Ontology type: schema:ScholarlyArticle Open Access: True
2018-10-01
AUTHORSDerek Klarin, Scott M. Damrauer, Kelly Cho, Yan V. Sun, Tanya M. Teslovich, Jacqueline Honerlaw, David R. Gagnon, Scott L. DuVall, Jin Li, Gina M. Peloso, Mark Chaffin, Aeron M. Small, Jie Huang, Hua Tang, Julie A. Lynch, Yuk-Lam Ho, Dajiang J. Liu, Connor A. Emdin, Alexander H. Li, Jennifer E. Huffman, Jennifer S. Lee, Pradeep Natarajan, Rajiv Chowdhury, Danish Saleheen, Marijana Vujkovic, Aris Baras, Saiju Pyarajan, Emanuele Di Angelantonio, Benjamin M. Neale, Aliya Naheed, Amit V. Khera, John Danesh, Kyong-Mi Chang, Gonçalo Abecasis, Cristen Willer, Frederick E. Dewey, David J. Carey, , , , , John Concato, J. Michael Gaziano, Christopher J. O’Donnell, Philip S. Tsao, Sekar Kathiresan, Daniel J. Rader, Peter W. F. Wilson, Themistocles L. Assimes
ABSTRACTThe Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least one blood lipid measurement, including 57,332 black and 24,743 Hispanic participants, we tested up to around 32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total n > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes) and PDE3B (triglycerides and coronary disease). More... »
PAGES1514-1523
http://scigraph.springernature.com/pub.10.1038/s41588-018-0222-9
DOIhttp://dx.doi.org/10.1038/s41588-018-0222-9
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1107327384
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30275531
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