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Competing Interests: None.

BackgroundClonal hematopoiesis of indeterminate potential (CHIP) occurs due to acquired mutations in bone marrow progenitor cells. CHIP confers a 2-fold risk of atherosclerotic cardiovascular disease. However, there are limited data regarding specific cardiovascular phenotypes. The purpose of this study was to define the coronary artery disease phenotype of the CHIP population-based on coronary angiography.MethodsWe recruited 1142 patients from the Vanderbilt University Medical Center cardiac catheterization laboratory and performed DNA sequencing to determine CHIP status. Multivariable logistic regression models and proportional odds models were used to assess the association between CHIP status and angiography phenotypes.ResultsWe found that 18.4% of patients undergoing coronary angiography had a CHIP mutation. Those with CHIP had a higher risk of having obstructive left main (odds ratio, 2.44 [95% CI, 1.40-4.27]; P=0.0018) and left anterior descending (odds ratio, 1.59 [1.12-2.24]; P=0.0092) coronary artery disease compared with non-CHIP carriers. We additionally found that a specific CHIP mutation, ten eleven translocase 2 (TET2), has a larger effect size on left main stenosis compared with other CHIP mutations.ConclusionsThis is the first invasive assessment of coronary artery disease in CHIP and offers a description of a specific atherosclerotic phenotype in CHIP wherein there is an increased risk of obstructive left main and left anterior descending artery stenosis, especially among TET2 mutation carriers. This serves as a basis for understanding enhanced morbidity and mortality in CHIP.

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

Statins reduce cholesterol, prevent cardiovascular disease, and are among the most commonly prescribed medications in the world. Statin-associated musculoskeletal symptoms (SAMS) impact statin adherence and ultimately can impede the long-term effectiveness of statin therapy. There are several identified pharmacogenetic variants that impact statin disposition and adverse events during statin therapy. SLCO1B1 encodes a transporter (SLCO1B1; alternative names include OATP1B1 or OATP-C) that facilitates the hepatic uptake of all statins. ABCG2 encodes an efflux transporter (BCRP) that modulates the absorption and disposition of rosuvastatin. CYP2C9 encodes a phase I drug metabolizing enzyme responsible for the oxidation of some statins. Genetic variation in each of these genes alters systemic exposure to statins (i.e., simvastatin, rosuvastatin, pravastatin, pitavastatin, atorvastatin, fluvastatin, lovastatin), which can increase the risk for SAMS. We summarize the literature supporting these associations and provide therapeutic recommendations for statins based on SLCO1B1, ABCG2, and CYP2C9 genotype with the goal of improving the overall safety, adherence, and effectiveness of statin therapy. This document replaces the 2012 and 2014 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for SLCO1B1 and simvastatin-induced myopathy.

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program (n = 63,302) and UK Biobank (n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.

BackgroundInsight into type 5 long QT syndrome (LQT5) has been limited to case reports and small family series. Improved understanding of the clinical phenotype and genetic features associated with rare KCNE1 variants implicated in LQT5 was sought through an international multicenter collaboration.MethodsPatients with either presumed autosomal dominant LQT5 (N = 229) or the recessive Type 2 Jervell and Lange-Nielsen syndrome (N = 19) were enrolled from 22 genetic arrhythmia clinics and 4 registries from 9 countries. KCNE1 variants were evaluated for ECG penetrance (defined as QTc >460 ms on presenting ECG) and genotype-phenotype segregation. Multivariable Cox regression was used to compare the associations between clinical and genetic variables with a composite primary outcome of definite arrhythmic events, including appropriate implantable cardioverter-defibrillator shocks, aborted cardiac arrest, and sudden cardiac death.ResultsA total of 32 distinct KCNE1 rare variants were identified in 89 probands and 140 genotype positive family members with presumed LQT5 and an additional 19 Type 2 Jervell and Lange-Nielsen syndrome patients. Among presumed LQT5 patients, the mean QTc on presenting ECG was significantly longer in probands (476.9±38.6 ms) compared with genotype positive family members (441.8±30.9 ms, P

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

Allopurinol, which lowers uric acid (UA) concentration, is increasingly being recognized for its benefits in cardiovascular and renal disease. However, response to allopurinol is variable. We gathered samples from 4,446 multiethnic subjects for a genome-wide association study of allopurinol response. Consistent with previous studies, we observed that the Q141K variant in ABCG2 (rs2231142), which encodes the efflux pump breast cancer resistance protein (BCRP), associated with worse response to allopurinol. However, for the first time this association reached genome-wide level significance (P = 8.06 × 10-11 ). Additionally, we identified a novel association with a variant in GREM2 (rs1934341, P = 3.22 × 10-6 ). In vitro studies identified oxypurinol, the active metabolite of allopurinol, as an inhibitor of the UA transporter GLUT9, suggesting that oxypurinol may modulate UA reabsorption. These results provide strong evidence for a role of BCRP Q141K in allopurinol response, and suggest that allopurinol may have additional hypouricemic effects beyond xanthine oxidase inhibition.

BackgroundRare genetic variants cause pulmonary arterial hypertension, but the contribution of common genetic variation to disease risk and natural history is poorly characterised. We tested for genome-wide association for pulmonary arterial hypertension in large international cohorts and assessed the contribution of associated regions to outcomes.MethodsWe did two separate genome-wide association studies (GWAS) and a meta-analysis of pulmonary arterial hypertension. These GWAS used data from four international case-control studies across 11 744 individuals with European ancestry (including 2085 patients). One GWAS used genotypes from 5895 whole-genome sequences and the other GWAS used genotyping array data from an additional 5849 individuals. Cross-validation of loci reaching genome-wide significance was sought by meta-analysis. Conditional analysis corrected for the most significant variants at each locus was used to resolve signals for multiple associations. We functionally annotated associated variants and tested associations with duration of survival. All-cause mortality was the primary endpoint in survival analyses.FindingsA locus near SOX17 (rs10103692, odds ratio 1·80 [95% CI 1·55-2·08], p=5·13 × 10-15) and a second locus in HLA-DPA1 and HLA-DPB1 (collectively referred to as HLA-DPA1/DPB1 here; rs2856830, 1·56 [1·42-1·71], p=7·65 × 10-20) within the class II MHC region were associated with pulmonary arterial hypertension. The SOX17 locus had two independent signals associated with pulmonary arterial hypertension (rs13266183, 1·36 [1·25-1·48], p=1·69 × 10-12; and rs10103692). Functional and epigenomic data indicate that the risk variants near SOX17 alter gene regulation via an enhancer active in endothelial cells. Pulmonary arterial hypertension risk variants determined haplotype-specific enhancer activity, and CRISPR-mediated inhibition of the enhancer reduced SOX17 expression. The HLA-DPA1/DPB1 rs2856830 genotype was strongly associated with survival. Median survival from diagnosis in patients with pulmonary arterial hypertension with the C/C homozygous genotype was double (13·50 years [95% CI 12·07 to >13·50]) that of those with the T/T genotype (6·97 years [6·02-8·05]), despite similar baseline disease severity.InterpretationThis is the first study to report that common genetic variation at loci in an enhancer near SOX17 and in HLA-DPA1/DPB1 is associated with pulmonary arterial hypertension. Impairment of SOX17 function might be more common in pulmonary arterial hypertension than suggested by rare mutations in SOX17. Further studies are needed to confirm the association between HLA typing or rs2856830 genotyping and survival, and to determine whether HLA typing or rs2856830 genotyping improves risk stratification in clinical practice or trials.FundingUK NIHR, BHF, UK MRC, Dinosaur Trust, NIH/NHLBI, ERS, EMBO, Wellcome Trust, EU, AHA, ACClinPharm, Netherlands CVRI, Dutch Heart Foundation, Dutch Federation of UMC, Netherlands OHRD and RNAS, German DFG, German BMBF, APH Paris, INSERM, Université Paris-Sud, and French ANR.

BackgroundCoronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown.MethodsWe performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus.ResultsThe meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35-1.86; P=2.6×10-10). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14-2.57; P=0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17-2.24; P=0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18-4.75; P=0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes.ConclusionsGenetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.

The article "A multi-stage genome-wide association study of uterine fibroids in African Americans", written by Jacklyn N. Hellwege, was originally published Online First without open access. After publication in volume 136, issue 10, page 1363-1373 the author decided to opt for Open Choice and to make the article an open access publication. Therefore, the copyright of the article has been changed to

Uterine fibroids are benign tumors of the uterus affecting up to 77% of women by menopause. They are the leading indication for hysterectomy, and account for $34 billion annually in the United States. Race/ethnicity and age are the strongest known risk factors. African American (AA) women have higher prevalence, earlier onset, and larger and more numerous fibroids than European American women. We conducted a multi-stage genome-wide association study (GWAS) of fibroid risk among AA women followed by in silico genetically predicted gene expression profiling of top hits. In Stage 1, cases and controls were confirmed by pelvic imaging, genotyped and imputed to 1000 Genomes. Stage 2 used self-reported fibroid and GWAS data from 23andMe, Inc. and the Black Women's Health Study. Associations with fibroid risk were modeled using logistic regression adjusted for principal components, followed by meta-analysis of results. We observed a significant association among 3399 AA cases and 4764 AA controls at rs739187 (risk-allele frequency = 0.27) in CYTH4 (OR (95% confidence interval) = 1.23 (1.16-1.30), p value = 7.82 × 10-9). Evaluation of the genetic association results with MetaXcan identified lower predicted gene expression of CYTH4 in thyroid tissue as significantly associated with fibroid risk (p value = 5.86 × 10-8). In this first multi-stage GWAS for fibroids among AA women, we identified a novel risk locus for fibroids within CYTH4 that impacts gene expression in thyroid and has potential biological relevance for fibroids.

BackgroundAtrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke.MethodsTo determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in 5 prospective studies comprising 18 919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P values ranging from

One potential use for the PR interval is as a biomarker of disease risk. We hypothesized that quantifying the shared genetic architectures of the PR interval and a set of clinical phenotypes would identify genetic mechanisms contributing to PR variability and identify diseases associated with a genetic predictor of PR variability. We used ECG measurements from the ARIC study (Atherosclerosis Risk in Communities; n=6731 subjects) and 63 genetically modulated diseases from the eMERGE network (Electronic Medical Records and Genomics; n=12 978). We measured pairwise genetic correlations (rG) between PR phenotypes (PR interval, PR segment, P-wave duration) and each of the 63 phenotypes. The PR segment was genetically correlated with atrial fibrillation (rG=-0.88; P=0.0009). An analysis of metabolic phenotypes in ARIC also showed that the P wave was genetically correlated with waist circumference (rG=0.47; P=0.02). A genetically predicted PR interval phenotype based on 645 714 single-nucleotide polymorphisms was associated with atrial fibrillation (odds ratio=0.89 per SD change; 95% confidence interval, 0.83-0.95; P=0.0006). The differing pattern of associations among the PR phenotypes is consistent with analyses that show that the genetic correlation between the P wave and PR segment was not significantly different from 0 (rG=-0.03 [0.16]). The genetic architecture of the PR interval comprises modulators of atrial fibrillation risk and obesity.

It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10-5). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10-8). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk.

We hypothesized that generalized linear mixed models (GLMMs), which estimate the additive genetic variance underlying phenotype variability, would facilitate rapid characterization of clinical phenotypes from an electronic health record. We evaluated 1,288 phenotypes in 29,349 subjects of European ancestry with single-nucleotide polymorphism (SNP) genotyping on the Illumina Exome Beadchip. We show that genetic liability estimates are primarily driven by SNPs identified by prior genome-wide association studies and SNPs within the human leukocyte antigen (HLA) region. We identify 44 (false discovery rate q

BackgroundEzetimibe lowers plasma levels of low-density lipoprotein (LDL) cholesterol by inhibiting the activity of the Niemann-Pick C1-like 1 (NPC1L1) protein. However, whether such inhibition reduces the risk of coronary heart disease is not known. Human mutations that inactivate a gene encoding a drug target can mimic the action of an inhibitory drug and thus can be used to infer potential effects of that drug.MethodsWe sequenced the exons of NPC1L1 in 7364 patients with coronary heart disease and in 14,728 controls without such disease who were of European, African, or South Asian ancestry. We identified carriers of inactivating mutations (nonsense, splice-site, or frameshift mutations). In addition, we genotyped a specific inactivating mutation (p.Arg406X) in 22,590 patients with coronary heart disease and in 68,412 controls. We tested the association between the presence of an inactivating mutation and both plasma lipid levels and the risk of coronary heart disease.ResultsWith sequencing, we identified 15 distinct NPC1L1 inactivating mutations; approximately 1 in every 650 persons was a heterozygous carrier for 1 of these mutations. Heterozygous carriers of NPC1L1 inactivating mutations had a mean LDL cholesterol level that was 12 mg per deciliter (0.31 mmol per liter) lower than that in noncarriers (P=0.04). Carrier status was associated with a relative reduction of 53% in the risk of coronary heart disease (odds ratio for carriers, 0.47; 95% confidence interval, 0.25 to 0.87; P=0.008). In total, only 11 of 29,954 patients with coronary heart disease had an inactivating mutation (carrier frequency, 0.04%) in contrast to 71 of 83,140 controls (carrier frequency, 0.09%).ConclusionsNaturally occurring mutations that disrupt NPC1L1 function were found to be associated with reduced plasma LDL cholesterol levels and a reduced risk of coronary heart disease. (Funded by the National Institutes of Health and others.).

ObjectiveAs genotyping technology has progressed, genome-wide association studies (GWAS) have matured into efficient and effective tools for mapping genes underlying human phenotypes.MethodsRecent studies have shown the utility of the GWAS approach for examining pharmacogenomic traits, including drug metabolism, efficacy, and toxicity.ResultsApplication of GWAS to pharmacogenomic outcomes presents unique challenges and opportunities.ConclusionIn the current review, we discuss the potential promises and potential caveats of this approach specifically as it relates to pharmacogenomic studies. Concerns with study design, power and sample size, and analysis are reviewed. We further examine the features of successful pharmacogenomic GWAS, and describe consortia efforts that are likely to expand the reach of pharmacogenomic GWAS in the future.

Drug-induced long QT syndrome (LQTS) is a prevalent disorder of uncertain etiology that predisposes to sudden death. KCNE2 encodes MinK-related peptide 1 (MiRP1), a subunit of the cardiac potassium channel I(Kr) that has been associated previously with inherited LQTS. Here, we examine KCNE2 in 98 patients with drug-induced LQTS, identifying three individuals with sporadic mutations and a patient with sulfamethoxazole-associated LQTS who carried a single-nucleotide polymorphism (SNP) found in approximately 1.6% of the general population. While mutant channels showed diminished potassium flux at baseline and wild-type drug sensitivity, channels with the SNP were normal at baseline but inhibited by sulfamethoxazole at therapeutic levels that did not affect wild-type channels. We conclude that allelic variants of MiRP1 contribute to a significant fraction of cases of drug-induced LQTS through multiple mechanisms and that common sequence variations that increase the risk of life-threatening drug reactions can be clinically silent before drug exposure.

Abstract Introduction The eMERGE (electronic MEdical Records and GEnomics) Network is an NHGRI-supported consortium of five institutions to explore the utility of DNA repositories coupled to Electronic Medical Record (EMR) systems for advancing discovery in genome science. eMERGE also includes a special emphasis on the ethical, legal and social issues related to these endeavors. Organization The five sites are supported by an Administrative Coordinating Center. Setting of network goals is initiated by working groups: (1) Genomics, (2) Informatics, and (3) Consent & Community Consultation, which also includes active participation by investigators outside the eMERGE funded sites, and (4) Return of Results Oversight Committee. The Steering Committee, comprised of site PIs and representatives and NHGRI staff, meet three times per year, once per year with the External Scientific Panel. Current progress The primary site-specific phenotypes for which samples have undergone genome-wide association study (GWAS) genotyping are cataract and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease, and type 2 diabetes. A GWAS is also being undertaken for resistant hypertension in ≈2,000 additional samples identified across the network sites, to be added to data available for samples already genotyped. Funded by ARRA supplements, secondary phenotypes have been added at all sites to leverage the genotyping data, and hypothyroidism is being analyzed as a cross-network phenotype. Results are being posted in dbGaP. Other key eMERGE activities include evaluation of the issues associated with cross-site deployment of common algorithms to identify cases and controls in EMRs, data privacy of genomic and clinically-derived data, developing approaches for large-scale meta-analysis of GWAS data across five sites, and a community consultation and consent initiative at each site. Future activities Plans are underway to expand the network in diversity of populations and incorporation of GWAS findings into clinical care. Summary By combining advanced clinical informatics, genome science, and community consultation, eMERGE represents a first step in the development of data-driven approaches to incorporate genomic information into routine healthcare delivery.

Objective: This study was undertaken to investigate the hypothesis that a genetic predisposition toward rheumatoid arthritis (RA) increases the risk of 10 cardiometabolic and autoimmune disorders previously associated with RA in epidemiologic studies, and to define new genetic pleiotropy present in RA. Methods: Two approaches were used to test our hypothesis. First, we constructed a weighted genetic risk score (wGRS) and then examined its association with 10 prespecified disorders. Additionally, a phenome‐wide association study (PheWAS) was carried out to identify potential new associations. Second, inverse variance–weighted regression (IVWR) meta‐analysis was used to characterize the association between genetic susceptibility to RA and the prespecified disorders, with the results expressed as odds ratios (ORs) and 95% confidence intervals (95% CIs). Results: The wGRS for RA was significantly associated with type 1 diabetes mellitus (DM) (OR 1.10 [95% CI 1.04–1.16]; P = 9.82 × 10−4) and multiple sclerosis (OR 0.82 [95% CI 0.77–0.88]; P = 1.73 × 10−8), but not with other cardiometabolic phenotypes. In the PheWAS, wGRS was also associated with an increased risk of several autoimmune phenotypes including RA, thyroiditis, and systemic sclerosis, and with a decreased risk of demyelinating disorders. In the IVWR meta‐analyses, RA was significantly associated with an increased risk of type 1 DM (P = 1.15 × 10−14), with evidence of horizontal pleiotropy (Mendelian Randomization–Egger intercept estimate P = 0.001) likely driven by rs2476601, a PTPN22 variant. The association between type 1 DM and RA remained significant (P = 9.53 × 10−9) after excluding rs2476601, with no evidence of horizontal pleiotropy (intercept estimate P = 0.939). RA was also significantly associated with type 2 DM and C‐reactive protein levels. These associations were driven by variation in the major histocompatibility complex region. Conclusion: This study presents evidence of pleiotropy between the genetic predisposition to RA and associated phenotypes found in other autoimmune and cardiometabolic disorders, including type 1 DM. [ABSTRACT FROM AUTHOR]

Importance: Polygenic risk scores comprising millions of single-nucleotide polymorphisms (SNPs) could be useful for population-wide coronary heart disease (CHD) screening.Objective: To determine whether a polygenic risk score improves prediction of CHD compared with a guideline-recommended clinical risk equation.Design, Setting, and Participants: A retrospective cohort study of the predictive accuracy of a previously validated polygenic risk score was assessed among 4847 adults of white European ancestry, aged 45 through 79 years, participating in the Atherosclerosis Risk in Communities (ARIC) study and 2390 participating in the Multi-Ethnic Study of Atherosclerosis (MESA) from 1996 through December 31, 2015, the final day of follow-up. The performance of the polygenic risk score was compared with that of the 2013 American College of Cardiology and American Heart Association pooled cohort equations.Exposures: Genetic risk was computed for each participant by summing the product of the weights and allele dosage across 6 630 149 SNPs. Weights were based on an international genome-wide association study.Main Outcomes and Measures: Prediction of 10-year first CHD events (including myocardial infarctions, fatal coronary events, silent infarctions, revascularization procedures, or resuscitated cardiac arrest) assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI).Results: The study population included 4847 adults from the ARIC study (mean [SD] age, 62.9 [5.6] years; 56.4% women) and 2390 adults from the MESA cohort (mean [SD] age, 61.8 [9.6] years; 52.2% women). Incident CHD events occurred in 696 participants (14.4%) and 227 participants (9.5%), respectively, over median follow-up of 15.5 years (interquartile range [IQR], 6.3 years) and 14.2 (IQR, 2.5 years) years. The polygenic risk score was significantly associated with 10-year CHD incidence in ARIC with hazard ratios per SD increment of 1.24 (95% CI, 1.15 to 1.34) and in MESA, 1.38 (95% CI, 1.21 to 1.58). Addition of the polygenic risk score to the pooled cohort equations did not significantly increase the C statistic in either cohort (ARIC, change in C statistic, -0.001; 95% CI, -0.009 to 0.006; MESA, 0.021; 95% CI, -0.0004 to 0.043). At the 10-year risk threshold of 7.5%, the addition of the polygenic risk score to the pooled cohort equations did not provide significant improvement in reclassification in either ARIC (NRI, 0.018, 95% CI, -0.012 to 0.036) or MESA (NRI, 0.001, 95% CI, -0.038 to 0.076). The polygenic risk score did not significantly improve calibration in either cohort.Conclusions and Relevance: In this analysis of 2 cohorts of US adults, the polygenic risk score was associated with incident coronary heart disease events but did not significantly improve discrimination, calibration, or risk reclassification compared with conventional predictors. These findings suggest that a polygenic risk score may not enhance risk prediction in a general, white middle-aged population. [ABSTRACT FROM AUTHOR]

Background: We recently reported a quantitative relationship between the degree of functional perturbation reported in the literature for 356 variants in the cardiac sodium channel gene SCN5A and the penetrance of resulting arrhythmia phenotypes. In the course of that work, we identified multiple SCN5A variants, including R1193Q, that are common in populations but are reported in human embryonic kidney (HEK) cells to generate large late sodium current (INa-L).Objective: The purpose of this study was to compare the functional properties of R1193Q with those of the well-studied type 3 long QT syndrome mutation ΔKPQ.Methods: We compared functional properties of SCN5A R1193Q with those of ΔKPQ in Chinese hamster ovary (CHO) cells at baseline and after exposure to intracellular phosphatidylinositol (3,4,5)-trisphosphate (PIP3), which inhibits INa-L generated by decreased Phosphoinositide 3-kinase (PI3K) activity. We also used CRISPR/Cas9 editing to generate R1193Q in human-induced pluripotent stem cells differentiated to cardiomyocytes (hiPSC-CMs).Results: Both R1193Q and ΔKPQ generated robust INa-L in CHO cells. PIP3 abrogated the late current phenotype in R1193Q cells but had no effect on ΔKPQ. Homozygous R1193Q hiPSC-CMs displayed increased INa-L and long action potentials with frequent triggered beats, which were reversed with the addition of PIP3.Conclusion: The consistency between the late current produced in HEK cells, CHO cells, and hiPSC-CMs suggests that the late current is a feature of the SCN5A R1193Q variant in human cardiomyocytes but that the mechanism by which the late current is produced is distinct and indirect, as compared with the more highly penetrant ΔKPQ. These data suggest that observing a late current in an in vitro setting does not necessarily translate to highly pathogenic type 3 long QT syndrome phenotype but depends on the underlying mechanism. [ABSTRACT FROM AUTHOR]

Background: The relation between burden of risk factors, familial coronary artery disease (CAD), and known genetic variants underlying CAD and low-density lipoprotein cholesterol (LDL-C) levels is not well-explored in clinical samples. We aimed to investigate the association of these measures with age at onset of CAD requiring revascularizations in a clinical sample of patients undergoing first-time coronary angiography. Methods: 1599 individuals (mean age 64 years [min-max 29–96 years], 28% women) were genotyped (from blood drawn as part of usual clinical care) in the Copenhagen area (2010–2014). The burden of common genetic variants was measured as aggregated genetic risk scores (GRS) of single nucleotide polymorphisms (SNPs) discovered in genome-wide association studies. Results: Self-reported familial CAD (prevalent in 41% of the sample) was associated with -3.2 years (95% confidence interval -4.5, -2.2, p<0.0001) earlier need of revascularization in sex-adjusted models. Patients with and without familial CAD had similar mean values of CAD-GRS (unweighted scores 68.4 vs. 68.0, p = 0.10, weighted scores 67.7 vs. 67.5, p = 0.49) and LDL-C-GRS (unweighted scores 58.5 vs. 58.3, p = 0.34, weighted scores 63.3 vs. 61.1, p = 0.41). The correlation between the CAD-GRS and LDL-C-GRS was low (r = 0.14, p<0.001). In multivariable adjusted regression models, each 1 standard deviation higher values of LDL-C-GRS and CAD-GRS were associated with -0.70 years (95% confidence interval -1.25, -0.14, p = 0.014) and -0.51 years (-1.07, 0.04, p = 0.07) earlier need for revascularization, respectively. Conclusions: Young individuals presenting with CAD requiring surgical interventions had a higher genetic burden of SNPs relating to LDL-C and CAD (although the latter was statistically non-significant), compared with older individuals. However, the absolute difference was modest, suggesting that genetic screening can currently not be used as an effective prediction tool of when in life a person will develop CAD. Whether undiscovered genetic variants can still explain a “missing heritability” in early-onset CAD warrants more research. [ABSTRACT FROM AUTHOR]

Background: Recent GWAS studies have identified more than 300 SNPs associated with variation in blood pressure. We investigated whether a genetic risk score constructed from these variants is associated with burden of coronary heart disease. Methods: From 2010–2014, 4,809 individuals admitted to coronary angiography in Capital Region of Copenhagen were genotyped. We calculated hypertension GRS comprised of GWAS identified SNPs associated with blood pressure. We performed logistic regression analyses to estimate the risk of hypertension and prevalent CHD. We also assessed the severity of CHD associated with the GRS. The analyses were performed using GRS quartiles. We used the Inter99 cohort to validate our results and to investigate for possible pleiotropy for the GRS with other CHD risk factors. Results: In COGEN, adjusted odds ratios comparing the 2nd, 3rd and 4th cumulative GRS quartiles with the reference were 1.12(95% CI 0.95–1.33), 1.35(95% CI 1.14–1.59) and 1.29(95% CI 1.09–1.53) respectively, for prevalent CHD. The adjusted multinomial logistic regression showed that 3rd and 4th GRS quartiles were associated with increased odds of developing two(OR 1.33, 95% CI 1.04–1.71 and OR 1.36, 95% CI 1.06–1.75, respectively) and three coronary vessel disease(OR 1.77, 95% CI 1.36–2.30 and OR 1.65, 95% CI 1.26–2.15, respectively). Similar results for incident CHD were observed in the Inter99 cohort. The hypertension GRS did not associate with type 2 diabetes, smoking, BMI or hyperlipidemia. Conclusion: Hypertension GRS quartiles were associated with an increased risk of hypertension, prevalent CHD, and burden of coronary vessel disease in a dose-response pattern. We showed no evidence for pleiotropy with other risk factors for CHD. [ABSTRACT FROM AUTHOR]

An editorial is presented on cardiovascular genetics which growing pain in patients. Topics discussed include landmark discovery of disease genes that have been critical for understanding basic physiological and pathophysiological process in the heart; list of disease genes for cardiovascular genetic disease and improvement in sequencing cost and efficiency that have enabled widespread application of panel based sequencing; and recognition of disease genes.

Aim: Rare variants of genes encoding the cardiac sodium channel and associated compounds have been linked with atrial fibrillation (AF). Nevertheless, current expert consensus does not support genetic testing in AF, which is in part based on the fact that “there is no therapeutic impact derived from AF genetic test results”. However, there are no studies available supporting this recommendation. Consequently, this study analyzed the impact of rare variants affecting the cardiac sodium channel on rhythm outcome of AF catheter ablation. Methods and results: In 137 consecutive patients with lone AF enrolled in the Leipzig Heart Center AF ablation registry, screening for mutations in SCN5A, SCN1B – 4B, CAV3, GPD1L, SNTA1 and MOG1 was performed. We identified 3 rare non-synonymous variants in SCN5A, 5 in SCN1B, 1 in SCN4B, 1 in CAV3, 6 in GPD1L, 3 in SNTA1 and 3 in MOG1 (16%). Variant carriers were otherwise comparable with non-variant carriers. Analysis of AF recurrence rates after radiofrequency AF catheter ablation by serial 7-day Holter ECG monitoring between 3 and 12 months revealed no difference between groups, i.e. 45% in variant carriers vs. 49% in non-variant carriers. Conclusions: Rare variants in genes encoding the cardiac sodium channel and associated compounds are frequently found in lone AF but were not found to impact the outcome of AF catheter ablation. This finding supports current recommendations not to screen for rare variants for the ablation outcome in AF. Nevertheless, it may at least be helpful for understanding AF mechanisms and larger studies are needed to further explore the possible association between genotype and response to AF therapies. [ABSTRACT FROM AUTHOR]

Objective: 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. Methods and materials: 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. Results: 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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

The potential impact of using human genetic data linked to longitudinal electronic medical records on drug development is extraordinary; however, the practical application of these data necessitates some organizational innovations. Vanderbilt has created resources such as an easily queried database of >2.6 million de-identified electronic health records linked to BioVU, which is a DNA biobank with more than 230,000 unique samples. To ensure these data are used to maximally benefit and accelerate both de novo drug discovery and drug repurposing efforts, we created the Accelerating Drug Development and Repurposing Incubator, a multidisciplinary think tank of experts in various therapeutic areas within both basic and clinical science as well as experts in legal, business, and other operational domains. The Incubator supports a diverse pipeline of drug indication finding projects, leveraging the natural experiment of human genetics. [ABSTRACT FROM AUTHOR]

Imputation of human leukocyte antigen (HLA) alleles from SNP-level data is attractive due to importance of HLA alleles in human disease, widespread availability of genome-wide association study (GWAS) data, and expertise required for HLA sequencing. However, comprehensive evaluations of HLA imputations programs are limited. We compared HLA imputation results of HIBAG, SNP2HLA, and HLA*IMP:02 to sequenced HLA alleles in 3,265 samples from BioVU, a de-identified electronic health record database coupled to a DNA biorepository. We performed four-digit HLA sequencing for HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1 using long-read 454 FLX sequencing. All samples were genotyped using both the Illumina HumanExome BeadChip platform and a GWAS platform. Call rates and concordance rates were compared by platform, frequency of allele, and race/ethnicity. Overall concordance rates were similar between programs in European Americans (EA) (0.975 [SNP2HLA]; 0.939 [HLA*IMP:02]; 0.976 [HIBAG]). SNP2HLA provided a significant advantage in terms of call rate and the number of alleles imputed. Concordance rates were lower overall for African Americans (AAs). These observations were consistent when accuracy was compared across HLA loci. All imputation programs performed similarly for low frequency HLA alleles. Higher concordance rates were observed when HLA alleles were imputed from GWAS platforms versus the HumanExome BeadChip, suggesting that high genomic coverage is preferred as input for HLA allelic imputation. These findings provide guidance on the best use of HLA imputation methods and elucidate their limitations. [ABSTRACT FROM AUTHOR]

Advances in genomics are enhancing our understanding of the genetic basis of cardiovascular diseases, both congenital and acquired, and stroke. These advances include finding genes that cause or increase the risk for childhood and adult-onset diseases, finding genes that influence how patients respond to medications, and the development of genetics-guided therapies for diseases. However, the ability of cardiovascular and stroke clinicians to fully understand and apply this knowledge to the care of their patients has lagged. This statement addresses what the specialist caring for patients with cardiovascular diseases and stroke should know about genetics; how they can gain this knowledge; how they can keep up-to-date with advances in genetics, genomics, and pharmacogenetics; and how they can apply this knowledge to improve the care of patients and families with cardiovascular diseases and stroke. [ABSTRACT FROM AUTHOR]

The article projects the future of cardiovascular treatment options in the U.S. Topics discussed include the concepts of cardiovascular disease and their association with therapy, the target population of cardiovascular community, various drug discovery approaches and their driving factors, and the emergence of different classes of therapeutics.

The process of scientific discovery is rapidly evolving. The funding climate has influenced a favorable shift in scientific discovery toward the use of existing resources such as the electronic health record. The electronic health record enables long-term outlooks on human health and disease, in conjunction with multidimensional phenotypes that include laboratory data, images, vital signs, and other clinical information. Initial work has confirmed the utility of the electronic health record for understanding mechanisms and patterns of variability in disease susceptibility, disease evolution, and drug responses. The addition of biobanks and genomic data to the information contained in the electronic health record has been demonstrated. The purpose of this statement is to discuss the current challenges in and the potential for merging electronic health record data and genomics for cardiovascular research. [ABSTRACT FROM AUTHOR]

Background--Considerable interest exists in the identification of genetic modifiers of disease severity in the long-QT syndrome (LQTS) as their identification may contribute to refinement of risk stratification. Methods and Results--We searched for single-nucleotide polymorphisms (SNPs) that modulate the corrected QT (QTc)- interval and the occurrence of cardiac events in 639 patients harboring different mutations in KCNH2. We analyzed 1201 SNPs in and around 18 candidate genes, and in another approach investigated 22 independent SNPs previously identified as modulators of QTc-interval in genome-wide association studies in the general population. In an analysis for quantitative effects on the QTc-interval, 3 independent SNPs at NOS1AP (rs10494366, P=9.5×10-8; rs12143842, P=4.8×10-7; and rs2880058, P=8.6×10-7) were strongly associated with the QTc-interval with marked effects (>12 ms/allele). Analysis of patients versus general population controls uncovered enrichment of QTc-prolonging alleles in patients for 2 SNPs, located respectively at NOS1AP (rs12029454; odds ratio, 1.85; 95% confidence interval, 1.32-2.59; P=3×10-4) and KCNQ1 (rs12576239; odds ratio, 1.84; 95% confidence interval, 1.31-2.60; P=5×10-4). An analysis of the cumulative effect of the 6 NOS1AP SNPs by means of a multilocus genetic risk score (GRSNOS1AP) uncovered a strong linear relationship between GRSNOS1AP and the QTc-interval (P=4.2×10-7). Furthermore, patients with a GRSNOS1AP in the lowest quartile had a lower relative risk of cardiac events compared with patients in the other quartiles combined (P=0.039). Conclusions--We uncovered unexpectedly large effects of NOS1AP SNPs on the QTc-interval and a trend for effects on risk of cardiac events. For the first time, we linked common genetic variation at KCNQ1 with risk of long-QT syndrome. [ABSTRACT FROM AUTHOR]

The article presents a study regarding the prevalence of atrial fibrillation (AF) among carriers and noncarriers of rare variants previously designated as pathogenic for AF. The study concluded that these variants are not associated with AF and suggested that caution is needed when ascribing variants as pathogenic or causative. The methods of the study are discussed.

Aims Positional cloning and candidate gene approaches have shown that atrial fibrillation (AF) is a complex disease with familial aggregation. Here, we employed whole-exome sequencing (WES) in AF kindreds to identify variants associated with familial AF. Methods and results WES was performed on 18 individuals in six modestly sized familial AF kindreds. After filtering very rare variants by multiple metrics, we identified 39 very rare and potentially pathogenic variants [minor allele frequency (MAF) ≤0.04%] in genes not previously associated with AF. Despite stringent filtering >1 very rare variants in the 5/6 of the kindreds were identified, whereas no plausible variants contributing to familial AF were found in 1/6 of the kindreds. Two candidate AF variants in the calcium channel subunit genes (CACNB2 and CACNA2D4) were identified in two separate families using expression data and predicted function. Conclusion By coupling family data with exome sequencing, we identified multiple very rare potentially pathogenic variants in five of six families, suggestive of a complex disease mechanism, whereas none were identified in the remaining AF pedigree. This study highlights some important limitations and challenges associated with performing WES in AF including the importance of having large well-curated multi-generational pedigrees, the issue of potential AF misclassification, and limitations of WES technology when applied to a complex disease. [ABSTRACT FROM PUBLISHER]

The coupling of electronic medical records (EMR) with genetic data has created the potential for implementing reverse genetic approaches in humans, whereby the function of a gene is inferred from the shared pattern of morbidity among homozygotes of a genetic variant. We explored the feasibility of this approach to identify phenotypes associated with low frequency variants using Vanderbilt's EMR-based BioVU resource. We analyzed 1,658 low frequency non-synonymous SNPs (nsSNPs) with a minor allele frequency (MAF)<10% collected on 8,546 subjects. For each nsSNP, we identified diagnoses shared by at least 2 minor allele homozygotes and with an association p<0.05. The diagnoses were reviewed by a clinician to ascertain whether they may share a common mechanistic basis. While a number of biologically compelling clinical patterns of association were observed, the frequency of these associations was identical to that observed using genotype-permuted data sets, indicating that the associations were likely due to chance. To refine our analysis associations, we then restricted the analysis to 711 nsSNPs in genes with phenotypes in the On-line Mendelian Inheritance in Man (OMIM) or knock-out mouse phenotype databases. An initial comparison of the EMR diagnoses to the known in vivo functions of the gene identified 25 candidate nsSNPs, 19 of which had significant genotype-phenotype associations when tested using matched controls. Twleve of the 19 nsSNPs associations were confirmed by a detailed record review. Four of 12 nsSNP-phenotype associations were successfully replicated in an independent data set: thrombosis (F5,rs6031), seizures/convulsions (GPR98,rs13157270), macular degeneration (CNGB3,rs3735972), and GI bleeding (HGFAC,rs16844401). These analyses demonstrate the feasibility and challenges of using reverse genetics approaches to identify novel gene-phenotype associations in human subjects using low frequency variants. As increasing amounts of rare variant data are generated from modern genotyping and sequence platforms, model organism data may be an important tool to enable discovery. [ABSTRACT FROM AUTHOR]

Type 2 diabetes (T2D) is a complex metabolic disease that disproportionately affects African Americans. Genome-wide association studies (GWAS) have identified several loci that contribute to T2D in European Americans, but few studies have been performed in admixed populations. We first performed a GWAS of 1,563 African Americans from the Vanderbilt Genome-Electronic Records Project and Northwestern University NUgene Project as part of the electronic Medical Records and Genomics (eMERGE) network. We successfully replicate an association in TCF7L2, previously identified by GWAS in this African American dataset. We were unable to identify novel associations at p<5.0×10−8 by GWAS. Using admixture mapping as an alternative method for discovery, we performed a genome-wide admixture scan that suggests multiple candidate genes associated with T2D. One finding, TCIRG1, is a T-cell immune regulator expressed in the pancreas and liver that has not been previously implicated for T2D. We performed subsequent fine-mapping to further assess the association between TCIRG1 and T2D in >5,000 African Americans. We identified 13 independent associations between TCIRG1, CHKA, and ALDH3B1 genes on chromosome 11 and T2D. Our results suggest a novel region on chromosome 11 identified by admixture mapping is associated with T2D in African Americans. [ABSTRACT FROM AUTHOR]

Interindividual heterogeneity in drug response is a central feature of all drug therapies. Studies in individual patients, families, and populations over the past several decades have identified variants in genes encoding drug elimination or drug target pathways that in some cases contribute substantially to variable efficacy and toxicity. Important associations of pharmacogenomics in cardiovascular medicine include clopidogrel and risk for in-stent thrombosis, steady-state warfarin dose, myotoxicity with simvastatin, and certain drug-induced arrhythmias. This review describes methods used to accumulate and validate these findings and points to approaches-now being put in place at some centers-to implementing them in clinical care. [ABSTRACT FROM AUTHOR]