Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy

Abstract

Abstract Objectives The underlying molecular mechanisms of diabetic nephropathy (DN) have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of DN. Methods We downloaded next generation sequencing (NGS) dataset GSE142025 from Gene Expression Omnibus (GEO) database having 28 DN samples and 9 normal control samples. The differentially expressed genes (DEGs) between DN and normal control samples were analyzed. Biological function analysis of the DEGs was enriched by GO and REACTOME pathway. Then we established the protein-protein interaction (PPI) network, modules, miRNA-DEG regulatory network and TF-DEG regulatory network. Hub genes were validated by using receiver operating characteristic (ROC) curve analysis. Results A total of 549 DEGs were detected including 275 up regulated and 274 down regulated genes. Biological process analysis of functional enrichment showed these DEGs were mainly enriched in cell activation, integral component of plasma membrane, lipid binding and biological oxidations. Analyzing the PPI network, miRNA-DEG regulatory network and TF-DEG regulatory network, we screened hub genes MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB and NR4A1 by the Cytoscape software. The ROC curve analysis confirmed that hub genes were of diagnostic value. Conclusions Taken above, using integrated bioinformatics analysis, we have identified key genes and pathways in DN, which could improve our understanding of the cause and underlying molecular events, and these key genes and pathways might be therapeutic targets for DN.