Sun Yaxuan, Wang Jing, Han Bin, Meng Kun, Han Yan, Ding Yongxia
Department of Neurology, Shanxi People's Hospital, Taiyuan, China.
College of Nursing, Shanxi Medical University, Taiyuan, China.
Front Integr Neurosci. 2021 Aug 16;15:638114. doi: 10.3389/fnint.2021.638114. eCollection 2021.
This study aimed to investigate the possible molecular mechanisms associated with ischemic stroke through the construction of a lncRNA-miRNA-mRNA network. miRNA expression profile in GSE55937, mRNA and lncRNA expression profiles in GSE122709, and mRNA expression profile in GSE146882 were downloaded from the NCBI GEO database. After the identification of the differentially expressed miRNA, lncRNA, and mRNA using GSE55937 and GSE122709 in ischemic stroke control groups, a protein-protein interaction (PPI) network was constructed. The lncRNA-miRNA, lncRNA-mRNA, and miRNA-mRNA pairs were predicted, and a lncRNA-miRNA-mRNA network was constructed. Additionally, the gene-drug interactions were predicted. Characteristic genes were used to construct a support vector machine (SVM) model and verified using quantitative reverse transcription polymerase chain reaction. In total 38 miRNAs, 115 lncRNAs, and 990 mRNAs were identified between ischemic stroke and control groups. A PPI network with 371 nodes and 2306 interaction relationships was constructed. The constructed lncRNA-miRNA-mRNA network contained 7 mRNAs, 14 lncRNAs, such as SND1-IT1, NAPA-AS1, LINC01001, LUCAT1, and ASAP1-IT2, and 8 miRNAs, such as miR-93-3p and miR-24-3p. The drug action analysis of the seven differential mRNAs included in the lncRNA-miRNA-mRNA network showed that four genes (, , and ) were predicted as molecular targets of drugs. The area under the curve of the constructed SVM model was 0.886. The verification results of the relative expression of RNA by qRT-PCR were consistent with the results of bioinformatics analysis. , , , and may serve as therapeutic targets of ischemic stroke. lncRNA-miRNA-mRNA regulatory axis such as SND1-IT1/NAPA-AS1/LINC01001-miR-24-3p-/ and LUCAT1/ASAP1-IT2-miR-93-3p may play important roles in the progression of ischemic stroke.
本研究旨在通过构建lncRNA-miRNA-mRNA网络来探究与缺血性中风相关的可能分子机制。从NCBI GEO数据库下载了GSE55937中的miRNA表达谱、GSE122709中的mRNA和lncRNA表达谱以及GSE146882中的mRNA表达谱。在使用GSE55937和GSE122709鉴定缺血性中风对照组中差异表达的miRNA、lncRNA和mRNA后，构建了蛋白质-蛋白质相互作用（PPI）网络。预测了lncRNA-miRNA、lncRNA-mRNA和miRNA-mRNA对，并构建了lncRNA-miRNA-mRNA网络。此外，还预测了基因-药物相互作用。使用特征基因构建支持向量机（SVM）模型，并通过定量逆转录聚合酶链反应进行验证。在缺血性中风组和对照组之间总共鉴定出38个miRNA、115个lncRNA和990个mRNA。构建了一个包含371个节点和2306个相互作用关系的PPI网络。构建的lncRNA-miRNA-mRNA网络包含7个mRNA、14个lncRNA，如SND1-IT1、NAPA-AS1、LINC01001、LUCAT1和ASAP1-IT2，以及8个miRNA，如miR-93-3p和miR-24-3p。对lncRNA-miRNA-mRNA网络中包含的7个差异mRNA进行的药物作用分析表明，4个基因（，，和）被预测为药物的分子靶点。构建的SVM模型的曲线下面积为0.886。qRT-PCR对RNA相对表达的验证结果与生物信息学分析结果一致。，，，和可能作为缺血性中风的治疗靶点。lncRNA-miRNA-mRNA调控轴，如SND1-IT1/NAPA-AS1/LINC01001-miR-24-3p-/和LUCAT1/ASAP1-IT2-miR-93-3p可能在缺血性中风的进展中起重要作用。
