Cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) have many shared risk factors, suggesting that they have common pathophysiological mechanisms. Our recent analysis of genome wide association studies (GWAS) of both CVD and T2D in three ethnic populations revealed a number of biological pathways, such as extracellular matrix and focal adhesion, to be genetically associated with both diseases. Building on our prior work employing knowledge-driven pathways, we performed data-driven integrative genomics analyses using gene co-expression networks constructed from a multitude of tissue-specific transcriptome datasets in conjunction with GWAS for CVD, T2D, and a vascular disease phenotype (VD, representing combined CVD+T2D) in three different ethnic groups of 8155 African Americans, 3494 Hispanic Americans and 3697 Caucasian Americans participated in the national Women’s Health Initiative (WHI) study. We examined a total of 2674 coexpression networks and found that 24 modules were significantly enriched for GWAS signatures for all three disease end points (15 modules) or VD only (9 modules) across multiple cohorts at false discovery rate <5%. These modules were enriched for the previously identified pathways like focal adhesion. Further, top modules for all three diseases were enriched for genes involved in citrate cycle and G-protein coupled receptor signaling, whereas top modules for VD were related to amino acid metabolism and BMP signaling, indicating novel processes that are shared between CVD and T2D. To pinpoint key driver (KD) for these modules, we integrated Bayesian networks of adipose, brain, kidney, liver and muscle tissue, and identified highly significant KDs such as BCL6B in adipose, MALAT1 in brain, ZNF565 in kidney, GLS2 in liver and MYL2 in muscle. Among the top KDs, MALAT1, GLS2 and MYL2 have been previously implicated in CVD and T2D, whereas the others represented novel findings. In summary, by leveraging multi-ethnic GWAS data on CVD and T2D and data-driven transcriptional networks, we uncovered both known and novel regulatory mechanisms that appeared to be shared by the two vascular diseases. These network regulators revealed may serve as important targets for future experimental validation.
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