数字中医药（英文）2025，Vol.8Issue(1)：90-99,10.DOI:10.1016/j.dcmed.2025.03.008
基于生物信息学分析糖尿病肾病自噬特征基因及潜在中药预测
Bioinformatics-based analysis of autophagy-related genes and prediction of potential Chinese medicines in diabetic kidney disease
摘要
Abstract
Objective To predict the autophagy-related pathogenesis and key diagnostic genes of diabet-ic kidney disease(DKD)through bioinformatics analysis,and to identify related Chinese medicines. Methods Data from sequencing microarrays GSE30528,GSE30529,and GSE1009 in the Gene Expression Omnibus(GEO)were employed.Differentially expressed genes(DEGs)with ad-justed P＜0.05 from GSE30528 and GSE30529 were identified.Combining these DEGs with the human autophagy gene database,Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses,and protein-protein interaction(PPI)network analy-sis were conducted on the obtained DKD autophagy-related genes.Subsequently,the least absolute shrinkage and selection operator(LASSO)regression and support vector machine-recursive feature elimination(SVM-RFE)algorithms were adopted to select autophagy-relat-ed genes.The diagnostic capability of these genes was assessed through analysis with the ex-ternal validation set from microarray GSE1009,and relevant Chinese medicines were inverse-ly predicted using the SymMap database. Results A total of 2 014 DEGs were selected from GSE30528 and GSE30529,leading to the identification of 37 DKD autophagy-related genes.GO analysis indicated 681 biological mechanisms,including autophagy regulation and plasma membrane microdomain activity.KEGG enrichment analysis identified 112 related signaling pathways.PPI network analysis showed a marked enrichment of autophagy-related genes in DKD.Through LASSO regres-sion and SVM-RFE,four core diagnostic genes for autophagy in DKD were identified:protein phosphatase 1 regulatory subunit 15A(PPP1R15A),hypoxia inducible factor 1 alpha subunit(HIF1α),deleted in liver cancer 1(DLC1),and ceroid lipofuscinosis neuronal 3(CLN3).The external validation set demonstrated high diagnostic efficiency for these genes.Finally,146 kinds of potential Chinese medicines were predicted using the SymMap database,with heat-clearing and detoxifying medicine and blood-activating and stasis-eliminating medicine ac-counting for the largest proportion(25/146 and 13/146,respectively). Conclusion This study analyzed and validated bioinformatics sequencing databases to eluci-date the potential molecular mechanisms of DKD autophagy and predicted key diagnostic genes,potential therapeutic targets,and related Chinese medicines,laying a solid foundation for clinical research and application.关键词
生物信息学/差异表达基因/糖尿病肾脏疾病/自噬基因/中药预测Key words
Bioinformatics/Differentially expressed genes/Diabetic kidney disease/Autophagy genes/Prediction of Chinese medicines引用本文复制引用
邢玉凤,彭紫凝,叶朝阳..基于生物信息学分析糖尿病肾病自噬特征基因及潜在中药预测[J].数字中医药（英文）,2025,8(1):90-99,10.基金项目
National Natural Science Foundation of China(82170747),and Shanghai Key Laboratory of Traditional Chinese Clinical Medicine(20DZ2272200). （82170747）
