Identification of Four Potential Biomarkers Associated With Coronary Artery Disease in Non-diabetic Patients by Gene Co-expression Network Analysis

Abstract

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 non-diabetic 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 non-diabetic patient need to be fully recognized. Materials and Methods: To screen out candidate genes associated with CAD in non-diabetic patients, weighted gene co-expression 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 co-expression modules via WGCNA after excluding the diabetic patients. As a result, 18 co-expression modules were screened out, including 1,225 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 was conducted, and we used gene network analysis 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 the yellow module played vital roles in the pathogenesis of CAD in non-diabetic patients. Additionally, CD40, F11R, TNRC18, and calcium/calmodulin-dependent protein kinase

Exome sequencing in patient‐parent trios suggests new candidate genes for early‐onset primary sclerosing cholangitis

“…Protein Coding gene. Diseases associated with TNRC18 include Atrial Septal Defect and Seckel Syndrome 33 . Lead CpGs at TNRC18 map to active enhancers in kidney cortex and are associated with renal fibrosis.…”

Circular RNA circitga7 accelerates glioma progression via miR-34a-5p/VEGFA axis

“…The WGCNA R package was used to conducted WGCNA analysis according to previous studies [ 35 ].…”

LncRNA LYPLAL1-DT in Type 2 Diabetes With Macrovascular Complication Contributes Protective Effects on Endothelial Cells via Regulating the miR-204-5p/SIRT1 Axis

“…The pathological changes of DMC are primarily due to higher serum glucose levels inducing abnormal metabolism, consequently in uencing the functions and homeostasis of endothelial cells [21][22][23]. A better understanding of lncRNAs response in EC under HG and IS is essential.…”