Department of Burns, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi China.
Department of Burns and Surgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, China.
Bioengineered. 2021 Dec;12(1):2592-2602. doi: 10.1080/21655979.2021.1936892.
Long non-coding RNAs (lncRNAs) were considered to be involved in vascular complications in diabetes mellitus, but still only limited knowledge in this regard has been obtained. Herein, we further explored the roles of lncRNAs and mRNAs in diabetic vasculopathy (DV) through conducting bioinformatics analysis using data set downloaded from GEO database. The differentially expressed lncRNAs and mRNAs were identified by edge package. GO enrichment analysis and KEGG pathway analysis were performed based on clusterprofiler package. The relationship between lncRNA and miRNA was predicted using starBase database, and the potential mRNAs targeted by miRNAs were predicted by TargetScan, miRTarbase and miRDB database. The string database was used to analyze the protein-protein interaction (PPI). As a result, a total of 12 lncRNAs and 711 mRNAs were found to be differentially expressed in the diabetic subdermal endothelial cells compared with normal controls. A ceRNA network was established, which was composed of seven lncRNA nodes, 49 miRNA nodes, 58 mRNA nodes and 183 edges, and MSC-AS1 and LINC01550 may serve as key nodes. GO function enrichment analysis showed enrichments of epithelial cell proliferation, intercellular junction, and cell adhesion molecule binding. KEGG pathway analysis revealed 33 enriched pathways. PPI protein interaction analysis identified 57 potential ceRNA-related proteins. Overall, this study suggests that multiple lncRNAs, specifically MSC-AS1 and LINC01550, may play an important role in DV development and they are like to be developed as the therapeutic targets for DV. However, further experiments in vitro and in vivo should be conducted to validate our results.
长链非编码 RNA（lncRNA）被认为参与糖尿病血管并发症，但在这方面的知识仍然有限。在此，我们通过使用从 GEO 数据库下载的数据进行生物信息学分析，进一步探讨了 lncRNA 和 mRNA 在糖尿病血管病变（DV）中的作用。通过 edge 包识别差异表达的 lncRNA 和 mRNA。基于 clusterprofiler 包进行 GO 富集分析和 KEGG 通路分析。使用 starBase 数据库预测 lncRNA 和 miRNA 之间的关系，使用 TargetScan、miRTarbase 和 miRDB 数据库预测 miRNA 靶向的潜在 mRNAs。使用 string 数据库分析蛋白质-蛋白质相互作用（PPI）。结果，与正常对照组相比，糖尿病皮肤下内皮细胞中发现共有 12 个 lncRNA 和 711 个 mRNAs 差异表达。建立了一个 ceRNA 网络，由 7 个 lncRNA 节点、49 个 miRNA 节点、58 个 mRNA 节点和 183 个边缘组成，MSC-AS1 和 LINC01550 可能作为关键节点。GO 功能富集分析显示上皮细胞增殖、细胞间连接和细胞黏附分子结合的富集。KEGG 通路分析显示 33 个富集通路。PPI 蛋白相互作用分析确定了 57 个潜在的 ceRNA 相关蛋白。总的来说，本研究表明，多种 lncRNA，特别是 MSC-AS1 和 LINC01550，可能在 DV 发展中发挥重要作用，它们可能被开发为 DV 的治疗靶点。然而，还需要进行体外和体内的进一步实验来验证我们的结果。
