The role of cellular crosstalk in the progression of diabetic nephropathy

Inflammation in glomerular diseases

The structural and functional integrity of glomerular cells is critical for maintaining normal kidney function. Glomerular diseases, which involve chronic histological damage to the kidney, are related to injury to glomerular cells such as endothelial cells, mesangial cells (MCs), and podocytes. When faced with pathogenic conditions, these cells release pro-inflammatory cytokines such as chemokines, inflammatory factors, and adhesion factors. These substances interact with glomerular cells through specific inflammatory pathways, resulting in damage to the structure and function of the glomeruli, ultimately causing glomerular disease. Although the role of inflammation in chronic kidney diseases is well known, the specific molecular pathways that result in glomerular diseases remain largely unclear. For a long time, it has been believed that only immune cells can secrete inflammatory factors. Therefore, targeted therapies against immune cells were considered the first choice for treating inflammation in glomerular disease. However, emerging research indicates that non-immune cells such as glomerular endothelial cells, MCs, and podocytes can also play a role in renal inflammation by releasing inflammatory factors. Similarly, targeted therapies against glomerular cells should be considered. This review aims to uncover glomerular diseases related to inflammation and pathways in glomerular inflammation, and for the first time summarized that non-immune cells in the glomerulus can participate in glomerular inflammatory damage by secreting inflammatory factors, providing valuable references for future strategies to prevent and treat glomerular diseases. More importantly, we emphasized targeted glomerular cell therapy, which may be a key direction for the future treatment of glomerular diseases.

Dapagliflozin inhibits ferroptosis and ameliorates renal fibrosis in diabetic C57BL/6J mice

Diabetic nephropathy (DN) is a common complication of diabetes and a major cause of end-stage renal disease, with complex pathogenesis involving inflammation, oxidative stress, fibrosis, and ferroptosis. Ferroptosis is linked to DN progression, yet treatment options are limited, particularly for targeting ferroptosis. Dapagliflozin (DAPA), an SGLT2 inhibitor, shows renal protective effects in diabetes, but its role in renal fibrosis and ferroptosis in DN is unclear. This study investigated DAPA's effect on renal fibrosis in DN by inhibiting ferroptosis, using a streptozotocin-induced diabetic mouse model. Results indicated that DAPA improved renal function, reduced fibrosis, and suppressed ferroptosis markers in diabetic mice. In vitro, DAPA inhibited ferroptosis and fibrosis in HK-2 cells under high glucose conditions. Molecular docking and network pharmacology suggested DAPA's anti-fibrotic and anti-ferroptotic effects may involve the Nrf2 and TGF-β signaling pathways. DAPA also reduced serum creatinine and blood urea nitrogen in diabetic mice, improved glomerulosclerosis and interstitial fibrosis, decreased iron deposition, and enhanced antioxidant activity. Overall, DAPA's multi-target mechanisms significantly improve DN progression, suggesting its potential as a targeted therapy against ferroptosis. Future studies should further explore DAPA's applications.

CD3D silencing alleviates diabetic nephropathy via inhibition of JAK/STAT pathway

Diabetic nephropathy (DN) is a severe microvascular complication of diabetes that poses a significant burden to global health. This investigation aims to illustrate the functional role of CD3D and its relevant mechanisms in DN progression. The pivotal genes between the GSE47183 and GSE30528 datasets were identified using bioinformatics methods. The effects of CD3D silencing on renal damage, inflammatory response, and lipid metabolism were validated in DN mice. Furthermore, the impacts of CD3D knockdown on cell viability, apoptotic rate, inflammation, and lipid levels were investigated in HK-2 cells under high glucose (HG) conditions. Additionally, RO8191 was employed to investigate the role of CD3D in the JAK/STAT pathway in HG-treated cells. A total of 5 focal genes were identified through bioinformatics and were found to be upregulated in renal tissues from DN mice. CD3D silencing mitigated pathological damage to kidneys, reduced inflammatory response, and decreased lipid accumulation in DN mice. HG stimulation restrained viability, increased apoptosis, promoted the release of inflammatory cytokines, and affected expressions of hallmarks related to lipid metabolism in HG-treated cells; these changes were partially abolished by CD3D knockdown. Mechanistically, CD3D downregulation ameliorated HG-induced injury in HK-2 cells by blocking the JAK/STAT pathway. This study underscores that CD3D silencing has significant potential as a promising candidate in the treatment of DN.

Tribbles pseudokinase 3 promoted renal fibrosis by regulating the expression of DNA damage-inducible transcript 3 in diabetic nephropathy

Diabetic nephropathy (DN) is a severe complication of prolonged diabetes, impacting millions worldwide with an increasing incidence. This study investigates the role of tribbles pseudokinase 3 (TRIB3), a protein implicated in the progression of DN, focusing on its mechanisms underlying glomerular damage. Through analysis of the Gene Expression Omnibus (GEO) database, we identified TRIB, among differentially expressed genes (DEGs) in streptozotocin (STZ)-treated C57BL/6J mice. Both in vitro and in vivo experiments were conducted to examine the effects of TRIB3 inhibition on high glucose (HG)-induced damage in podocytes and DN mouse models. The results demonstrated that TRIB3 inhibition reduced inflammatory responses and extracellular matrix (ECM) production inMPC5 cells, mediated by the downregulation of DNA damage-inducible transcript 3 (DDIT3) - a critical regulator of proinflammatory cytokine secretion and ECM synthesis. Inhibiting TRIB3 decreased inflammatory factors and ECM deposition in diabetic mice in vivo, confirming its pivotal role in DN pathogenesis. These findings indicate that TRIB3 and its interaction with DDIT3 contribute significantly to DN by promoting inflammatory cascades and ECM accumulation, presenting potential therapeutic targets for managing the disease.

Sirt7/HIC1 complex participates in hyperglycaemia-mediated EndMT via modulation of SDC1 expression in diabetic kidney disease and metabolic memory

Diabetic kidney disease (DKD), a primary microvascular complication arising from diabetes, may result in end-stage renal disease. Epigenetic regulation of endothelial mesenchymal transition (EndMT) has been recently reported to exert function in metabolic memory and DKD. Here, we investigated the mechanism which Sirt7 modulated EndMT in human glomerular endothelial cells (HGECs) in the occurrence of metabolic memory in DKD. Lower levels of SDC1 and Sirt7 were noted in the glomeruli of both DKD patients and diabetes-induced renal injury rats, as well as in human glomerular endothelial cells (HGECs) with high blood sugar. Endothelial-to-mesenchymal transition (EndMT) was sustained despite the normalization of glycaemic control. We also found that Sirt7 overexpression associated with glucose normalization promoted the SDC1 expression and reversed EndMT in HGECs. Furthermore, the sh-Sirt7-mediated EndMT could be reversed by SDC1 overexpression. The ChIP assay revealed enrichment of Sirt7 and H3K18ac in the SDC1 promoter region. Furthermore, hypermethylated in cancer 1 (HIC1) was found to be associated with Sirt7. Overexpression of HIC1 with normoglycaemia reversed high glucose-mediated EndMT in HGECs. The knockdown of HIC1-mediated EndMT was reversed by SDC1 upregulation. In addition, the enrichment of HIC1 and Sirt7 was observed in the same promoter region of SDC1. The overexpressed Sirt7 reversed EndMT and improved renal function in insulin-treated diabetic models. This study demonstrated that the hyperglycaemia-mediated interaction between Sirt7 and HIC1 exerts a role in the metabolic memory in DKD by inactivating SDC1 transcription and mediating EndMT despite glucose normalization in HGECs.

Integrated machine learning and deep learning for predicting diabetic nephropathy model construction, validation, and interpretability

OBJECTIVE

To construct a risk prediction model for assisted diagnosis of Diabetic Nephropathy (DN) using machine learning algorithms, and to validate it internally and externally.

METHODS

Firstly, the data was cleaned and enhanced, and was divided into training and test sets according to the 7:3 ratio. Then, the metrics related to DN were filtered by difference analysis, Least Absolute Shrinkage and Selection Operator (LASSO), Recursive Feature Elimination (RFE), and Max-relevance and Min-redundancy (MRMR) algorithms. Ten machine learning models were constructed based on the key variables. The best model was filtered by Receiver Operating Characteristic (ROC), Precision-Recall (PR), Accuracy, Matthews Correlation Coefficient (MCC), and Kappa, and was internally and externally validated. Based on the best model, an online platform had been constructed.

RESULTS

15 key variables were selected, and among the 10 machine learning models, the Random Forest model achieved the best predictive performance. In the test set, the area under the ROC curve was 0.912, and in two external validation cohorts, the area under the ROC curve was 0.828 and 0.863, indicating excellent predictive and generalization abilities.

CONCLUSION

The model has a good predictive value and is expected to help in the early diagnosis and screening of clinical DN.