Identification of susceptibility modules for coronary artery disease using a genome wide integrated network analysis.

Although recent genome-wide association studies (GWAS) have identified a handful of variants with best significance for coronary artery disease (CAD), it remains a challenge to summarize the underlying biological information from the abundant genotyping data. Here, we propose an integrated network analysis that effectively combines GWAS genotyping dataset, protein-protein interaction (PPI) database, literature and pathway annotation information. This three-step approach was illustrated for a comprehensive network analysis of CAD as the following. First, a network was constructed from PPI database and CAD seed genes mined from the available literatures. Then, susceptibility network modules were captured from the results of gene-based association tests. Finally, susceptibility modules were annotated with potential mechanisms for CAD via the KEGG pathway database. Our network analysis identified four susceptibility modules for CAD including a complex module that consisted of 15 functional inter-connected sub-modules, AGPAT3-AGPAT4-PPAP2B module, ITGA11-ITGB1 module and EMCN-SELL module. MAPK10 and COL4A2 among the top-scored focal adhesion pathway related module were the most significant genes (MAPK10: OR=32.5, P=3.5 × 10(-11); COL4A2: OR=2.7, P=2.8 × 10(-10)). The significance of the two genes were further validated by other two gene-based association tests (MAPK10: P=0.009 and 0.007; COL4A2: P=0.001 and 0.023) and another independent GWAS dataset (MAPK10: P=0.001; COL4A2: P=0.0004). Furthermore, 34 out of 44 previously reported CAD susceptibility genes were captured by our CAD PPI network and 17 of them were also significant genes. The susceptibility modules identified in our study might provide novel clues for the clarification of CAD pathogenesis in the future.