Yapay Zeka Hızlı Bakış & Çıkarımlar
AI InsightThese findings provide a framework for future experimental validation and drug development efforts in AKI caused by IRI.
📌 3 Maddede Bu Makale
Özet
Aims: This study aimed to identify key genes and pathways involved in the pathogenesis of renal ischemia–reperfusion injury (IRI)-induced acute kidney injury (AKI) using an integrative bioinformatics approach. Methods: Publicly available gene expression profiles from two independent rat kidney microarray datasets (GSE27274 and GSE58438) were analyzed to identify differentially expressed genes (DEGs) between IRI and control groups. DEGs with an adjusted p-value 1 were considered significant. Common DEGs from both datasets were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Protein–protein interaction networks were constructed using STRING and cytoscape, and hub genes were identified with the maximal clique centrality algorithm via the CytoHubba plugin. Results: A total of 189 overlapping DEGs were identified (117 upregulated, 72 downregulated). Upregulated DEGs were enriched in pathways associated with glutathione metabolism and oxidative stress response, while downregulated DEGs were associated with DNA replication and inflammatory signaling. Hub genes for upregulated DEGs included Gclc, Gclm, Anpep, and Gss, while downregulated hub genes included Mcm2, Gins1, Pcna, and Tnf. These genes represent potential regulatory nodes in the renal IRI response. Conclusion: This study highlights redox regulation, amino acid metabolism, immune modulation, and cell cycle arrest as major components in the molecular pathogenesis of renal IRI. The identified hub genes may serve as potential diagnostic biomarkers and therapeutic targets. These findings provide a framework for future experimental validation and drug development efforts in AKI caused by IRI.
Abstract
Aims: This study aimed to identify key genes and pathways involved in the pathogenesis of renal ischemia–reperfusion injury (IRI)-induced acute kidney injury (AKI) using an integrative bioinformatics approach. Methods: Publicly available gene expression profiles from two independent rat kidney microarray datasets (GSE27274 and GSE58438) were analyzed to identify differentially expressed genes (DEGs) between IRI and control groups. DEGs with an adjusted p-value 1 were considered significant. Common DEGs from both datasets were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Protein–protein interaction networks were constructed using STRING and cytoscape, and hub genes were identified with the maximal clique centrality algorithm via the CytoHubba plugin. Results: A total of 189 overlapping DEGs were identified (117 upregulated, 72 downregulated). Upregulated DEGs were enriched in pathways associated with glutathione metabolism and oxidative stress response, while downregulated DEGs were associated with DNA replication and inflammatory signaling. Hub genes for upregulated DEGs included Gclc, Gclm, Anpep, and Gss, while downregulated hub genes included Mcm2, Gins1, Pcna, and Tnf. These genes represent potential regulatory nodes in the renal IRI response. Conclusion: This study highlights redox regulation, amino acid metabolism, immune modulation, and cell cycle arrest as major components in the molecular pathogenesis of renal IRI. The identified hub genes may serve as potential diagnostic biomarkers and therapeutic targets. These findings provide a framework for future experimental validation and drug development efforts in AKI caused by IRI.