An integrated bioinformatics analysis and experimental study identified key biomarkers CD300A or CXCL1, pathways and immune infiltration in diabetic nephropathy mice

Abstract

Diabetic nephropathy (DN) is a common microvascular complication that easily leads to end-stage renal disease. It is important to explore the key biomarkers and molecular mechanisms relevant to diabetic nephropathy (DN). We used highthroughput RNA sequencing to obtain the genes related to DN glomerular tissues and healthy glomerular tissues of mice. Then we used LIMMA to analyze differentially expressed genes (DEGs) between DN and non-diabetic glomerular samples. And we performed KEGG, gene ontology functional (GO) enrichment, and gene set enrichment analysis to reveal the signaling pathway of the disease. The CIBERSORT algorithm based on support vector machine was used to determine the immune infiltration score. Random forest algorithm and Cytoscape obtained hub genes. Finally, we applied co-staining, immunohistochemical staining, RT-qPCR and western blotting to validate the protein and mRNA expression of both hub genes. We obtained 913 DEGs mainly related to inflammatory factors and immunity. GSEA results showed that differential genes were mainly enriched in IL-17 signaling pathway, lipid and atherosclerosis, rheumatoid arthritis, TNF signaling pathway, neutrophil extracellular trap formation, Staphylococcus aureus infection and other pathways. The intersection of the random forest algorithm and Cytoscape revealed both hub genes of CD300A and CXCL1. Experiments have shown that the both key genes of CD300A and CXCL1 shown increased expression in glomerular podocytes, and are related to the inflammation of diabetic nephropathy. And immunohistochemical staining and RT-qPCR further confirmed that the protein and mRNA expression level of CD300A or CXCL1 in glomeruli tissue in DN mice were increased. The expression levels of CD300A and CXCL1 increased significantly under HG (high glucose) stimulation, further confirming that diabetes can lead to increased levels of CD300A and CXCL1 at the cellular level. Through bioinformatics analysis, machine learning algorithms, and experimental research, CD300A and CXCL1 are confirmed as both potential biomarkers in diabetic nephropathy. And we further revealed the main pathways of differential genes and the differentially distributed immune infiltrating cells in diabetic nephropathy.