Liu Yaozhong, Liu Na, Bai Fan, Liu Qiming
Department of Cardiovascular Medicine, Second Xiangya Hospital, Central South University, Changsha, China.
Front Genet. 2021 Jun 23;12:653474. doi: 10.3389/fgene.2021.653474. eCollection 2021.
Atrial fibrillation (AF) is the most common arrhythmia. We aimed to construct competing endogenous RNA (ceRNA) networks associated with the susceptibility and persistence of AF by applying the weighted gene co-expression network analysis (WGCNA) and prioritize key genes using the random walk with restart on multiplex networks (RWR-M) algorithm. RNA sequencing results from 235 left atrial appendage samples were downloaded from the GEO database. The top 5,000 lncRNAs/mRNAs with the highest variance were used to construct a gene co-expression network using the WGCNA method. AF susceptibility- or persistence-associated modules were identified by correlating the module eigengene with the atrial rhythm phenotype. Using a module-specific manner, ceRNA pairs of lncRNA-mRNA were predicted. The RWR-M algorithm was applied to calculate the proximity between lncRNAs and known AF protein-coding genes. Random forest classifiers, based on the expression value of key lncRNA-associated ceRNA pairs, were constructed and validated against an independent data set. From the 21 identified modules, magenta and tan modules were associated with AF susceptibility, whereas turquoise and yellow modules were associated with AF persistence. ceRNA networks in magenta and tan modules were primarily involved in the inflammatory process, whereas ceRNA networks in turquoise and yellow modules were primarily associated with electrical remodeling. A total of 106 previously identified AF-associated protein-coding genes were found in the ceRNA networks, including 16 that were previously implicated in the genome-wide association study. Myocardial infarction-associated transcript (MIAT) and LINC00964 were prioritized as key lncRNAs through RWR-M. The classifiers based on their associated ceRNA pairs were able to distinguish AF from sinus rhythm with respective AUC values of 0.810 and 0.940 in the training set and 0.870 and 0.922 in the independent test set. The AF-related single-nucleotide polymorphism rs35006907 was found in the intronic region of LINC00964 and negatively regulated the LINC00964 expression. Our study constructed AF susceptibility- and persistence-associated ceRNA networks, linked genetics with epigenetics, identified MIAT and LINC00964 as key lncRNAs, and constructed random forest classifiers based on their associated ceRNA pairs. These results will help us to better understand the mechanisms underlying AF from the ceRNA perspective and provide candidate therapeutic and diagnostic tools.
心房颤动（AF）是最常见的心律失常。我们旨在通过应用加权基因共表达网络分析（WGCNA）构建与AF易感性和持续性相关的竞争性内源RNA（ceRNA）网络，并使用多重网络上的重启随机游走（RWR-M）算法对关键基因进行优先级排序。从GEO数据库下载了235个左心耳样本的RNA测序结果。使用方差最高的前5000个lncRNA/mRNA，通过WGCNA方法构建基因共表达网络。通过将模块特征基因与心房节律表型相关联，识别出与AF易感性或持续性相关的模块。以模块特异性方式预测lncRNA-mRNA的ceRNA对。应用RWR-M算法计算lncRNA与已知AF蛋白编码基因之间的接近度。基于关键lncRNA相关ceRNA对的表达值构建随机森林分类器，并在独立数据集中进行验证。在识别出的21个模块中，品红色和棕褐色模块与AF易感性相关，而蓝绿色和黄色模块与AF持续性相关。品红色和棕褐色模块中的ceRNA网络主要参与炎症过程，而蓝绿色和黄色模块中的ceRNA网络主要与电重构相关。在ceRNA网络中总共发现了106个先前确定的与AF相关的蛋白编码基因，其中16个曾在全基因组关联研究中涉及。心肌梗死相关转录本（MIAT）和LINC00964通过RWR-M被优先列为关键lncRNA。基于其相关ceRNA对的分类器能够在训练集中分别以0.810和0.940的AUC值以及在独立测试集中以0.870和0.922的AUC值区分AF与窦性心律。在LINC00964的内含子区域发现了与AF相关的单核苷酸多态性rs35006907，并且它对LINC00964的表达具有负调控作用。我们的研究构建了与AF易感性和持续性相关的ceRNA网络，将遗传学与表观遗传学联系起来，将MIAT和LINC00964鉴定为关键lncRNA，并基于其相关ceRNA对构建了随机森林分类器。这些结果将有助于我们从ceRNA角度更好地理解AF的潜在机制，并提供候选的治疗和诊断工具。
