Identification of Four Potential Biomarkers Associated With Coronary Artery Disease in Non-diabetic Patients by Gene Co-expression Network Analysis - Jiao, Min; Li, Jingtian; Zhang, Quan; Xu, Xiufeng; Li, Ruidong; Dong, Peikang; Meng, Chun; Li, Yi; Wang, Lijuan; Qi, Wanpeng; Kang, Kai; Wang, Hongjie; et al. (Frontiers in Genetics, 2020)
Background: Coronary artery disease (CAD) is a type of cardiovascular disease that greatly hurts the health of human beings. Diabetic status is one of the largest clinical factors affecting CAD-associated gene expression changes. Most of the studies focus on diabetic patients, whereas few have been done for nondiabetic patients. Since the pathophysiological processes may vary among these patients, we cannot simply follow the standard based on the data from diabetic patients. Therefore, the prognostic and predictive diagnostic biomarkers for CAD in nondiabetic patient need to be fully recognized. Materials/Methods: To screen out candidate genes associated with CAD in nondiabetic patients, weighted gene coexpression network analysis (WGCNA) was constructed to conduct an analysis of microarray expression profiling in patients with CAD. First, the microarray data GSE20680 and GSE20681 were downloaded from NCBI. We constructed coexpression modules via WGCNA after excluding the diabetic patients. As a result, 16 coexpression modules were screened out, including 1225 differentially expressed genes (DEGs) that were obtained from 152 patients (luminal stenosis ≥ 50% in at least one major vessel) and 170 patients (stenosis of < 50%). Subsequently, a Pearson’s correlation analysis was conducted between the modules and clinical traits. Then, a functional enrichment analysis and protein-protein interaction (PPI) analysis was conducted to reveal hub genes. Last, we validated the hub genes with peripheral blood samples in an independent patient cohort using RT-qPCR. Results: The results showed that the midnight blue module and yellow module played vital roles in the pathogenesis of CAD in nondiabetic patients. Additionally, CD40, F11R, TNRC18, and CAMK2G were screened out and validated using enzyme-linked immunosorbent assay (ELISA) in an independent patient cohort and immunohistochemical (IHC) staining in an atherosclerosis mouse model. Conclusions: Our findings demonstrate that hub genes, CD40, F11R, TNRC18, and CAMK2G, are surrogate diagnostic biomarkers and/or therapeutic targets for CAD in nondiabetic patients and require deeper validation. Keywords: coronary artery disease (CAD); nondiabetic patients; weighted gene coexpression network analysis (WGCNA); function enrichment analysis; biomarkers.