Discovery and systematic characterization of risk variants and genes for 1 coronary artery disease in over a million participants
View / Open Files
Authors
Butterworth, adam
Jiang, tao
Journal Title
Nature Genetics
ISSN
1061-4036
Publisher
Nature Research
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Butterworth, a., & Jiang, t. Discovery and systematic characterization of risk variants and genes for 1 coronary artery disease in over a million participants. Nature Genetics https://doi.org/10.17863/CAM.83077
Abstract
Rapid progress of the discovery of genetic loci associated with common, complex diseases has outpaced the elucidation of mechanisms pertinent to disease pathogenesis. To address relevant barriers for coronary artery disease (CAD), we combined genetic discovery analyses with downstream characterization of likely causal variants, genes, and biological pathways. Specifically, we conducted a genome-wide association study (GWAS) comprising 181,522 predominantly European ancestry cases of CAD among 1,165,690 participants. We detected 241 associations, including 54 associations and 30 loci not previously linked to CAD. Cross-ancestry meta-analysis with a large Japanese GWAS yielded 38 additional novel loci. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling, and vascular cell migration and proliferation in the pathogenesis of CAD. We then prioritized likely causal variants using functionally-informed fine-mapping, yielding 42 associations with fewer than five variants in the 95% credible set. Combining eight complementary approaches, we prioritized 220 candidate causal genes, including 123 genes supported by three or more approaches. Using CRISPR-Cas9 at one of our risk loci, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk via regulation of vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.
Embargo Lift Date
2025-03-31
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.83077
This record's URL: https://www.repository.cam.ac.uk/handle/1810/335646
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.