Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease

Abstract

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/11 089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15 502 cases/55 730 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-β/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.

Keywords: coronary artery disease; pathway analysis.

Figure 1. Analytical approach

Schematic of analytical approach as described in detail in Methods section.

Figure 2. Replicated Reactome pathways for CAD using i-GSEA4GWAS with a 100kb mapping interval

Replicated pathways are represented in a hierarchical Reactome pathway diagram. Top-level pathways, representing core biological processes, are listed to the left, and sub-levels corresponding to each top level are illustrated progressively to the right. The 9 top-level pathways that contain at least one replicated pathway (top-level and/or sub-levels) are shown. No sub-level pathways are shown to the right of the last replicated pathway. Pathways are color coded according to their gene-set enrichment p-value from the replication stage as indicated in the legend. A p <0.05 corresponds to an FDR <12.5%. Pathways containing less than 10 or greater than 200 genes were not tested. Replicated pathways with >50% overlap of genes with other replicated pathways are also identified as indicated in the legend.

Figure 3. Functionally interacting network modules constructed from genes belonging to the replicated, CAD-associated pathways

Functional interactions among the genes from all replicated pathways were analyzed and clustered by the ReactomeFI tool and visualized in Cytoscape. Genes are represented as nodes and interactions among genes are represented as edges. The parent network was further analyzed to yield sub-network clusters; each cluster is shown separately and color coded for clarity. Inter-cluster connectivity is exemplified in red for cluster 4. The top GO-BP terms that are enriched in each cluster are listed in the blue boxes. For each cluster, all terms are at FDR<0.0001 and contain a minimum of 10 genes (unless otherwise indicated in parentheses). A maximum of 10 GO-BP terms are shown for each cluster. Genes that were not linked to at least one other gene were excluded from the network diagram.

Figure 4. Topology based network analysis in replicated pathways

Topological relationships among genes are shown for a merged Reactome functional interaction network created in Cytoscape from two replicated pathways associated with cell-cell interactions (NCAM signaling for neurite outgrowth and CRMPs in Sema3a signaling). Genes (nodes) in the network are color coded by their replication p-values (deep red, p<0.001; lighter red, 0.001<p<0.01; lightest red, 0.01<p<0.05; white, p>0.05) and sized by their “betweenness” network centrality score (calculated via Centiscape 2.0). The individual gene names and their “betweenness” scores are listed beside the network diagram. Betweenness scores are not calculated for genes that do not connect to at least one other gene in the network (these genes are indicated with #N/A for betweenness).