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bioRxiv · 10.1101/2022.01.24.476744

Mathematical Modeling of Thyroid Homeostasis: Implications for the Allan-Herndon-Dudley Syndrome

Wolff, T. M.·Veil, C.·Dietrich, J. W.·Mueller, M. A.
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Abstract

ObjectiveA mathematical model of the pituitary-thyroid feedback loop is extended to deepen the understanding of the Allan-Herndon-Dudley syndrome (AHDS). BackgroundThe AHDS is characterized by unusual thyroid hormone concentrations and a mutation in the SLC16A2 gene encoding for the monocarboxylate transporter 8 (MCT8). This mutation leads to a loss of thyroid hormone transport activity. One hypothesis to explain the unusual hormone concentrations of AHDS patients is that due to the loss of thyroid hormone transport activity, thyroxine (T4) is partially retained in thyroid cells. MethodsThis hypothesis is investigated by extending a mathematical model of the pituitary-thyroid feedback loop to include a model of the net effects of membrane transporters such that the thyroid hormone transport activity can be considered. Two modeling approaches of the membrane transporters are employed: on the one hand a nonlinear approach based on the Michaelis-Menten kinetics and on the other hand its linear approximation. The unknown parameters are identified through a constrained parameter optimization. ResultsIn dynamic simulations, damaged membrane transporters result in a retention of T4 in thyroid cells and ultimately in the unusual hormone concentrations of AHDS patients. The two different modeling approaches lead to similar results. ConclusionThe results support the hypothesis that a partial retention of T4 in thyroid cells represents one mechanism responsible for the unusual hormone concentrations of AHDS patients. Moreover, our results suggest that the retention of T4 in thyroid cells could be the main reason for the unusual hormone concentrations of AHDS patients.

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Wolff, T. M., Veil, C., Dietrich, J. W., Mueller, M. A.. 2022-01-24. Mathematical Modeling of Thyroid Homeostasis: Implications for the Allan-Herndon-Dudley Syndrome. https://doi.org/10.1101/2022.01.24.476744

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