Ke Xiangyu, Zhang Junguo, Huang Xin, Li Shuai, Leng Meifang, Ye Zebing, Li Guowei
Centre for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China.
Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Front Cardiovasc Med. 2022 Jan 24;9:791156. doi: 10.3389/fcvm.2022.791156. eCollection 2022.
Accumulated studies have revealed that long non-coding RNAs (lncRNAs) play critical roles in human diseases by acting as competing endogenous RNAs (ceRNAs). However, functional roles and regulatory mechanisms of lncRNA-mediated ceRNA in atrial fibrillation (AF) remain unknown. In the present study, we aimed to construct the lncRNA-miRNA-mRNA network based on ceRNA theory in AF by using bioinformatic analyses of public datasets.
Microarray data sets of GSE115574 and GSE79768 from the Gene Expression Omnibus database were downloaded. Twenty-one AF right atrial appendage (RAA) samples and 22 sinus rhythm (SR) subjects RAA samples were selected for subsequent analyses. After merging all microarray data and adjusting for batch effect, differentially expressed genes were identified. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out. A ceRNA network was constructed.
A total of 8 lncRNAs and 43 mRNAs were significantly differentially expressed with fold change >1.5 ( < 0.05) in RAA samples of AF patients when compared with SR. GO and KEGG pathway analysis showed that cardiac muscle contraction pathway were involved in AF development. The ceRNA was predicted by co-expressing LOC101928304/ LRRC2 from the constructional network analysis, which was competitively combined with miR-490-3p. The expression of LOC101928304 and LRRC were up-regulated in myocardial tissue of patients with AF, while miR-490-3p was down-regulated.
We constructed the LOC101928304/miR-490-3p/LRRC2 network based on ceRNA theory in AF in the bioinformatic analyses of public datasets. The ceRNA network found from this study may help improve our understanding of lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of AF.
大量研究表明，长链非编码RNA（lncRNA）作为竞争性内源RNA（ceRNA）在人类疾病中发挥关键作用。然而，lncRNA介导的ceRNA在心房颤动（AF）中的功能作用和调控机制仍不清楚。在本研究中，我们旨在通过对公共数据集进行生物信息学分析，基于ceRNA理论构建AF中的lncRNA- miRNA- mRNA网络。
从基因表达综合数据库下载GSE115574和GSE79768的微阵列数据集。选择21个AF右心耳（RAA）样本和22个窦性心律（SR）受试者的RAA样本进行后续分析。合并所有微阵列数据并调整批次效应后，鉴定差异表达基因。进行基因本体（GO）分类和京都基因与基因组百科全书（KEGG）通路富集分析。构建ceRNA网络。
与SR相比，AF患者RAA样本中共有8个lncRNA和43个mRNA显著差异表达，倍数变化> 1.5（<0.05）。GO和KEGG通路分析表明，心肌收缩通路参与AF的发生发展。通过构建网络分析共表达LOC101928304/LRRC2预测ceRNA，其与miR-490-3p竞争性结合。AF患者心肌组织中LOC101928304和LRRC的表达上调，而miR-490-3p下调。
在公共数据集的生物信息学分析中，我们基于ceRNA理论构建了AF中的LOC101928304/miR-490-3p/LRRC2网络。本研究发现的ceRNA网络可能有助于提高我们对lncRNA介导的ceRNA调控机制在AF发病机制中的理解。
