Pan Defeng, Zhou Yufei, Xiao Shengjue, Hu Yue, Huan Chunyan, Wu Qi, Wang Xiaotong, Pan Qinyuan, Liu Jie, Zhu Hong
Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221004, People's Republic of China.
Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, People's Republic of China.
Int J Gen Med. 2022 Jan 5;15:103-114. doi: 10.2147/IJGM.S334122. eCollection 2022.
Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, but the molecular mechanisms underlying AF are not known. We aimed to identify the pivotal genes and pathways involved in AF pathogenesis because they could become potential biomarkers and therapeutic targets of AF.
The microarray datasets of GSE31821 and GSE41177 were downloaded from the Gene Expression Omnibus database. After combining the two datasets, differentially expressed genes (DEGs) were screened by the Limma package. MicroRNAs (miRNAs) confirmed experimentally to have an interaction with AF were screened through the miRTarBase database. Target genes of miRNAs were predicted using the miRNet database, and the intersection between DEGs and target genes of miRNAs, which were defined as common genes (CGs), were analyzed. Functional and pathway-enrichment analyses of DEGs and CGs were performed using the databases DAVID and KOBAS. Protein-protein interaction (PPI) network, miRNA- messenger(m) RNA network, and drug-gene network was visualized. Finally, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was used to validate the expression of hub genes in the miRNA-mRNA network.
Thirty-three CGs were acquired from the intersection of 65 DEGs from the integrated dataset and 9777 target genes of miRNAs. Fifteen "hub" genes were selected from the PPI network, and the miRNA-mRNA network, including 82 miRNAs and 9 target mRNAs, was constructed. Furthermore, with the validation by RT-qPCR, macrophage migration inhibitory factor (), MYC proto-oncogene, bHLH transcription factor (, inhibitor of differentiation 1 (, and C-X-C Motif Chemokine Receptor 4 () were upregulated and superoxide Dismutase 2 ( was downregulated in patients with AF compared with healthy controls. We also found , and were enriched in the transforming growth factor (TGF)-β and Hippo signaling pathway.
We identified several pivotal genes and pathways involved in AF pathogenesis. , and might participate in AF progression through the TGF-β and Hippo signaling pathways. Our study provided new insights into the mechanisms of action of AF.
心房颤动（AF）是最常见的持续性心律失常，但其潜在的分子机制尚不清楚。我们旨在确定参与AF发病机制的关键基因和通路，因为它们可能成为AF的潜在生物标志物和治疗靶点。
从基因表达综合数据库下载GSE31821和GSE41177的微阵列数据集。合并两个数据集后，使用Limma软件包筛选差异表达基因（DEG）。通过miRTarBase数据库筛选经实验证实与AF相互作用的微小RNA（miRNA）。使用miRNet数据库预测miRNA的靶基因，并分析DEG与miRNA靶基因之间的交集，将其定义为共同基因（CG）。使用DAVID和KOBAS数据库对DEG和CG进行功能和通路富集分析。对蛋白质-蛋白质相互作用（PPI）网络、miRNA-信使核糖核酸（mRNA）网络和药物-基因网络进行可视化。最后，使用逆转录定量实时聚合酶链反应（RT-qPCR）验证miRNA-mRNA网络中枢纽基因的表达。
从整合数据集中的65个DEG与miRNA的9777个靶基因的交集中获得了33个CG。从PPI网络中选择了15个“枢纽”基因，并构建了包括82个miRNA和9个靶mRNA的miRNA-mRNA网络。此外，经RT-qPCR验证，与健康对照相比，AF患者中巨噬细胞迁移抑制因子（）、MYC原癌基因、bHLH转录因子（、分化抑制因子1（和C-X-C基序趋化因子受体4（上调，超氧化物歧化酶2（下调。我们还发现，和在转化生长因子（TGF）-β和Hippo信号通路中富集。
我们确定了几个参与AF发病机制的关键基因和通路。，和可能通过TGF-β和Hippo信号通路参与AF进展。我们的研究为AF的作用机制提供了新的见解。
