Abstract
Atrial fibrillation (AF) is one of the most prevalent arrhythmias and is characterized by a high risk of heart failure and embolic stroke, yet its underlying mechanism is unclear. The primary goal of this study was to establish a miRNA-mRNA network and identify the miRNAs associated with chronic AF by bioinformatics and experimental validation. The GSE79768 dataset was collected from the Gene Expression Omnibus(GEO) database to extract data from patients with or without persistent AF. Differentially expressed genes (DEGs) were identified in left atrial appendages (LAAs). The STRING platform was utilized for protein-protein interaction (PPI) network analysis. The target miRNAs for the top 20 hub genes were predicted by using the miRTarBase Web tool. The miRNA-mRNA network was established and visualized using Cytoscape software. The key miRNAs selected for verification in the animal experiment were confirmed by miRwalk Web tool. We used a classic animal model of rapid ventricular pacing for chronic AF. Two groups of animals were included in the experiment, namely, the ventricular pacing group (VP group), where ventricular pacing was maintained at 240-280 bpm for 2 weeks, and the control group was the sham-operated group (SO group). Finally, we performed reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to validate the expression of miR-1 and miR-499 in LAA tissues of the VP group and the SO group. Left atrial fibrosis and apoptosis were evaluated by Masson staining and caspase-3 activity assays, respectively. The networks showed 48 miRNAs in LAA tissues. MiR-1 and miR-499 were validated using an animal model of chronic AF. The expression level of miR-1 was increased, and miR-499 was decreased in VP group tissues compared to SO group tissues in LAAs (P < 0.05), which were correlated with left atrial fibrosis and apoptosis in AF. This study provides a better understanding of the alterations in miRNA-1 and miR-499 in chronic AF from the perspective of the miRNA-mRNA network and corroborates findings through experimental validation. These findings may offer novel potential therapeutic targets for AF in the future.
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