The Department of Cardiovascular Medicine, The Second People's Hospital of Changshu, Jiangsu, China.
Biomed Res Int. 2020 Oct 6;2020:1470867. doi: 10.1155/2020/1470867. eCollection 2020.
Acute myocardial infarction (AMI) is regarded as an urgent clinical entity, and identification of differentially expressed genes, lncRNAs, and altered pathways shall provide new insight into the molecular mechanisms behind AMI.
Microarray data was collected to identify key genes and lncRNAs involved in AMI pathogenesis. The differential expression analysis and gene set enrichment analysis (GSEA) were employed to identify the upregulated and downregulated genes and pathways in AMI. The protein-protein interaction network and protein-RNA interaction analysis were utilized to reveal key long noncoding RNAs.
In the present study, we utilized gene expression profiles of circulating endothelial cells (CEC) from 49 patients of AMI and 50 controls and identified a total of 552 differentially expressed genes (DEGs). Based on these DEGs, we also observed that inflammatory response-related genes and pathways were highly upregulated in AMI. Mapping the DEGs to the protein-protein interaction (PPI) network and identifying the subnetworks, we found that and were the hub nodes of two subnetworks with the highest connectivity, which were found to be involved in circadian rhythm and organ- or tissue-specific immune response. Furthermore, 23 lncRNAs were differentially expressed between AMI and control groups. Specifically, we identified some functional lncRNAs, including and its antisense RNA, , and three lncRNAs (, , and ), which were predicted to be interacting with and participate in Toll-like receptor signaling pathway. In addition, we also employed the MMPC algorithm to identify six gene signatures for AMI diagnosis. Particularly, the multivariable SVM model based on the six genes has achieved a satisfying performance (AUC = 0.97).
In conclusion, we have identified key regulatory lncRNAs implicated in AMI, which not only deepens our understanding of the lncRNA-related molecular mechanism of AMI but also provides computationally predicted regulatory lncRNAs for AMI researchers.
急性心肌梗死(AMI)被认为是一种紧急的临床实体,鉴定差异表达基因、lncRNAs 和改变的途径将为 AMI 背后的分子机制提供新的见解。
收集微阵列数据以鉴定参与 AMI 发病机制的关键基因和 lncRNAs。采用差异表达分析和基因集富集分析(GSEA)鉴定 AMI 中的上调和下调基因和途径。利用蛋白质-蛋白质相互作用网络和蛋白质-RNA 相互作用分析揭示关键长非编码 RNA。
在本研究中,我们利用 49 例 AMI 患者和 50 例对照的循环内皮细胞(CEC)的基因表达谱,共鉴定出 552 个差异表达基因(DEGs)。基于这些 DEGs,我们还观察到 AMI 中炎症反应相关基因和途径高度上调。将 DEGs 映射到蛋白质-蛋白质相互作用(PPI)网络并识别出具有最高连接度的两个子网的节点,我们发现和是两个具有最高连接度的子网的节点,这些节点被发现与昼夜节律和器官或组织特异性免疫反应有关。此外,23 个 lncRNAs 在 AMI 和对照组之间差异表达。具体来说,我们鉴定了一些功能 lncRNAs,包括和它的反义 RNA、、和三个 lncRNAs(、、和),它们被预测与和参与 Toll 样受体信号通路。此外,我们还采用 MMPC 算法识别用于 AMI 诊断的六个基因特征。特别是,基于这六个基因的多变量 SVM 模型取得了令人满意的性能(AUC=0.97)。
总之,我们已经鉴定出与 AMI 相关的关键调控 lncRNAs,这不仅加深了我们对 AMI 相关 lncRNA 分子机制的理解,还为 AMI 研究人员提供了计算预测的调控 lncRNAs。