trait N-ACu 3 +obesity Obesity 3 +bone mineral density (paediatric, upper limb) Bone Mineral Density|Bone UL-BMD 3 +mathematical ability in children with dyslexia Mathematical Abilities|Dyslexia|Myosin 3 +black vs. red hair color Hair Color|Skin Pigmentation 2 +height Stature 3 +systemic sclerosis Systemic Sclerosis 3 +red blood cell traits Cell Traits|Red Blood Cell|Resistance 3 +common traits (other) Common Traits Asparagus 3 +sphingolipid levels Sphingolipids 3 +obesity-related traits Childhood Obesity|Childhood Fat free mass (kg) 3 +digestive system disease (barrett's esophagus and esophageal adenocarcinoma combined) Barrett’s Esophagus|Esophageal Adenocarcinoma 3 +diastolic blood pressure Blood Pressure DBP 3 +optic nerve measurement (disc area) Optic Disc Size Disc 3 +atopy Respiratory|Atopy 3 +rheumatoid arthritis Rheumatoid Arthritis|Biology 3 +waist circumference Body Fat Distribution WC_women 2 +type 1 diabetes nephropathy Type 1 Diabetes|Kidney Disease|Diabetic Nephropathy ESRD 3 +white blood cell count White Blood Cell Count|Cell Phenotypes|White Blood Cell WBC 3 +eye color Common Traits Hair color 0 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease Neuritic Plaque (Ordinal) 2 +narcolepsy Narcolepsy|Influenza|Changes 3 +n-glycan levels Master|Plasma Protein DG1 3 +select biomarker traits Biomarker Traits Vitamin K plasma phylloquinone 3 +primary tooth development (time to first tooth eruption) Primary Tooth Development 2 +diastolic blood pressure (alcohol consumption interaction) Blood Pressure DBP 3 +chronic hepatitis b infection Infection 0 +qrs duration in tripanosoma cruzi seropositivity Chagas Cardiomyopathy|Trypanosoma Cruzi Seropositive QRS 3 +protein quantitative trait loci Protein Quantitative Trait|Genome|Association 3 +inflammatory biomarkers Inflammation hsCRP 3 +colorectal cancer Colorectal Cancer 3 +chronic bronchitis and chronic obstructive pulmonary disease Chronic Obstructive Pulmonary Disease|Chronic Bronchitis 3 +red blood cell traits Cell Traits|Red Blood Cell|Resistance MCH 3 +pulmonary function Pulmonary Function percent predicted fev 3 +n-glycan levels Master|Plasma Protein FUCA 2 +waist circumference Body Fat Distribution WC_men 2 +metabolite levels Metabolite Quantitative Trait BAIBu 3 +carotid intima media thickness Intima Media Thickness|Plaque 3 +red blood cell traits Cell Traits|Red Blood Cell RBC count 3 +echocardiographic traits Exercise Responses|Artery left ventricular mass 3 +quantitative traits Complex Disease Height 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome BP-GLUC 3 +dementia and core alzheimer's disease neuropathologic changes Dementias|Alzheimer's Disease CAA (Case-Control) 3 +adiponectin levels Adiponectin Levels 3 +obesity (early onset extreme) Onset|Obesity-Related Traits|Body-Weight 3 +neurofibrillary tangles Dementias|Alzheimer's Disease NFT Braak (Ordinal II) 2 +freckling Common Traits Freckling 3 +plasma homocysteine levels (post-methionine load test) Homocysteine|Methionine|Metabolism 2 +body mass index Waist Circumference|Body Mass Index 3 +hair color Common Traits Hair color 3 +waist circumference - triglycerides (wc-tg) Metabolic Syndrome 2 +psoriasis Psoriasis 3 +substance dependence European-Origin|Substance Dependence 3 +metabolic syndrome Metabolic Syndrome 3 +intraocular pressure Primary Open-Angle Glaucoma|Intraocular Pressure 3 +coronary heart disease Coronary Artery Stenosis|Coronary Artery 3 +osteoporosis Osteoporosis 3 +tonometry Arterial Stiffness|Blood Pressure CB-PWV 2 +sexual dysfunction (female) Sexual Dysfunction Overall FSD 3 +left ventricular mass Left Ventricular Mass 3 +hdl cholesterol - triglycerides (hdlc-tg) Metabolic Syndrome 2 +echocardiographic traits Exercise Responses|Artery left ventricular fractional shortening 3 +hair color Common Traits Red hair 3 +very long-chain saturated fatty acid levels (fatty acid 22:0) Long-Chain Saturated Fatty Acids 3 +type 2 diabetes Obese|Type 2 Diabetes 3 +bipolar disorder with mood-incongruent psychosis Bipolar Disorder 3 +osteoporosis-related phenotypes Osteoporosis-Related Phenotypes 3 +red blood cell traits Cell Traits|Red Blood Cell|Resistance RBC count 3 +creutzfeldt-jakob disease Creutzfeldt–Jakob Disease 3 +aging traits Age-Related Phenotypes|Longevity Biologic age by osseographic scoring system 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome 3 +coronary artery calcification Atherosclerosis 3 +kawasaki disease Kawasaki Disease 3 +vertical cup-disc ratio Optic Disc 3 +myopia (pathological) Pathological Myopia 3 +celiac disease Celiac Disease 3 +hip bone size Hip Bone Size|Females 3 +stroke (ischemic) Ischaemic Stroke 3 +pancreatitis Pancreatitis 3 +metabolic syndrome Metabolic Syndrome DBP (mmHg) 3 +non-albumin protein levels Immunoglobulin Isotypes|Non-Albumin Protein NAP 3 +primary tooth development (number of teeth) Tooth Eruption|Height 3 +callous-unemotional behaviour Behavior 0 +overweight status Body Mass Index Overweight: Male 3 +osteoporosis-related phenotypes Osteoporosis-Related Traits|Gene Expression Profiling NW 3 +obesity-related traits Childhood Obesity|Childhood Trunk fat mass (kg) 3 +bone mineral density (paediatric, skull) Bone Mineral Density|Bone 2 +cardiovascular disease risk factors Cardiovascular Disease HDL-cholesterol 3 +hypertension Coronary Heart Disease Hypertension 3 +optic nerve measurement (cup-to-disc ratio) Optic Disc Size Cup 3 +pulmonary function Pulmonary Function for latest exam 3 +systolic blood pressure Blood Pressure SBP 2 +smoking behavior Smoking Behaviors AOI 3 +chronic kidney disease Kidney|Follow-Up 2 +bone mineral density (hip) Bone Mineral Density 3 +major depressive disorder (broad) Major Depression 3 +waist-hip ratio Body Fat Distribution WHR_BMI_Men 2 +endometriosis Endometriosis 3 +atrial fibrillation Cardiovascular Disease atrial fibrillation 3 +sleep-related phenotypes Circadian Phenotypes|Sleep Bedtime 3 +asthma (childhood onset) Asthma 3 +metabolic syndrome Metabolic Syndrome HDLC-TG 3 +hearing function Kinase|Hearing 3 +exercise treadmill test traits Exercise Responses|Artery Stage 2 Exercise systolic blood pressure 3 +metabolic syndrome Metabolic Syndrome T2D 3 +triglycerides Lipid 2 +celiac disease or rheumatoid arthritis Rheumatoid Arthritis|Celiac Disease 3 +magnesium levels Potassium|Serum Magnesium|Serum Magnesium Levels 3 +obesity-related traits Childhood Obesity|Childhood Sleep RQ 3 +crohn's disease Crohn's Disease 3 +diabetes related insulin traits Diabetes-Related Traits homeostasis model insulin resistance 3 +cortical thickness Bone Mineral Density|Bone|Osteoporotic Fracture 2 +hip geometry Association Bone necklengf 2 +white blood cell count Cell Phenotypes|White Blood Cell Lymphocytes 3 +testicular germ cell tumor Testicular Cancer 3 +anticoagulant levels Protein C PC 0 +select biomarker traits Biomarker Traits Atrial natriuretic peptide exam 6 3 +ovarian cancer in brca1 mutation carriers Breast Cancer|Breast Ovarian Cancer|Carriers 2 +restless legs syndrome Restless Legs Syndrome 3 +c-reactive protein levels C-Reactive Protein Levels 3 +telomere length Telomere Length 3 +cerebral amyloid angiopathy Dementias|Alzheimer's Disease Neuritic Plaque (Ordinal) 2 +triglycerides-blood pressure (tg-bp) Metabolic Syndrome HDLC-TG 2 +glaucoma (primary open-angle) Glaucoma|Optic-Nerve 3 +obesity (extreme) Extremely|Overweight|Body Mass Index 3 +central corneal thickness Central Corneal Thickness|Brittle Cornea Syndrome|Blinding Disease 3 +marginal zone lymphoma Marginal Zone Lymphoma 3 +alzheimer's disease Alzheimer's Disease 3 +alzheimer's disease (late onset) Late-Onset Alzheimer’s Disease 3 +bone mineral density (paediatric, lower limb) Bone Mineral Density|Bone TBLH-BMD 2 +cerebral amyloid angiopathy Dementias|Alzheimer's Disease NFT Braak (Ordinal I) 2 +aging traits Age-Related Phenotypes|Longevity Age at death 3 +calcium levels Serum Calcium 3 +chronic bronchitis in chronic obstructive pulmonary disease Chronic Obstructive Pulmonary Disease|Chronic Bronchitis 3 +fasting glucose-related traits Fasting Glucose|Type 2 Diabetes|Glucose Homeostasis 3 +triglycerides-blood pressure (tg-bp) Metabolic Syndrome WC-TG 3 +colorectal cancer Colon Cancer 3 +obesity-related traits Childhood Obesity|Childhood Urinary nitrogen (g/d) 3 +ldl cholesterol Coronary Heart Disease LDL-C 3 +celiac disease Celiac Disease|Celiac 3 +caffeine consumption Caffeine Consumption|Cyp1A2 3 +bitter taste perception Bitter Taste|Bitter Taste Perception 3 +hdl cholesterol - triglycerides (hdlc-tg) Metabolic Syndrome WC-TG 2 +cardiovascular disease risk factors Cardiovascular Disease waist circumference 3 +ige levels Serum IgE 3 +metabolic syndrome (bivariate traits) Metabolic Syndrome HDLC-TG 3 +select biomarker traits Biomarker Traits 3 +diabetes related insulin traits Diabetes-Related Traits hemoglobin a1c 3 +volumetric brain mri Brain|Cognitive Test ALLV 2 +self-employment Self-Employment 3 +waist circumference - triglycerides (wc-tg) Metabolic Syndrome HDLC-TG 0 +response to antipsychotic treatment Antipsychotic Drugs|Metabolic Side Effects Clozapine - Triglycerides 3 +bone mineral density (paediatric, total body less head) Bone Mineral Density|Bone LL-BMD 2 +fetal hemoglobin levels in sickle cell anemia Sickle Cell Anemia|Fetal Hemoglobin|Sickle Cell 3 +primary biliary cirrhosis Primary Biliary Cirrhosis 3 +cholesterol Serum Cholesterol Levels HDL-C 3 +proinsulin levels Type 2 Diabetes|Proinsulin Levels 3 +cerebrospinal fluid levels of alzheimer's disease-related proteins Proteins Involved|Inflammation|Alzheimer's Disease CCL4 2 +serum metabolite levels Intermediate Phenotypes 0 +mean platelet volume Platelet Count|Mean Platelet Volume 3 +hippocampal volume Hippocampal Volume 3 +bipolar disorder Bipolar Disorder 3 +cardiovascular disease risk factors Cardiovascular Disease triglycerides 3 +metabolic syndrome Metabolic Syndrome WC-TG 3 +hemostatic factors and hematological phenotypes Hematological Phenotypes Viscosity 3 +exercise treadmill test traits Exercise Responses|Artery Stage 2 Exercise heart rate 3 +n-glycan levels Master|Plasma Protein DG11 3 +neuritic plaque Dementias|Alzheimer's Disease NFT Braak (Ordinal I) 3 +cerebrospinal fluid levels of alzheimer's disease-related proteins Proteins Involved|Inflammation|Alzheimer's Disease ACE 3 +psoriatic arthritis Psoriatic Arthritis 3 +common traits (other) Common Traits Sneeze 3 +response to mtor inhibitor (rapamycin) Biomarker 0 +ldl cholesterol Lipid Levels 2 +metabolic syndrome Metabolic Syndrome HDLC-WC 3 +neurofibrillary tangles Dementias|Alzheimer's Disease CAA (Case-Control) 2 +menopause (age at onset) Age Menopause 3 +osteoporosis-related phenotypes Osteoporosis-Related Traits|Gene Expression Profiling NSA 3 +crohn's disease Ibd Disease 2 +bone mineral density Bone Mineral Density 3 +eye color Common Traits Freckling 0 +cardiovascular disease risk factors Cardiovascular-Related Traits 3 +schizophrenia Schizophrenia 3 +congenital heart disease Congenital Heart Disease|Atrial Septal Defect 3 diff --git a/notebooks/util/rels.discovered.annotated.txt b/notebooks/util/rels.discovered.annotated.txt new file mode 100644 index 0000000..7e98264 --- /dev/null +++ b/notebooks/util/rels.discovered.annotated.txt @@ -0,0 +1,100 @@ +18483556 rs164741 Hair Color|Skin Pigmentation 2 REPEAT The SNP is in a table that summarizes significant results from a previous study; it was not discovered in this paper per se. +18846228 rs2511211 Serum IgE Levels 3 TRUE All of the p-values reported for this SNP in the paper pass the 1e-5 significance threshold +19197348 rs2849176 complex disease 0 TRUE The phenotype is incorrect, but several other gold SNPs in the same table with the same or worse SNPs are reported in GWAS Central +19197348 rs328 complex disease 0 REPEAT The SNP is in a table that summarizes significant results from a previous study; it was not discovered in this paper per se. +19247474 rs1400363 Smoking Behaviors|Cigarette Smoking 2 TRUE The SNP is only significant in the combined SNP, but another SNP with very similar p-values (rs1402279) is reported in GWAS Catalog and is also only significant in the GWAS Central study +19300500 rs1877252 Chronic Obstructive Pulmonary Disease COPD|Pulmonary Function 2 TRUE This is correct according to our specification, but may not have been reported in GWAS Catalog because of a rounding error (i.e. it is significant at 1e-5 if we first round to one significant digits and then filter, but not vice versa) +19343178 rs6817306 Stature 3 TRUE "SNP is mentioned in the text and it says that it's ""one of the strongest"" associations" +19412175 rs17487792 neuroblastoma 3 TRUE It is not significant at 1e-5 in each testing method but its neighbor is reported in GWAS Central, and is also not significant everywhere. +19448621 rs402511 age menarche|menopause 2 TRUE Its significance is confirmed in the text. +19503597 rs780093 Uric Acid 3 TRUE The SNP is significant in men but not not in women. It should still be included in the database, in the same way that SNPs that are significant in only one ethnicity are included. +19503597 rs942379 Uric Acid 3 TRUE This SNP is significant at 1e-5 in both men and women, but is not reported for some reason. +19557197 rs6714750 Distribution|Adiposity|Waist Circumference 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +19798445 rs12889954 Sphingolipid 3 TRUE Study specifies range of pvalues for various lipids, and at least one is significant; reported snps are also not significant for all p-values, hence this SNP should have been included. +19874204 rs2036417 Bone Mineral Density|Femoral Neck Bone 2 TRUE It’s described in the text as significant +20169177 rs9271366 Systemic Lupus Erythematosus 3 TRUE Text says this is the most significant snp +20395239 rs4517412 optic disc size Disc 3 TRUE Other reported snps have worse pvalues +20463881 rs9782955 Eye Color S 2 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +20686608 rs11242674 Pancreatic Cancer 3 TRUE Not significant in one model, but there are gold snps not significant in >2 models +20838585 rs11258628 Cardiovascular Disease LDL 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +20838585 rs12069004 Cardiovascular Disease glucose 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +20838585 rs6726786 Cardiovascular Disease triglycerides 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +20838585 rs781718 Cardiovascular Disease glucose 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +20838585 rs8131349 Cardiovascular Disease total cholesterol 3 TRUE "All reported p-values for this SNP are significant, table is labeled ""significant hits""" +20861866 rs3750848 age-related macular degeneration 3 TRUE Mentioned as significant in the text and in the meta-analysis +20953186 rs13190932 psoriasis|psoriatic arthritis 3 TRUE Confirmed in the paper text +20953186 rs13210247 psoriasis|psoriatic arthritis 3 TRUE Confirmed in the paper text +21297633 rs6556412 ulcerative colitis 3 TRUE This SNP is significant for Crohn’s disease at 1e-14 but is significant for Ulcerative Colitis at 1.7e-5. It should be included because the second, lower pvalue is not a confirmation cohort or meta-analysis. +21390209 rs624225 Late-Onset Alzheimer's Disease 3 SOME_COHORTS This SNP was not found significant in a replication study, but was significant in the main study. +21502949 rs4752194 brain 0 SOME_COHORTS Phenotype was parsed incorrectly. It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +21738487 rs1079597 Parkinson's Disease 3 FALSE "P-value parsing error: pvalue column is labeled just ""p"" (and the title is a GIF) and all siginificant snp pvalues are GIFs, not text entries" +21738491 rs12143842 Sudden Cardiac Death QT 3 FALSE P-value parsing error. +21750679 rs342070 Systemic Sclerosis 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +21804549 rs335016 Asthma 3 SOME_COHORTS It is significant in Latino’s in the main cohort but not in combined cohort and replication study; all reported snps are significant in both. +21827660 rs3779505 increased disease risk 0 SOME_COHORTS Phenotype parsed incorrectly. It is significant in one cohort but not in combined cohort; all reported snps are significant in all cohorts. +21829393 rs478582 Type 1 Diabetes|Autoantibody 2 TRUE Not significant for some subdiseases, but other snps with same profile are in gold set +21931564 rs2014355 nuclear magnetic resonance C3/C4 3 TRUE "Text confirms that indicates that SNP is ""identified by this study""" +21935397 rs2798311 body mass index 2 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +21935397 rs4771122 body mass index 2 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +22087292 rs13299777 Appendicular Lean Mass|Femoral Neck Bone Geometry 2 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both; the p-vaues can be tagged via the column name +22087292 rs1368998 Appendicular Lean Mass|Femoral Neck Bone Geometry 2 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +22087292 rs3849874 Appendicular Lean Mass|Femoral Neck Bone Geometry 2 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +22238593 rs6930576 Type 2 Diabetes 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +22291609 rs11829037 Inflammation ESR 2 TRUE Confirmed in the paper text +22368281 rs1985096 LDL-c response|Lpa 3 TRUE All the p-values associated with this SNP are <1e-5. +22430674 rs744373 Alzheimer's disease 2 FALSE Haplotype and snp in same line; hap is significant, snp is not +22452962 rs10995190 breast cancer|Breast Cancer 3 REPEAT The SNP is in a table that summarizes significant results from a previous study; it was not discovered in this paper per se. +22479419 rs4699030 Treatment Refractory Schizophrenia 3 TRUE Confirmed in the paper text +22509378 rs4821536 Sexual Dysfunction Overall FSD 3 TRUE GWAS Central snps from gwas catalog are in the same table with similar or worse sets of p-values +22719876 rs738407 Non-Alcoholic Fatty Liver Disease|Liver Disease 3 TRUE Confirmed in text as significant at 1e-7, which is enough for us (paper is stricter) +22792070 rs2536182 Bone Mineral Density,|Bone|Osteoporotic Fracture 3 TRUE Its p-value look just like the top hit in GWAS Central +22832964 rs1245577 smoking behaviors AOI 2 TRUE It’s in the same table as top hit and the pvalue is below 1e-5 +22843504 rs6653872 autism spectrum 3 FALSE The p-value associated with this snp is from another study. It is snot significant in this study. +22843504 rs9302952 autism spectrum 3 TRUE The p-values for this SNP are all <1e-7. The top SNP in GWAS Central is also only found in this table and has the same p-values. +22843504 rs11118968 autism spectrum 3 TRUE The p-values for this SNP are all <1e-7. The top SNP in GWAS Central is also only found in this table and has the same p-values. +23001564 rs1317082 homeostasis 3 TRUE Confirmed in the paper text +23028483 rs1564606 Asthma 3 REPEAT This SNP was found to be significant in the GABRIEL study +23028483 rs1588265 Asthma 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +23251661 rs2266788 Childhood Obesity|Childhood Triglycerides(mg/dL) 3 TRUE GWAS Catalog reports many SNPs from the same table (e.g. rs3733402) and they have almost the same p-value. There is only one p-value reported per SNP. +23259602 rs505982 dental caries 3 TRUE Although the SNP is significant in only one cohort, GWC reports other SNPs from the same table as significant even though they have lower p-values (rs1953743) +23300701 rs7136702 Colorectal Cancer 3 REPEAT This SNP was found to be significant in an earlier study; this study reports a second SNP that affects colorectal cancer by interacting with the first SNP. +23326239 rs3115663 Antibodies|Epstein-Barr Virus Nuclear Antigen 3 TRUE This SNP is described as statistically significant with the main SNP; however, it is also in LD with the main SNP and this is probably why it has not been reported. +23326239 rs7754768 Antibodies|Epstein-Barr Virus Nuclear Antigen 3 SOME_COHORTS "Was significant in main and joint cohorts, but not in the replication cohort. We were unable to extract the ""replication"" tag." +23326239 rs2858870 Antibodies|Epstein-Barr Virus Nuclear Antigen 3 TRUE Confirmed in the paper text +23382691 rs10276619 Human Immunoglobulin|Cancers|-Glycosylation 0 TRUE This SNP is a valid association, but is actually associated with hippocampal atrophy, and is in the same gene as a variant associated with the main trait. +23509613 rs17411480 Antiphospholipid Antibodies 3 TRUE Table is described as hosting “significant” SNPs and its pvalues are <1e-5 +23667675 rs6438424 Age Menarche 3 REPEAT This SNP was found significant in a previous study, but not in this study. +23703922 rs6832439 uric acid levels 3 TRUE The same SNP is significant in every cohort. Another SNP that is significant in every cohort and that is in the same table is reported (rs6449213). +23738518 rs11666805 reading|language 2 TRUE SNP is present in main paper table, and there is only one cohort. Other, less significant SNPs from same table are in GWC (e.g. rs4807927) +23844046 rs11265260 C-Reactive Protein 3 TRUE SNP is present in main table and is discussed at length in the paper text (as one of the significant variants) +23966867 rs2958759 Body Fat Distribution WC_pooled 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +23979607 rs6888413 borderline personality 3 SOME_COHORTS SNP is one of 7 to be reported in paper and is significant in main cohort, meta-analysis, but not in replication (we couldn't tag it) +23979607 rs6894288 borderline personality 3 SOME_COHORTS SNP is one of 7 to be reported in paper and is significant in main cohort, meta-analysis, but not in replication (we couldn't tag it) +23984888 rs11683662 airway responsiveness 3 TRUE The SNP is reported in the main table; its replication p-value is similar to that of the one SNP reported in GWC (rs6731443 at p<0.012); study says 0.05 is the cutoff for significance in replication cohort, and our SNP passes it. +24025145 rs7318267 chemotherapy-induced alopecia|breast cancer 3 TRUE SNP appears in main table. It is not significant in one statistical model. However, no SNP in the study is significant in all models, including ones in GWC, therefore it should be in the database. +24025145 rs6725180 chemotherapy-induced alopecia|breast cancer 3 TRUE SNP appears in main table. It is not significant in one statistical model. However, no SNP in the study is significant in all models, including ones in GWC, therefore it should be in the database. +24086445 rs10770359 Schizophrenia|Matter Volume 2 TRUE SNP appeaers in main table, there is no replication, and other equally significant SNPs from the same table have been reported (rs11044045) in GWC. +24133439 rs10778511 Autistic-Like Traits 3 TRUE SNP is in main table, there is no replication, only one p-value given per SNP and other SNPs from this table are in GWC. +24133439 rs1420612 Autistic-Like Traits 2 TRUE SNPs have only one p-value and the one for this SNP is significant. +24166486 rs34706883 Schizophrenia 3 TRUE SNP is in main table, there is no replication, only one p-value given per SNP and other SNPs from this table are in GWC (rs6558872). +24166486 rs4721190 Schizophrenia 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +24166486 rs2039839 Schizophrenia 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +24376456 rs6479671 blood pressure Alcohol drinking 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +24483146 rs11636687 biomarkers 0 TRUE The SNP is not significant in every methodology, but there are many such SNPs reported in GWAS Catalog (rs10495285) +24483146 rs13171512 biomarkers 0 TRUE The SNP is not significant in every methodology, but there are many such SNPs reported in GWAS Catalog (rs10495285) +24513273 rs1394125 serum uric acid 3 REPEAT This SNP was significant in a previous study with Europeans but not in this study of Asians +24586186 rs37370 Metabolic Traits 3-Aminoisobutyrate 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +24714607 rs4760851 Chronic Mucus Hypersecretion, 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +24755620 rs6859 Glutamate|Alzheimer's Disease 3 TRUE SNPs have only one p-value and the one for this SNP is significant. Also confirmed in the text +24892410 rs17338512 Hypertension|Pulse Pressure Nighttime PP 3 SOME_COHORTS It is significant in one cohort but not in combined cohort; all reported snps are significant in both. +25060954 rs6472312 kinase|hearing 3 TRUE The study uses p<1e-8 as the significance cutoff. This SNP has p=1e-7, which is significant enough for us. It only has one p-value and is associated with the same trait as the one SNP that was found “significant” +25064009 rs11724635 Parkinson’s disease 3 TRUE The SNP is significant in all cohorts. +25133637 rs794149 Body Mass Index BMI 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +25162662 rs4666783 Serum Ferritin 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +25241909 rs114384494 Chronic Obstructive Pulmonary Disease|Chronic Bronchitis 3 TRUE The SNP is not significant in some cohorts, but another SNP that also has a combined p-value of 1e-7 is reported in GWAS Catalog (rs114931935). +25340798 rs7926920 Proteins Involved|Inflammation|Alzheimer's Disease MMP3 3 TRUE "All p-values for this SNP are significant, table is labeled ""significant hits""" +25367360 rs6708111 astigmatism|refractive error 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +25367360 rs9366427 astigmatism|refractive error 3 TRUE SNPs have only one p-value and the one for this SNP is significant. +25436638 rs12138950 Serum Thyroid Stimulating Hormone 3 TRUE Confirmed in the paper text +25436638 rs7940871 Serum Thyroid Stimulating Hormone 3 REPEAT The SNP is in a table that summarizes significant results from a previous study; it was not discovered in this paper per se. +25742292 rs7919841 Parity 2 TRUE The SNP has only one p-value and it is significant. diff --git a/set_env.sh b/set_env.sh index 7f9da95..21797c1 100755 --- a/set_env.sh +++ b/set_env.sh @@ -2,6 +2,7 @@ export SNORKELHOME="`pwd`/snorkel-tables" echo "Snorkel home directory: $SNORKELHOME" export GWASDBHOME="`pwd`/src" echo "GwasDB home directory: $GWASDBHOME" -export PYTHONPATH="$PYTHONPATH:$SNORKELHOME:$SNORKELHOME/treedlib:$GWASDBHOME" +# export PYTHONPATH="$PYTHONPATH:$SNORKELHOME:$SNORKELHOME/treedlib:$GWASDBHOME" +export PYTHONPATH="$PYTHONPATH:$SNORKELHOME:$SNORKELHOME/treedlib:$SNORKELHOME/treedlib/treedlib:$GWASDBHOME" export PATH="$PATH:$SNORKELHOME:$SNORKELHOME/treedlib" echo "Environment variables set!" diff --git a/src/crawler/dl_non_gwas_papers.py b/src/crawler/dl_non_gwas_papers.py new file mode 100644 index 0000000..e0268eb --- /dev/null +++ b/src/crawler/dl_non_gwas_papers.py @@ -0,0 +1,48 @@ +import argparse +from contextlib import closing +import numpy as np +import os +import requests +import time +import urllib + + +def _get_oa_body(pubmed_id, pmc_id, outfolder): + url = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pmc&id=%s' % pmc_id + response = requests.get(url) + if response.status_code == requests.codes.ok: + xml_target = outfolder + '/' + str(pubmed_id) + '.xml' + if not os.path.isfile(xml_target): + with open(xml_target, 'w') as f: + f.write(response.content) + return True + else: + return False + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument('--num-files', help='Number of papers to download', + type=int) + parser.add_argument('--download-folder', help='Path to target folder') + parser.add_argument('--wait', help='Wait time in between server calls', + type=int, default=1) + args = parser.parse_args() + + url = 'ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_file_list.txt' + with closing(urllib.urlopen(url)) as f: + lines = f.readlines()[1:] + n_lines = len(lines) + order = np.random.permutation(n_lines) + for i in order[:args.num_files]: + fields = lines[i].strip().split('\t') + if len(fields) < 4: continue + pmid = fields[3][5:] + pmc = fields[2] + if pmid == '' or pmc == '': continue + _get_oa_body(int(pmid), pmc, args.download_folder) + time.sleep(args.wait) + + +if __name__ == "__main__": + main() diff --git a/src/crawler/dl_papers.py b/src/crawler/dl_papers.py index a0f7bc8..7850c0a 100644 --- a/src/crawler/dl_papers.py +++ b/src/crawler/dl_papers.py @@ -42,7 +42,8 @@ def mark_oa(open_access): f.readline() for line in f: fields = line.strip().split('\t') - if len(fields) < 4: continue + if len(fields) < 5: continue + if not fields[3] or not fields[2]: continue pmid = int(fields[3][5:]) pmc = fields[2] pubmed_to_pmc[pmid] = pmc diff --git a/src/crawler/dl_predicted_papers.py b/src/crawler/dl_predicted_papers.py new file mode 100644 index 0000000..c77a171 --- /dev/null +++ b/src/crawler/dl_predicted_papers.py @@ -0,0 +1,38 @@ +import argparse +import os +import requests +import time + + +def _get_oa_body(pmc_id, outfolder): + url = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pmc&id=%s' % pmc_id + response = requests.get(url) + if response.status_code == requests.codes.ok: + xml_target = outfolder + '/' + pmc_id + '.xml' + if not os.path.isfile(xml_target): + with open(xml_target, 'w') as f: + f.write(response.content) + return True + else: + return False + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument('--filter-type', help='Filter used for prediction', + choices=['basic', 'weak', 'strong']) + parser.add_argument('--download-folder', help='Path to target folder') + parser.add_argument('--wait', help='Wait time in between server calls', + type=int, default=1) + args = parser.parse_args() + + predicted_papers_file = '../../data/db/predicted/' + args.filter_type + with open(predicted_papers_file) as f: + lines = f.readlines() + for pmc_id in lines: + _get_oa_body(pmc_id, args.download_folder) + time.sleep(args.wait) + + +if __name__ == "__main__": + main() diff --git a/src/crawler/parse_gwas_catalog.py b/src/crawler/parse_gwas_catalog.py index 780e9f4..68ce305 100644 --- a/src/crawler/parse_gwas_catalog.py +++ b/src/crawler/parse_gwas_catalog.py @@ -47,9 +47,12 @@ def crawl(fname, phenotype_fname, db_session): with open(fname) as f: f.readline() - for line in f: + for i, line in enumerate(f): fields = line.split('\t') + if i % 500 == 0: + print '%d associations parsed' % i + # create paper pubmed_id = _get_int(fields[1]) journal_name = fields[4] @@ -192,4 +195,4 @@ def _get_chrom(s): # ---------------------------------------------------------------------------- if __name__ == '__main__': - main() \ No newline at end of file + main() diff --git a/src/crawler/parse_gwas_central.py b/src/crawler/parse_gwas_central.py index 0925961..6a6a4f6 100644 --- a/src/crawler/parse_gwas_central.py +++ b/src/crawler/parse_gwas_central.py @@ -21,6 +21,8 @@ def main(): parser.add_argument('--init', action='store_true', help='Init db') parser.add_argument('--ids', help='List of paper ids') parser.add_argument('--min-neg-log-pval', default=5, type=int) + parser.add_argument('--start-at', default=0, type=int) + parser.add_argument('--overwrite', action='store_true') args = parser.parse_args() @@ -28,11 +30,12 @@ def main(): init_db() if args.ids: - crawl(args.ids, args.min_neg_log_pval) + crawl(args.ids, args.min_neg_log_pval, start_at=args.start_at, + overwrite=args.overwrite) # ---------------------------------------------------------------------------- -def crawl(pubmed_id_f, cutoff): +def crawl(pubmed_id_f, cutoff, start_at=0, overwrite=False): # collect papers to parse pubmed_ids = list() with open(pubmed_id_f) as f: @@ -40,9 +43,14 @@ def crawl(pubmed_id_f, cutoff): # download GWC data for each paper for pmid in pubmed_ids: - # check for previous associations: - assocs = db_session.query(Association).join(Association.paper).filter(Paper.pubmed_id==pmid).filter(Association.source=='gwas_central').all() - if len(assocs) > 1: continue + if pmid < start_at: continue + + # overwrite previous associations: + if overwrite: + assocs = db_session.query(Association).join(Association.paper).filter(Paper.pubmed_id==pmid).filter(Association.source=='gwas_central').all() + if assocs: + for a in assocs: db_session.delete(a) + db_session.commit() # create/load paper paper = db_session.query(Paper).filter(Paper.pubmed_id==pmid).first() diff --git a/src/extractor/candidates.py b/src/extractor/candidates.py new file mode 100644 index 0000000..78c536c --- /dev/null +++ b/src/extractor/candidates.py @@ -0,0 +1,25 @@ +def deduplicate(candidates, i=0): + # load existing candidates into a dict + span_dict = { unicode(cand.get_arguments()[i].parent) : list() for cand in candidates } + for cand in candidates: + span = cand.get_arguments()[i] # note: assumes this is not a relation + span_dict[unicode(span.parent)].append( (span.char_start, span.char_end) ) + + def nested(ivl1, ivl2): + if ivl1 != ivl2 and ivl2[0] <= ivl1[0] <= ivl1[1] <= ivl2[1]: + return True + else: + return False + + new_candidates = list() + for cand in candidates: + span = cand.get_arguments()[i] + span_ivl = span.char_start, span.char_end + span_name = unicode(span.parent) + if all([not nested(span_ivl, other_ivl) for other_ivl in span_dict[span_name]]): + yield cand + +def filter_cand(candidates, filter_fn): + for cand in candidates: + if filter_fn(cand): + yield cand \ No newline at end of file diff --git a/src/extractor/parser.py b/src/extractor/parser.py index b91abf3..0fc155a 100644 --- a/src/extractor/parser.py +++ b/src/extractor/parser.py @@ -4,13 +4,13 @@ from itertools import chain from collections import defaultdict -from snorkel.parser import XMLDocParser, TableParser +from snorkel.parser import XMLMultiDocParser from snorkel.models import Corpus, Document, Sentence, Table, Cell, Phrase from snorkel.utils import corenlp_cleaner, sort_X_on_Y, split_html_attrs # ---------------------------------------------------------------------------- -class UnicodeXMLDocParser(XMLDocParser): +class UnicodeXMLDocParser(XMLMultiDocParser): """Changes default Snorkel XMLDocParser. String are stored in unicode. @@ -21,7 +21,7 @@ class UnicodeXMLDocParser(XMLDocParser): def __init__(self, path, doc='.//document', text='./text/text()', id='./id/text()', keep_xml_tree=False): - XMLDocParser.__init__(self, path, doc, text, id, keep_xml_tree) + XMLMultiDocParser.__init__(self, path, doc, text, id, keep_xml_tree) def parse_file(self, f, file_name): for i,doc in enumerate(et.parse(f).xpath(self.doc)): @@ -31,7 +31,7 @@ def parse_file(self, f, file_name): attribs = {'root':doc} if self.keep_xml_tree else {} yield Document(name=str(id), file=str(file_name), attribs=attribs), unicode(text) -class GWASXMLAbstractParser(XMLDocParser): +class GWASXMLAbstractParser(XMLMultiDocParser): """For parsing GWAS pubmed papers It uses the title and abstract. If there is no abstract it uses par 1 instead. @@ -40,7 +40,7 @@ class GWASXMLAbstractParser(XMLDocParser): def __init__(self, path, doc, title, abstract, par1, id, keep_xml_tree=False): text = title + ' | ' + abstract - XMLDocParser.__init__(self, path, doc, text, id, keep_xml_tree) + XMLMultiDocParser.__init__(self, path, doc, text, id, keep_xml_tree) self.title = title self.abstract = abstract self.par1 = par1 @@ -54,15 +54,19 @@ def parse_file(self, f, file_name): if not title_text.endswith('.'): title_text = title_text + '.' ids = doc.xpath(self.id) - id = ids[0] if len(ids) > 0 else None - attribs = {'root':doc} if self.keep_xml_tree else {} + doc_id = ids[0] if len(ids) > 0 else None if abstract_text: text = title_text + ' ' + abstract_text else: text = title_text + ' ' + par1_text - yield Document(name=str(id), file=str(file_name), attribs=attribs), unicode(text) - -class GWASXMLDocParser(XMLDocParser): + + meta = {'file_name': str(file_name)} + if self.keep_xml_tree: + meta['root'] = et.tostring(doc) + stable_id = self.get_stable_id(doc_id) + yield Document(name=doc_id, stable_id=stable_id, meta=meta), unicode(text) + +class GWASXMLDocParser(XMLMultiDocParser): """For parsing GWAS pubmed papers It uses the title and abstract. If there is no abstract it uses par 1 instead. @@ -71,7 +75,7 @@ class GWASXMLDocParser(XMLDocParser): def __init__(self, path, doc, title, abstract, n_par, id, keep_xml_tree=False): text = title + ' | ' + abstract - XMLDocParser.__init__(self, path, doc, text, id, keep_xml_tree) + XMLMultiDocParser.__init__(self, path, doc, text, id, keep_xml_tree) self.title = title self.abstract = abstract self.n_par = n_par @@ -87,10 +91,12 @@ def parse_file(self, f, file_name): if not abstract_text.endswith('.'): abstract_text = abstract_text + '.' ids = doc.xpath(self.id) - id = ids[0] if len(ids) > 0 else None - attribs = {'root':doc} if self.keep_xml_tree else {} - text = title_text + ' ' + abstract_text + ' ' + par_text - yield Document(name=str(id), file=str(file_name), attribs=attribs), unicode(text) + doc_id = ids[0] if len(ids) > 0 else None + meta = {'file_name': str(file_name)} + if self.keep_xml_tree: + meta['root'] = et.tostring(doc) + stable_id = self.get_stable_id(doc_id) + yield Document(name=doc_id, stable_id=stable_id, meta=meta), unicode(text) def _et2str(t): return ''.join(t.xpath('.//text()')) @@ -98,8 +104,8 @@ def _et2str(t): # ---------------------------------------------------------------------------- # for tables -class UnicodeXMLTableDocParser(XMLDocParser): - """Changes default Snorkel XMLDocParser. +class UnicodeXMLTableDocParser(XMLMultiDocParser): + """Changes default Snorkel XMLMultiDocParser. String are stored in unicode. @@ -107,61 +113,16 @@ class UnicodeXMLTableDocParser(XMLDocParser): breaks p-value formatting). """ - def __init__(self, path, doc='.//document', text='./text/text()', id='./id/text()', - keep_xml_tree=False): - super(UnicodeXMLTableDocParser, self).__init__(path, doc, text, id, keep_xml_tree) - def parse_file(self, f, file_name): for i,doc in enumerate(et.parse(f).xpath(self.doc)): - # print et.tostring(doc)[:100] - # print f - # print et.parse('../data/db/papers/19305408.xml').xpath('./*')[0].xpath('.//table') - # print doc.xpath('.//table') text = '\n'.join([ et.tostring(elem) for elem in doc.xpath(self.text) if elem is not None]) ids = doc.xpath(self.id) - # print i, ids - id = ids[0] if len(ids) > 0 else None - attribs = {'root':doc} if self.keep_xml_tree else {} - # print 'ok ok', text, self.text - yield Document(name=str(id), file=str(file_name), attribs=attribs), unicode(text) + doc_id = ids[0] if len(ids) > 0 else None + meta = {'file_name': str(file_name)} + if self.keep_xml_tree: + meta['root'] = et.tostring(doc) + stable_id = self.get_stable_id(doc_id) + yield Document(name=doc_id, stable_id=stable_id, meta=meta), text def _can_read(self, fpath): - return fpath.endswith('.xml') or fpath.endswith('.nxml') - -class UnicodeTableParser(TableParser): - def __init__(self, tok_whitespace=False): - super(UnicodeTableParser, self).__init__(tok_whitespace) - - def parse_table(self, table): - soup = BeautifulSoup(table.text, 'lxml') - position = 0 - for row_num, row in enumerate(soup.find_all('tr')): - ancestors = ([(row.name, row.attrs.items())] - + [(ancestor.name, ancestor.attrs.items()) - for ancestor in row.parents if ancestor is not None][:-2]) - (tags, attrs) = zip(*ancestors) - html_anc_tags = tags - html_anc_attrs = split_html_attrs(chain.from_iterable(attrs)) - col_num = 0 - for html_cell in row.children: - # TODO: include title, caption, footers, etc. - if html_cell.name in ['th','td']: - parts = defaultdict(list) - parts['document_id'] = table.document_id - parts['table_id'] = table.id - parts['position'] = position - parts['document'] = table.document - parts['table'] = table - - parts['text'] = unicode(html_cell.get_text(" ", strip=True)) - parts['row_num'] = row_num - parts['col_num'] = col_num - parts['html_tag'] = html_cell.name - parts['html_attrs'] = split_html_attrs(html_cell.attrs.items()) - parts['html_anc_tags'] = html_anc_tags - parts['html_anc_attrs'] = html_anc_attrs - cell = Cell(**parts) - html_cell['snorkel_id'] = cell.id # add new attribute to the html - yield cell - position += 1 - col_num += 1 \ No newline at end of file + return fpath.endswith('.xml') or fpath.endswith('.nxml') \ No newline at end of file diff --git a/src/extractor/util.py b/src/extractor/util.py index 57f70bf..8db5441 100644 --- a/src/extractor/util.py +++ b/src/extractor/util.py @@ -8,6 +8,9 @@ # ---------------------------------------------------------------------------- # statistics +def _context(candidate): + return candidate.get_attributes()[0].parent + def gold_rsid_stats(candidates, gold_set): """Computes gold stats for rsids @@ -16,7 +19,7 @@ def gold_rsid_stats(candidates, gold_set): """ gold = gold_set if isinstance(gold_set, set) else set(gold_set) - pmids = set( [ (ngram.context.document.name, ngram.get_attrib_span('words')) for ngram in candidates] ) + pmids = set( [ (_context(ngram).document.name, ngram.get_attrib_span('words')) for ngram in candidates] ) nc = len(pmids) ng = len(gold) both = len(gold.intersection(pmids)) @@ -27,16 +30,16 @@ def gold_rsid_stats(candidates, gold_set): def gold_rsid_recall(candidates, gold_set): gold = gold_set if isinstance(gold_set, set) else set(gold_set) - pmids = set( [ (ngram.context.document.name, ngram.get_attrib_span('words')) for ngram in candidates] ) + pmids = set( [ (_context(ngram).document.name, ngram.get_attrib_span('words')) for ngram in candidates] ) missing = [p for p in gold - pmids] missing_pmids = set ([p[0] for p in missing]) return gold - pmids def gold_rsid_precision(candidates, gold_set): gold = gold_set if isinstance(gold_set, set) else set(gold_set) - pmids = set( [ (ngram.context.document.name, ngram.get_attrib_span('words')) for ngram in candidates] ) + pmids = set( [ (_context(ngram).document.name, ngram.get_attrib_span('words')) for ngram in candidates] ) strange = [p for p in pmids - gold] - return [ngram for ngram in candidates if (ngram.context.document.name, ngram.get_span()) in strange] + return [ngram for ngram in candidates if (_context(ngram).document.name, ngram.get_span()) in strange] def gold_pval_stats(candidates, gold_set): """Computes gold stats for pvalues @@ -46,7 +49,7 @@ def gold_pval_stats(candidates, gold_set): # store collected and gold sets gold = gold_set if isinstance(gold_set, set) else set(gold_set) - pmids = set( [ (ngram.context.document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) + pmids = set( [ (_context(ngram).document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) # only keep exponents gold = { (doc_id, floor(log10(pval))) for doc_id, pval in gold if pval > 0 } @@ -68,11 +71,11 @@ def gold_pval_stats_limited(candidates, gold_set_dict, rsid_candidates): """ # store collected and gold sets - rsids_found = { ngram.context.document.name : set() for ngram in rsid_candidates } + rsids_found = { _context(ngram).document.name : set() for ngram in rsid_candidates } for ngram in rsid_candidates: - rsids_found[ngram.context.document.name].add(str(ngram.get_attrib_span('words'))) + rsids_found[_context(ngram).document.name].add(str(ngram.get_attrib_span('words'))) gold = set([ (pmid, assoc.pvalue) for pmid in gold_set_dict for assoc in gold_set_dict[pmid] if pmid in rsids_found and str(assoc.snp.rs_id) in rsids_found[pmid] ]) - pmids = set( [ (ngram.context.document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) + pmids = set( [ (_context(ngram).document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) print list(sorted(gold))[:10] # only keep exponents @@ -98,11 +101,11 @@ def gold_pval_recall(candidates, gold_set_dict, rsid_candidates): """ # store collected and gold sets - rsids_found = { ngram.context.document.name : set() for ngram in rsid_candidates } + rsids_found = { _context(ngram).document.name : set() for ngram in rsid_candidates } for ngram in rsid_candidates: - rsids_found[ngram.context.document.name].add(str(ngram.get_attrib_span('words'))) + rsids_found[_context(ngram).document.name].add(str(ngram.get_attrib_span('words'))) gold = set([ (pmid, assoc.pvalue) for pmid in gold_set_dict for assoc in gold_set_dict[pmid] if pmid in rsids_found and str(assoc.snp.rs_id) in rsids_found[pmid] ]) - pmids = set( [ (ngram.context.document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) + pmids = set( [ (_context(ngram).document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) # only keep exponents gold = { (doc_id, floor(log10(pval))) for doc_id, pval in gold if pval > 0 } @@ -112,7 +115,7 @@ def gold_pval_recall(candidates, gold_set_dict, rsid_candidates): def gold_pval_precision(candidates, gold_set): gold = gold_set if isinstance(gold_set, set) else set(gold_set) - pmids = set( [ (ngram.context.document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) + pmids = set( [ (_context(ngram).document.name, pvalue_to_float(ngram.get_attrib_span('words'))) for ngram in candidates] ) # only keep exponents gold = { (doc_id, floor(log10(pval))) for doc_id, pval in gold if pval > 0 } @@ -124,8 +127,8 @@ def gold_pval_precision(candidates, gold_set): for doc_id, pval in strange: pval_dict[doc_id].append(pval) - return [ ngram for ngram in candidates if ngram.context.document.name in strange_pmids - and floor(log10(pvalue_to_float(ngram.get_attrib_span('words')))) in pval_dict[ngram.context.document.name]] + return [ ngram for ngram in candidates if _context(ngram).document.name in strange_pmids + and floor(log10(pvalue_to_float(ngram.get_attrib_span('words')))) in pval_dict[_context(ngram).document.name]] def gold_phen_stats(candidates, gold_set, phen2id): gold = gold_set if isinstance(gold_set, set) else set(gold_set) @@ -137,8 +140,8 @@ def gold_phen_stats(candidates, gold_set, phen2id): for span in candidates: phen_name = span.get_span() phen_id = phen2id.get(change_name(phen_name), None) - if phen_id in gold_dict[span.context.document.name]: - correct_candidates.add( (span.context.document.name, phen_id) ) + if phen_id in gold_dict[_context(span).document.name]: + correct_candidates.add( (_context(span).document.name, phen_id) ) # compute stats nc = len(candidates) @@ -160,8 +163,8 @@ def gold_phen_recall(candidates, gold_set, phen2id): for span in candidates: phen_name = span.get_span() phen_id = phen2id.get(change_name(phen_name), None) - if phen_id in gold_dict[span.context.document.name]: - correct_candidates.add( (span.context.document.name, phen_id) ) + if phen_id in gold_dict[_context(span).document.name]: + correct_candidates.add( (_context(span).document.name, phen_id) ) return gold - correct_candidates @@ -177,8 +180,8 @@ def gold_agg_phen_stats(candidates, gold_set, phen2id): phen_name = span.get_span() phen_ids = phen2id.get(change_name(phen_name), None) # aggregate ids if phen_ids: - for phen_id in phen_ids & gold_dict[span.context.document.name]: - correct_candidates.add( (span.context.document.name, phen_id) ) + for phen_id in phen_ids & gold_dict[_context(span).document.name]: + correct_candidates.add( (_context(span).document.name, phen_id) ) assert len(correct_candidates - gold_set) == 0 # ours is subset of gold_set @@ -205,8 +208,8 @@ def gold_agg_phen_recall(candidates, gold_set, phen2id): phen_name = span.get_span() phen_ids = phen2id.get(change_name(phen_name), None) # aggregate ids if phen_ids: - for phen_id in phen_ids & gold_dict[span.context.document.name]: - correct_candidates.add( (span.context.document.name, phen_id) ) + for phen_id in phen_ids & gold_dict[_context(span).document.name]: + correct_candidates.add( (_context(span).document.name, phen_id) ) assert len(correct_candidates - gold_set) == 0 # ours is subset of gold_set @@ -244,10 +247,23 @@ def gold_rspval_precision(candidates, gold_set): # ---------------------------------------------------------------------------- # other helpers +def make_ngrams(L, n_max=10, n_min=3, delim=' '): + for l in L: + yield l + tokens = l.strip().split(delim) + for ngram in slice_into_ngrams(tokens, n_max=n_max, n_min=n_min, delim=delim): + yield ngram + +def slice_into_ngrams(tokens, n_max=3, n_min=1, delim='_'): + N = len(tokens) + for root in range(N): + for n in range(max(0,n_min-1), min(n_max, N - root)): + yield delim.join(tokens[root:root+n+1]) + def pvalue_to_float(pstr): # extract groups via regex # rgx1 = u'([1-9]\d?[\.\xb7]?\d*)\s*[\xd7\*]\s*10\s*[-\u2212\u2013]\s*(\d+)' - rgx1 = u'([1-9]\d?[\xb7\.]?\d*)[\s\u2009]*[\xd7\*][\s\u2009]*10[\s\u2009]*[-\u2212\u2013\u2012][\s\u2009]*(\d+)' + rgx1 = u'([1-9]\d?[\xb7\.]?\d*)[\s\u2009]*[\xd7\xb7\*][\s\u2009]*10[\s\u2009]*[-\u2212\u2013\u2012][\s\u2009]*(\d+)' result1 = re.search(rgx1, pstr) # rgx2 = u'([1-9]\d?[\xb7\.]?\d*)\s*[eE][-\u2212\u2013](\d+)' rgx2 = u'([1-9]\d?[\xb7\.]?\d*)[\s\u2009]*[eE][\s\u2009]*[-\u2212\u2013\u2012][\s\u2009]*(\d+)'