Exome sequencing and analysis of 454,787 UK Biobank participants

Joshua D. Backman, Alexander H. Li, Anthony Marcketta, Dylan Sun, Joelle Mbatchou, Michael D. Kessler, Christian Benner, Daren Liu, Adam E. Locke, Suganthi Balasubramanian, Ashish Yadav, Nilanjana Banerjee, Christopher E. Gillies, Amy Damask, Simon Liu, Xiaodong Bai, Alicia Hawes, Evan Maxwell, Lauren Gurski, Kyoko Watanabe, Jack A. Kosmicki, Veera Rajagopal, Jason Mighty, Marcus Jones, Lyndon Mitnaul, Eli Stahl, Giovanni Coppola, Eric Jorgenson, Lukas Habegger, William J. Salerno, Alan R. Shuldiner, Luca A. Lotta, John D. Overton, Michael N. Cantor, Jeffrey G. Reid, George Yancopoulos, Hyun M. Kang, Jonathan Marchini, Aris Baras, Gonçalo R. Abecasis () and Manuel A. R. Ferreira ()
Additional contact information
Joshua D. Backman: Regeneron Genetics Center
Alexander H. Li: Regeneron Genetics Center
Anthony Marcketta: Regeneron Genetics Center
Dylan Sun: Regeneron Genetics Center
Joelle Mbatchou: Regeneron Genetics Center
Michael D. Kessler: Regeneron Genetics Center
Christian Benner: Regeneron Genetics Center
Daren Liu: Regeneron Genetics Center
Adam E. Locke: Regeneron Genetics Center
Suganthi Balasubramanian: Regeneron Genetics Center
Ashish Yadav: Regeneron Genetics Center
Nilanjana Banerjee: Regeneron Genetics Center
Christopher E. Gillies: Regeneron Genetics Center
Amy Damask: Regeneron Genetics Center
Simon Liu: Regeneron Genetics Center
Xiaodong Bai: Regeneron Genetics Center
Alicia Hawes: Regeneron Genetics Center
Evan Maxwell: Regeneron Genetics Center
Lauren Gurski: Regeneron Genetics Center
Kyoko Watanabe: Regeneron Genetics Center
Jack A. Kosmicki: Regeneron Genetics Center
Veera Rajagopal: Regeneron Genetics Center
Jason Mighty: Regeneron Genetics Center
Marcus Jones: Regeneron Genetics Center
Lyndon Mitnaul: Regeneron Genetics Center
Eli Stahl: Regeneron Genetics Center
Giovanni Coppola: Regeneron Genetics Center
Eric Jorgenson: Regeneron Genetics Center
Lukas Habegger: Regeneron Genetics Center
William J. Salerno: Regeneron Genetics Center
Alan R. Shuldiner: Regeneron Genetics Center
Luca A. Lotta: Regeneron Genetics Center
John D. Overton: Regeneron Genetics Center
Michael N. Cantor: Regeneron Genetics Center
Jeffrey G. Reid: Regeneron Genetics Center
George Yancopoulos: Regeneron Genetics Center
Hyun M. Kang: Regeneron Genetics Center
Jonathan Marchini: Regeneron Genetics Center
Aris Baras: Regeneron Genetics Center
Gonçalo R. Abecasis: Regeneron Genetics Center
Manuel A. R. Ferreira: Regeneron Genetics Center

Nature, 2021, vol. 599, issue 7886, 628-634

Abstract: Abstract A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing1 to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study2. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P ≤ 2.18 × 10−11. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene–trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.

Date: 2021
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DOI: 10.1038/s41586-021-04103-z

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