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Contextualizing genetic risk score for disease screening and rare variant discovery

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Yu, Dongmei 
Scharf, Jeremiah M. 
Mathews, Carol A. 
McGrath, Lauren 


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.


Funder: U.S. Department of Health & Human Services | National Institutes of Health (NIH)


Article, /631/114/2397, /631/208/205/2138, /631/208/457/649/2219, /45, /45/43, article

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Nature Communications

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Nature Publishing Group UK
U.S. Department of Health & Human Services | National Institutes of Health (NIH) (R35HG010718, R01HG011138, R01GM140287)