Identification of Key Gene Modules and Potential ceRNA Network in Progressive Coronary Artery Disease by Weighted Gene Co-Expression Network Analysis
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Abstract
Coronary Artery Disease (CAD) is a global chronic inflammatory disease with high morbidity and mortality, seriously endangering human health and life quality. Therefore, exploring the critical molecular mechanisms and identifying potential signaling pathways in CAD progression is vital. We reanalyzed peripheral blood mRNA microarray expression data from the GSE34822 dataset and identified 15 gene co-expression modules using weighted gene co-expression network analysis (WGCNA). One of the modules was found to be closely associated with CAD progression, mediating pathways such as platelet degranulation, platelet activation, and platelet aggregation. Genes including NID2, PGRMC1, TSC22D1, LOC340508, KIAA1211, and SMIM3 were significantly correlated with CAD progression. Positive regulation of interleukin−13 production and regulation of monocyte differentiation were identified to be related to these six key genes. Specifically, we discovered that the SMIM3 gene was associated with monocyte infiltration and further developed a SMIM3-related competitive endogenous RNA (ceRNA) network. This suggests that SMIM3 plays a role in monocyte differentiation, contributing to plaque instability and accelerating CAD progression. In this study, we identified six key genes in the crucial module as potential biomarkers for diagnosing and treating progressive CAD. Additionally, we constructed a ceRNA network offering insights into CAD’s underlying regulatory mechanisms.
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