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Principal Investigator: Genevieve Lianne Wojcik
Organization: JOHNS HOPKINS UNIVERSITY
Fiscal Year: 2024
Award: $466,437
Funding agency: National Human Genome Research Institute
PROJECT SUMMARY
The majority of genomics research is conducted in populations of European descent, leaving other
groups behind as we rapidly move from genetic discovery to clinical translation, exacerbating existing
health inequities. The transferability of findings is further complicated in admixed populations, those with
recent ancestry from two or more continents, in that there is substantial genetic heterogeneity both
between and within groups. It is therefore necessary to understand these biases in a comprehensive
manner across multiple ancestries, study designs, and traits, to better inform future methodological
developments and biomedical research frameworks. The research program I propose in this
application would use existing individual-level genetic data and published summary statistics to
disentangle the relative contributions of genetics and environment to human health in admixed
populations. This multi-factorial proposal seeks to (1) quantify bias due to admixture on a global and
local ancestry level and (2) deconvolute the interaction between genetic ancestry and environmental
variables when estimating genetic effect sizes. These investigations will occur on both a variant-level and
genome-wide with polygenic risk scores (PRS). Variant-level analyses, such as genome-wide association
studies (GWAS), seek to pinpoint genes and regulatory mechanisms that underlie a particular trait. To
identify biological targets, it is necessary to determine if a lack of transferability is due to population
genetics (allele frequencies, linkage disequilibrium) or ancestry-specific gene-by-environment
interactions. PRS sum effects across the genome to estimate the genetic liability of a trait and stratify
individuals by risk. By expanding their scope, PRS often capture the off-target study characteristics,
whether by confounding or true pleiotropy, in turn limiting the portability between populations. These
relationships, both on a variant- and genome-wide level, are further complicated in admixed populations,
with ancestry patterns being correlated with the trait, genetic variants of interest, and the prevalence of
non-genetic variables. The proposed research program will examine these dynamics using both global
admixture proportions and local ancestry haplotypes from individual-level data in well-characterized
cohorts, disentangling of genetic and non-genetic factors in a precise manner, and providing a
comprehensive catalog of ancestry-trait considerations and an admixture-aware framework for the
evaluation of variant- (GWAS) and genome-wide (PRS) genetic effect estimates to the wider research
community. By systematically exploring these relationships, we will better inform future method
development and risk assessment frameworks in parallel with on-going consortia efforts to
increase diverse representation in genomic studies, setting up the next generation of genomic
research to address existing health inequities.
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