Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.
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ABSTRACT:
SUBMITTER: Denny JC
PROVIDER: S-EPMC3969265 | biostudies-literature | 2013 Dec
REPOSITORIES: biostudies-literature
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Project description:BackgroundMajor depressive disorder (MDD) is a leading cause of disease-associated disability, with much of the increased burden due to psychiatric and medical comorbidity. This comorbidity partly reflects common genetic influences across conditions. Integrating molecular-genetic tools with health records enables tests of association with the broad range of physiological and clinical phenotypes. However, standard phenome-wide association studies analyze associations with individual genetic variants. For polygenic traits such as MDD, aggregate measures of genetic risk may yield greater insight into associations across the clinical phenome.MethodsWe tested for associations between a genome-wide polygenic risk score for MDD and medical and psychiatric traits in a phenome-wide association study of 46,782 unrelated, European-ancestry participants from the Michigan Genomics Initiative.ResultsThe MDD polygenic risk score was associated with 211 traits from 15 medical and psychiatric disease categories at the phenome-wide significance threshold. After excluding patients with depression, continued associations were observed with respiratory, digestive, neurological, and genitourinary conditions; neoplasms; and mental disorders. Associations with tobacco use disorder, respiratory conditions, and genitourinary conditions persisted after accounting for genetic overlap between depression and other psychiatric traits. Temporal analyses of time-at-first-diagnosis indicated that depression disproportionately preceded chronic pain and substance-related disorders, while asthma disproportionately preceded depression.ConclusionsThe present results can inform the biological links between depression and both mental and systemic diseases. Although MDD polygenic risk scores cannot currently forecast health outcomes with precision at the individual level, as molecular-genetic discoveries for depression increase, these tools may augment risk prediction for medical and psychiatric conditions.
| S-EPMC10712651 | biostudies-literature
Project description:Testing the association between genetic scores for Attention Deficit Hyperactivity Disorder (ADHD) and health conditions, can help us better understand its complex etiology. Electronic health records linked to genetic data provide an opportunity to test whether genetic scores for ADHD correlate with ADHD and additional health outcomes in a health care context across different age groups. We generated polygenic scores (ADHD-PGS) trained on summary statistics from the latest genome-wide association study of ADHD (N = 55,374) and applied them to genome-wide data from 12,383 unrelated individuals of African-American ancestry and 66,378 unrelated individuals of European ancestry from the Vanderbilt Biobank. Overall, only Tobacco use disorder (TUD) was associated with ADHD-PGS in the African-American ancestry group (Odds ratio [95% confidence intervals] = 1.23[1.16-1.31], p = 9.3 × 10-09 ). Eighty-six phenotypes were associated with ADHD-PGS in the European ancestry individuals, including ADHD (OR[95%CIs] = 1.22[1.16-1.29], p = 3.6 × 10-10 ), and TUD (OR[95%CIs] = 1.22[1.19-1.25], p = 2.8 × 10-46 ). We then stratified outcomes by age (ages 0-11, 12-18, 19-25, 26-40, 41-60, and 61-100). Our results suggest that ADHD polygenic scores are associated with ADHD diagnoses early in life and with an increasing number of health conditions throughout the lifespan (even in the absence of ADHD diagnosis). This study reinforces the utility of applying trait-specific PGSs to biobank data, and performing exploratory sensitivity analyses, to probe relationships among clinical conditions.
| S-EPMC9378640 | biostudies-literature
Project description:Excess thyroid hormones have complex metabolic effects, particularly hyperthyroidism, and are associated with various cardiovascular risk factors. Previous candidate gene studies have indicated that genetic variants may contribute to this variable response. Electronic medical record (EMR) biobanks containing clinical and genomic data on large numbers of individuals have great potential to inform the disease comorbidity development. In this study, we combined electronic medical record (EMR) -derived phenotypes and genotype information to conduct a genome-wide analysis of hyperthyroidism in a 35,009-patient cohort in Taiwan. Diagnostic codes were used to identify 2,767 patients with hyperthyroidism. Our genome-wide association study (GWAS) identified 44 novel genomic risk markers in 10 loci on chromosomes 2, 6, and 14 (P < 5 × 10-14), including CTLA4, HCP5, HLA-B, POU5F1, CCHCR1, HLA-DRA, HLA-DRB9, TSHR, RPL17P3, and CEP128. We further conducted a comorbidity analysis of our results, and the data revealed a strong correlation between hyperthyroidism patients with thyroid storm and stroke. In this study, we demonstrated application of the PheWAS using large EMR biobanks to inform the comorbidity development in hyperthyroidism patients. Our data suggest significant common genetic risk factors in patients with hyperthyroidism. Additionally, our results show that sex, body mass index (BMI), and thyroid storm are associated with an increased risk of stroke in subjects with hyperthyroidism.
| S-EPMC9390483 | biostudies-literature
Project description:Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect of heparin treatment resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. No genome-wide evaluations have been performed to identify potential genetic influences on HIT. Here, we performed a genome-wide association study (GWAS) and candidate gene study using HIT cases and controls identified using electronic medical records (EMRs) coupled to a DNA biobank and attempted to replicate GWAS associations in an independent cohort. We subsequently investigated influences of GWAS-associated single nucleotide polymorphisms (SNPs) on PF4/heparin antibodies in non-heparin treated individuals. In a recessive model, we observed significant SNP associations (odds ratio [OR] 18.52; 95% confidence interval [CI] 6.33-54.23; p=3.18×10(-9)) with HIT near the T-Cell Death-Associated Gene 8 (TDAG8). These SNPs are in linkage disequilibrium with a missense TDAG8 SNP. TDAG8 SNPs trended toward an association with HIT in replication analysis (OR 5.71; 0.47-69.22; p=0.17), and the missense SNP was associated with PF4/heparin antibody levels and positive PF4/heparin antibodies in non-heparin treated patients (OR 3.09; 1.14-8.13; p=0.02). In the candidate gene study, SNPs at HLA-DRA were nominally associated with HIT (OR 0.25; 0.15-0.44; p=2.06×10(-6)). Further study of TDAG8 and HLA-DRA SNPs is warranted to assess their influence on the risk of developing HIT.
| S-EPMC4433536 | biostudies-literature
Project description:The Electronic Medical Record (EMR) is a potential source for high throughput phenotyping to conduct genome-wide association studies (GWAS), including those of medically relevant quantitative traits. We describe use of the Mayo Clinic EMR to conduct a GWAS of red blood cell (RBC) traits in a cohort of patients with peripheral arterial disease (PAD) and controls without PAD.Results for hemoglobin level, hematocrit, RBC count, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration were extracted from the EMR from January 1994 to September 2009. Out of 35,159 RBC trait values in 3,411 patients, we excluded 12,864 values in 1,165 patients that had been measured during hospitalization or in the setting of hematological disease, malignancy, or use of drugs that affect RBC traits, leaving a final genotyped sample of 3,012, 80% of whom had ?2 measurements. The median of each RBC trait was used in the genetic analyses, which were conducted using an additive model that adjusted for age, sex, and PAD status. We identified four genomic loci that were associated (P<5 × 10(-8)) with one or more of the RBC traits (HBLS1/MYB on 6q23.3, TMPRSS6 on 22q12.3, HFE on 6p22.1, and SLC17A1 on 6p22.2). Three of these loci (HBLS1/MYB, TMPRSS6, and HFE) had been identified in recent GWAS and the allele frequencies, effect sizes, and the directions of effects of the replicated SNPs were similar to the prior studies.Our results demonstrate feasibility of using the EMR to conduct high throughput genomic studies of medically relevant quantitative traits.
| S-EPMC2946914 | biostudies-literature
Project description:To compare three groupings of Electronic Health Record (EHR) billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations. The three tested coding systems were the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM (CCS), and manually curated "phecodes" designed to facilitate phenome-wide association studies (PheWAS) in EHRs.We selected 100 disease phenotypes and compared the ability of each coding system to accurately represent them without performing additional groupings. The 100 phenotypes included 25 randomly-chosen clinical phenotypes pursued in prior genome-wide association studies (GWAS) and another 75 common disease phenotypes mentioned across free-text problem lists from 189,289 individuals. We then evaluated the performance of each coding system to replicate known associations for 440 SNP-phenotype pairs.Out of the 100 tested clinical phenotypes, phecodes exactly matched 83, compared to 53 for ICD-9-CM and 32 for CCS. ICD-9-CM codes were typically too detailed (requiring custom groupings) while CCS codes were often not granular enough. Among 440 tested known SNP-phenotype associations, use of phecodes replicated 153 SNP-phenotype pairs compared to 143 for ICD-9-CM and 139 for CCS. Phecodes also generally produced stronger odds ratios and lower p-values for known associations than ICD-9-CM and CCS. Finally, evaluation of several SNPs via PheWAS identified novel potential signals, some seen in only using the phecode approach. Among them, rs7318369 in PEPD was associated with gastrointestinal hemorrhage.Our results suggest that the phecode groupings better align with clinical diseases mentioned in clinical practice or for genomic studies. ICD-9-CM, CCS, and phecode groupings all worked for PheWAS-type studies, though the phecode groupings produced superior results.
| S-EPMC5501393 | biostudies-literature
Project description:BackgroundMedication-wide association studies (MWAS) have been applied to assess the risk of individual prescription use and a wide range of health outcomes, including cancer, acute myocardial infarction, acute liver failure, acute renal failure, and upper gastrointestinal ulcers. Current literature on the use of preconception and periconception medication and its association with the risk of multiple gestation pregnancies (eg, monozygotic and dizygotic) is largely based on assisted reproductive technology (ART) cohorts. However, among non-ART pregnancies, it is unknown whether other medications increase the risk of multifetal pregnancies.ObjectiveThis study aimed to investigate the risk of multiple gestational births (eg, twins and triplets) following preconception and periconception exposure to prescription medications in patients who delivered at Penn Medicine.MethodsWe used electronic health record data between 2010 and 2017 on patients who delivered babies at Penn Medicine, a health care system in the Greater Philadelphia area. We explored 3 logistic regression models: model 1 (no adjustment); model 2 (adjustment for maternal age); and model 3-our final logistic regression model (adjustment for maternal age, ART use, and infertility diagnosis). In all models, multiple births (MBs) were our outcome of interest (binary outcome), and each medication was assessed separately as a binary variable. To assess our MWAS model performance, we defined ART medications as our gold standard, given that these medications are known to increase the risk of MB.ResultsOf the 63,334 distinct deliveries in our cohort, only 1877 pregnancies (2.96%) were prescribed any medication during the preconception and first trimester period. Of the 123 medications prescribed, we found 26 (21.1%) medications associated with MB (using nominal P values) and 10 (8.1%) medications associated with MB (using Bonferroni adjustment) in fully adjusted model 3. We found that our model 3 algorithm had an accuracy of 85% (using nominal P values) and 89% (using Bonferroni-adjusted P values).ConclusionsOur work demonstrates the opportunities in applying the MWAS approach with electronic health record data to explore associations between preconception and periconception medication exposure and the risk of MB while identifying novel candidate medications for further study. Overall, we found 3 novel medications linked with MB that could be explored in further work; this demonstrates the potential of our method to be used for hypothesis generation.
| S-EPMC9214620 | biostudies-literature
Project description:UnlabelledBackgroundThe ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by inadequate sample size due to associated costs for genotyping and phenotyping of study subjects. This has prompted several academic medical centers to form "biobanks" where biospecimens linked to personal health information, typically in electronic health records (EHRs), are collected and stored on a large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypotheses generation.ResultsIn this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical and genotype data stored at the Mayo Clinic Biobank to mine the phenotype data for genetic associations. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR diagnoses and procedure data, and enable federated querying via standardized Web protocols to identify subjects genotyped for Type 2 Diabetes and Hypothyroidism to discover gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries.ConclusionsThis study demonstrates how Semantic Web technologies can be applied in conjunction with clinical data stored in EHRs to accurately identify subjects with specific diseases and phenotypes, and identify genotype-phenotype associations.
| S-EPMC3554594 | biostudies-literature
Project description:ObjectivesIn contrast to coronary heart disease (CHD), genetic variants that influence susceptibility to peripheral arterial disease (PAD) remain largely unknown.BackgroundWe performed a two-stage genomic association study leveraging an electronic medical record (EMR) linked-biorepository to identify genetic variants that mediate susceptibility to PAD.MethodsPAD was defined as a resting/post-exercise ankle-brachial index (ABI) ≤0.9 or ≥1.4 and/or history of lower extremity revascularization. Controls were patients without history of PAD. In Stage I we performed a genome-wide association analysis adjusting for age and sex, of 537, 872 SNPs in 1641 PAD cases (66 ± 11 years, 64% men) and 1604 control subjects (61 ± 7 year, 60% men) of European ancestry. In Stage II we genotyped the top 48 SNPs that were associated with PAD in Stage I, in a replication cohort of 740 PAD cases (70 ± 11 year, 63% men) and 1051 controls (70 ± 12 year, 61% men).ResultsThe SNP rs653178 in the ATXN2-SH2B3 locus was significantly associated with PAD in the discovery cohort (OR = 1.23; P = 5.59 × 10(-5)), in the replication cohort (OR = 1.22; 8.9 × 10(-4)) and in the combined cohort (OR = 1.22; P = 6.46 × 10(-7)). In the combined cohort this SNP remained associated with PAD after additional adjustment for cardiovascular risk factors including smoking (OR = 1.22; P = 2.15 × 10(-6)) and after excluding patients with ABI > 1.4 (OR = 1.24; P = 3.98 × 10(-7)). The SNP is in near-complete linkage disequilibrium (LD) (r (2) = 0.99) with a missense SNP (rs3184504) in SH2B3, a gene encoding an adapter protein that plays a key role in immune and inflammatory response pathways and vascular homeostasis. The SNP has pleiotropic effects and has been previously associated with multiple phenotypes including myocardial infarction.ConclusionsOur findings suggest that the ATXN2-SH2B3 locus influences susceptibility to PAD.
| S-EPMC4070196 | biostudies-literature
Project description:Although mosaic autosomal chromosomal abnormalities are being increasingly detected as part of high-density genotyping studies, the clinical correlates are unclear. From an electronic medical record (EMR)-based genome-wide association study (GWAS) of peripheral arterial disease, log-R-ratio and B-allele-frequency data were used to identify mosaic autosomal chromosomal abnormalities including copy number variation and loss of heterozygosity. The EMRs of patients with chromosomal abnormalities and those without chromosomal abnormalities were reviewed to compare clinical characteristics. Among 3336 study participants, 0.75% (n = 25, mean age = 74.8 ± 10.7 years, 64% men) had abnormal intensity plots indicative of autosomal chromosomal abnormalities. A hematologic malignancy was present in 8 patients (32%), of whom 4 also had a solid organ malignancy while 2 patients had a solid organ malignancy only. In 50 age- and sex-matched participants without chromosomal abnormalities, there was a lower rate of hematologic malignancies (2% vs 32%, P < .001) but not solid organ malignancies (20% vs 24%, P = .69). We also report the clinical characteristics of each patient with the observed chromosomal abnormalities. Interestingly, among 5 patients with 20q deletions, 4 had a myeloproliferative disorder while all 3 men in this group had prostate cancer. In summary, in a GWAS of 3336 adults, 0.75% had autosomal chromosomal abnormalities and nearly a third of them had hematologic malignancies. A potential novel association between 20q deletions, myeloproliferative disorders, and prostate cancer was also noted.
| S-EPMC4130164 | biostudies-literature