基于GEO数据库和生物信息学分析筛选大鼠心肌缺血再灌注损伤相关潜在通路和靶点

doi:10.3877/cma.j.issn.1674-0785.2023.04.013

目的

基于基因表达数据库（GEO）运用生物信息学分析筛选与大鼠心肌缺血再灌注损伤（MIRI）相关的关键基因（Hub gene）、通路及候选药物。

方法

从GEO数据库下载大鼠GSE122020数据集并利用GEO2R在线工具筛选差异表达基因（DEGs）。通过基因本体（GO）注释和京都基因和基因组百科全书（KEGG）通路分析研究MIRI相关DEGs涉及的病理生理过程和潜在的信号通路。使用STRING等数据库构建MIRI相关DEGs蛋白-蛋白相互作用（PPI）网络并筛选PPI网络中关键基因并使用Cytoscape软件进行可视化分析。利用Enrichr数据库筛选关键基因的潜在候选药物。

结果

共筛选出377个差异基因，其中109个上调、268个下调；KEGG通路富集分析显示，上调的109个基因富集到包括Janus激酶-信号转导及转录启动蛋白（JAK-STAT signaling pathway）等在内的6条通路；下调的268个基因富集到包括肿瘤坏死因子（TNF）等在内的58条通路。STRING和Gene MANIA数据库与Cytoscape软件联合分析筛选到20个关键DEGs，其中，上调的4个基因通过Enrichr数据库中的DSigDB数据库预测到包括烟酸、槲皮素等在内的55个潜在药物，下调的16个基因预测到包括3，3′-二吲哚基甲烷、重铬酸钾等在内的92个潜在药物。

结论

通过生物信息学方法，可以有效挖掘MIRI的致病基因，为进一步探讨MIRI的分子机制和治疗靶点提供新的思路和切入点。

关键词: GEO数据库, 生物信息学, 心肌缺血再灌注损伤, 差异表达基因

Objective

To screen key genes (Hub genes), pathways, and drug candidates related to myocardial ischemia-reperfusion injury (MIRI) in rats by bioinformatics analysis based on the gene expression omnibus (GEO) database.

Methods

The rat GSE122020 dataset was downloaded from the GEO database and differentially expressed genes (DEGs) were screened using the GEO2R online tool. Pathophysiological processes and potential signaling pathways involved in MIRI-related DEGs were investigated by Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The MIRI-related DEGs protein-protein interaction (PPI) network was constructed using databases such as STRING, and the key genes in the PPI network were screened and visualized using Cytoscape software. Potential drug candidates for key genes were screened using the Enrichr database.

Results

A total of 377 differential genes were screened, of which 109 were up-regulated and 268 down-regulated. KEGG pathway enrichment analysis showed that the up-regulated 109 genes were enriched in six pathways including the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway, while the 268 down-regulated genes were enriched in 58 pathways including the tumor necrosis factor (TNF) signaling pathway. Combined analysis based on the STRING and Gene MANIA databases and Cytoscape software resulted in the identification of 20 key DEGs, of which 4 were up-regulated and 16 down-reglated. For the 4 up-regulated genes, 55 potential drugs including nicotinic acid and quercetin were predicted based on the DSigDB database in the Enrichr database, while for the 16 down-regulated genes, 92 potential drugs including 3,3'-diindolylmethane and potassium dichromate were predicted.

Conclusion

Through bioinformatics methods, the pathogenic genes of MIRI can be effectively discovered, which provides new ideas and entry points for further exploring the molecular mechanism and therapeutic targets for MIRI.

Key words: GEO database, Bioinformatics analysis, Myocardial ischemia-reperfusion injury, Differentially expressed genes

图1 差异表达基因火山图。红色为上调基因；蓝色为下调基因

图2 DEGs的GO和KEGG功能富集分析。图a为109个基因的GO富集分析结果（p.adj＜0.1 & qvalue＜0.2），分别选取BP、CC、MF三个层面的前4个结果进行气泡图展示；图b为268个下调基因的GO富集分析结果（p.adj＜0.1 & qvalue＜0.2），分别选取BP、CC、MF三个层面的前4个结果进行气泡图展示；图c为109个上调基因的KEGG富集分析结果（p.adj＜0.1 & qvalue＜0.2），选取前5个结果进行网络图展示；图d为268个下调基因的KEGG富集分析结果（p.adj＜0.1 & qvalue＜0.2），选取前5个结果进行网络图展示

图3 Hub基因的PPI网络图。图a为得分前20个Hub基因，其中上调基因4个，下调基因16个；图b为得分前20 Hub基因的PPI网络图，共计188条边，20个节点；图c、d为得分前20 Hub基因的相关分子关系网络图

图4 Hub基因的潜在候选药物。图a为4个上调基因预测的前10位的潜在候选药物；图b为16个下调基因预测的前10位的潜在候选药物

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Bioinformatics screening of potential pathways and targets related to myocardial ischemia-reperfusion injury in rats based on GEO database

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Bioinformatics screening of potential pathways and targets related to myocardial ischemia-reperfusion injury in rats based on GEO database