Large-scale association analysis identifies new risk loci for coronary artery disease

Panos Deloukas, Stavroula Kanoni, Christina Willenborg, Martin Farrall, Themistocles L Assimes, John R Thompson, Erik Ingelsson, Danish Saleheen, Jeanette Erdmann, Benjamin A Goldstein, Kathleen Stirrups, Inke R König, Jean-Baptiste Cazier, Asa Johansson, Alistair S Hall, Jong-Young Lee, Cristen J Willer, John C Chambers, Tõnu Esko, Lasse FolkersenAnuj Goel, Elin Grundberg, Aki S Havulinna, Weang K Ho, Jemma C Hopewell, Niclas Eriksson, Marcus E Kleber, Kati Kristiansson, Per Lundmark, Leo-Pekka Lyytikäinen, Suzanne Rafelt, Dmitry Shungin, Rona J Strawbridge, Gudmar Thorleifsson, Emmi Tikkanen, Natalie Van Zuydam, Benjamin F Voight, Lindsay L Waite, Weihua Zhang, Andreas Ziegler, Devin Absher, David Altshuler, Anthony J Balmforth, Inês Barroso, Peter S Braund, Christof Burgdorf, Simone Claudi-Boehm, Alexander S. F. Doney, Andrew D Morris, Colin N A Palmer, CARDIoGRAMplusC4D Consortium

    Research output: Contribution to journalArticlepeer-review

    1355 Citations (Scopus)

    Abstract

    Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) <0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.
    Original languageEnglish
    Pages (from-to)25-33
    Number of pages9
    JournalNature Genetics
    Volume45
    Issue number1
    Early online date2 Dec 2012
    DOIs
    Publication statusPublished - Jan 2013

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