Model-Dependent Renal Phenotypes in Diabetic Kidney Disease: Comparative Histopathological Characterization of Commonly Used Animal Models

08 Jul 20264 min read0 viewsVerified Feed

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Background: Diabetic kidney disease (DKD) remains a leading cause of end-stage renal disease worldwide, characterized by progressive structural and metabolic alterations secondary to chronic hyperglycemia. While numerous type 1 and type 2 rodent models have been developed to study the pathophysiology of DKD, no single model perfectly recapitulates the full clinical spectrum of human disease.
The selection of an optimal model depends deeply on the specific research objective, as phenotypic expression and histopathological severity vary significantly across different strains and induction methods. The present study provides a comparative analysis of the renal histological of three widely utilized murine models: the chemically induced streptozotocin (STZ) model and the genetic Akita (type 1) and db/db (type 2) models.
Methods: Male STZ-induced (28 weeks post-induction), heterozygous Akita (28 weeks old), and db/db mice at two different age intervals (18-21 and 16-24 weeks old) were assessed. Renal injury was quantified using four light-microscopic parameters: glomerulomegaly, mesangial hypercellularity, tubular vacuolization and arteriolar hyalinosis.
Due to observed discrepancies between metabolic and structural findings in the db/db strain, transmission electron microscopy (TEM) was employed for subcellular characterization.

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bioRxiv (Biomedical Preprints)

Model-Dependent Renal Phenotypes in Diabetic Kidney Disease: Comparative Histopathological Characterization of Commonly Used Animal Models

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Clinical Editorial

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Model-Dependent Renal Phenotypes in Diabetic Kidney Disease: Comparative Histopathological Characterization of Commonly Used Animal Models

GIST (Key Takeaways)

Clinical Editorial

Source Reference

Related by Condition/Drug

Genetic and sociodemographic factors associated with trajectories of physical and mental health multimorbidity in a South Asian cohort in the UK: A multistate modelling analysis

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