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Systems genetics analysis of genome-wide association study reveals novel associations between key biological processes and coronary artery disease.
Arterioscler. Thromb. Vasc. Biol. 35, 1712-1722 (2015)
Objective Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Approaches and Results Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15502 cases/55730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. Conclusions These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Coronary Artery Disease ; Pathway Analysis; Set Enrichment Analysis; Guidance Cue Netrin-1; Expression; Identification; Pathway; Loci; Atherosclerosis; Susceptibility; Macrophages; Inference
ISSN (print) / ISBN 1079-5642
Quellenangaben Volume: 35, Issue: 7, Pages: 1712-1722
Publisher Lippincott Williams & Wilkins
Publishing Place Philadelphia
Reviewing status Peer reviewed