基于生物信息学方法筛选抑郁症免疫诊断标志物  

Screening of immune diagnostic biomarkers for depression based on bioinformatics methods

作　　者：刘漠 孙大中 丁新蕊 姜春玉 张波[1] LIU Mo;SUN Dazhong;DING Xinrui;JIANG Chunyu;ZHANG Bo(Basic Medical College,Jiamusi University,Jiamusi 154007,China)

机构地区：[1]佳木斯大学基础医学院,黑龙江佳木斯154007

出　　处：《黑龙江医药科学》2025年第1期1-4,共4页Heilongjiang Medicine and Pharmacy

基　　金：黑龙江省创新训练项目国家级一般项目,编号:202210222038;黑龙江省卫生健康委科研课题,编号:20230202060379。

摘　　要：目的:通过生物信息学方法筛选、分析潜在的与抑郁症具有相关性的免疫细胞浸润生物学标志物及进一步探讨其在抑郁症发生、发展过程中的生物学作用。方法:从GEO数据库中选取与抑郁症相关的GSE-98793和GSE-52790数据集,首先所得数据经背景矫正和归一化以及降维处理后,分析数据集中抑郁症的差异表达基因;随后对差异基因使用SVM-RFE、LASSO和RF算法进行免疫相关性分析,构建免疫相关抑郁症诊断预测模型;GO功能和KEGG富集分析;免疫浸润CIBERSORT算法对DEGs进一步筛选,得出22个差异表达基因;使用STRING和Cytoscape软件构建PPI分子网络,并进行内部验证。结果:通过Cytoscap软件构建PPI网络,筛选出11个与免疫相关的差异表达基因,分别为TLR2、CD1C、S100A12、MARCO、CD48、XCL1、LTB、RETN、PTX3、IFNK、ERAP2基因,其中TLR2、S100A12、XCL1、LTB基因参与免疫炎症反应的调节,且参与免疫细胞的浸润,可作为免疫细胞浸润生物学标志物。结论:本研究筛选出了与抑郁症具有相关性且参与免疫细胞浸润的相关基因,可能作为预测其发生的生物标志物,有望将其研发为免疫靶向药物作用靶点提供可能性。Objective:To screen and analyze potential immune cell infiltration biomarkers related to depression through bioinformatics methods,and further explore their biological roles in the occurrence and development of depression.Methods:The depression-related datasets GSE-98793 and GSE-52790 were selected from the GEO database.Firstly,the obtained data underwent background correction,normalization and dimensionality reduction,and then the differentially expressed genes related to depression within the dataset were analyzed.Subsequently,immune-related analysis was performed on the differentially expressed genes using SVM-RFE,LASSO and RF algorithms to construct an immune-related depression diagnostic prediction model.GO function and KEGG enrichment analyses were performed.The CIBERSORT algorithm for immune infiltration was applied to further screen the DEGs,resulting in a total of 22 differentially expressed genes.STRING and Cytoscape software were used to construct a PPI molecular network and subjected to internal validation.Results:The PPI network was constructed using Cytoscape software,and 11 immune-related differentially expressed genes were screened out,including TLR2,CD1C,S100A12,MARCO,CD48,XCL1,LTB,RETN,PTX3,IFNK and ERAP2.Among them,TLR2,S100A12,XCL1 and LTB genes are involved in the regulation of immune inflammatory responses and the infiltration of immune cells,suggesting their potential as biomarkers for immune cell infiltration.Conclusion:The genes identified in this study,which are related to depression and involved in immune cell infiltration,have the potential to serve as biomarkers for predicting the onset of depression,and they offer possibilities for the development of targets for immune-targeted drug therapies.

关 键 词：抑郁症 生物信息学 免疫细胞浸润 生物标志物 差异基因 

分 类 号：R749.4[医药卫生—神经病学与精神病学]