ArticleFrontiers in pharmacology2024
A mathematical model of glomerular fibrosis in diabetic kidney disease to predict therapeutic efficacy.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Association Between Blood Lead Levels and Diabetic Kidney Disease: A Cross-sectional Analysis of NHANES Data (1999-2018).Current molecular medicine · 2026Article
- DFT-ML-Based Property Prediction of Transition Metal Complex Photosensitizers for Photodynamic Therapy.ACS omega · 2025Article
- Logic-based modeling of inflammatory macrophage cross talk with glomerular endothelial cells in diabetic kidney disease.American journal of physiology. Renal physiology · 2025Article
- Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease.International journal of molecular sciences · 2024Article
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2 authors.
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Abstract
Background: Glomerular fibrosis is a tissue damage that occurs within the kidneys of chronic and diabetic kidney disease patients. Effective treatments are lacking, and the mechanism of glomerular damage reversal is poorly understood. Methods: A mathematical model suitable for hypothesis-driven systems pharmacology of glomerular fibrosis in diabetes was developed from a previous model of interstitial fibrosis. The adapted model consists of a system of ordinary differential equations that models the complex disease etiology and progression of glomerular fibrosis in diabetes. Results: Within the scope of the mechanism incorporated, advanced glycation end products (AGE)-matrix proteins that are modified due to high blood glucose-were identified as major contributors to the delay in the recovery from glomerular fibrosis after glucose control. The model predicted that inhibition of AGE production is not an effective approach for accelerating the recovery from glomerular fibrosis. Further, the model predicted that treatment breaking down accumulated AGE is the most productive at reversing glomerular fibrosis. The use of the model led to the identification that glucose control and aminoguanidine are ineffective treatments for reversing advanced glomerular fibrosis because they do not remove accumulated AGE. Additionally, using the model, a potential explanation was generated for the lack of efficacy of alagebrium in treating advanced glomerular fibrosis, which is due to the inability of alagebrium to reduce TGF- Impact: Using the mathematical model, a mechanistic understanding of disease etiology and complexity of glomerular fibrosis in diabetes was illuminated, and then hypothesis-driven explanations for the lack of efficacy of different pharmacological agents for treating glomerular fibrosis were provided. This understanding can enable the development of more efficacious therapeutics for treating kidney damage in diabetes.
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