Aim: Diabetic kidney disease (DKD) continues to be devastating complication of diabetes mellitus. Immune response and inflammatory reaction play essential roles in the progression of DKD. But the specific mechanism of immune cells, and their act on renal innate cells remains unclear. This article focused on immune cells and their communication with renal innate cells to provide bioinformatic evidence for further understanding the immune mechanism in DKD.
Methods: Data were analyzed to evaluate the differentially expressed genes (DEGs) and their pathways in DKD patients and mice. Gene set enrichment analysis (GSEA) was used to explore the immune inflammation-related pathways. CIBERSORT was applied to evaluate the distribution of inflammatory cells in different states. Cell-type DEGs and their enrichment pathways were further explored in podocytes, proximal tubule cells and injured tubule cells. Cellchat was used to reveal the cellular communication between immune cells and renal innate cells in DKD.
Results: GO and KEGG analysis showed that DEGs were mainly enriched in immune inflammation-related pathways. Monocytes, M2 macrophages and T cells were significantly increased in DKD samples, especially in renal tubule. ScRNA datasets showed that the immune cells number in DKD were significantly increased. Cell-type DEGs were involved in kidney growth and development. In DKD, the interaction numbers and strength between immune cells and innate cells were significantly increased. VISTANT, SPP1 and IGF signal flow were increased in DKD. SPP1-CD44, NRG1-ERBB4, NAMPT-INSR, and Igf1-Igf1r receptor ligand pairs were enhanced in DKD, which mediated the communication between immune-inflammatory cells and innate cells.
Conclusion: Our study explored the pathogenesis of renal injury promoted by immunoinflammatory in DKD. VISTANT, SPP1, and IGF signaling pathways and SPP1-CD44, NRG1-ERBB4, NAMPT-INSR, and Igf1- Igf1r receptor ligand pairs might occupy essential place in the occurrence and progress of DKD.
Keywords: diabetic kidney disease, immune cells, renal innate cells, bioinformatics