Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry

Assessment of multi-population polygenic risk scores for lipid traits in African Americans

Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRS_LDL-Cwas nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available.

A phenome-wide association study (PheWAS) in the Population Architecture using Genomics and Epidemiology (PAGE) study reveals potential pleiotropy in African Americans

We performed a hypothesis-generating phenome-wide association study (PheWAS) to identify and characterize cross-phenotype associations, where one SNP is associated with two or more phenotypes, between thousands of genetic variants assayed on the Metabochip and hundreds of phenotypes in 5,897 African Americans as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study. The PAGE I study was a National Human Genome Research Institute-funded collaboration of four study sites accessing diverse epidemiologic studies genotyped on the Metabochip, a custom genotyping chip that has dense coverage of regions in the genome previously associated with cardio-metabolic traits and outcomes in mostly European-descent populations. Here we focus on identifying novel phenome-genome relationships, where SNPs are associated with more than one phenotype. To do this, we performed a PheWAS, testing each SNP on the Metabochip for an association with up to 273 phenotypes in the participating PAGE I study sites. We identified 133 putative pleiotropic variants, defined as SNPs associated at an empirically derived p-value threshold of p<0.01 in two or more PAGE study sites for two or more phenotype classes. We further annotated these PheWAS-identified variants using publicly available functional data and local genetic ancestry. Amongst our novel findings is SPARC rs4958487, associated with increased glucose levels and hypertension. SPARC has been implicated in the pathogenesis of diabetes and is also known to have a potential role in fibrosis, a common consequence of multiple conditions including hypertension. The SPARC example and others highlight the potential that PheWAS approaches have in improving our understanding of complex disease architecture by identifying novel relationships between genetic variants and an array of common human phenotypes.

A Social Determinant of Health May Modify Genetic Associations for Blood Pressure: Evidence From a SNP by Education Interaction in an African American Population

African Americans experience the highest burden of hypertension in the United States compared with other groups. Genetic contributions to this complex condition are now emerging in this as well as other populations through large-scale genome-wide association studies (GWAS) and meta-analyses. Despite these recent discovery efforts, relatively few large-scale studies of blood pressure have considered the joint influence of genetics and social determinants of health despite extensive evidence supporting their impact on hypertension. To identify these expected interactions, we accessed a subset of the Vanderbilt University Medical Center (VUMC) biorepository linked to de-identified electronic health records (EHRs) of adult African Americans genotyped using the Illumina Metabochip (n = 2,577). To examine potential interactions between education, a recognized social determinant of health, and genetic variants contributing to blood pressure, we used linear regression models to investigate two-way interactions for systolic and diastolic blood pressure (DBP). We identified a two-way interaction between rs6687976 and education affecting DBP (p = 0.052). Individuals homozygous for the minor allele and having less than a high school education had higher DBP compared with (1) individuals homozygous for the minor allele and high school education or greater and (2) individuals not homozygous for the minor allele and less than a high school education. To our knowledge, this is the first EHR -based study to suggest a gene-environment interaction for blood pressure in African Americans, supporting the hypothesis that genetic contributions to hypertension may be modulated by social factors.

Racial Disparities in Lung Cancer Survival: The Contribution of Stage, Treatment, and Ancestry

INTRODUCTION

Lung cancer is a leading cause of cancer-related death worldwide. Racial disparities in lung cancer survival exist between blacks and whites, yet they are limited by categorical definitions of race. We sought to examine the impact of African ancestry on overall survival among blacks and whites with NSCLC cases.

METHODS

Incident cases of NSCLC in blacks and whites from the prospective Southern Community Cohort Study (N = 425) were identified through linkage with state cancer registries in 12 southern states. Vital status was determined by linkage with the National Death Index and Social Security Administration. We evaluated the impact of African ancestry (as estimated by using genome-wide ancestry-informative markers) on overall survival by calculating the time-dependent area under the curve (AUC) for Cox proportional hazards models, adjusting for relevant covariates such as stage and treatment. We replicated our findings in an independent population of NSCLC cases in blacks.

RESULTS

Global African ancestry was not significantly associated with overall survival among NSCLC cases. There was no change in model performance when Cox proportional hazards models with and without African ancestry were compared (AUC = 0.79 for each model). Removal of stage and treatment reduced the average time-dependent AUC from 0.79 to 0.65. Similar findings were observed in our replication study.

CONCLUSIONS

Stage and treatment are more important predictors of survival than African ancestry is. These findings suggest that racial disparities in lung cancer survival may disappear with similar early detection efforts for blacks and whites.

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.

Unravelling the human genome-phenome relationship using phenome-wide association studies

Advances in genotyping technology have, over the past decade, enabled the focused search for common genetic variation associated with human diseases and traits. With the recently increased availability of detailed phenotypic data from electronic health records and epidemiological studies, the impact of one or more genetic variants on the phenome is starting to be characterized both in clinical and population-based settings using phenome-wide association studies (PheWAS). These studies reveal a number of challenges that will need to be overcome to unlock the full potential of PheWAS for the characterization of the complex human genome-phenome relationship.

Socioeconomic Position, But Not African Genomic Ancestry, Is Associated With Blood Pressure in the Bambui-Epigen (Brazil) Cohort Study of Aging

The study objective is to examine the role of African genome origin on baseline and 11-year blood pressure trajectories in community-based ethnoracially admixed older adults in Brazil. Data come from 1272 participants (aged ≥60 years) of the Bambui cohort study of aging during 11 years of follow-up. Outcome measures were systolic blood pressure, diastolic blood pressure, and hypertension control. Potential confounding variables were demographic characteristics, socioeconomic position (schooling and household income), and health indicators (smoking, sedentary lifestyle, high-density lipoprotein cholesterol, waist circumference, diabetes mellitus, and cardiovascular diseases), including antihypertensive drug use. We used 370 539 single-nucleotide polymorphisms to estimate each individual's African, European, and Native American trihybrid ancestry proportions. Median African, European, and Native American ancestry were 9.6%, 84.0%, and 5.3%, respectively. Among those with African ancestry, 59.4% came from East and 40.6% from West Africa. Baseline systolic and diastolic blood pressure, controlled hypertension, and their respective trajectories, were not significantly (P>0.05) associated with level (in quintiles) of African genomic ancestry. Similar results were found for West and East African subcontinental origins. Lower schooling level (<4 years versus higher) showed a significant and positive association with systolic blood pressure (Adjusted β=2.92; 95% confidence interval, 0.85-4.99). Lower monthly household income per capita (<USD 180.00 versus higher) showed an inverse association with hypertension control (β=-0.35; 95% confidence interval, -0.63 to -0.08, respectively). Our results support the view that favors social and environmental factors as determinants of blood pressure and hypertension control.

Phenome-Wide Association Studies: Embracing Complexity for Discovery

The inherent complexity of biological systems can be leveraged for a greater understanding of the impact of genetic architecture on outcomes, traits, and pharmacological response. The genome-wide association study (GWAS) approach has well-developed methods and relatively straight-forward methodologies; however, the bigger picture of the impact of genetic architecture on phenotypic outcome still remains to be elucidated even with an ever-growing number of GWAS performed. Greater consideration of the complexity of biological processes, using more data from the phenome, exposome, and diverse -omic resources, including considering the interplay of pleiotropy and genetic interactions, may provide additional leverage for making the most of the incredible wealth of information available for study. Here, we describe how incorporating greater complexity into analyses through the use of additional phenotypic data and widespread deployment of phenome-wide association studies may provide new insights into genetic factors influencing diseases, traits, and pharmacological response.