Abstract
In the clinic, atrial fibrillation (AF) is a common arrhythmia. Despite constant innovation in treatments for AF, they remain limited by a lack of knowledge of the underlying mechanism responsible for AF. In this study, we examined the molecular mechanisms associated with primary mitral regurgitation (MR) in AF using several bioinformatics techniques. Limma was used to identify differentially expressed genes (DEGs) associated with AF using microarray data from the GSE115574 dataset. WGCNA was used to identify significant module genes. A functional enrichment analysis for overlapping genes between the DEGs and module genes was done and several AF hub genes were identified from a protein-protein interaction (PPI) network. Receiver operating characteristic (ROC) curves were generated to evaluate the validity of the hub genes. We examined 306 DEGs and 147 were upregulated and 159 were downregulated. WGCNA analysis revealed black and ivory modules that contained genes associated with AF. Functional enrichment analysis revealed various biological process terms related to AF. The AUCs for the 8 hub genes screened by the PPI network analysis were > 0.7, indicating satisfactory diagnostic accuracy. The 8 AF-related hub genes included SYT13, VSNL1, GNAO1, RGS4, RALYL, CPLX1, CHGB, and CPLX3. Our findings provide novel insight into the molecular mechanisms of AF and may lead to the development of new treatments.
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