内科2025，Vol.20Issue(2)：188-194,7.DOI:10.16121/j.cnki.cn45-1347/r.2025.02.12
基于GEO数据库的衰老关键基因筛选与生物信息学分析
GEO database-based screening and bioinformatics analysis of key aging-related genes
摘要
Abstract
Objective Using bioinformatics methods to screen key aging-related genes and explore the mechanisms of aging,as well as the association between aging-related pathways and cognition.Methods Aging-related microarray data of rat hippocampal samples were downloaded from the GEO database.The R programming language was used to screen differentially expressed genes(DEGs),followed by Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Gnomes(KEGG)pathway analysis.The STRING 12.0 database was employed to construct protein-protein interaction(PPI)networks,and Cytoscape software with the CytoHubba plugin was used to analyze hub genes in the PPI networks for screening key aging-related genes.Results In the GSE5666 dataset,23 upregulated aging-related DEGs were identified,while no downregulated aging-related DEG or cognition-related DEG was found.In the GSE9990 dataset,70 upregulated and 9 downregulated aging-related DEGs were screened.GO functional enrichment analysis showed that the above DEGs were primarily involved in biological processes such as antigen processing,adaptive immune response,and immunoglobulin-mediated immune response.KEGG pathway analysis indicated that the DEGs were mainly enriched in infection-and immunity-related pathways.Through PPI network analyses,four common key genes were identified in the GSE9990 and GSE5666 datasets:Cd74,RT1-Da,C1qb,and Ctss.Conclusion Immune responses involving major histocompatibility complex class Ⅱ are associated with aging in rats,but aging-related genes may not necessarily be linked to cognitive function deficits.关键词
衰老/抗原呈递/免疫/Ⅱ类主要组织相容性复合体/差异表达基因/生物信息学Key words
Aging/Antigen processing/Immunity/Major histocompatibility complex class Ⅱ/Differentially expressed genes/Bioinformatics分类
基础医学引用本文复制引用
刘丽丽,黄东明,杨翠语..基于GEO数据库的衰老关键基因筛选与生物信息学分析[J].内科,2025,20(2):188-194,7.基金项目
广西自然科学基金(2020JJA140152) （2020JJA140152）
