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Identifying Novel Gene Variants in Coronary Artery Disease and Shared Genes with Several Cardiovascular Risk Factors

  • Marissa Leblanc
  • , Verena Zuber
  • , Bettina Kulle Andreassen
  • , Aree Witoelar
  • , Lingyao Zeng
  • , Francesco Bettella
  • , Yunpeng Wang
  • , Linda K. McEvoy
  • , Wesley K. Thompson
  • , Andrew J. Schork
  • , Sjur Reppe
  • , Elizabeth Barrett-Connor
  • , Symen Ligthart
  • , Abbas Dehghan
  • , Kaare M. Gautvik
  • , Christopher P. Nelson
  • , Heribert Schunkert
  • , Nilesh J. Samani
  • , Paul M. Ridker
  • , Daniel I. Chasman
  • Pål Aukrust, Srdjan Djurovic, Arnoldo Frigessi, Rahul S. Desikan, Anders M. Dale, Ole A. Andreassen
  • University of Oslo
  • Oslo University Hospital
  • Technical University of Munich
  • Deutsches Zentrum für Herz-Kreislauf-Forschung
  • University of California, San Diego
  • Department of Neurosciences
  • Department of Psychiatry
  • Lovisenberg Diaconal Hospital
  • Erasmus University Medical Center
  • University of Leicester
  • Glenfield Hospital
  • Harvard Medical School
  • University of California San Francisco

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

Rationale: Coronary artery disease (CAD) is a critical determinant of morbidity and mortality. Previous studies have identified several cardiovascular disease risk factors, which may partly arise from a shared genetic basis with CAD, and thus be useful for discovery of CAD genes. Objective: We aimed to improve discovery of CAD genes and inform the pathogenic relationship between CAD and several cardiovascular disease risk factors using a shared polygenic signal-informed statistical framework. Methods and Results: Using genome-wide association studies summary statistics and shared polygenic pleiotropy-informed conditional and conjunctional false discovery rate methodology, we systematically investigated genetic overlap between CAD and 8 traits related to cardiovascular disease risk factors: low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, type 2 diabetes mellitus, C-reactive protein, body mass index, systolic blood pressure, and type 1 diabetes mellitus. We found significant enrichment of single-nucleotide polymorphisms associated with CAD as a function of their association with low-density lipoprotein, high-density lipoprotein, triglycerides, type 2 diabetes mellitus, C-reactive protein, body mass index, systolic blood pressure, and type 1 diabetes mellitus. Applying the conditional false discovery rate method to the enriched phenotypes, we identified 67 novel loci associated with CAD (overall conditional false discovery rate <0.01). Furthermore, we identified 53 loci with significant effects in both CAD and at least 1 of low-density lipoprotein, high-density lipoprotein, triglycerides, type 2 diabetes mellitus, C-reactive protein, systolic blood pressure, and type 1 diabetes mellitus. Conclusions: The observed polygenic overlap between CAD and cardiometabolic risk factors indicates a pathogenic relation that warrants further investigation. The new gene loci identified implicate novel genetic mechanisms related to CAD.

Original languageEnglish
Pages (from-to)83-94
Number of pages12
JournalCirculation Research
Volume118
Issue number1
DOIs
StatePublished - 8 Jan 2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Women's Genome Health Study
  • coronary artery disease
  • coronary heart disease
  • genetic pleiotropy
  • genome-wide association study
  • lipids
  • molecular epidemiology
  • myocardial infarction

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