Recent advances in animal models of diabetic nephropathy

Boris Betz1, Bryan R Conway

  • 1Centres for Inflammation Research, University of Edinburgh, Edinburgh, UK.

Insights

Developing effective diabetic nephropathy (DN) treatments requires better animal models. Recent research highlights specific mouse strains and hypertension models that better mimic human DN pathology, aiding therapeutic development.

Area of Science:

  • Nephrology
  • Diabetology
  • Animal Modeling

Background:

  • Diabetic nephropathy (DN) is a leading cause of end-stage kidney disease.
  • Current progress in developing novel DN therapies is limited by the lack of robust animal models.
  • Understanding DN pathogenesis requires accurate preclinical models.

Purpose of the Study:

  • To review recent advances in animal models for diabetic nephropathy.
  • To discuss the impact of genetic background, hypertension, and transcriptomic profiling on DN modeling.
  • To identify suitable models for studying specific aspects of DN.

Main Methods:

  • Comparison of different mouse strains (C57BL/6J, FVB, BTBR ob/ob) for DN susceptibility.
  • Evaluation of hypertensive models (eNOS(-/-) mice, Cyp1a1mRen2 rats) in diabetic conditions.
  • Analysis of transcriptomic profiling in animal models versus human DN.
  • Assessment of therapeutic interventions in specific models (e.g., leptin treatment in BTBR mice).

Main Results:

  • FVB strain mice, particularly Ove26 and db/db, show susceptibility to type 1 and type 2 DN.
  • BTBR ob/ob mice exhibit key DN pathologies, with leptin treatment showing therapeutic potential.
  • Hypertension exacerbates DN; eNOS(-/-) mice and Cyp1a1mRen2 rats develop significant DN features.
  • Transcriptomic data from eNOS(-/-) mice and Cyp1a1mRen2 rats align with human DN gene expression changes.

Conclusions:

  • No single animal model perfectly replicates all human DN features, necessitating further refinement.
  • Specific mouse strains and hypertensive models offer valuable tools for studying DN.
  • Transcriptomic data can guide the selection of appropriate models for targeted research.