Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.
Comput Math Methods Med. 2021 Mar 6;2021:6680211. doi: 10.1155/2021/6680211. eCollection 2021.
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.
心房颤动（AF）是全球最常见的室上性心律失常之一。然而，AF 的具体分子机制尚不清楚。我们的研究旨在通过生物信息学分析鉴定与持续性房颤（pAF）相关的关键 microRNAs（miRNAs）和靶基因。下载了三个与 pAF 相关的基因表达数组数据集（GSE31821、GSE41177 和 GSE79768）和一个 miRNA 表达数组数据集（GSE68475）。使用 LIMMA 软件包鉴定差异表达基因（DEGs），并从 GSE68475 中筛选差异表达 miRNA（DEMs）。使用 miRTarBase 数据库预测 DEMs 的靶基因，并选择这些靶基因和 DEGs 的交集进行进一步分析，包括生成蛋白质-蛋白质相互作用（PPI）网络、miRNA-转录因子-靶调控网络和药物-基因网络。在 pAF 组和对照组之间共鉴定出 264 个 DEGs 和 40 个 DEMs。对上调和下调的 DEGs 进行了功能和通路富集分析。共同基因（CGs）主要富集在磷脂酰肌醇 3-激酶-（PI3K-）蛋白激酶 B（Akt）信号通路、细胞分裂的负调控和对缺氧的反应中。使用 Cytoscape 构建了 PPI 网络、miRNA-转录因子-靶调控网络和药物-基因网络。本研究揭示了一些参与 pAF 的新的 miRNAs 和基因。我们推测 miR-4298、miR-3125、miR-4306 和 miR-671-5p 可能代表在 pAF 发展过程中作用于靶基因超氧化物歧化酶 2（SOD2）的重要 miRNAs，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 发病机制中发挥作用。
