Genetic ancestry effects on molecular and complex traits in TOPMed

University Of California, San Francisco, San Francisco CA

Investigators

Abstract

ABSTRACT: The Trans-Omics for Precision Medicine (TOPMed) project has reached a critical size threshold. Freeze 10 of the TOPMed cohort now includes n=180,852 individuals with high coverage WGS, with over 1.074 BILLION variants characterized. Beyond genomic data, TOPMed also includes n=73,294 individuals with RNA-seq gene expression data, n=92,659 individuals with metabolomic data, n=85,684 individuals with methylation data, and n=43,057 individuals with proteomic data. These ‘omics phenotypes enable rich characterization of the multiple dimensions of biology that are relevant for human disease. Importantly, 60% of individuals identify as non-White with n>51k of individuals identifying as Black/African American, n>34k identifying as Hispanic/Latino, and span multiple HLBS phenotypes. We will utilize the TOPMed project data to address two pressing questions. First, how do race, ethnicity, and genetic ancestry contribute to complex traits across the continuum of human populations in the US? Second, how do alleles at different frequencies in different genetic ancestry groups contribute to complex traits? This project will leverage data from whole genome sequencing (WGS), RNAseq expression, metabolomics, and a bevy of heart, lung, blood, and sleep disorders to make headway understanding how to keep the continuum of human populations at the forefront of precision medicine.