Identification of novel proteins for coronary artery disease by integrating GWAS data and human plasma proteomes.

Background: Most coronary artery disease (CAD) risk loci identified by genome-wide association studies (GWAS) are located in non-coding regions, hampering the interpretation of how they confer CAD risk. It is essential to integrate GWAS with molecular traits data to further explore the genetic basis of CAD. Methods: We used the probabilistic Mendelian randomization (PMR) method to identify potential proteins involved in CAD by integrating CAD GWAS data (∼76,014 cases and ∼264,785 controls) and human plasma proteomes (N = 35,559). Then, Bayesian co-localization analysis, confirmatory PMR analysis using independent plasma proteome data (N = 7752), and gene expression data (N1 = 213, N2 = 670) were performed to validate candidate proteins. We further investigated the associations between candidate proteins and CAD-related traits and explored the rationality and biological functions of candidate proteins through disease enrichment, cell type-specific, GO, and KEGG enrichment analysis. Results: This study inferred that the abundance of 30 proteins in the plasma was causally associated with CAD ( Conclusions: Our integration analysis has identified 30 candidate proteins for CAD, which may provide important leads to design future functional studies and potential drug targets for CAD.