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利用加权共表达网络分析和RNA测序数据鉴定心房颤动中的关键mRNA和lncRNA

Identification of Hub mRNAs and lncRNAs in Atrial Fibrillation Using Weighted Co-expression Network Analysis With RNA-Seq Data.

作者信息

Yang Pan, Cao Yujing, Jian Huagang, Chen Hao

机构信息

Emergency Department, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Department of Cardiovascular Surgery, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, China.

出版信息

Front Cell Dev Biol. 2021 Oct 4;9:722671. doi: 10.3389/fcell.2021.722671. eCollection 2021.

Abstract

Atrial fibrillation (AF)/paroxysmal AF (PAF) is the main cause of cardiogenic embolism. In recent years, the progression from paroxysmal AF to persistent AF has attracted more and more attention. However, the molecular mechanism of the progression of AF is unclear. In this study, we performed RNA sequencing for normal samples, paroxysmal AF and persistent AF samples to identify differentially expressed gene (DEG) and explore the roles of these DEGs in AF. Totally, 272 differently expressed mRNAs (DEmRNAs) and 286 differentially expressed lncRNAs (DElncRNAs) were identified in paroxysmal AF compared to normal samples; 324 DEmRNAs and 258 DElncRNAs were found in persistent atrial fibrillation compared with normal samples; and 520 DEmRNAs and 414 DElncRNAs were identified in persistent AF compared to paroxysmal AF samples. Interestingly, among the DEGs, approximately 50% were coding genes and around 50% were non-coding RNAs, suggesting that lncRNAs may also have a crucial role in the progression of AF. Bioinformatics analysis demonstrated that these DEGs were significantly related to regulating multiple AF associated pathways, such as the regulation of vascular endothelial growth factor production and binding to the CXCR chemokine receptor. Furthermore, weighted gene co-expression network analysis (WGCNA) was conducted to identify key modules and hub RNAs and lncRNAs to determine their potential associations with AF. Five hub modules were identified in the progression of AF, including blue, brown, gray, turquoise and yellow modules. Interestingly, blue module and turquoise module were significantly negatively and positively correlated to the progression of AF respectively, indicating that they may have a more important role in the AF. Moreover, the hub protein-protein interaction (PPI) networks and lncRNA-mRNA regulatory network were constructed. Bioinformatics analysis on the hub PPI network in turquoise was involved in regulating immune response related signaling, such as leukocyte chemotaxis, macrophage activation, and positive regulation of α-β T cell activation. Our findings could clarify the underlying molecular changes associated fibrillation, and provide a useful resource for identifying AF marker.

摘要

心房颤动(AF)/阵发性心房颤动(PAF)是心源性栓塞的主要原因。近年来,阵发性心房颤动向持续性心房颤动的进展越来越受到关注。然而,心房颤动进展的分子机制尚不清楚。在本研究中,我们对正常样本、阵发性心房颤动样本和持续性心房颤动样本进行了RNA测序,以鉴定差异表达基因(DEG),并探讨这些DEG在心房颤动中的作用。与正常样本相比,阵发性心房颤动中共鉴定出272个差异表达的mRNA(DEmRNA)和286个差异表达的lncRNA(DElncRNA);与正常样本相比,持续性心房颤动中发现324个DEmRNA和258个DElncRNA;与阵发性心房颤动样本相比,持续性心房颤动中鉴定出520个DEmRNA和414个DElncRNA。有趣的是,在这些DEG中,约50%是编码基因,约50%是非编码RNA,这表明lncRNA在心房颤动的进展中可能也起着关键作用。生物信息学分析表明,这些DEG与调节多个与心房颤动相关的途径显著相关,如血管内皮生长因子产生的调节以及与CXCR趋化因子受体的结合。此外,进行了加权基因共表达网络分析(WGCNA)以识别关键模块以及中枢RNA和lncRNA,以确定它们与心房颤动的潜在关联。在心房颤动进展过程中鉴定出五个中枢模块,包括蓝色、棕色、灰色、蓝绿色和黄色模块。有趣的是,蓝色模块和蓝绿色模块分别与心房颤动的进展呈显著负相关和正相关,表明它们可能在心房颤动中发挥更重要的作用。此外,构建了中枢蛋白质-蛋白质相互作用(PPI)网络和lncRNA-mRNA调控网络。对蓝绿色中枢PPI网络的生物信息学分析涉及调节免疫反应相关信号,如白细胞趋化性、巨噬细胞活化以及α-β T细胞活化的正调节。我们的研究结果可以阐明与心房颤动相关的潜在分子变化,并为鉴定心房颤动标志物提供有用的资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91d9/8520999/f40882844063/fcell-09-722671-g001.jpg

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