PRS Center for Admixed Populations and Health Equity (CAPE)
Project Number5U01HG011715-04
Contact PI/Project LeaderPASANIUC, BOGDAN Other PIs
Awardee OrganizationUNIVERSITY OF CALIFORNIA LOS ANGELES
Description
Abstract Text
Project Summary/Abstract
Polygenic risk scores (PRS), that aggregate risk across common variants in the genome, have emerged as a
powerful tool towards implementing genomic medicine. Unfortunately, the vast majority of genomic data from
which current PRS are estimated is coming from European ancestry individuals thus prohibiting the
implementation of PRS for non-European individuals. To address this gap, multiple large-scale genomic
studies are currently performed in non-European individuals. Of particular interest are individuals with recent
ancestry from multiple continental sources such as African Americans and/or Hispanic Americans whose
genomes are a mosaic of segments of various ancestries. Such diversity in genetic ancestry raises unique
challenges in the equitable PRS development as the accuracy and bias of existing PRS varies across genomic
ancestries. Unlike existing paradigm that largely views genetic ancestry as a confounder in PRS studies, we
aim to fully integrate population genetics of the admixture process to yield admixture-PRS that provide
equitable accuracies for all individuals irrespective of genetic ancestries. We will integrate data of over 230,000
admixed individuals across five diverse medical systems including UCLA, Mt Sinai, Colorado to develop,
calibrate and benchmark PRS for admixed individuals.
Public Health Relevance Statement
PROJECT NARRATIVE
Although genetic studies of complex human traits have been tremendously successful in identifying thousands
of genomic risk regions that harbor variants increasing risk, Unfortunately, the vast majority include individuals
of European ancestry making the transferability to individuals with mixed ancestries (e.g., African Americans)
challenging. In this proposal we develop and apply new statistical and experimental methods to build
admixture-aware polygenic risk scores for complex traits. We leverage a unique data set of >230,000 admixed
individuals whose genotypes are linked to electronic health records to develop and calibrate PRS in admixed
populations.
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