Atrial fibrillation (AF) is one of the most common supraventricular arrhythmias worldwide. However, the specific molecular mechanism underlying AF remains unclear. Our study is aimed at identifying pivotal microRNAs (miRNAs) and targeting genes associated with persistent AF (pAF) using bioinformatics analysis. Three gene expression array datasets (GSE31821, GSE41177, and GSE79768) and an miRNA expression array dataset (GSE68475) associated with pAF were downloaded. Differentially expressed genes (DEGs) were identified using the LIMMA package, and differentially expressed miRNAs (DEMs) were screened from GSE68475. Target genes for DEMs were predicted using the miRTarBase database, and intersections between these target genes and DEGs were selected for further analysis, including the generation of protein–protein interaction (PPI) network, miRNA–transcription factor–target regulatory network, and drug–gene network. A total of 264 DEGs and 40 DEMs were identified between the pAF and control groups. Functional and pathway enrichment analyses of up- and downregulated DEGs were performed. The common genes (CGs) were primarily enriched in the phosphoinositide 3-kinase- (PI3K-) protein kinase B (Akt) signaling pathway, negative regulation of cell division, and response to hypoxia. The PPI network, miRNA–transcription factor–target regulatory network, and drug–gene network were constructed using Cytoscape. The present study revealed several novel miRNAs and genes involved in pAF. We speculated that miR-4298, miR-3125, miR-4306, and miR-671-5p could represent significant miRNAs that act on the target gene superoxide dismutase 2 (SOD2) during the development of pAF and may serve as essential biomarkers for pAF diagnosis and treatment. Moreover, MYC might function in pAF pathogenesis through the PI3K–Akt signaling pathway.

中文翻译：

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基于生物信息学分析与持续性心房颤动相关的关键微RNA和靶基因的鉴定

心房颤动 (AF) 是世界范围内最常见的室上性心律失常之一。然而，AF 的具体分子机制仍不清楚。我们的研究旨在使用生物信息学分析识别关键的 microRNA (miRNA) 和靶向与持续性 AF (pAF) 相关的基因。下载了与 pAF 相关的三个基因表达阵列数据集（GSE31821、GSE41177 和 GSE79768）和一个 miRNA 表达阵列数据集（GSE68475）。使用 LIMMA 程序包鉴定差异表达基因 (DEG)，并从 GSE68475 中筛选差异表达的 miRNA (DEM)。使用 miRTarBase 数据库预测 DEM 的靶基因，并选择这些靶基因和 DEG 之间的交叉点进行进一步分析，包括生成蛋白质 - 蛋白质相互作用（PPI）网络，miRNA-转录因子-靶标调控网络和药物-基因网络。在 pAF 和对照组之间共鉴定出 264 个 DEG 和 40 个 DEM。对上调和下调的 DEG 进行了功能和途径富集分析。共同基因 (CG) 主要富集于磷酸肌醇 3-激酶- (PI3K-) 蛋白激酶 B (Akt) 信号通路、细胞分裂的负调节和对​​缺氧的反应。使用Cytoscape构建PPI网络、miRNA-转录因子-靶标调控网络和药物-基因网络。本研究揭示了几种与 pAF 相关的新型 miRNA 和基因。我们推测 miR-4298、miR-3125、miR-4306、和 miR-671-5p 可以代表在 pAF 发展过程中作用于靶基因超氧化物歧化酶 2 (SOD2) 的重要 miRNA，并可能作为 pAF 诊断和治疗的重要生物标志物。此外，MYC 可能通过 PI3K-Akt 信号通路在 pAF 发病机制中起作用。