期刊
DIABETES
卷 49, 期 3, 页码 373-382出版社
AMER DIABETES ASSOC
DOI: 10.2337/diabetes.49.3.373
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资金
- NATIONAL HUMAN GENOME RESEARCH INSTITUTE [T32HG000042] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [R01DK029867] Funding Source: NIH RePORTER
- NHGRI NIH HHS [T32-HG-0042] Funding Source: Medline
- NIA NIH HHS [AG-00093] Funding Source: Medline
- NIDDK NIH HHS [DK-29867] Funding Source: Medline
The implication of beta-cell failure as an early defect in type 2 diabetes exacerbates the need for accurate but facile assessment of islet cell secretory rate, particularly in large group studies in which individual assessment of C-peptide kinetics is impractical. This study was designed to examine whether it is possible to obtain accurate secretory rates from the extended combined model, which provides insulin and C-peptide kinetics from plasma measurements of the two peptides, Equimolar intraportal infusions of insulin and C-peptide that are designed to simulate insulin secretion rates during both oral and intravenous glucose tolerance tests were used to generate plasma insulin and C-peptide data in conscious dogs that were examined under clamped glucose conditions. The plasma peptide kinetics were analyzed using the extended combined model to generate estimates of prehepatic insulin secretion that were then compared with the known intraportal infusion rates. The extended combined model was able to reproduce the known intraportal infusion profiles. The model-predicted rates were similar to those calculated with methods that require separate assessment of C-peptide kinetics. Simulation results supported lesser clearance of insulin during rapid changes of portal insulin (as measured by an intravenous glucose tolerance test) versus slow changes in portal insulin (as measured by an oral glucose tolerance test). The extended combined model accurately calculates prehepatic insulin appearance. It may be possible to apply this approach to large studies of beta-cell function designed to identify changes in islet function in subjects at risk for diabetes. Such an approach could strengthen epidemiological and genetic studies of the pathogenesis of diabetes.
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