Abstract

Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens and environmental factors impacting specific sub-populations. Here, we propose a framework for repurposing data from electronic health records (EHRs) in concert with genomic data to explore the demographic ties that can impact disease burdens. Using data from a diverse biobank in New York City, we identified 17 communities sharing recent genetic ancestry. We observed 1,177 health outcomes that were statistically associated with a specific group and demonstrated significant differences in the segregation of genetic variants contributing to Mendelian diseases. We also demonstrated that fine-scale population structure can impact the prediction of complex …

Date

April 15, 2021

Authors

Gillian M Belbin, Sinead Cullina, Stephane Wenric, Emily R Soper, Benjamin S Glicksberg, Denis Torre, Arden Moscati, Genevieve L Wojcik, Ruhollah Shemirani, Noam D Beckmann, Ariella Cohain, Elena P Sorokin, Danny S Park, Jose-Luis Ambite, Steve Ellis, Adam Auton, Erwin P Bottinger, Judy H Cho, Ruth JF Loos, Noura S Abul-Husn, Noah A Zaitlen, Christopher R Gignoux, Eimear E Kenny

Journal

Cell

Volume

184

Issue

8

Pages

2068-2083. e11

Publisher

Elsevier