Objective Renal fibrosis (RF) is a pathophysiological change leading to abnormal deposition of extracellular matrix in kidney and replacement of normal renal structure. It is the sole pathway for a rapid progression of chronic kidney disease (CKD) into end-stage renal disease (ESRD). Preventing and treating RF are vital for arresting the progression of CKD. It has been a hot spot and a difficult point of kidney disease researches. Therefore identifying key genes associated with RF is crucial for developing new strategies for RF.
Methods The gene expression characteristics of kidney tissues were retrieved from two databases (GSE35257 & GSE121190) and geo2R was employed for obtaining the differentially expressed genes (DEG). Then Database for Annotation, Visualization and Integrated Discovery (DAVID) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized. Subsequently the STRING database was employed for constructing a protein-protein-interactions (PPI) network and cytoHubba plug-ins of Cytoscape were utilized for selecting hub genes.
Results A total of 930 DEGs were harvested from GSE35257 database, including 504 up-regulated DEGs and 426 down-regulated DEGs. And 2053 DEGs were filtered from GSE121190 database, including 898 up-regulated DEGs and 1155 down-regulated DEGs. Functional enrichment analysis revealed that DEGs involved many functional and expression pathways, such as exosome, drug response, NAD/NADP as receptor, nuclear system, development and protein kinase binding. PPI network was composed of 97 nodes (proteins) and 404 PPI edges (interactions). Finally, ten genes including GAPDH, CCND1, ACTA2, MTOR, ABL1, ANK3, CXCL12, PRRX1, CTSB and MAP2K7 were identified as new candidates for rF-related key genes.
Conclusions The results of this study provide comprehensive insights into the pathogenesis of RF and designing potential new therapeutic targets.
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