Christy L. Avery

Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.

The Use of Phenome-Wide Association Studies (PheWAS) for Exploration of Novel Genotype-Phenotype Relationships and Pleiotropy Discovery

The field of phenomics has been investigating network structure among large arrays of phenotypes, and genome‐wide association studies (GWAS) have been used to investigate the relationship between genetic variation and single diseases/outcomes. A novel approach has emerged combining both the exploration of phenotypic structure and genotypic variation, known as the phenome‐wide association study (PheWAS). The Population Architecture using Genomics and Epidemiology (PAGE) network is a National Human Genome Research Institute (NHGRI)‐supported collaboration of four groups accessing eight extensively characterized epidemiologic studies. The primary focus of PAGE is deep characterization of well‐replicated GWAS variants and their relationships to various phenotypes and traits in diverse epidemiologic studies that include European Americans, African Americans, Mexican Americans/Hispanics, Asians/Pacific Islanders, and Native Americans. The rich phenotypic resources of PAGE studies provide a unique opportunity for PheWAS as each genotyped variant can be tested for an association with the wide array of phenotypic measurements available within the studies of PAGE, including prevalent and incident status for multiple common clinical conditions and risk factors, as well as clinical parameters and intermediate biomarkers. The results of PheWAS can be used to discover novel relationships between SNPs, phenotypes, and networks of interrelated phenotypes; identify pleiotropy; provide novel mechanistic insights; and foster hypothesis generation. The PAGE network has developed infrastructure to support and perform PheWAS in a high‐throughput manner. As implementing the PheWAS approach has presented several challenges, the infrastructure and methodology, as well as insights gained in this project, are presented herein to benefit the larger scientific community. Genet. Epidemiol. 2011.

Sources of Variability in Measurements of Cardiac Troponin T in a Community-Based Sample: The Atherosclerosis Risk in Communities Study

BACKGROUND Application of cardiac troponin T (cTnT) as a marker of myocyte damage requires knowledge of its measurement variability. Using a highly sensitive assay for measurement, we evaluated the long-term storage stability of plasma cTnT at -70 °C and the sources of cTnT variability. METHODS Samples from the Atherosclerosis Risk in Communities study collected in 1996-1998 and 2005-2006 were assayed centrally to quantify variability in cTnT attributable to processing (replicates from same blood draw, n = 87), laboratory (replicates after freeze thaw, n = 29), short-term (n = 40) and long-term biological variation (repeat visit, n = 38), and degradation in frozen storage (n = 7677). RESULTS Approximately 30% of this population-based cohort had cTnT concentrations below the detection limit (3 ng/L). Reliability coefficients for all paired comparisons exceeded 0.93 except for samples drawn 8 years apart (r = 0.36). Sources of cTnT variation (as CVs) were: laboratory, 2.1% and 11.2% in those with and without heart failure, respectively; processing, 18.3%; biological, 16.6% at 6 weeks and 48.4% at 8 years. The reference change value at 6 weeks (68.5%) indicated that 4 samples are needed to determine a homeostatic set point within ±25%. The estimated cTnT degradation rate over the first year in long-term frozen storage was 0.36 ng/L per year. CONCLUSIONS cTnT was detectable in approximately 70% of community-dwelling middle-aged study participants and stable in -70 °C storage. The variability in cTnT attributable to 1 freeze-thaw cycle is of small magnitude. The observed high laboratory and intraindividual (biological) reliability of cTnT support its use for population-based research, and in clinical settings that rely on classification and serial measurements.

A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

Estimating error in using ambient PM2.5 concentrations as proxies for personal exposures: A review

Background: Several methods have been used to account for measurement error inherent in using ambient concentration of particulate matter <2.5 &mgr;m/m3 (PM2.5) as a proxy for personal exposure. Such methods commonly rely on the estimated correlation between ambient and personal PM2.5 concentrations (r). However, studies of r have not been systematically and quantitatively assessed for publication bias or heterogeneity. Methods: We searched 7 electronic reference databases for studies of the within-participant correlation between ambient and personal PM2.5. Results: We identified 567 candidate studies, 18 (3%) of which met inclusion criteria and were abstracted. The studies were published between 1999 and 2008, representing 619 nonsmoking participants aged 6–93 years in 17 European and North American cities. Correlation coefficients (median 0.54; range 0.09–0.83) were based on a median of 8 ambient-personal PM2.5 pairs per participant (range 5–20) collected over 27–547 days. Overall, there was little evidence for publication bias (funnel plot symmetry tests: Beggs log-rank test, P = 0.9; Eggers regression asymmetry test, P = 0.2). However, strong evidence for heterogeneity was noted (Cochrans Q test for heterogeneity, P < 0.001). European locales, eastern longitudes in North America, higher ambient PM2.5 concentrations, higher relative humidity, and lower between-participant variation in r were associated with increased r. Conclusions: Characteristics of participants, studies, and the environments in which they are conducted may affect the accuracy of ambient PM2.5 as a proxy for personal exposure.

The Population Burden of Heart Failure Attributable to Modifiable Risk Factors: The ARIC (Atherosclerosis Risk in Communities) Study

OBJECTIVES The goal of this study was to estimate the population burden of heart failure and the influence of modifiable risk factors. BACKGROUND Heart failure is a common, costly, and fatal disorder, yet few studies have evaluated the population-level influence of modifiable risk factors. METHODS From 14,709 ARIC (Atherosclerosis Risk in Communities) study participants, we estimated incidence rate differences (IRD) for the association between 5 modifiable risk factors (cigarette smoking, diabetes, elevated low-density lipoproteins, hypertension, and obesity) and heart failure. Potential impact fractions were used to measure expected changes in the heart failure incidence assuming achievement of a 5% proportional decrement in the prevalence of each risk factor. RESULTS Over an average of 17.6 years of follow-up, 1 in 3 African American and 1 in 4 Caucasian participants were hospitalized with heart failure, defined as the first hospitalization with International Classification of Diseases, Ninth Revision discharge codes of 428.x. Of the 5 modifiable risk factors, the largest IRD was observed for diabetes, which was associated with 1,058 (95% confidence interval [CI]: 787 to 1,329) and 660 (95% CI: 514 to 805) incident hospitalizations of heart failure/100,000 person-years among African-American and Caucasian participants, respectively. A 5% proportional reduction in the prevalence of diabetes would result in approximately 53 and 33 fewer incident heart failure hospitalizations per 100,000 person-years in African-American and Caucasian ARIC participants, respectively. When applied to U.S. populations, this reduction may prevent approximately 30,000 incident cases of heart failure annually. CONCLUSIONS Modest decrements in the prevalence of modifiable heart failure risk factors such as diabetes may substantially decrease the incidence of this major disease.

Impact of ancestry and common genetic variants on QT interval in African Americans.

Background—Ethnic differences in cardiac arrhythmia incidence have been reported, with a particularly high incidence of sudden cardiac death and low incidence of atrial fibrillation in individuals of African ancestry. We tested the hypotheses that African ancestry and common genetic variants are associated with prolonged duration of cardiac repolarization, a central pathophysiological determinant of arrhythmia, as measured by the electrocardiographic QT interval. Methods and Results—First, individual estimates of African and European ancestry were inferred from genome-wide single-nucleotide polymorphism (SNP) data in 7 population-based cohorts of African Americans (n=12 097) and regressed on measured QT interval from ECGs. Second, imputation was performed for 2.8 million SNPs, and a genome-wide association study of QT interval was performed in 10 cohorts (n=13 105). There was no evidence of association between genetic ancestry and QT interval (P=0.94). Genome-wide significant associations (P<2.5×10–8) were identified with SNPs at 2 loci, upstream of the genes NOS1AP (rs12143842, P=2×10–15) and ATP1B1 (rs1320976, P=2×10–10). The most significant SNP in NOS1AP was the same as the strongest SNP previously associated with QT interval in individuals of European ancestry. Low probability values (P<10–5) were observed for SNPs at several other loci previously identified in genome-wide association studies in individuals of European ancestry, including KCNQ1, KCNH2, LITAF, and PLN. Conclusions—We observed no difference in duration of cardiac repolarization with global genetic indices of African American ancestry. In addition, our genome-wide association study extends the association of polymorphisms at several loci associated with repolarization in individuals of European ancestry to include individuals of Afr.

Generalized estimating equations for genome-wide association studies using longitudinal phenotype data.

Many longitudinal cohort studies have both genome-wide measures of genetic variation and repeated measures of phenotypes and environmental exposures. Genome-wide association study analyses have typically used only cross-sectional data to evaluate quantitative phenotypes and binary traits. Incorporation of repeated measures may increase power to detect associations, but also requires specialized analysis methods. Here, we discuss one such method-generalized estimating equations (GEE)-in the contexts of analysis of main effects of rare genetic variants and analysis of gene-environment interactions. We illustrate the potential for increased power using GEE analyses instead of cross-sectional analyses. We also address challenges that arise, such as the need for small-sample corrections when the minor allele frequency of a genetic variant and/or the prevalence of an environmental exposure is low. To illustrate methods for detection of gene-drug interactions on a genome-wide scale, using repeated measures data, we conduct single-study analyses and meta-analyses across studies in three large cohort studies participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium-the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Rotterdam Study.

Reducing the Blood Pressure-Related Burden of Cardiovascular Disease: Impact of Achievable Improvements in Blood Pressure Prevention and Control.

Background US blood pressure reduction policies are largely restricted to hypertensive populations and associated benefits are often estimated based on unrealistic interventions. Methods and Results We used multivariable linear regression to estimate incidence rate differences contrasting the impact of 2 pragmatic hypothetical interventions to reduce coronary heart disease, stroke, and heart failure (HF) incidence: (1) a population‐wide intervention that reduced systolic blood pressure by 1 mm Hg and (2) targeted interventions that reduced the prevalence of unaware, untreated, or uncontrolled blood pressure above goal (per Eighth Joint National Committee treatment thresholds) by 10%. In the Atherosclerosis Risk in Communities Study (n=15 744; 45 to 64 years at baseline, 1987–1989), incident coronary heart disease and stroke were adjudicated by physician panels. Incident HF was defined as the first hospitalization with discharge diagnosis code of “428.” A 10% proportional reduction in unaware, untreated, or uncontrolled blood pressure above goal resulted in ≈4.61, 3.55, and 11.01 fewer HF events per 100 000 person‐years in African Americans, and 3.77, 1.63, and 4.44 fewer HF events per 100 000 person‐years, respectively, in whites. In contrast, a 1 mm Hg population‐wide systolic blood pressure reduction was associated with 20.3 and 13.3 fewer HF events per 100 000 person‐years in African Americans and whites, respectively. Estimated event reductions for coronary heart disease and stroke were smaller than for HF, but followed a similar pattern for both population‐wide and targeted interventions. Conclusions Modest population‐wide shifts in systolic blood pressure could have a substantial impact on cardiovascular disease incidence and should be developed in parallel with interventions targeting populations with blood pressure above goal.

Novel Loci Associated With PR Interval in a Genome-Wide Association Study of 10 African American Cohorts

Background—The PR interval, as measured by the resting, standard 12-lead ECG, reflects the duration of atrial/atrioventricular nodal depolarization. Substantial evidence exists for a genetic contribution to PR, including genome-wide association studies that have identified common genetic variants at 9 loci influencing PR in populations of European and Asian descent. However, few studies have examined loci associated with PR in African Americans. Methods and Results—We present results from the largest genome-wide association study to date of PR in 13 415 adults of African descent from 10 cohorts. We tested for association between PR (ms) and ≈2.8 million genotyped and imputed single-nucleotide polymorphisms. Imputation was performed using HapMap 2 YRI and CEU panels. Study-specific results, adjusted for global ancestry and clinical correlates of PR, were meta-analyzed using the inverse variance method. Variation in genome-wide test statistic distributions was noted within studies (&lgr; range: 0.9–1.1), although not after genomic control correction was applied to the overall meta-analysis (&lgr;: 1.008). In addition to generalizing previously reported associations with MEIS1, SCN5A, ARHGAP24, CAV1, and TBX5 to African American populations at the genome-wide significance level (P<5.0×10−8), we also identified a novel locus: ITGA9, located in a region previously implicated in SCN5A expression. The 3p21 region harboring SCN5A also contained 2 additional independent secondary signals influencing PR (P<5.0×10−8). Conclusions—This study demonstrates the ability to map novel loci in African Americans as well as the generalizability of loci associated with PR across populations of African, European, and Asian descent.