Abstract
Context
The molecular mechanism by which Swertiamarin (SM) prevents advanced glycation end products (AGEs) induced diabetic nephropathy (DN) has never been explored.
Objective
To evaluate the effect of SM in preventing the progression of DN in high fat diet-streptozotocin-induced diabetic rats.
Materials and methods
After 1 week of acclimatisation, the rats were divided randomly into five groups as follows: (1) Control group, which received normal chow diet; (2) High-fat diet (HFD) group which was fed diet comprising of 58.7% fat, 27.5% carbohydrate and 14.4% protein); (3) Aminoguanidine (AG) group which received HFD + 100 mg/k.b.w.AG (intraperitoneal); (4) Metformin (Met) group which received HFD + 70 mg/k.b.w. the oral dose of Met and (5) SM group which was supplemented orally with 50 mg/k.b.w.SM along with HFD. After 12 weeks all HFD fed animals were given a single 35 mg/k.b.w. dose of streptozotocin with continuous HFD feeding for additional 18 weeks. Later, various biochemical assays, urine analyses, histopathological analysis of kidneys, levels of AGEs, expression of various makers, and in-silico analysis were performed.
Results
The diabetic group demonstrated oxidative stress, increased levels of AGEs, decreased renal function, fibrosis in the renal tissue, higher expression of the receptor for advanced glycation end products (RAGE), which were ameliorated in the SM treated group. In-silico analysis suggests that SM can prevent the binding of AGEs with RAGE.
Conclusions
SM ameliorated DN by inhibiting the oxidative stress induced by AGEs.
SM reduces the levels of hyperglycaemia-induced advanced glycation end products in serum and renal tissue.
SM prevents renal fibrosis by inhibiting the EMT in the kidney tissue.
The in-silico analysis proves that SM can inhibit the binding of various AGEs with RAGE, thereby inhibiting the AGE-RAGE axis.
Highlights
Notes on Contributor
Kirti Parwani and Farhin Patel contributed equally to this work
Acknowledgements
The author would like to acknowledge Charotar University of Science and Technology for providing the author with a CHARUSAT Ph.D. Scholar Fellowship (CPSF). The authors are thankful to the Indian Institute of Technology Gandhinagar, for the support provided in accessing the computational facilities and Schrödinger software for the in-silico studies.
Disclosure statement
The authors declare no conflict of interest.
Data availability statement
The authors confirm that the data supporting the findings of this study are available within the article