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

Shauna D. O'Donovan (Corresponding author), Michael Lenz, Roel G. Vink, Nadia J.T. Roumans, Theo M.C.M. de Kok, Edwin C.M. Mariman, Ralf L.M. Peeters, Natal A.W. van Riel, Marleen A. van Baak, Ilja C.W. Arts

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    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.

    Original languageEnglish
    Article numbere1007400
    Number of pages23
    JournalPLoS Computational Biology
    Volume15
    Issue number10
    Early online date3 Oct 2019
    DOIs
    Publication statusPublished - Oct 2019

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