Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes

Konrad J. Karczewski(Broad Institute), Matthew Solomonson(Broad Institute), Katherine R. Chao(Broad Institute), Julia K. Goodrich(Broad Institute), Grace Tiao(Broad Institute), Wenhan Lu(Broad Institute), Bridget Riley‐Gillis(AbbVie (United States)), Ellen Tsai(Biogen (United States)), Hye In Kim(Pfizer (United States)), Xiuwen Zheng(AbbVie (United States)), Fedik Rahimov(AbbVie (United States)), Sahar Esmaeeli(AbbVie (United States)), A. Jason Grundstad(AbbVie (United States)), Mark Reppell(AbbVie (United States)), Jeff Waring(AbbVie (United States)), Howard J. Jacob(AbbVie (United States)), David Sexton(Biogen (United States)), Paola G. Bronson(Biogen (United States)), Xing Chen(Pfizer (United States)), Xinli Hu(Pfizer (United States)), Jacqueline I. Goldstein(Broad Institute), Daniel King(Broad Institute), Christopher Vittal(Broad Institute), Timothy Poterba(Broad Institute), Duncan S. Palmer(Broad Institute), Claire Churchhouse(Broad Institute), Daniel P. Howrigan(Broad Institute), Wei Zhou(Broad Institute), Nicholas A. Watts(Broad Institute), Kevin Nguyen(Broad Institute), Huy Nguyen(Broad Institute), Cara Mason(Broad Institute), Christopher Farnham(Broad Institute), Charlotte Tolonen(Broad Institute), Laura D. Gauthier(Broad Institute), Namrata Gupta(Broad Institute), Daniel G. MacArthur(Broad Institute), Heidi L. Rehm(Broad Institute), Cotton Seed(Broad Institute), Anthony Philippakis(Broad Institute), Mark J. Daly(Broad Institute), J. Wade Davis(AbbVie (United States)), Heiko Runz(Biogen (United States)), Melissa Miller(Pfizer (United States)), Benjamin M. Neale(Broad Institute)
Cell Genomics
August 15, 2022
Cited by 291Open Access
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Abstract

Genome-wide association studies have successfully discovered thousands of common variants associated with human diseases and traits, but the landscape of rare variations in human disease has not been explored at scale. Exome-sequencing studies of population biobanks provide an opportunity to systematically evaluate the impact of rare coding variations across a wide range of phenotypes to discover genes and allelic series relevant to human health and disease. Here, we present results from systematic association analyses of 4,529 phenotypes using single-variant and gene tests of 394,841 individuals in the UK Biobank with exome-sequence data. We find that the discovery of genetic associations is tightly linked to frequency and is correlated with metrics of deleteriousness and natural selection. We highlight biological findings elucidated by these data and release the dataset as a public resource alongside the Genebass browser for rapidly exploring rare-variant association results.


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