Background: Increasing evidence suggests that immune cell infiltration contributes to the pathogenesis and progression of diabetic nephropathy (DN). We aim to unveil the immune infiltration pattern in the glomerulus of DN and provide potential targets for immunotherapy.
Methods: Infiltrating percentage of 22 types of immune cell in the glomerulus tissues were estimated by the CIBERSORT algorithm based on three transcriptome datasets mined from the GEO database. Differentially expressed genes (DEGs) were identified by the "limma" package. Then immune-related DEGs were identified by intersecting DEGs with immune-related genes (downloaded from Immport database). The protein-protein interactions of Immune-related DEGs were explored using the STRING database and visualized by Cytoscape. The enrichment analyses for KEGG pathways and GO terms were carried out by the gene set enrichment analysis (GSEA) method.
Results: 11 types of immune cell were revealed to be significantly altered in the glomerulus tissues of DN (Up: B cells memory, T cells gamma delta, NK cells activated, Macrophages.M1, Macrophages M2, Dendritic cells resting, Mast cells resting; Down: B cells naive, NK cells resting, Mast cells activated, Neutrophils). Several pathways related to immune, autophagy and metabolic process were significantly activated. Moreover, 6 hub genes with a medium to strong correlation with renal function (eGFR) were identified (SERPINA3, LTF, C3, PTGDS, EGF and ALB).
Conclusion: In the glomerulus of DN, the immune infiltration pattern changed significantly. A complicated and tightly regulated network of immune cells exists in the pathological of DN. The hub genes identified here will facilitate the development of immunotherapy.
Keywords: Bioinformatics; CIBERSORT; Diabetic nephropathy; GSEA (gene set enrichment analysis); Immune cell infiltration.
© 2022. The Author(s).