Abstract
BackgroundCoronary 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 MethodsTo 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.ResultsThe 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 type II gamma (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.ConclusionOur findings demonstrate that hub genes, CD40, F11R, TNRC18, and CAMK2G, are surrogate diagnostic biomarkers and/or therapeutic targets for CAD in non-diabetic patients and require deeper validation.
Highlights
Coronary artery disease (CAD), which is called atherosclerotic cardiovascular disease and coronary heart disease (CHD), is the leading cause of cardiovascular deaths (CVDs) globally (Roth et al, 2017), with a death rate that is predicted to increase
In general statistics work under certain restrictions, the hub genes we identified here are calculated based on a fixed cutoff value, which has been described in the “Materials and Methods” section; it is not surprising that the results may vary when a different cutoff value is given
We hypothesized that these four hub genes might be the diagnostic biomarkers and/or therapeutic targets for CAD, and that further study is needed to explore them in detail
Summary
Coronary artery disease (CAD), which is called atherosclerotic cardiovascular disease and coronary heart disease (CHD), is the leading cause of cardiovascular deaths (CVDs) globally (Roth et al, 2017), with a death rate that is predicted to increase. Since diabetic status is one of the largest clinical factors affecting CAD-associated gene expression changes, most studies have focused on diabetic patients (Wingrove et al, 2008; Guo et al, 2018), and few have been done on non-diabetic patients (Sinnaeve et al, 2009; Elashoff et al, 2011). To gain more insight into the latent molecular mechanisms of CAD in non-diabetic patients, the weighted gene co-expression network analysis (WGCNA) method was utilized in current research. Diabetic status is one of the largest clinical factors affecting CAD-associated gene expression changes. The prognostic and predictive diagnostic biomarkers for CAD in non-diabetic patient need to be fully recognized
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