Identification of hub genes correlated with the initiation and development in chronic kidney disease via bioinformatics analysis

Abstract

Introduction: Chronic kidney disease (CKD) is a major public health issue worldwide, which is characterized by irreversible loss of nephron and renal function. However, the molecular mechanism of CKD remains underexplored. Methods: This study integrated three transcriptional profile datasets to investigate the molecular mechanism of CKD. The differentially expressed genes (DEGs) between Con and unilateral ureteral obstruction (UUO)-operated mice were analyzed by utilizing the limma package in R. The shared DEGs were analyzed by Gene Ontology (GO) and functional enrichment. Protein-protein interactions (PPI) were constructed by utilizing the STRING database. Hub genes were analyzed by MCODE and Cytohubba. We further validated the gene expression by using the other dataset and mice UUO model. Results: A total of 315 shared DEGs between Con and UUO samples were identified. Gene function and KEGG pathway enrichment revealed that DEGs were mainly enriched in inflammatory response, immune system process and chemokine signaling pathway. Two modules were clustered based on PPI network analysis. Module 1 contained 13 genes, related to macrophage activation, migration, and chemotaxis. Ten hub genes were identified by PPI network analysis. Subsequently, the expression levels of hub genes were validated with the other dataset. Finally, these four validated hub genes were further confirmed by our UUO mice. Three validated hub genes, Gng2, Pf4 and Ccl9, showed significant response to UUO. Conclusion: Our study reveals the coordination of genes during UUO, and provides a promising gene panel CKD treatment. GNG2 and PF4 were identified as potential targets for developing CKD drugs.