Genome-wide association studies (GWASs) have been performed extensively in diverse populations to identify single nucleotide polymorphisms (SNPs) associated with complex diseases or traits. However, to date, the SNPs identified fail to explain a large proportion of the variance of the traits/diseases. GWASs on type 2 diabetes (T2D) and coronary artery disease (CARD) are generally performed as single-trait studies, rather than analyzing the related traits simultaneously. Despite the extensive evidence suggesting that these two phenotypes share both genetic and environmental risk factors, the shared overlapping genetic biological mechanisms between these traits remain largely unexplored. Here, we adopted a recently developed genetic pleiotropic conditional false discovery rate (cFDR) approach to discover novel loci associated with T2D and CARD by incorporating the summary statistics from existing GWASs of these two traits. Applying the cFDR level of 0.05, 33 loci were identified for T2D and 34 loci for CARD, 9 of which for both. By incorporating pleiotropic effects into a conditional analysis framework, we observed that there is significant pleiotropic enrichment between T2D and CARD. These findings may provide novel insights into the etiology of T2D and CARD, as well as the processes that may influence disease development both individually and jointly.
Keywords: Conditional FDR; Coronary artery disease; Pleiotropic; T2D; Type 2 diabetes.
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