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PLoS Comput Biol. 2019 Oct 3;15(10):e1007400. doi: 10.1371/journal.pcbi.1007400. [Epub ahead of print]

A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data.

Author information

1
Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.
2
Division of Human Health and Nurtrition, Wageningen University, Wageningen, The Netherlands.
3
Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany.
4
Preventive Cardiology and Preventative Medicine - Center for Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
5
Dept. Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.
6
Dept. Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
7
Dept. Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands.
8
Dept. Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
9
Dept. Epidemiology, CARIM School for Cardiovascular Disease, Maastricht University, Maastricht, The Netherlands.

Abstract

Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with the development of Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models of glucose-insulin dynamics have been extended to account for the interplay with NEFA. In this study, we use arteriovenous measurement across the subcutaneous adipose tissue during a mixed meal challenge test to evaluate the performance and underlying assumptions of three existing models of adipose tissue metabolism and construct a new, refined model of adipose tissue metabolism. Our model introduces new terms, explicitly accounting for the conversion of glucose to glyceraldehye-3-phosphate, the postprandial influx of glycerol into the adipose tissue, and several physiologically relevant delays in insulin signalling in order to better describe the measured adipose tissues fluxes. We then applied our refined model to human adipose tissue flux data collected before and after a diet intervention as part of the Yoyo study, to quantify the effects of caloric restriction on postprandial adipose tissue metabolism. Significant increases were observed in the model parameters describing the rate of uptake and release of both glycerol and NEFA. Additionally, decreases in the model's delay in insulin signalling parameters indicates there is an improvement in adipose tissue insulin sensitivity following caloric restriction.

PMID:
31581241
DOI:
10.1371/journal.pcbi.1007400
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Conflict of interest statement

The authors have declared that no competing interests exist.

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