摘要
目的 从生物信息学角度分析干燥综合征(sjogren's syndrome,SS)伴发疲劳相关的生物标记物,探讨SS伴发疲劳的发病机制,并通过差异基因预测治疗SS伴发疲劳的潜在中药。方法 从基因表达数据库(gene expression omnibus,GEO)下载GSE66795数据集,使用R语言分析得到差异表达基因(differentially expressed genes,DEGs),对其进行基因本体(gene ontology,GO)及京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)富集分析,后通过STRING数据库、Cytoscape软件及其插件得到关键基因,将关键基因与医学本体信息检索平台相互映射,筛选出治疗SS伴发疲劳的中药。结果 共得到48个DEGs,包括46个上调基因和2个下调基因,并筛选出10个关键基因。GO和KEGG富集分析显示,这些基因多富集甲型流感、丙型肝炎、麻疹、冠状病毒-COVID-19等多条病毒感染通路。筛选出3类潜在中药,分别为清肝、补肾、清热解毒类药物。结论 通过对DEGs的分析加深了对SS伴发疲劳发生机制的认识,并为中药治疗本病提供了潜在基因靶标及思路。
Objective Analyze the biomarkers related to fatigue in Sjogren's syndrome(SS)from the perspective of bioinformatics,explore the pathogenesis of SS accompanied fatigue,and predict potential traditional Chinese medicine treatments for SS accompanied fatigue through differential genes.Methods The GSE66795 data set was downloaded from the Gene Expression Omnibus(GEO),and the differentially expressed genes(DEGs)were obtained by using R language analysis.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis was performed,and then the key genes were obtained through STRING database,Cytoscape software and its plug-in.The key genes were mapped with the medical ontology information retrieval platform(Coremine Medical)to screen the Chinese medicine for treating SS accompanied fatigue.Results A total of 48 DEGs were screened,including 46 up-regulated genes and 2 down-regulated genes.Among them,10 key genes were screened.Go and KEGG enrichment analysis showed that these genes were mostly enriched influenza A,hepatitis C,and measles,coronavirus-COVID-19 and other viral infection pathways.The potential traditional Chinese medicines were mostly classified into three categories:clearing liver,tonifying kidney,clearing heat and detoxifying drugs.Conclusion Through the analysis of DEGs,we deepen our understanding of the mechanism of SS with fatigue,and provide potential gene targets and ideas for the treatment of traditional Chinese medicine.
作者
王梦洁
刘英
黄迪
WANG Mengjie;LIU Ying;HUANG Di(Shandong University of Traditional Chinese Medicine,Ji’nan 250300,China;Affiliated Hospital of Shandong University of Traditional Chinese Medicine,Ji’nan 250000,China)
出处
《中国中医基础医学杂志》
CAS
CSCD
2024年第1期82-87,共6页
JOURNAL OF BASIC CHINESE MEDICINE
基金
山东省自然科学基金项目(ZR2023MH332)
国家中医药管理局第三届国医大师传承工作室及全国名中医传承工作室建设项目(国中医药办人教函[2018] 119号)
山东省卫生健康委员会2020年齐鲁医派中医学术流派传承项目(鲁卫函[2020]132号)。
关键词
干燥综合征
疲劳
生物信息学
差异表达基因
中药预测
Sjogren's syndrome
Fatigue
Bioinformatics
Differentially expressed genes
Prediction of Chinese herbs
