摘要
目的利用加权基因共表达网络分析(WGCNA)构建局灶节段性肾小球硬化症(FSGS)的枢纽基因网络,筛选与FSGS相关的枢纽基因。方法从基因表达综合数据库(GEO)下载表达谱芯片GSE104948并获取FSGS和正常肾小球组织的基因表达谱,利用WGCNA构建FSGS的基因共表达网络模块,并筛选与FSGS发生相关性最高的模块,并对该模块内的基因进行GO和KEGG富集分析,从最有意义的GO分析项中构建共表达子网络,使用CytoHubba插件鉴定枢纽基因。同时使用Nephroseq芯片数据库验证枢纽基因的临床意义。结果共获得16例FSGS和21例正常肾小球标本基因的数据,共筛选出5942个基因,8个共表达模块,其中brown模块被认为与FSGS显著相关,该模块中74个差异表达基因,包括68个上调基因和6个下调基因,对其进行富集分析,主要富集于炎症、细胞外基质和细胞因子相互作用等生物学方面。关键的枢纽基因为CD48基因。Nephroseq芯片数据库检测发现CD48在FSGS肾小球组织中表达上调且CD48表达与肾小球滤过率呈负相关。结论利用WGCNA可识别与FSGS相关的枢纽基因,为FSGS的治疗提供新的潜在靶标。
Objective To construct a prognostic gene network for focal segmental glomerulosclerosis(FSGS)using weighted gene co-expression analysis(WGCNA)and to screen hub genes related to FSGS.Methods The gene co-expression network module for FSGS was constructed by WGCNA,and the module with the highest correlation with FSGS was screened.The module analysis was carried out and the genes in the module were enriched by GO analysis and KEGG pathway analysis,and the co-expression network was constructed.CytoHubba Plug-in was used to identify the hub genes.Nephroseq database was used to verify the clinical significance of the hub gene.Results The data of 16 FSGS and 21 normal glomerular samples were obtained.5942 genes and 8 co-expression modules were screened,and the brown module was considered to be significantly related to FSGS.74 differentially expressed genes in this module,including 68 up-regulated genes and 6 down-regulated genes,and they were enriched mainly in terms such as inflammation,extracellular matrix and cytokine interaction.The key gene was CD48.Analysis of the data from Nephroseq database showed that CD48 was significantly over cxpressed in FSGS glomerular tissues,and the expression of CD48 was negatively correlated with glomerular filtration rate.Conclusion WGCNA can identify the key genes related to FSGS and provide a new potential target for the treatment of FSGS.
出处
《浙江临床医学》
2020年第12期1710-1713,共4页
Zhejiang Clinical Medical Journal
