Literature DB >> 11815483

Assessing insulin secretion by modeling in multiple-meal tests: role of potentiation.

Andrea Mari1, Andrea Tura, Amalia Gastaldelli, Ele Ferrannini.   

Abstract

We developed a mathematical model of the glucose control of insulin secretion capable of quantifying beta-cell function from a physiological meal test. The model includes a static control, i.e., a secretion component that is a function of plasma glucose concentration (the dose-response function), and a dynamic control, i.e., a secretion component that is proportional to the positive values of the glucose concentration derivative. Furthermore, the dose-response function is assumed to be modulated by a time-varying potentiation factor. To test the model, nine nondiabetic control subjects and nine type 2 diabetic patients received three standardized mixed meals over a period of 14-15 h. Blood samples were drawn for the measurement of glucose, insulin, and C-peptide concentration. The dose-response function, the parameter of the dynamic control, and the potentiation factor were determined by fitting the model to glucose and C-peptide concentrations. In diabetic patients, the dose-response function was shifted to the right (glucose concentration at a reference insulin secretion of 300 pmol.min(-1).m(-2) was 11.7 +/- 1.1 vs. 7.2 +/- 0.7 mmol/l; P < 0.05), and decreased in slope (53 +/- 15 vs. 148 +/- 38 pmol.min(-1).m(-2).mmol(-1).l; P < 0.05) and the parameter of the dynamic control was decreased (220 +/- 67 vs. 908 +/- 276 pmol.m(-2).mmol(-1).l; P < 0.05) compared with the nondiabetic control subjects. Furthermore, potentiation was markedly blunted and delayed: maximum potentiation was observed at the first meal in normal subjects and at the second meal (about 4 h later) in diabetic subjects; the mean time for the potentiation factor was higher (7.1 +/- 0.2 vs. 5.9 +/- 0.2 h; P < 0.01), and the size of potentiation was reduced (2.6 +/- 0.5 vs. 7.2 +/- 1.5 fold increase; P < 0.005). In conclusion, our model of insulin secretion extracts multiple indexes of beta-cell function from a physiological meal test. Use of the model in patients with type 2 diabetes retrieves known defects in insulin secretion but also uncovers new facets of beta-cell dysfunction.

Entities:  

Mesh:

Substances:

Year:  2002        PMID: 11815483     DOI: 10.2337/diabetes.51.2007.s221

Source DB:  PubMed          Journal:  Diabetes        ISSN: 0012-1797            Impact factor:   9.461


  76 in total

1.  Impact of family history of diabetes on β-cell function and insulin resistance among Chinese with normal glucose tolerance.

Authors:  Gang Chen; Meizhi Li; Yuan Xu; Nianhui Chen; Huibin Huang; Jixing Liang; Liantao Li; Junping Wen; Lixiang Lin; Jin Yao
Journal:  Diabetes Technol Ther       Date:  2012-03-09       Impact factor: 6.118

2.  Altered pattern of the incretin effect as assessed by modelling in individuals with glucose tolerance ranging from normal to diabetic.

Authors:  Andrea Tura; Elza Muscelli; Amalia Gastaldelli; Ele Ferrannini; Andrea Mari
Journal:  Diabetologia       Date:  2014-06       Impact factor: 10.122

3.  Restoration of normal glucose tolerance in severely obese patients after bilio-pancreatic diversion: role of insulin sensitivity and beta cell function.

Authors:  A Mari; M Manco; C Guidone; G Nanni; M Castagneto; G Mingrone; E Ferrannini
Journal:  Diabetologia       Date:  2006-07-04       Impact factor: 10.122

4.  Postdinner resistance exercise improves postprandial risk factors more effectively than predinner resistance exercise in patients with type 2 diabetes.

Authors:  Timothy D Heden; Nathan C Winn; Andrea Mari; Frank W Booth; R Scott Rector; John P Thyfault; Jill A Kanaley
Journal:  J Appl Physiol (1985)       Date:  2014-12-24

5.  Influence of endogenous NEFA on beta cell function in humans.

Authors:  Eleni Rebelos; Marta Seghieri; Andrea Natali; Beverly Balkau; Alain Golay; Pier Marco Piatti; Nebojsa M Lalic; Markku Laakso; Andrea Mari; Ele Ferrannini
Journal:  Diabetologia       Date:  2015-07-10       Impact factor: 10.122

6.  Predictive performance for population models using stochastic differential equations applied on data from an oral glucose tolerance test.

Authors:  Jonas B Møller; Rune V Overgaard; Henrik Madsen; Torben Hansen; Oluf Pedersen; Steen H Ingwersen
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-12-16       Impact factor: 2.745

7.  β-Cell lipotoxicity after an overnight intravenous lipid challenge and free fatty acid elevation in African American versus American white overweight/obese adolescents.

Authors:  Kara S Hughan; Riccardo C Bonadonna; SoJung Lee; Sara F Michaliszyn; Silva A Arslanian
Journal:  J Clin Endocrinol Metab       Date:  2013-03-22       Impact factor: 5.958

8.  Progression to diabetes in relatives of type 1 diabetic patients: mechanisms and mode of onset.

Authors:  Ele Ferrannini; Andrea Mari; Valentina Nofrate; Jay M Sosenko; Jay S Skyler
Journal:  Diabetes       Date:  2009-12-22       Impact factor: 9.461

9.  One-hour plasma glucose identifies insulin resistance and beta-cell dysfunction in individuals with normal glucose tolerance: cross-sectional data from the Relationship between Insulin Sensitivity and Cardiovascular Risk (RISC) study.

Authors:  Melania Manco; Simona Panunzi; David P Macfarlane; Alain Golay; Olle Melander; Thomas Konrad; John R Petrie; Geltrude Mingrone
Journal:  Diabetes Care       Date:  2010-09       Impact factor: 19.112

Review 10.  Beta cell function and its relation to insulin action in humans: a critical appraisal.

Authors:  E Ferrannini; A Mari
Journal:  Diabetologia       Date:  2004-04-23       Impact factor: 10.122

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.