通过生物信息学分析、单细胞测序分析并结合体内验证来鉴定肾缺血再灌注损伤的生物标志物。

Identification of biomarkers of renal ischemia-reperfusion injury by bioinformatics analysis and single-cell sequencing analysis combined with in vivo validation.

作者信息

Zhu Qin, Ren Shiqi, Sun Zhaoyang, Qin Jun, Sheng Xiaoming

机构信息

Department of Hand Surgery, Nantong University Affiliated Hospital, Nantong 226001, China.

Department of Trauma Center, Affiliated Hospital of Nantong University, Nantong 226001, China.

出版信息

Transpl Immunol. 2023 Dec;81:101928. doi: 10.1016/j.trim.2023.101928. Epub 2023 Sep 11.

DOI:10.1016/j.trim.2023.101928

PMID:37704087

Abstract

BACKGROUND

Renal ischemia-reperfusion injury (IRI) is a serious clinical complication of kidney injury. This research dealt with investigating the hub genes and pathways associated with renal IRI.

METHODS

The transcriptome expression dataset of mouse renal ischemia samples (GSE39548) was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were filtered by R software for key genes utilized for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene enrichment analysis (GSEA). The gene co-expression network was developed by WGCNA analysis to screen important modules. Hub genes from the intersection of DEGs and WGCNA were subjected to protein-protein interaction (PPI) network. The biomarkers obtained by SVM-REF and LASSO algorithm were validated by other datasets and subjected to GSEA analysis. The expression of biomarkers in renal IRI was detected by qRT-PCR and subjected to single-cell analysis.

RESULTS

A total of 157 DEGs were discovered. Biological function analysis depicted that the DEGs were primarily involved in cytokine-cytokine receptor interaction, as well as the signaling pathways IL-17, MAPK, and TNF. The intersection of DEGs and the genes obtained by WGCNA analysis yielded 149 hubs genes. Based on SVM-REF and LASSO algorithm, cyp1a1 and pdk4 were determined as potential biomarkers in individuals with renal ischemia and showed good diagnostic value. qRT-PCR results depicted that cyp1a1 and pdk4 were significantly up-regulated in renal ischemia mice (P < 0.05). Finally, the single-cell analysis identified the expression of Cyp1a1 and Pdk4 in mice kidney tissue.

CONCLUSION

cyp1a1 and pdk4 were identified to play important roles in renal IRI. This research provides a new perspective and basis for studying the pathogenesis of renal IRI and developing new treatments.

摘要

背景

肾缺血再灌注损伤（IRI）是肾损伤的一种严重临床并发症。本研究旨在探究与肾IRI相关的枢纽基因和通路。

方法

从小鼠肾缺血样本的转录组表达数据集（GSE39548）获取自基因表达综合数据库（GEO）。利用R软件筛选差异表达基因（DEG），用于基因本体论（GO）、京都基因与基因组百科全书（KEGG）通路富集分析以及基因富集分析（GSEA）的关键基因。通过加权基因共表达网络分析（WGCNA）构建基因共表达网络以筛选重要模块。对DEG与WGCNA交集得到的枢纽基因构建蛋白质 - 蛋白质相互作用（PPI）网络。通过支持向量机递归特征消除法（SVM - REF）和套索算法（LASSO）获得的生物标志物在其他数据集中进行验证并进行GSEA分析。通过qRT - PCR检测生物标志物在肾IRI中的表达并进行单细胞分析。

结果

共发现157个DEG。生物学功能分析表明，DEG主要参与细胞因子 - 细胞因子受体相互作用，以及白细胞介素 - 17、丝裂原活化蛋白激酶（MAPK）和肿瘤坏死因子（TNF）信号通路。DEG与WGCNA分析得到的基因交集产生了149个枢纽基因。基于SVM - REF和LASSO算法，确定细胞色素P450 1A1（cyp1a1）和丙酮酸脱氢酶激酶4（pdk4）为肾缺血个体的潜在生物标志物，并显示出良好的诊断价值。qRT - PCR结果表明，cyp1a1和pdk4在肾缺血小鼠中显著上调（P < 0.05）。最后，单细胞分析确定了Cyp1a1和Pdk4在小鼠肾组织中的表达。