Genetic associations of protein-coding variants in human disease.
Authors
Kurki, Mitja I
Foley, Christopher N
Mechakra, Asma
Chen, Chia-Yen
Marshall, Eric
Wilk, Jemma B
Biogen Biobank Team
Chevalier, Philippe
FinnGen
Daly, Mark J
Publication Date
2022-03Journal Title
Nature
ISSN
0028-0836
Publisher
Springer Science and Business Media LLC
Volume
603
Issue
7899
Pages
95-102
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Sun, B. B., Kurki, M. I., Foley, C. N., Mechakra, A., Chen, C., Marshall, E., Wilk, J. B., et al. (2022). Genetic associations of protein-coding variants in human disease.. Nature, 603 (7899), 95-102. https://doi.org/10.1038/s41586-022-04394-w
Abstract
Genome-wide association studies (GWAS) have identified thousands of genetic variants linked to the risk of human disease. However, GWAS have so far remained largely underpowered in relation to identifying associations in the rare and low-frequency allelic spectrum and have lacked the resolution to trace causal mechanisms to underlying genes1. Here we combined whole-exome sequencing in 392,814 UK Biobank participants with imputed genotypes from 260,405 FinnGen participants (653,219 total individuals) to conduct association meta-analyses for 744 disease endpoints across the protein-coding allelic frequency spectrum, bridging the gap between common and rare variant studies. We identified 975 associations, with more than one-third being previously unreported. We demonstrate population-level relevance for mutations previously ascribed to causing single-gene disorders, map GWAS associations to likely causal genes, explain disease mechanisms, and systematically relate disease associations to levels of 117 biomarkers and clinical-stage drug targets. Combining sequencing and genotyping in two population biobanks enabled us to benefit from increased power to detect and explain disease associations, validate findings through replication and propose medical actionability for rare genetic variants. Our study provides a compendium of protein-coding variant associations for future insights into disease biology and drug discovery.
Keywords
Article, /631/208/205, /631/208/457/649, /692/699, /631/208/727/2000, /45/43, article
Identifiers
s41586-022-04394-w, 4394
External DOI: https://doi.org/10.1038/s41586-022-04394-w
This record's URL: https://www.repository.cam.ac.uk/handle/1810/334593
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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