To support a hypothesis that there is an intrinsic interplay between coronary artery disease (CAD) and type 2 diabetes (T2D), we used RNA-seq to identify unique gene expression signatures of CAD, T2D, and coexisting conditions.
After transcriptome sequencing, differential expression analysis was performed between each disordered state and normal control group. By comparing gene expression profiles of CAD, T2D, and coexisting conditions, common and specific patterns of each disordered state were displayed. To verify the specific gene expression patterns of CAD or T2D, the gene expression data of GSE23561 was extracted.
A strong overlap of 191 genes across CAD, T2D and coexisting conditions, were mainly involved in a viral infectious cycle, anti-apoptosis, endocrine pancreas development, innate immune response, and blood coagulation. In T2D-specific PPI networks involving 64 genes, TCF7L2 (Degree = 169) was identified as a key gene in T2D development, while in CAD-specific PPI networks involving 64 genes, HIF1A (Degree = 124), SMAD1 (Degree = 112) and SKIL (Degree = 94) were identified as key genes in the CAD development. Interestingly, with the provided expression data from GSE23561, the three genes were all up-regulated in CAD, and SMAD1 and SKIL were specifically differentially expressed in CAD, while HIF1A was differentially expressed in both CAD and T2D, but with opposite trends.
This study provides some evidences in transcript level to uncover the association of T2D, CAD and coexisting conditions, and may provide novel drug targets and biomarkers for these diseases.