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Modelling the effect of very low calorie diet on weight and fasting plasma glucose in obese type 2 diabetic patients
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Research Group)
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Background: Change in weight (WT) as a result of diet changes is closely associated with change in fasting plasma glucose (FPG) in type 2 diabetes mellitus (T2DM) patients. Two hypotheses on this relationship are 1) weight loss induces a change in an intermediary effector that reduces FPG, with the intermediary effector being insulin sensitivity (IS) or 2) an underlying change of the system affects weight as well as FPG. The aim of this study was to test these hypotheses using non-linear mixed effects modelling on summary level data from publications of weight loss with very low calorie diets (VLCD).

Methods: Summary level data was gathered from 8 clinical studies of diabetic patients (n=167 from 12 arms) treated with VLCD where weight and FPG was measured. The patients had a baseline weight ranging from 93-118 kg, and baseline FPG ranging from 91-321 mg/dL, treated with VLCD for up to 224 days. Non-linear mixed-effects modelling was performed using NONMEM 7.2.

Results: Both weight and FPG was modelled using indirect response models, with VLCD implemented as an instantaneous inhibitory effect on the input. The objective function value for the model describing hypothesis 2 was significantly lower than for hypothesis 1. The VLCD diet was estimated to reduce 42% of the Kin of weight and 51% of the Kin of FPG. Baseline BMI was a significant covariate effect on the scaling factor for the effect on FPG.

Conclusions: The model with an underlying mechanism that affects both weight and FPG was found to better describe the data than using weight loss as an effector on a mediator through which FPG is reduced.

Keyword [en]
Body weight, fasting plasma glucose, type 2 diabetes, very low calorie diet, modelling, weight loss, meta-analysis
National Category
Endocrinology and Diabetes
Research subject
Pharmaceutical Science
Identifiers
URN: urn:nbn:se:uu:diva-272229OAI: oai:DiVA.org:uu-272229DiVA: diva2:893558
Available from: 2016-01-12 Created: 2016-01-12 Last updated: 2016-02-08
In thesis
1. Semi-mechanistic models of glucose homeostasis and disease progression in type 2 diabetes
Open this publication in new window or tab >>Semi-mechanistic models of glucose homeostasis and disease progression in type 2 diabetes
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by consistently high blood glucose, resulting from a combination of insulin resistance and reduced capacity of β-cells to secret insulin. While the exact causes of T2DM is yet unknown, obesity is known to be a major risk factor as well as co-morbidity for T2DM. As the global prevalence of obesity continues to increase, the association between obesity and T2DM warrants further study. Traditionally, mathematical models to study T2DM were mostly empirical and thus fail to capture the dynamic relationship between glucose and insulin. More recently, mechanism-based population models to describe glucose-insulin homeostasis with a physiological basis were proposed and offered a substantial improvement over existing empirical models in terms of predictive ability.

The primary objectives of this thesis are (i) examining the predictive usefulness of semi-mechanistic models in T2DM by applying an existing population model to clinical data, and (ii) exploring the relationship between obesity and T2DM and describe it mathematically in a novel semi-mechanistic model to explain changes to the glucose-insulin homeostasis and disease progression of T2DM.

Through the use of non-linear mixed effects modelling, the primary mechanism of action of an antidiabetic drug has been correctly identified using the integrated glucose-insulin model, reinforcing the predictive potential of semi-mechanistic models in T2DM. A novel semi-mechanistic model has been developed that incorporated a relationship between weight change and insulin sensitivity to describe glucose, insulin and glycated hemoglobin simultaneously in a clinical setting. This model was also successfully adapted in a pre-clinical setting and was able to describe the pathogenesis of T2DM in rats, transitioning from healthy to severely diabetic.

This work has shown that a previously unutilized biomarker was found to be significant in affecting glucose homeostasis and disease progression in T2DM, and that pharmacometric models accounting for the effects of obesity in T2DM would offer a more complete physiological understanding of the disease.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 78 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 210
Keyword
pharmacokinetics, pharmacodynamics, pharmacometrics, glucose homeostasis, insulin, type 2 diabetes, obesity, weight, visceral adipose tissue, HbA1c, non-linear mixed effects, modelling, disease progression, ZDSD rats
National Category
Endocrinology and Diabetes
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-273709 (URN)978-91-554-9456-8 (ISBN)
Public defence
2016-03-04, B41, Biomedicinskt Centrum (BMC), Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2016-02-05 Created: 2016-01-17 Last updated: 2016-02-12

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Choy, Steve

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