Abstract
Purpose:
Diabetic nephropathy (DN), a major complication of type 2 diabetes and leading cause of end-stage renal disease, lacks complete molecular understanding. To elucidate the mechanisms underlying kidney injury in DN, we analyzed mRNA and protein expression changes in mouse kidney tissue, aiming to provide a theoretical foundation for drug development.
Methods:
C57BL/6 mice were divided into two groups: a normal control group and a diabetes model group. The type 2 diabetes model was established using a high-fat diet (HFD) combined with streptozotocin (STZ). Fasting blood glucose levels and glucose tolerance tests were performed to evaluate glucose metabolism. Kidney tissues were collected, with the left kidney rapidly frozen in liquid nitrogen for transcriptomic and proteomic analyses, and the right kidney fixed in paraformaldehyde for subsequent preparation of paraffin-embedded blocks and staining.
Results:
Diabetic nephropathy (DN) mice showed significant transcriptomic and proteomic alterations in kidney tissues compared to controls. Transcriptomic analysis revealed 4156 upregulated and 1121 downregulated genes, while proteomic analysis identified 887 differentially expressed proteins (DEPs: 687 upregulated, 200 downregulated). 240 genes were synchronously upregulated and 111 synchronously downregulated at both levels, functionally linked to cellular immunity, autophagy, inflammation, and lipid metabolism. CytoHubba identified 10 hub genes: FN1, TTR, APOA1, ITGB2, APOE, PTPRC, STAT3, VTN, ICAM1, and ANXA2. Nephroseq database analysis of human DN patients showed FN1, STAT3, ICAM1, and ANXA2 were significantly upregulated and APOA1 was significantly downregulated in kidney tissues. Furthermore, FN1, ICAM1, and ANXA2 negatively correlated with eGFR, while APOA1 positively correlated with eGFR.
Conclusion:
Diabetic mice exhibited varying degrees of pathological changes in the kidneys. Combined transcriptomic and proteomic analyses highlighted four genes-FN1, ICAM1, ANXA2, and APOA1-as potential therapeutic targets for improving diabetic nephropathy.
Keywords:
diabetic nephropathy; hub genes; kidney function; multi-omics analysis; proteomics; transcriptomics.