4.7 Article

Contribution of Gene Regulatory Networks to Heritability of Coronary Artery Disease

Journal

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
Volume 73, Issue 23, Pages 2946-2957

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jacc.2019.03.520

Keywords

coronary artery disease; gene regulatory networks; heritability; systems genetics

Funding

  1. National Institutes of Health (NIH) [R01HL125863]
  2. American Heart Association [A14SFRN20840000]
  3. Swedish Research Council [2018-02529]
  4. Heart Lung Foundation [20170265]
  5. Foundation Leducq (PlaqueOmics: Novel Roles of Smooth Muscle and Other Matrix Producing Cells in Atherosclerotic Plaque Stability and Rupture) [18CVD02]
  6. Deutsche Forschungsgemeinschaft (DFG) [Sonderforschungsbereich CRC 1123]
  7. Fondation Leducq (CADgenomics: Understanding CAD Genes) [12CVD02]
  8. German Federal Ministry of Education and Research (BMBF) [01KL1802, 16GW0198K, 01ZX1706C]
  9. DigiMed Bayern
  10. National Institutes of Health [R01HL130423]
  11. Foundation Leducq (CADgenomics: Understanding CAD Genes) [12CVD02]
  12. Foundation Leducq
  13. Vinnova [2018-02529] Funding Source: Vinnova
  14. Swedish Research Council [2018-02529] Funding Source: Swedish Research Council

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BACKGROUND Genetic variants currently known to affect coronary artery disease (CAD) risk explain less than one-quarter of disease heritability. The heritability contribution of gene regulatory networks (GRNs) in CAD, which are modulated by both genetic and environmental factors, is unknown. OBJECTIVES This study sought to determine the heritability contributions of single nucleotide polymorphisms affecting gene expression (eSNPs) in GRNs causally linked to CAD. METHODS Seven vascular and metabolic tissues collected in 2 independent genetics-of-gene-expression studies of patients with CAD were used to identify eSNPs and to infer coexpression networks. To construct GRNs with causal relations to CAD, the prior information of eSNPs in the coexpression networks was used in a Bayesian algorithm. Narrow-sense CAD heritability conferred by the GRNs was calculated from individual-level genotype data from 9 European genome-wide association studies (GWAS) (13,612 cases, 13,758 control cases). RESULTS The authors identified and replicated 28 independent GRNs active in CAD. The genetic variation in these networks contributed to 10.0% of CAD heritability beyond the 22% attributable to risk loci identified by GWAS. GRNs in the atherosclerotic arterial wall (n = 7) and subcutaneous or visceral abdominal fat (n = 9) were most strongly implicated, jointly explaining 8.2% of CAD heritability. In all, these 28 GRNs (each contributing to >0.2% of CAD heritability) comprised 24 to 841 genes, whereof 1 to 28 genes had strong regulatory effects (key disease drivers) and harbored many relevant functions previously associated with CAD. The gene activity in these 28 GRNs also displayed strong associations with genetic and phenotypic cardiometabolic disease variations both in humans and mice, indicative of their pivotal roles as mediators of gene-environmental interactions in CAD. CONCLUSIONS GRNs capture a major portion of genetic variance and contribute to heritability beyond that of genetic loci currently known to affect CAD risk. These networks provide a framework to identify novel risk genes/pathways and study molecular interactions within and across disease-relevant tissues leading to CAD. (C) 2019 by the American College of Cardiology Foundation.

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