Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province, China.
Department of Medical Records, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei Province, China.
DNA Cell Biol. 2021 Feb;40(2):283-292. doi: 10.1089/dna.2020.6106. Epub 2020 Dec 17.
Long noncoding RNAs (lncRNAs) have been increasingly accepted to function importantly in human diseases by serving as competing endogenous RNAs (ceRNAs). To date, the ceRNA mechanisms of lncRNAs in the progression of atherosclerosis (AS) remain largely unclear. On the basis of ceRNA theory, we implemented a multistep computational analysis to construct an lncRNA-mRNA network for AS progression (ASpLMN). The probe reannotation method and microRNA-target interactions from databases were systematically integrated. Three lncRNAs (, , and ) with central topological features in the ASpLMN were firstly identified. By using subnetwork analysis, we then obtained two highly clustered modules and one dysregulated module from the ASpLMN network. These modules, sharing three lncRNAs (, , and ), were significantly enriched in biological pathways such as regulation of actin cytoskeleton, tryptophan metabolism, lysosome, and arginine and proline metabolism. In addition, random walking in the ASpLMN network indicated that lncRNA and may also play an essential role in the pathology of AS progression. The identified six lncRNAs from the aforementioned steps could distinguish advanced- from early-staged AS, with a strong diagnostic power for AS occurrence. In conclusion, the results of this study will improve our understanding about the ceRNA-mediated regulatory mechanisms in AS progression, and provide novel lncRNAs as biomarkers or therapeutic targets for acute cardiovascular events.
长链非编码 RNA（lncRNA）作为竞争性内源 RNA（ceRNA），在人类疾病中发挥重要作用的观点已被广泛接受。迄今为止，lncRNA 在动脉粥样硬化（AS）进展中的 ceRNA 机制在很大程度上仍不清楚。基于 ceRNA 理论，我们进行了多步计算分析，构建了一个用于 AS 进展（ASpLMN）的 lncRNA-mRNA 网络。系统地整合了探针重新注释方法和数据库中的 miRNA-靶相互作用。首先鉴定出 ASpLMN 中具有中心拓扑特征的三个 lncRNA（lncRNA 12736，lncRNA 14033 和 lncRNA 3160）。然后通过子网络分析，我们从 ASpLMN 网络中获得了两个高度聚类的模块和一个失调模块。这些模块共享三个 lncRNA（lncRNA 12736，lncRNA 14033 和 lncRNA 3160），显著富集于生物途径，如肌动蛋白细胞骨架调节、色氨酸代谢、溶酶体和精氨酸和脯氨酸代谢。此外，ASpLMN 网络中的随机游走表明 lncRNA 和 也可能在 AS 进展的病理学中发挥重要作用。从上述步骤中鉴定出的六个 lncRNA 可以区分晚期和早期 AS，对 AS 发生具有很强的诊断能力。总之，本研究的结果将提高我们对 AS 进展中 ceRNA 介导的调控机制的认识，并为急性心血管事件提供新的 lncRNA 作为生物标志物或治疗靶点。
