E-DES-PROT: A novel computational model to describe the effects of amino acids and protein on postprandial glucose and insulin dynamics in humans
Bart van Sloun,
Gijs H. Goossens,
Balázs Erdõs,
Shauna D. O’Donovan,
Cécile M. Singh-Povel,
Jan M.W. Geurts,
Natal A.W. van Riel,
Ilja C.W. Arts
Affiliations
Bart van Sloun
TiFN, Wageningen, the Netherlands; Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands; Corresponding author
Gijs H. Goossens
TiFN, Wageningen, the Netherlands; Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
Balázs Erdõs
TiFN, Wageningen, the Netherlands; Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
Shauna D. O’Donovan
Division of Human Nutrition and Health, Wageningen University, Wageningen, the Netherlands; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
Cécile M. Singh-Povel
FrieslandCampina, Amersfoort, the Netherlands
Jan M.W. Geurts
FrieslandCampina, Amersfoort, the Netherlands
Natal A.W. van Riel
Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands; Department of Experimental Vascular Medicine, Amsterdam University Medical Centers, location AMC, Amsterdam, the Netherlands
Ilja C.W. Arts
TiFN, Wageningen, the Netherlands; Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
Summary: Current computational models of whole-body glucose homeostasis describe physiological processes by which insulin regulates circulating glucose concentrations. While these models perform well in response to oral glucose challenges, interaction with other nutrients that impact postprandial glucose metabolism, such as amino acids (AAs), is not considered. Here, we developed a computational model of the human glucose-insulin system, which incorporates the effects of AAs on insulin secretion and hepatic glucose production. This model was applied to postprandial glucose and insulin time-series data following different AA challenges (with and without co-ingestion of glucose), dried milk protein ingredients, and dairy products. Our findings demonstrate that this model allows accurate description of postprandial glucose and insulin dynamics and provides insight into the physiological processes underlying meal responses. This model may facilitate the development of computational models that describe glucose homeostasis following the intake of multiple macronutrients, while capturing relevant features of an individual’s metabolic health.