# Characterizing pleiotropy in cardiometabolic phenotypes among diverse populations

> **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2020 · $646,762

## Abstract

ABSTRACT
Genetic susceptibility underlies a majority of cardiovascular diseases (CVD) and their antecedents, underscored
by genome-wide association studies (GWAS) that identified >1,500 loci to-date. Each GWAS-identified locus
potentially provides novel mechanistic insight, yet translation of study findings remains largely incomplete,
representing a critical barrier to progress. Pleiotropy, a variant that affects multiple phenotypes, is a long-
described and pervasive, but largely uncharacterized avenue to advance genomic medicine. Specifically, studies
of pleiotropy have the potential to clarify molecular functions, identify mechanistic “common denominators",
inform diagnosis and treatment, and prioritize variants for functional interrogation. Systematic and
comprehensive interrogation of pleiotropy is particularly relevant for CVD phenotypes, as decades of human and
animal studies support a shared genetic architecture that collectively affects downstream clinical disease. Yet,
few studies have comprehensively and systematically evaluated pleiotropy within or across cardiovascular
phenotypes or extended investigations to examine how pleiotropic variants affect clinical disease. Further, many
CVDs and their antecedents disproportionately affect African Americans (AA) and Hispanic/Latinos (HL).
However, the majority (>80%) of participants included in GWAS to-date are of European (EU) ancestry. This
research disparity creates a biased view of human variation, fails to leverage the unique genetic architecture of
AAs and HLs for fine-mapping, and hinders translation of genetic findings into clinical and public health
applications relevant for broad populations. We respond to these gaps by leveraging high-quality, harmonized,
and centrally available phenotype and genotype data from the Population Architecture Using Genomics in
Epidemiology (PAGE) consortium and the Reasons for Geographic and Racial Differences in Stroke
(REGARDS) study (n=100,917; 35% AA; 32% EU; 24% HL) as well as cutting edge statistical methods to
comprehensively identify loci with potential evidence of pleiotropy within and across blood pressure, cholesterol,
cardiac conduction, glycemic, inflammatory, and obesity cardiovascular domains as well as incident MI and
stroke (Aim 1). At known and novel loci with strong evidence of potential pleiotropy, we will leverage population
structure, haplotypic architecture, and phenotype correlation through multi-ethnic, multi-phenotype fine-mapping
to prioritize variants for further interrogation (Aim 2). Finally, we will leverage longitudinal data and pathway
models to disaggregate variants displaying evidence of biological pleiotropy (i.e. variant affects multiple
phenotypes due to shared biology) from variants displaying evidence of mediated pleiotropy (e.g. variant
influences one phenotype and this phenotype influences a second phenotype) (Aim 3). We hypothesize that
CVD phenotypes and clinical disease may be more accurately characterized ...

## Key facts

- **NIH application ID:** 9869037
- **Project number:** 5R01HL142825-02
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Christy Leigh Avery
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $646,762
- **Award type:** 5
- **Project period:** 2019-02-10 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9869037

## Citation

> US National Institutes of Health, RePORTER application 9869037, Characterizing pleiotropy in cardiometabolic phenotypes among diverse populations (5R01HL142825-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9869037. Licensed CC0.

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