基于自噬相关基因表达水平的尿毒症诊断模型  

A diagnostic model of uremia based on autophagy⁃related gene expression levels

作　　者：马思佳 王永涛 谷劼楠 徐世杰[1] MA Sijia;WANG Yongtao;GU Jienan;XU Shijie(Institute of Basic Theory of Traditional Chinese Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China)

机构地区：[1]中国中医科学院中医基础理论研究所,北京100700

出　　处：《生物信息学》2024年第4期296-304,共9页Chinese Journal of Bioinformatics

基　　金：中国中医科学院科技创新工程项目(No.CI2021B001)

摘　　要：基于生物信息方法筛选尿毒症(Uremia,UA)与自噬相关的差异表达基因(AT-DEGs),探讨自噬相关生物标志物在UA发生发展中的作用,以期为UA的诊断和治疗提供新的思路。从GEO数据库下载原始数据集并进一步整合分析。采用R软件筛选UA组与健康对照组的差异表达基因,之后对差异基因进行GO,KEGG和DisGeNet富集分析。通过LASSO和交叉验证筛选核心的AT-DEGs,之后构建受试者工作特征(ROC)曲线,探讨关键基因对UA的诊断价值。根据ROC曲线分析显示,FKBP1B和FOS是与自噬相关具有较高的诊断价值关键基因,可为后期UA的诊断和治疗提供一定的思路与支持。This study screens the differentially expressed genes associated with autophagy(AT⁃DEGs)in uremia(UA)based on biological information methods,and explores the role of autophagy related biomarkers in the occurrence and development of UA,with a view to providing new ideas for the diagnosis and treatment of UA.Downloads the raw data set from the GEO database and further integrate the analysis.The DEGs of UA group and healthy control group are screened by R software,and then GO,KEGG and DisGeNet enrichment analysis of the AT⁃DEGs are performed.The core AT⁃DEGs are screened by LASSO and cross validation,and then the receiver operating characteristic(ROC)curve is constructed to explore the diagnostic value of core genes for UA.According to the ROC curve analysis,FKBP1B and FOS are the core genes related to autophagy with high diagnostic value,which can provide certain ideas and support for the diagnosis and treatment of UA in the follow⁃up study.

关 键 词：尿毒症 生物信息学 自噬 诊断基因 GEO数据库 

分 类 号：Q344.13[生物学—遗传学]