基于GEO数据库筛选影响同种异体肾移植术后肾功能的关键基因及生物学因素

Screening of key genes and biological factors affecting renal function after allogeneic kidney transplantation based on GEO database

目的本研究旨在通过生物信息学算法探讨影响同种异体肾移植术后肾功能的关键基因及生物学因素。方法通过GEO网站筛选GSE181757、GSE30718和GSE147089数据集进行数据挖掘。使用R语言的limma包进行数据预处理及差异基因分析。使用R语言的Clusterprofiler包进行GO、KEGG富集分析。蛋白互作网络是基于STRING数据库构建, 并使用Cytoscape进行可视化。使用Cytoscape中的插件CytoHubba计算蛋白互作网络中排名前5的核心基因。采用CIBERSORT和Xcell反卷积算法被用来进行基于转录谱的免疫微环境量化。结果基于GSE181757芯片数据, 247个基因被鉴定和肾移植患者的远期肾功能相关。差异基因参与的生物学过程主要有类固醇激素生物合成、化学致癌、细胞色素P450-外源性物质代谢、细胞色素P450-药物代谢、视黄醇代谢和全身动脉血压的调节。基于STRING数据库的蛋白互作网络结果显示, MMP7、LCN2、LGALS3、ALB、CYP3A5被认为在调控肾移植患者的远期肾功能中起到核心作用。此外, GSE30718和GSE147089的结果提示, 这5个核心基因可能通过介导急性肾损伤和抗体介导的排斥反应来影响移植肾的远期肾功能。浆细胞和活化的NK细胞在肾功能下降患者的组织中也显著增多。结论通过芯片数据的深入挖掘, 发现了肾移植患者肾功能下降的潜在生物学机制, 为术后出现肾功能下降的肾移植患者提供了新的诊断与治疗思路。

Objective To explore the key genes and biological factors that affect renal function after allogeneic kidney transplantation through bioinformatics analysis.Methods GSE181757,GSE30718 and GSE147089 was identified through GEO website for data mining.Limma package in R language was used for data preprocessing and differential gene analysis.The Clusterprofiler package in R language was used for GO and KECG enrichment analysis.The protein interaction network is built on a STRING database and visualized using Cytoscape.Compute the top 5 core genes in the protein interaction network using CytoHubba,a plugin in Cytoscape.CIBERSORT and Xcell deconvolution algorithms are used to quantify the immune microenvironment based on transcriptional profiles.Results Based on the data of GSE181757,247 DEGs were identified,which might be related to the long-term renal function of kidney transplant patients.These DEGs were involved in steroid hormone biosynthesis,chemical carcinogenesis,metabolism of xenobiotics by cytochrome P450,drug metabolism-cytochrome P450,retinol metabolism and regulation of systemic arterial blood pressure.MMP7,LCN2,LGALS3,ALB,CYP3A5 were identified as the hub genes in regulating long-term renal function of kidney transplant patients in the protein interaction network based on the STRING database.Moreover,the result of GSE30718 and GSE147089 indicated that these five genes might affect renal function through mediating acute kidney injury and antibody mediated rejection.Meanwhile,plasma cells and activated NK cells were significantly increased in the tissues of patients with decreased renal function,suggesting the potential role of these two cells.Conclusions Through in-depth mining of chip data,the underlying biological mechanism of renal function decline in kidney transplant patients was discovered,which provided new diagnosis and treatment ideas for kidney transplant patients with kidney function decline after surgery.