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生物信息学方法下脑老化关键基因与通路的筛选及中药预测研究 被引量:2

Scr eening of key genes and pathways of brain aging and prediction of potential effective Chinese medicinals: based on bioinformatics
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摘要 通过生物信息学技术分析比较认知完好的老年人(60~99岁)与中青年人(20~59岁)脑部海马组织(hippocampal tissue,HC)的基因芯片数据,初步筛选出差异表达基因,进而预测治疗脑老化的潜在中药药物。从基因表达数据库(Gene Expression Omnibus,GEO)下载GSE11882基因芯片,基于R语言软件筛选差异表达基因(differentially expressed genes, DEGs),通过STRING数据库、Cytoscape软件及其插件分析得到差异表达基因的关键基因,对关键基因进行基因本体论(Gene Ontology,GO)及京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)分析,通过关键基因与医学本体信息检索平台(Coremine Medical)相互映射,筛选治疗脑老化的中药,并构建"药物-活性成分-作用靶点"网络。筛选出268个差异表达基因,包括246个下调基因和22个上调基因。差异表达基因共得出15个关键基因,关键基因主要参与白细胞迁移、中性粒细胞活化、细胞趋化运动、小胶质细胞活化、免疫效应过程的调节等生物过程。KEGG通路分析显示关键基因主要富集于炎症过程、免疫反应、细胞因子-细胞因子受体相互作用、PI3K-Akt信号通路、Rap1信号通路、趋化因子信号通路、Toll样受体信号通路、产生Ig A的肠道免疫网络通路等。筛选得到治疗脑老化的潜在中药为三七、人参、丹参、黄芪等。差异表达基因和关键基因的分析促进了对脑老化机制的理解,该研究为脑老化中药干预的新药开发提供了潜在基因靶标与研发思路。 Microarray data of hippocampal tissue(HC) of the cognitively intact elderly(60-99 years old) were compared with those of the middle-aged and the young(20-59 years old) by bioinformatics techniques to initially screen out differentially expressed genes(DEGs) and then predict potential effective Chinese medicinals for the treatment of brain aging. The gene expression profile(accession: GSE11882) was downloaded from the Gene Expression Omnibus(GEO) and DEGs were screened based on R package. The key DEGs were identified by STRING, Cytoscape and the plug-in, followed by Gene Ontology(GO) term and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis. Then the key genes and the medical ontology information retrieval platform(Coremine Medical) were mapped against each other to single out the Chinese medicinals for the treatment of brain aging and construct the " Chinese medicinal-active constituent-target" network. Among the resultant 268 DEGs(246 down-regulated and 22 up-regulated), the 15 key genes were mainly involved in biological processes such as leukocyte migration, neutrophil activation, cell chemotaxis, microglia activation and response to external stimulus, and pathways such as inflammatory process, immune response, cytokine-cytokine receptor interaction, PI3 K-Akt signaling pathway, Rap1 signaling pathway, chemokine signaling pathway and Toll-like receptor signaling pathway. The potential effective Chinese medicinals were Notoginseng Radix et Rhizoma, Ginseng Radix et Rhizoma, Salviae Miltiorrhizae Radix et Rhizoma and Astragali Radix. The analysis of DEGs and key genes enhances the understanding of the mechanisms of brain aging. This study provides potential gene targets and ideas for the development of Chinese medicine for brain aging.
作者 吴丹 王雪 杨静 吴烨 刘逸南 修成奎 王佳丽 刘奕清 雷燕 WU Dan;WANG Xue;YANG Jing;WU Ye;LIU Yi-nan;XIU Cheng-kui;WANG Jia-li;LIU Yi-qing;LEI Yan(Beijing Key Laboratory of Taditional Chinese Medicine Basic Research on Prevention and Treatment of Major Disease,Experimental Research Center,China Academy of Chinese Medical Sciences,Beijing 100700,China)
出处 《中国中药杂志》 CAS CSCD 北大核心 2021年第21期5701-5709,共9页 China Journal of Chinese Materia Medica
基金 国家自然科学基金项目(81503448,82074260) 中国中医科学院自主选题项目(ZZ2019012)。
关键词 脑老化 生物信息学 差异表达基因 中药预测 brain aging bioinformatics differentially expressed genes prediction of taditional Chinese medicine
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