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Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Release:Dec 14, 2022 Update:Dec 14, 2022
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Professor Yoichiro Kamatani of the Department of Computational Biology and Medical Sciences in the Graduate School of Frontier Sciences played a leading role in the research project.

Abstract

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Article

Title:
Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Authors:
Krishna G Aragam, Tao Jiang, Anuj Goel, Stavroula Kanoni, Brooke N Wolford,Deepak S Atri, Elle M Weeks, Minxian Wang, George Hindy, Wei Zhou, Christopher, Grace, Carolina Roselli, Nicholas A Marston, Frederick K Kamanu, Ida Surakka, Loreto Muñoz Venegas, Paul Sherliker, Satoshi Koyama, Kazuyoshi Ishigak, Bjørn O Åsvold, Michael R Brown, Ben Brumpton, Paul S de Vries, Olga Giannakopoulou, Panagiota Giardoglou, Daniel F Gudbjartsson, Ulrich Güldener, Syed M. Ijlal Haider, Anna Helgadottir, Maysson Ibrahim, Adnan Kastrati, Thorsten Kessler, Theodosios Kyriakou, Tomasz Konopka, Ling Li, Lijiang Ma, Thomas Meitinger, Sören Mucha, Matthias Munz, Federico Murgia, Jonas B Nielsen, Markus M Nöthen, Shichao Pang, Tobias Reinberger, Gavin Schnitzler, Damian Smedley, Gudmar Thorleifsson, Moritz von Scheidt, Jacob K Ulirsch, David O Arnar, Noël P Burtt, Maria C Costanzo, Jason Flannick, Kaoru Ito, Dong-Keun Jang, Yoichiro Kamatani, Amit V Khera, Issei Komuro, Iftikhar J Kullo, Luca A Lotta, Christopher P Nelson, Robert Roberts, Gudmundur Thorgeirsson, Unnur Thorsteinsdottir, Thomas R Webb, Aris Baras, Johan LM Björkegren, Eric Boerwinkle, George Dedoussis, Hilma Holm, Kristian Hveem, Olle Melander, Alanna C Morrison, Marju Orho-Melander, Loukianos S Rallidis, Arno Ruusalepp, Marc S Sabatine, Kari Stefansson, Pierre Zalloua, Patrick T Ellinor, Martin Farrall, John Danesh, Christian T Ruff, Hilary K Finucane, Jemma C Hopewell, Robert Clarke, Rajat M Gupta, Jeanette Erdmann, Nilesh J Samani, Heribert Schunker, Hugh Watkins, Cristen J Willer, Panos Deloukas, Sekar Kathiresan, Adam S Butterworth on behalf of the CARDIoGRAMplusC4D Consortium.

Publication:
Nature Genetics

DOI:
10.1038/s41588-022-01233-6

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