Contextualizing genetic risk score for disease screening and rare variant discovery

Dan Zhou, Dongmei Yu, Jeremiah M. Scharf, Carol A. Mathews, Lauren McGrath, Edwin Cook, S. Hong Lee, Lea K. Davis () and Eric R. Gamazon ()
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Dan Zhou: Vanderbilt University Medical Center
Dongmei Yu: Massachusetts General Hospital
Jeremiah M. Scharf: Massachusetts General Hospital
Carol A. Mathews: University of Florida
Lauren McGrath: University of Denver
Edwin Cook: University of Illinois at Chicago
S. Hong Lee: University of South Australia
Lea K. Davis: Vanderbilt University Medical Center
Eric R. Gamazon: Vanderbilt University Medical Center

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract Studies of the genetic basis of complex traits have demonstrated a substantial role for common, small-effect variant polygenic burden (PB) as well as large-effect variants (LEV, primarily rare). We identify sufficient conditions in which GWAS-derived PB may be used for well-powered rare pathogenic variant discovery or as a sample prioritization tool for whole-genome or exome sequencing. Through extensive simulations of genetic architectures and generative models of disease liability with parameters informed by empirical data, we quantify the power to detect, among cases, a lower PB in LEV carriers than in non-carriers. Furthermore, we uncover clinically useful conditions wherein the risk derived from the PB is comparable to the LEV-derived risk. The resulting summary-statistics-based methodology (with publicly available software, PB-LEV-SCAN) makes predictions on PB-based LEV screening for 36 complex traits, which we confirm in several disease datasets with available LEV information in the UK Biobank, with important implications on clinical decision-making.

Date: 2021
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DOI: 10.1038/s41467-021-24387-z

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