海南医学院学报2024，Vol.30Issue(2)：120-128,9.DOI:10.13210/j.cnki.jhmu.20230920.001
通过生物信息学分析肾移植后慢性排斥反应差异表达基因
To analyze the differentially expressed genes in chronic rejection after renal transplantation by bioinformatics
摘要
Abstract
Objective:To use bioinformatics technology to analyze the differentially expressed genes in chronic rejection af-ter renal transplantation,we can screen potential pathogenic targets related to the development of the disease,and provide theoreti-cal basis for finding new therapeutic targets.Methods:Gene microarray data were downloaded from the Gene Expression Omnibus(GEO)database,and cross-calculations were performed to identify differentially expressed genes(DEGs).Differentially ex-pressed genes(DEGs)and gene ontology(GO)analysis are used to study the expression differences of genes under different con-ditions as well as their functions and interrelationships,while Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis is a tool to explore the functions and pathways of genes in specific biological processes.By calculating the distribution of immune cell infiltration,the immune infiltration results of the rejection group can be analyzed as traits in the weighted gene co-expression network analysis(WGCNA)to obtain the genes related to rejection.Then,a protein-protein interaction network(PPI)was constructed using STRING database and Cytoscape software to identify hub gene markers.Results:A total of 60 inte-grated DEGs were obtained from 3 datasets(GSE7392,GSE181757,GSE222889).Through GO and KEGG analysis,GEDs mainly focused on the regulation of immune response,defense response,regulation of immune system processes,and stimulus re-sponse.Pathways were mainly enriched in antigen processing and presentation,Epstein-Barr virus infection,graft-versus-host dis-ease,allograft rejection,natural killer cell-mediated cytotoxicity,etc.HLA-A,HLA-B,HLA-F and TYROBP were identified as Hub genes by WGCNA and PPI network screening.The data GSE21374 with clinical information was selected to construct the diagnostic efficacy and risk prediction model maps of the four Hub genes,and the results showed that all the four hub genes had good diagnostic value(the area under the curve was 0.794-0.819).It can be concluded by reasoning that four genes,HLA-A,HLA-B,HLA-F and TYROBP,may have important roles in the development and progression of chronic rejection after renal transplantation.Conclusion:DEGs play an important role in the study of the pathogenesis of chronic rejection after kidney trans-plantation.Through enrichment analysis,hub gene screening,and inference analysis of related diagnostic efficacy and disease risk prediction,it provides theoretical support for further study of the pathogenesis of chronic rejection after kidney transplantation and discovery of new therapeutic targets.关键词
肾脏疾病/肾移植/慢性排斥反应/生物信息学分析/GEO数据库/Hub基因Key words
Kidney disease/Kidney transplantation/Chronic rejection/Bioinformatics analysis/GEO database/Hub gene分类
医药卫生引用本文复制引用
靳帅,余一凡,宋佳华,李涛,王毅..通过生物信息学分析肾移植后慢性排斥反应差异表达基因[J].海南医学院学报,2024,30(2):120-128,9.基金项目
This study was supported by National Natural Science Foundation of China(82260154) 国家自然科学基金资助项目(82260154) （82260154）
