Detection of pleiotropy through a Phenome-wide association study (PheWAS) of epidemiologic data as part of the Environmental Architecture for Genes Linked to Environment (EAGLE) study.

We performed a Phenome-wide association study (PheWAS) utilizing diverse genotypic and phenotypic data existing across multiple populations in the National Health and Nutrition Examination Surveys (NHANES), conducted by the Centers for Disease Control and Prevention (CDC), and accessed by the Epidemiological Architecture for Genes Linked to Environment (EAGLE) study. We calculated comprehensive tests of association in Genetic NHANES using 80 SNPs and 1,008 phenotypes (grouped into 184 phenotype classes), stratified by race-ethnicity. Genetic NHANES includes three surveys (NHANES III, 1999-2000, and 2001-2002) and three race-ethnicities: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We identified 69 PheWAS associations replicating across surveys for the same SNP, phenotype-class, direction of effect, and race-ethnicity at p<0.01, allele frequency >0.01, and sample size >200. Of these 69 PheWAS associations, 39 replicated previously reported SNP-phenotype associations, 9 were related to previously reported associations, and 21 were novel associations. Fourteen results had the same direction of effect across more than one race-ethnicity: one result was novel, 11 replicated previously reported associations, and two were related to previously reported results. Thirteen SNPs showed evidence of pleiotropy. We further explored results with gene-based biological networks, contrasting the direction of effect for pleiotropic associations across phenotypes. One PheWAS result was ABCG2 missense SNP rs2231142, associated with uric acid levels in both non-Hispanic whites and Mexican Americans, protoporphyrin levels in non-Hispanic whites and Mexican Americans, and blood pressure levels in Mexican Americans. Another example was SNP rs1800588 near LIPC, significantly associated with the novel phenotypes of folate levels (Mexican Americans), vitamin E levels (non-Hispanic whites) and triglyceride levels (non-Hispanic whites), and replication for cholesterol levels. The results of this PheWAS show the utility of this approach for exposing more of the complex genetic architecture underlying multiple traits, through generating novel hypotheses for future research.

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.

Characterization of mitochondrial haplogroups in a large population-based sample from the United States.

Mitochondrial DNA (mtDNA) haplogroups are valuable for investigations in forensic science, molecular anthropology, and human genetics. In this study, we developed a custom panel of 61 mtDNA markers for high-throughput classification of European, African, and Native American/Asian mitochondrial haplogroup lineages. Using these mtDNA markers, we constructed a mitochondrial haplogroup classification tree and classified 18,832 participants from the National Health and Nutrition Examination Surveys (NHANES). To our knowledge, this is the largest study to date characterizing mitochondrial haplogroups in a population-based sample from the United States, and the first study characterizing mitochondrial haplogroup distributions in self-identified Mexican Americans separately from Hispanic Americans of other descent. We observed clear differences in the distribution of maternal genetic ancestry consistent with proposed admixture models for these subpopulations, underscoring the genetic heterogeneity of the United States Hispanic population. The mitochondrial haplogroup distributions in the other self-identified racial/ethnic groups within NHANES were largely comparable to previous studies. Mitochondrial haplogroup classification was highly concordant with self-identified race/ethnicity (SIRE) in non-Hispanic whites (94.8 %), but was considerably lower in admixed populations including non-Hispanic blacks (88.3 %), Mexican Americans (81.8 %), and other Hispanics (61.6 %), suggesting SIRE does not accurately reflect maternal genetic ancestry, particularly in populations with greater proportions of admixture. Thus, it is important to consider inconsistencies between SIRE and genetic ancestry when performing genetic association studies. The mitochondrial haplogroup data that we have generated, coupled with the epidemiologic variables in NHANES, is a valuable resource for future studies investigating the contribution of mtDNA variation to human health and disease.

Genetic variation in the ß1-adrenergic receptor is associated with the risk of atrial fibrillation after cardiac surgery.

BACKGROUND: Postoperative atrial fibrillation (PoAF) after cardiac surgery is common and associated with increased morbidity and mortality. Increased sympathetic activation after surgery contributes to PoAF, and ß-blockers are the first-line recommendation for its prevention. We examined the hypothesis that common functional genetic variants in the ß1-adrenoreceptor, the mediator of cardiac sympathetic activation and drug target of ß-blockers, are associated with the risk for PoAF and with the protective effect of ß-blockers. METHODS: In a prospective cohort study, we studied 947 adult European Americans who underwent cardiac surgery at Vanderbilt University between 1999 and 2005. We genotyped 2 variants in the ß1-adrenoreceptor, rs1801253 (Arg389Gly) and rs1801252 (Ser49Gly), and used logistic regression to examine the association between genotypes and PoAF occurring within 14 days after surgery, before and after adjustment for demographic and clinical covariates. RESULTS: Postoperative atrial fibrillation occurred in 239 patients (25.2%) and was associated with rs1801253 genotype (adjusted P = .008), with Gly389Gly having an odds ratio of 2.63 (95% CI 1.42-4.89) for PoAF compared to the common Arg389Arg (P = .002). In a predefined subgroup analysis, this association appeared to be stronger among patients without ß-blocker prophylaxis (adjusted odds ratio 7.00, 95% CI 1.82-26.96, P = .005) compared to patients with ß-blocker prophylaxis, among whom the association between rs1801253 genotype and PoAF was not statistically significant (adjusted P = .11). CONCLUSION: The Gly389 variant in the ß1-adrenoreceptor is associated with PoAF, and this association appears to be modulated by ß-blocker therapy. Future studies of the association of other adrenergic pathway genes with PoAF will be of interest.

Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study.

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS-identified variants in diverse population-based studies. We genotyped 49 GWAS-identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (~20,000), African American (~9,000), American Indian (~6,000), Mexican American/Hispanic (~2,500), Japanese/East Asian (~690), and Pacific Islander/Native Hawaiian (~175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.

Combining zip code-based population data and pharmacy administrative claims data to create measures of social determinants of health.

BACKGROUND: Social determinants of health (SDoH) are key factors that impact health outcomes. However, there are many barriers to collecting SDoH data (eg, cost of data collection, technological barriers, and lack of standardized measures). Population data may provide an accessible alternative to collecting SDoH data for patients. OBJECTIVE: To explain how population data can be leveraged to create SDoH measures, assess the association of population SDoH measures with diabetic medication adherence, and discuss how understanding a patient's SDoH can inform care plans and patient engagement. METHODS: A nationally representative commercial sample of patients who were aged 18 years and older and met Pharmacy Quality Alliance inclusion criteria for diabetes mellitus were analyzed (N = 37,789). US Census and North American Industry Classification System data were combined with pharmacy administrative claims data to create SDoH measures. Derived measures represent 2 SDoH domains: (1) economic stability (housing density, housing relocation, jobs per resident, and average salary) and (2) health care access and quality (urban/rural classification, distance traveled to prescriber and pharmacy, use of a primary care provider [PCP], and residents per PCP). The association of population SDoH measures with diabetic medication adherence (proportion of days covered) was assessed via logistic regression, which included covariates (eg, sex, age, comorbidities, and prescription plan attributes). RESULTS: As housing density (houses per resident) increased, so did the likelihood of adherence (odds ratio = 1.54, 95% CI = 1.21-1.97, P = 0.001). Relative to patients who did not move, patients who moved once had 0.87 (95% CI = 0.81-0.93, P < 0.001) the odds of being adherent, and patients who moved 2 or more times had 0.82 (95% CI = 0.71-0.95, P = 0.008) the odds of being adherent. Compared with areas with fewer jobs per resident, patients living within a zip code with 0.16 to 0.26 jobs per resident were 1.12 (95% CI = 1.04-1.20, P = 0.002) times more likely to be adherent. Patients who lived in an urban cluster were 1.11 (95% CI = 1.01-1.22, P = 0.037) times more likely to be adherent than patients living in a rural area. Patients who travel at least 25 miles to their prescriber had 0.82 (95% CI = 0.77-0.86, P < 0.001) the odds of being adherent. Community pharmacy users had 0.65 (95% CI = 0.59-0.71, P < 0.001) the odds of being adherent compared with mail order pharmacy users. Patients who had a PCP were 1.26 (95% CI = 1.18-1.34, P < 0.001) times more likely to be adherent to their medication. CONCLUSIONS: Leveraging publicly available population data to create SDoH measures is an accessible option to overcome barriers to SDoH data collection. Derived measures can be used to increase equity in care received by identifying patients who could benefit from assistance with medication adherence.

Association of functional polymorphism rs2231142 (Q141K) in the ABCG2 gene with serum uric acid and gout in 4 US populations: the PAGE Study.

A loss-of-function mutation (Q141K, rs2231142) in the ATP-binding cassette, subfamily G, member 2 gene (ABCG2) has been shown to be associated with serum uric acid levels and gout in Asians, Europeans, and European and African Americans; however, less is known about these associations in other populations. Rs2231142 was genotyped in 22,734 European Americans, 9,720 African Americans, 3,849 Mexican Americans, and 3,550 American Indians in the Population Architecture using Genomics and Epidemiology (PAGE) Study (2008-2012). Rs2231142 was significantly associated with serum uric acid levels (P = 2.37 × 10(-67), P = 3.98 × 10(-5), P = 6.97 × 10(-9), and P = 5.33 × 10(-4) in European Americans, African Americans, Mexican Americans, and American Indians, respectively) and gout (P = 2.83 × 10(-10), P = 0.01, and P = 0.01 in European Americans, African Americans, and Mexican Americans, respectively). Overall, the T allele was associated with a 0.24-mg/dL increase in serum uric acid level (P = 1.37 × 10(-80)) and a 1.75-fold increase in the odds of gout (P = 1.09 × 10(-12)). The association between rs2231142 and serum uric acid was significantly stronger in men, postmenopausal women, and hormone therapy users compared with their counterparts. The association with gout was also significantly stronger in men than in women. These results highlight a possible role of sex hormones in the regulation of ABCG2 urate transporter and its potential implications for the prevention, diagnosis, and treatment of hyperuricemia and gout.

Post-genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study.

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.

No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population.

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.

Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record.

Large-scale DNA databanks linked to electronic medical record (EMR) systems have been proposed as an approach for rapidly generating large, diverse cohorts for discovery and replication of genotype-phenotype associations. However, the extent to which such resources are capable of delivering on this promise is unknown. We studied whether an EMR-linked DNA biorepository can be used to detect known genotype-phenotype associations for five diseases. Twenty-one SNPs previously implicated as common variants predisposing to atrial fibrillation, Crohn disease, multiple sclerosis, rheumatoid arthritis, or type 2 diabetes were successfully genotyped in 9483 samples accrued over 4 mo into BioVU, the Vanderbilt University Medical Center DNA biobank. Previously reported odds ratios (OR(PR)) ranged from 1.14 to 2.36. For each phenotype, natural language processing techniques and billing-code queries were used to identify cases (n = 70-698) and controls (n = 808-3818) from deidentified health records. Each of the 21 tests of association yielded point estimates in the expected direction. Previous genotype-phenotype associations were replicated (p < 0.05) in 8/14 cases when the OR(PR) was > 1.25, and in 0/7 with lower OR(PR). Statistically significant associations were detected in all analyses that were adequately powered. In each of the five diseases studied, at least one previously reported association was replicated. These data demonstrate that phenotypes representing clinical diagnoses can be extracted from EMR systems, and they support the use of DNA resources coupled to EMR systems as tools for rapid generation of large data sets required for replication of associations found in research cohorts and for discovery in genome science.

Lipid trait-associated genetic variation is associated with gallstone disease in the diverse Third National Health and Nutrition Examination Survey (NHANES III).

BACKGROUND: Gallstone disease is one of the most common digestive disorders, affecting more than 30 million Americans. Previous twin studies suggest a heritability of 25% for gallstone formation. To date, one genome-wide association study (GWAS) has been performed in a population of European-descent. Several candidate gene studies have been performed in various populations, but most have been inconclusive. Given that gallstones consist of up to 80% cholesterol, we hypothesized that common genetic variants associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) would also be associated with gallstone risk. METHODS: To test this hypothesis, the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study as part of the Population Architecture using Genomics and Epidemiology (PAGE) study performed tests of association between 49 GWAS-identified lipid trait SNPs and gallstone disease in non-Hispanic whites (446 cases and 1,962 controls), non-Hispanic blacks (179 cases and 1,540 controls), and Mexican Americans (227 cases and 1,478 controls) ascertained for the population-based Third National Health and Nutrition Examination Survey (NHANES III). RESULTS: At a liberal significance threshold of 0.05, five, four, and four SNP(s) were associated with disease risk in non-Hispanic whites, non-Hispanic blacks, and Mexican Americans, respectively. No one SNP was associated with gallstone disease risk in all three racial/ethnic groups. The most significant association was observed for ABCG5 rs6756629 in non-Hispanic whites [odds ratio (OR) = 1.89; 95% confidence interval (CI) = 1.44-2.49; p = 0.0001). ABCG5 rs6756629 is in strong linkage disequilibrium with rs11887534 (D19H), a variant previously associated with gallstone disease risk in populations of European-descent. CONCLUSIONS: We replicated a previously associated variant for gallstone disease risk in non-Hispanic whites. Further discovery and fine-mapping efforts in diverse populations are needed to fully describe the genetic architecture of gallstone disease risk in humans.

Genetic variation in recipient B-cell activating factor modulates phenotype of GVHD.

B-cell activating factor (BAFF) single nucleotide polymorphisms (SNPs) are associated with autoimmune diseases. Because patients with classic and overlap chronic GVHD (cGVHD) have features of autoimmune diseases, we studied the association of recipient and/or donor BAFF SNPs with the phenotype of GVHD after allogeneic stem cell transplantation. Twenty tagSNPs of the BAFF gene were genotyped in 164 recipient/donor pairs. GVHD after day 100 occurred in 124 (76%) patients: acute GVHD (aGVHD) subtypes (n = 23), overlap GVHD (n = 29), and classic cGVHD (n = 72). In SNP analyses, 9 of the 20 tag SNPs were significant comparing classic/overlap cGVHD versus aGVHD subtypes/no GVHD. In multivariate analyses, 4 recipient BAFF SNPs (rs16972217 [odds ratio = 2.72, P = .004], rs7993590 [odds ratio = 2.35, P = .011], rs12428930 [odds ratio2.53, P = .008], and rs2893321 [odds ratio = 2.48, P = .009]) were independent predictors of GVHD subtypes, adjusted for conventional predictors of cGVHD. This study shows that genetic variation of BAFF modulates GVHD phenotype after allogeneic stem cell transplantation.

Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study.

BACKGROUND: High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study. RESULTS: A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses. CONCLUSIONS: We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.

Genetic variation in donor CTLA-4 regulatory region is a strong predictor of outcome after allogeneic hematopoietic cell transplantation for hematologic malignancies.

Relapse remains a major cause of death after allogeneic hematopoietic cell transplantation (allo-HCT). Graft-versus-tumor effect is primarily mediated by donor T cells. Cytotoxic T lymphocyte antigen-4 (CTLA-4) is a critical inhibitor of T cell proliferation. Single nucleotide polymorphisms (SNPs) in CTLA-4 may affect immune responses. We hypothesized that CTLA-4 SNPs will be associated with disease control after allo-HCT. One hundred sixty-four adult patients with the availability of pretransplantation recipient and donor DNA samples were included in this analysis. Ten tagSNPs of the CTLA-4 gene were identified. Donor CTLA-4 SNP rs4553808 was associated with decreased relapse-free survival (RFS) (P = .019) and overall survival (OS) (P = .033). In multivariable analysis of an additive genetic model, genotype of CTLA-4 SNP rs4553808 was an independent risk factor for inferior RFS (hazard ratio [HR] = 1.73, 95% confidence interval [CI] 1.10-2.71, P = .017) and OS (HR = 1.84, 95% CI 1.13-3.0, P = .015). CTLA-4 SNPs can be used to identify high-risk patient subsets that may benefit from preemptive immunomodulation to decrease relapse rates and improve survival.

Serum vitamins A and E as modifiers of lipid trait genetics in the National Health and Nutrition Examination Surveys as part of the Population Architecture using Genomics and Epidemiology (PAGE) study.

Both environmental and genetic factors impact lipid traits. Environmental modifiers of known genotype-phenotype associations may account for some of the "missing heritability" of these traits. To identify such modifiers, we genotyped 23 lipid-associated variants identified previously through genome-wide association studies (GWAS) in 2,435 non-Hispanic white, 1,407 non-Hispanic black, and 1,734 Mexican-American samples collected for the National Health and Nutrition Examination Surveys (NHANES). Along with lipid levels, NHANES collected environmental variables, including fat-soluble macronutrient serum levels of vitamin A and E levels. As part of the Population Architecture using Genomics and Epidemiology (PAGE) study, we modeled gene-environment interactions between vitamin A or vitamin E and 23 variants previously associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. We identified three SNP × vitamin A and six SNP × vitamin E interactions at a significance threshold of p < 2.2 × 10(-3). The most significant interaction was APOB rs693 × vitamin E (p = 8.9 × 10(-7)) for LDL-C levels among Mexican-Americans. The nine significant interaction models individually explained 0.35-1.61% of the variation in any one of the lipid traits. Our results suggest that vitamins A and E may modify known genotype-phenotype associations; however, these interactions account for only a fraction of the overall variability observed for HDL-C, LDL-C, and TG levels in the general population.

Evidence for age as a modifier of genetic associations for lipid levels.

In order to identify novel genetic variants that influence plasma lipid concentrations, we performed a genome-wide association study (GWAS) comprised of 411 children under 18 years of age, ascertained at St. Jude Children's Research Hospital, all of whom were of European, African, or Mexican descent. Promising associations (p < 10(-5)) were subsequently examined in 1040 additional youths and 3508 adults from the Third National Health and Nutrition Examination Survey (NHANES III), a diverse population-based study. Three genotype-phenotype associations replicated in NHANES III youths and three associated in NHANES III adults at p < 0.05; however, no single association was significant in both youths and adults. The most significant association (p= 0.009) in NHANES III youths was between low-density lipoprotein cholesterol (LDL-C) and intronic rs2429917 among participants of African descent. Given the known age dependency of lipid levels, we also tested for gene-age interactions in NHANES III participants across all ages. We identified a significant (p= 0.024) age-dependent association between SGSM2 rs2429917 and LDL-C. This finding illustrates the utility of using children to discover novel variants associated with complex phenotypes and the importance of considering age-dependent genetic effects in association studies of lipid levels.

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

MOTIVATION: Emergence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility of phenome-wide association scans (PheWAS) for disease-gene associations. We propose a novel method to scan phenomic data for genetic associations using International Classification of Disease (ICD9) billing codes, which are available in most EMR systems. We have developed a code translation table to automatically define 776 different disease populations and their controls using prevalent ICD9 codes derived from EMR data. As a proof of concept of this algorithm, we genotyped the first 6005 European-Americans accrued into BioVU, Vanderbilt's DNA biobank, at five single nucleotide polymorphisms (SNPs) with previously reported disease associations: atrial fibrillation, Crohn's disease, carotid artery stenosis, coronary artery disease, multiple sclerosis, systemic lupus erythematosus and rheumatoid arthritis. The PheWAS software generated cases and control populations across all ICD9 code groups for each of these five SNPs, and disease-SNP associations were analyzed. The primary outcome of this study was replication of seven previously known SNP-disease associations for these SNPs. RESULTS: Four of seven known SNP-disease associations using the PheWAS algorithm were replicated with P-values between 2.8 x 10(-6) and 0.011. The PheWAS algorithm also identified 19 previously unknown statistical associations between these SNPs and diseases at P < 0.01. This study indicates that PheWAS analysis is a feasible method to investigate SNP-disease associations. Further evaluation is needed to determine the validity of these associations and the appropriate statistical thresholds for clinical significance. AVAILABILITY: The PheWAS software and code translation table are freely available at http://knowledgemap.mc.vanderbilt.edu/research.

Assessing the accuracy of observer-reported ancestry in a biorepository linked to electronic medical records.

PURPOSE: The Vanderbilt DNA Databank (BioVU) is a biorepository that currently contains >80,000 DNA samples linked to electronic medical records. Although BioVU is a valuable source of samples and phenotypes for genetic association studies, it is unclear whether the administratively assigned race/ethnicity in BioVU can accurately describe and be used as a proxy for genetic ancestry. METHODS: We genotyped 360 single nucleotide polymorphisms on the Illumina DNA Test Panel containing ancestry informative markers in 1910 BioVU samples with observer-reported ancestry and 384 samples from the Multiple Sclerosis Genetics Group with self-reported ancestry. Genetic ancestry was inferred for all individuals using Structure 2.2. RESULTS: More than 98% of observer-reported European Americans were genetically inferred to have at least 60% European ancestry. Ninety-three percent of observer-reported African Americans were genetically inferred to be predominantly of African ancestry. We determined that the concordance of observer-reported race/ethnicity and inferred genetic ancestry was not significantly different from that of self-reported race/ethnicity in either population (P = 0.09 and 0.94 in European Americans and African Americans, respectively). CONCLUSIONS: Observer-reported race/ethnicity for European Americans and African Americans approximates genetic ancestry as well as self-reported race/ethnicity, making biorepositories linked to electronic medical records such as BioVU a viable source of DNA samples for future large-scale genetic association studies.

KIDNEY DISEASE GENETICS AND THE IMPORTANCE OF DIVERSITY IN PRECISION MEDICINE.

Kidney disease is a well-known health disparity in the United States where African Americans are affected at higher rates compared with other groups such as European Americans and Mexican Americans. Common genetic variants in the myosin, heavy chain 9, non-muscle (MYH9) gene were initially identified as associated with non-diabetic end-stage renal disease in African Americans, and it is now understood that these variants are in strong linkage disequilibrium with likely causal variants in neighboring APOL1. Subsequent genome-wide and candidate gene studies have suggested that MYH9 common variants among others are also associated with chronic kidney disease and quantitative measures of kidney function in various populations. In a precision medicine setting, it is important to consider genetic effects or genetic associations that differ across racial/ethnic groups in delivering data relevant to disease risk or individual-level patient assessment. Kidney disease and quantitative trait-associated genetic variants have yet to be systematically characterized in multiple racial/ethnic groups. Therefore, to further characterize the prevalence of these genetic variants and their association with kidney related traits, we have genotyped 10 kidney disease or quantitative trait-associated single nucleotide polymorphisms (SNPs) (rs2900976, rs10505955, rs10502868, rs1243400, rs9305354, rs12917707, rs17319721, rs2467853, rs2032487, and rs4821480) in 14,998 participants from the population-based cross-sectional National Health and Nutrition Examination Surveys (NHANES) III and 1999-2002 as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study. In this general adult population ascertained regardless of health status (6,293 non-Hispanic whites, 3,013 non-Hispanic blacks, and 3,542 Mexican Americans), we observed higher rates of chronic kidney disease among non-Hispanic blacks compared with the other groups as expected. We performed single SNP tests of association using linear regressions assuming an additive genetic model adjusted for age, sex, diastolic blood pressure, systolic blood pressure, and type 2 diabetes status for several outcomes including creatinine (urinary), creatinine (serum), albumin (urinary), eGFR, and albumin-to-urinary creatinine ratio (ACR). We also tested for associations between each SNP and chronic kidney disease and albuminuria using logistic regression. Surprisingly, none of the MYH9 variants tested was associated with kidney diseases or traits in non-Hispanic blacks (p>0.05), perhaps attributable to the clinical heterogeneity of kidney disease in this population. Several associations were observed in each racial/ethnic group at p<0.05, but none were consistently associated in the same direction in all three groups. The lack of significant and consistent associations is most likely due to power highlighting the importance of the availability of large, diverse populations for genetic association studies of complex diseases and traits to inform precision medicine efforts in diverse patient populations.

Population Stratification in the Context of Diverse Epidemiologic Surveys Sans Genome-Wide Data.

Population stratification or confounding by genetic ancestry is a potential cause of false associations in genetic association studies. Estimation of and adjustment for genetic ancestry has become common practice thanks in part to the availability of ancestry informative markers on genome-wide association study (GWAS) arrays. While array data is now widespread, these data are not ubiquitous as several large epidemiologic and clinic-based studies lack genome-wide data. One such large epidemiologic-based study lacking genome-wide data accessible to investigators is the National Health and Nutrition Examination Surveys (NHANES), population-based cross-sectional surveys of Americans linked to demographic, health, and lifestyle data conducted by the Centers for Disease Control and Prevention. DNA samples (n = 14,998) were extracted from biospecimens from consented NHANES participants between 1991-1994 (NHANES III, phase 2) and 1999-2002 and represent three major self-identified racial/ethnic groups: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We as the Epidemiologic Architecture for Genes Linked to Environment study genotyped candidate gene and GWAS-identified index variants in NHANES as part of the larger Population Architecture using Genomics and Epidemiology I study for collaborative genetic association studies. To enable basic quality control such as estimation of genetic ancestry to control for population stratification in NHANES san genome-wide data, we outline here strategies that use limited genetic data to identify the markers optimal for characterizing genetic ancestry. From among 411 and 295 autosomal SNPs available in NHANES III and NHANES 1999-2002, we demonstrate that markers with ancestry information can be identified to estimate global ancestry. Despite limited resolution, global genetic ancestry is highly correlated with self-identified race for the majority of participants, although less so for ethnicity. Overall, the strategies outlined here for a large epidemiologic study can be applied to other datasets accessible for genotype-phenotype studies but are sans genome-wide data.