The mortality rate of patients with coronary artery disease (CAD) increases year by year, and the age of onset is decreasing, primarily because of the lack of an efficient and convenient diagnostic method for CAD. In the present study, we aimed to detect CAD‐correlated biomarkers and the regulatory pathways involved through weighted co‐expression network analysis. The microarray data originated from 93 CAD patients and 48 controls within the Gene Expression Omnibus (GEO) database. The gene network was implemented by weighted gene co‐expression network analysis, and the genes were observed to fall into a range of modules. We took the intersection of genes in the modules most correlated with CAD with the differentially expressed genes of CAD, which were identified by applying the limma package. Lasso regression and support vector machine recursive feature elimination algorithms were used to determine CAD candidate signature genes. The biomarkers for diagnosing CAD were detected by validating candidate signature gene diagnostic capabilities (receiver operating characteristic curves) based on data sets from GEO. Three modules were selected, and 26 vital genes were identified. Eight of these genes were reported as the optimal candidate features in terms of CAD diagnosis. Through receiver operating characteristic curve analysis, we identified three genes ( ERCC5 , HES6 and RORA ; area under the curve > 0.8) capable of distinguishing CAD from the control, and observed that these genes are correlated with the immune response. In summary, ERCC5 , HES6 and RORA may have potential for diagnosis of CAD.
Myocardial ischemia-reperfusion injury in diabetic patients leads to an increased incidence of complications and mortality. Secreted frizzled-related protein 4 (SFRP4) plays a critical role in diabetic myocardial ischemia-reperfusion. This paper aims to uncover the underlying mechanisms of SFRP4 in hypoxia/reoxygenation (H/R) injury of diabetic myocardial cells. An in vitro ischemia/reperfusion (I/R) injury model was established using high glucose-induced H9c2 cardiomyocytes. Expression of SFRP4 was detected by real-time reverse transcriptase-polymerase chain reaction and Western blotting. After transfection of SFRP4, the binding of SFRP4 to protein tyrosine phosphatase nonreceptor type 12 (PTPN12) was predicted by database and verified by co-immunoprecipitation assay. P13 K/AKT protein levels were examined by Western blotting. PTPN12 levels were tested by RT-qPCR and Western blotting, cell viability by Cell Counting Kit-8, lactose dehydrogenase kit, terminal dUTP nick-end labeling assay, and cell inflammation and oxidative stress by Western blotting and enzyme linked immunosorbent assay. After overexpression of PTPN12, the experiments for cell viability, inflammation and oxidative stress were repeated once more. SFRP4 expression was upregulated in a high-glucose-stimulated H/R cardiomyocyte model. The interference of SFRP4 promoted cell viability, inhibited the inflammatory and oxidative stress response of H/R cardiomyocytes induced by high glucose. SFRP4 interacted with PTPN12 and inhibited the PI3K/AKT signaling pathway. PTPN12 overexpression reversed the inhibitory effect of sh-SFRP4 on H/R cardiomyocyte damage induced by high glucose. Downregulation of SFRP4 inhibited H/R cell damage in diabetic cardiomyocytes by binding to PTPN12.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.