Liu Wei-Hua, Cao Fang, Lin Miao, Hong Fu-Yuan
Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China,
Department of Nephrology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China.
Kidney Blood Press Res. 2025;50(1):14-32. doi: 10.1159/000542787. Epub 2024 Nov 22.
The morbidity and mortality of acute kidney injury (AKI) are increasing. Epigenetic regulation and immune cell infiltration are thought to be involved in AKI. However, the relationship between epigenetic regulation and immune cell infiltration in AKI has not been elucidated. This study was conducted to identify the differentially expressed genes (DEGs), differentially expressed RNA methylation genes (DEMGs), and infiltrated immune cells in the kidneys of ischemia-reperfusion induced-acute kidney injury (IRI-AKI) models and further explore their relationships in IRI-AKI.
This is a bioinformatic analysis using R programming language in 3 selected IRI-AKI datasets from the Gene Expression Omnibus (GEO) database, including 16 IRI-AKI kidney tissues and 10 normal kidney tissues. The DEGs were screened, and enrichment pathways were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The DEMGs and core DEMGs were identified using the R package. The ROC curve was plotted to predict disease occurrence of 7 core DEMGs. The correlation of 7 core DEMGs and other genes was analyzed using Pearson's correlation test. The gene set enrichment analysis (GSEA) of each DEMG was conducted using the R package. The upstream miRNAs and transcript factors of 7 core DEMGs were predicted based on the RegNetwork database and Cytoscape software. The STITCH database was used to predict the possible binding compounds of the 7 core DEMGs. Immune cell infiltration in kidney tissues between the IRI-AKI group and control group was evaluated using the R package.
A total of 2,367 DEGs were obtained, including 1,180 upregulated and 1,187 downregulated genes in IRI-AKI kidney associated with the cell structure, proliferation, molecule binding/interaction, and signaling pathways such as the leukocyte migration and chemokine signaling pathways. Ten DEMGs were identified, with Ythdf1, Rbm15, Trmt6, Hnrnpc, and Dnmt1 being significantly upregulated, while Lrpprc, Cyfip2, Mettl3, Ncbp2, and Nudt7 were significantly downregulated in IRI-AKI tissues. The molecules interacting with 7 core DEMGs were identified. Significant changes in the infiltration of 8 types of immune cells were observed in IRI-AKI kidneys compared to normal controls. The significant correlation between 6 core DEMGs and the infiltration of immune cells was observed.
IRI may induce AKI through RNA methylation to regulate the expression of genes involved in immune cell infiltration.
急性肾损伤（AKI）的发病率和死亡率正在上升。表观遗传调控和免疫细胞浸润被认为与AKI有关。然而，AKI中表观遗传调控与免疫细胞浸润之间的关系尚未阐明。本研究旨在鉴定缺血再灌注诱导的急性肾损伤（IRI-AKI）模型肾脏中的差异表达基因（DEGs）、差异表达的RNA甲基化基因（DEMGs）和浸润的免疫细胞，并进一步探讨它们在IRI-AKI中的关系。
这是一项使用R编程语言对来自基因表达综合数据库（GEO）的3个选定IRI-AKI数据集进行的生物信息学分析，包括16个IRI-AKI肾脏组织和10个正常肾脏组织。筛选DEGs，并使用基因本体论（GO）和京都基因与基因组百科全书（KEGG）数据库分析富集途径。使用R包鉴定DEMGs和核心DEMGs。绘制ROC曲线以预测7个核心DEMGs的疾病发生情况。使用Pearson相关检验分析7个核心DEMGs与其他基因的相关性。使用R包对每个DEMG进行基因集富集分析（GSEA）。基于RegNetwork数据库和Cytoscape软件预测7个核心DEMGs的上游miRNA和转录因子。使用STITCH数据库预测7个核心DEMGs可能的结合化合物。使用R包评估IRI-AKI组和对照组之间肾脏组织中的免疫细胞浸润情况。
共获得2367个DEGs，其中IRI-AKI肾脏中1180个基因上调，1187个基因下调，这些基因与细胞结构、增殖、分子结合/相互作用以及白细胞迁移和趋化因子信号通路等信号通路相关。鉴定出10个DEMGs，在IRI-AKI组织中，Ythdf1、Rbm15、Trmt6、Hnrnpc和Dnmt1显著上调，而Lrpprc、Cyfip2、Mettl3、Ncbp2和Nudt7显著下调。鉴定出与7个核心DEMGs相互作用的分子。与正常对照相比，IRI-AKI肾脏中观察到8种免疫细胞浸润的显著变化。观察到6个核心DEMGs与免疫细胞浸润之间存在显著相关性。
IRI可能通过RNA甲基化诱导AKI，以调节参与免疫细胞浸润的基因表达。
