基于生物信息学分析动脉粥样硬化的关键基因及潜在中药

Key Genes and Potential Prediction of Traditional Chinese Medicine in Treatment of Atherosclerosis Based on Bioinformatics

目的:基于生物信息学预测与动脉粥样硬化(atherosclerosis,AS)相关的关键基因及中药,为AS诊断、药物干预提供新思路。方法:从高通量基因表达(gene expression omnibus,GEO)数据库下载GSE13985和GSE6088的基因表达数据集,在AS和健康样本之间鉴定差异表达基因(differentially expressed genes,DEGs)。随后进行基因本体(Gene Ontology,GO)功能富集分析、京都基因和基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集分析,并将筛选出的DEGs排列成蛋白质-蛋白质相互作用(protein-protein interaction,PPI)网络,利用COREMINE数据库对关键基因进行中药预测。结果:在GSE13985数据集中总共鉴定出2135个DEGs(744个上调,1391个下调),在GSE6088数据集中鉴定出1725个DEGs(773个上调,952个下调)。富集分析涉及98个GO条目(52个BF,28个CC,18个MF),18条KEGG信号通路。结论:黄芩等中药可能通过代谢途径和缺氧诱导因子-1信号通路调控关键基因CTNNB1、POLR2A和CREBBP的表达发挥治疗AS的作用。

Objective:To predict the key genes and traditional Chinese medicine related to atherosclerosis(AS)based on bioinformatics,to provide new ideas for AS diagnosis and drug intervention.Method:Download the gene expression datasets of GSE13985 and GSE6088 from the gene expression omnibus(GEO)database and identify differentially expressed genes(DEGs)between AS and healthy samples.Subsequently,gene ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were performed,and the selected DEGs were arranged into a protein protein interaction(PPI)network.The COREMINE database was used to predict key genes for traditional Chinese medicine.Result:A total of 2135 DEGs(744 upregulated and 1391 downregulated)were identified in the GSE13985 dataset,and 1725 DEGs(773 upregulated and 952 downregulated)were identified in the GSE6088 dataset.Enrichment analysis involved 98 GO entries(52 BF,28 CC,18 MF)and 18 KEGG signaling pathways.Conclusion:Traditional Chinese medicine such as Huangqin(scutellaria baicalensis)may exert therapeutic effects on AS by regulating the expression of key genes CTNNB1,POLR2A,and CREBBP through metabolic pathways and hypoxia inducible factor-1 signaling pathway.