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Communication Dans Un Congrès Année : 2024

Modeling Intestinal Glucose Absorption from D-xylose Data

Danilo Dursoniah
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Maxime Folschette
Cédric Lhoussaine

Résumé

Type 2 Diabetes (T2D) is one of the main epidemics of this century. One of the hypothesis of medical research is that an important cause of T2D may be the abnormal regulation of intestinal glucose absorption (IGA). Early detection of IGA disorders, and, more generally, precision medicine, may help to prevent the risk of T2D. This could be achieved by predictive models of glucose dynamics in blood following an oral ingestion. Even though many such models have been proposed, they either do not cope with IGA at all, or their calibration requires the use of complex and invasive tracer protocols that make them clinically unusable on a daily basis. To overcome this issue, D-xylose may be used as an IGA marker. Indeed, it is a glucose analogue with similar intestinal absorption mechanisms but, contrary to glucose, its dynamics in blood only results from gastric emptying, intestinal absorption and elimination by the kidney. In this paper, we investigate, for the first time, a model-based assessment of IGA based on D-xylose dynamics in blood after oral absorption. We show that a multi-compartment model of instestinal absorption can fit very well D-xylose data obtained from different experimental conditions and be a good qualitative estimate of IGA. And addition, because gastric emptying is a possible confounding factor with intestinal absorption, we explore the relative contribution of both mechanisms to the rate of D-xylose (and thus glucose) appearance in blood.
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Dates et versions

hal-04329210 , version 1 (07-12-2023)
hal-04329210 , version 2 (12-12-2023)
hal-04329210 , version 3 (22-04-2024)

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Danilo Dursoniah, Maxime Folschette, Rebecca Goutchtat, Violeta Raverdy, François Pattou, et al.. Modeling Intestinal Glucose Absorption from D-xylose Data. 15th International Conference on Bioinformatics, Models, Methods and Algorithms, Feb 2024, Rome, Italy. pp.438-445, ⟨10.5220/0012358300003657⟩. ⟨hal-04329210v3⟩
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