基于生物信息学分析的抑郁症诊断标志物筛选

Screening of Diagnostic Markers for Depressive Disorder Based on Bioinformatics

目的:本研究旨在筛选重度抑郁症(MDD)的外周血潜在诊断标志物。方法:首先,从GEO数据库下载基因表达谱数据集GSE32280。通过R软件筛选MDD与正常对照外周血样本的差异表达基因(DEGs)。对筛选出来的DEGs进行GO功能注释以及KEGG通路富集分析;然后,采用Cytoscape软件构建蛋白质-蛋白质相互作用(PPI)网络,并从中筛选出关键(hub)基因。采用R软件对hub基因进行ROC分析,进而鉴定出具有诊断价值的hub基因。结果:从GSE32280数据集中共筛选出104个DEGs,其中上调基因47个,下调基因57个。GO功能注释显示,104个DEGs主要涉及细胞增殖、炎症反应、转运调控等功能。KEGG通路富集分析结果显示,DEGs主要富集在NK细胞介导的细胞毒性、细胞因子与其受体相互作用和趋化因子信号通路。从PPI网络中获取16个hub基因。对hub基因进行ROC分析结果显示,CXCL1、EGF、IFNG和CXCL8在MDD中具有较高的诊断价值。结论:CXCL1、EGF、IFNG和CXCL8是MDD重要的诊断标志物。

Objective:To screen the potential diagnostic biomarkers in peripheral blood lymphocytes of major depressive disorder(MDD).Methods:Firstly,the GSE32280 were downloaded from the Gene Expression Omnibus(GEO)database.The differentially expressed genes(DEGs)of MDD were detected by R software.GO function annotation and KEGG pathway enrichment analysis were carried out on the DEGs.Then,Cytoscape software was used to construct the protein-protein interaction(PPI)network,and hub genes were screened.ROC analysis was performed on hub genes by R software to screen out hub genes with diagnostic value.Results:A total of 104 DEGs were selected from GSE32280 dataset,among which 47 genes were up-regulated and 57 genes were down-regulated.The GO function annotation showed that 104 DEGs were mainly involved in cell proliferation,inflammatory response,transport regulation and so on.Enrichment analysis of KEGG pathway showed that DEGs were mainly concentrated in NK cell-mediated cytotoxicity,cytokine and receptor interaction,and chemokine signaling pathways.Sixteen hub genes were obtained from PPI network.ROC analysis indicated that CXCL1,EGF,IFNG and CXCL8 possessed high diagnostic value in MDD.Conclusion:CXCL1,EGF,IFNG and CXCL8 could be used as important diagnostic biomarkers for MDD.