Journal of Pharmacokinetics and Pharmacodynamics

, Volume 38, Issue 1, pp 143–162 | Cite as

Mechanism-based disease progression modeling of type 2 diabetes in Goto-Kakizaki rats

  • Wei Gao
  • Sébastien Bihorel
  • Debra C. DuBois
  • Richard R. Almon
  • William J. Jusko
Article
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Received:
Accepted:

Abstract

The dynamics of aging and type 2 diabetes (T2D) disease progression were investigated in normal [Wistar-Kyoto (WKY)] and diabetic [Goto-Kakizaki (GK)] rats and a mechanistic disease progression model was developed for glucose, insulin, and glycosylated hemoglobin (HbA1c) changes over time. The study included 30 WKY and 30 GK rats. Plasma glucose and insulin, blood glucose and HbA1c concentrations and hematological measurements were taken at ages 4, 8, 12, 16 and 20 weeks. A mathematical model described the development of insulin resistance (IR) and β-cell function with age/growth and diabetes progression. The model utilized transit compartments and an indirect response model to quantitate biomarker changes over time. Glucose, insulin and HbA1c concentrations in WKY rats increased to a steady-state at 8 weeks due to developmental changes. Glucose concentrations at 4 weeks in GK rats were almost twice those of controls, and increased to a steady-state after 8 weeks. Insulin concentrations at 4 weeks in GK rats were similar to controls, and then hyperinsulinemia occurred until 12–16 weeks of age indicating IR. Subsequently, insulin concentrations in GK rats declined to slightly below WKY controls due to β-cell failure. HbA1c showed a delayed increase relative to glucose. Modeling of HbA1c was complicated by age-related changes in hematology in rats. The diabetes model quantitatively described the glucose/insulin inter-regulation and HbA1c production and reflected the underlying pathogenic factors of T2D—IR and β-cell dysfunction. The model could be extended to incorporate other biomarkers and effects of various anti-diabetic drugs.

Keywords

Type 2 diabetes Disease progression modeling Insulin resistance β-cell function 
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Notes

Acknowledgments

This work was supported by the UB-Pfizer Strategic Alliance and by National Institutes of Health Grant GM24211.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Wei Gao
    • 1
  • Sébastien Bihorel
    • 1
    • 4
  • Debra C. DuBois
    • 2
  • Richard R. Almon
    • 2
    • 3
  • William J. Jusko
    • 1
  1. 1.Department of Pharmaceutical SciencesState University of New YorkBuffaloUSA
  2. 2.Department of Biological SciencesState University of New York at BuffaloBuffaloUSA
  3. 3.New York State Center of Excellence in Bioinformatics and Life SciencesBuffaloUSA
  4. 4.Cognigen CorporationBuffaloUSA

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