Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

Thomas R Webb, Jeanette Erdmann, Kathleen E Stirrups, Nathan O Stitziel, Nicholas G D Masca, Henning Jansen, Stavroula Kanoni, Christopher P Nelson, Paola G Ferrario, Inke R König, John D Eicher, Andrew D Johnson, Stephen E Hamby, Christer Betsholtz, Arno Ruusalepp, Oscar Franzén, Eric E Schadt, Johan L M Björkegren, Peter E Weeke, Paul L AuerUrsula M Schick, Yingchang Lu, He Zhang, Marie-Pierre Dube, Anuj Goel, Martin Farrall, Gina M Peloso, Hong-Hee Won, Ron Do, Erik van Iperen, Jochen Kruppa, Anubha Mahajan, Robert A Scott, Christina Willenborg, Peter S Braund, Julian C van Capelleveen, Alex S F Doney, Louise A Donnelly, Rosanna Asselta, Pier A Merlini, Stefano Duga, Nicola Marziliano, Josh C Denny, Christian Shaffer, Nour Eddine El-Mokhtari, Andre Franke, Stefanie Heilmann, Christian Hengstenberg, Andrew D Morris, Colin N A Palmer, Wellcome Trust Case Control Consortium, MORGAM Investigators, Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators

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Abstract

Background: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits.

Objectives: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci.

Methods: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs.

Results: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10(-4) with a range of other diseases/traits.

Conclusions: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.

Original languageEnglish
Pages (from-to)823-836
Number of pages14
JournalJournal of the American College of Cardiology
Volume69
Issue number7
Early online date13 Feb 2017
DOIs
Publication statusPublished - 21 Feb 2017

Keywords

  • Cholesteryl ester transfer protein
  • Expression quantitative trait loci
  • Genetics
  • Genome-wide association
  • Single nucleotide polymorphism

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    Webb, T. R., Erdmann, J., Stirrups, K. E., Stitziel, N. O., Masca, N. G. D., Jansen, H., Kanoni, S., Nelson, C. P., Ferrario, P. G., König, I. R., Eicher, J. D., Johnson, A. D., Hamby, S. E., Betsholtz, C., Ruusalepp, A., Franzén, O., Schadt, E. E., Björkegren, J. L. M., Weeke, P. E., ... Wellcome Trust Case Control Consortium, MORGAM Investigators, Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators (2017). Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease. Journal of the American College of Cardiology, 69(7), 823-836. https://doi.org/10.1016/j.jacc.2016.11.056