A data-driven computational model for obesity-driven diabetes onset and remission through weight loss

Vehpi Yildirim; Vivek M. Sheraton; Ruud Brands; Loes Crielaard; Rick Quax; Natal A.W. van Riel; Karien Stronks; Mary Nicolaou; Peter M.A. Sloot

doi:10.1016/j.isci.2023.108324

A data-driven computational model for obesity-driven diabetes onset and remission through weight loss

Vehpi Yildirim (Corresponding author), Vivek M. Sheraton, Ruud Brands, Loes Crielaard, Rick Quax, Natal A.W. van Riel, Karien Stronks, Mary Nicolaou, Peter M.A. Sloot

Onderzoeksoutput: Bijdrage aan tijdschrift › Tijdschriftartikel › Academic › peer review

3 Citaten (Scopus)

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Samenvatting

Obesity is a major risk factor for the development of type 2 diabetes (T2D), where a sustained weight loss may result in T2D remission in individuals with obesity. To design effective and feasible intervention strategies to prevent or reverse T2D, it is imperative to study the progression of T2D and remission together. Unfortunately, this is not possible through experimental and observational studies. To address this issue, we introduce a data-driven computational model and use human data to investigate the progression of T2D with obesity and remission through weight loss on the same timeline. We identify thresholds for the emergence of T2D and necessary conditions for remission. We explain why remission is only possible within a window of opportunity and the way that window depends on the progression history of T2D, individual's metabolic state, and calorie restrictions. These findings can help to optimize therapeutic intervention strategies for T2D prevention or treatment.

Originele taal-2	Engels
Artikelnummer	108324
Aantal pagina's	25
Tijdschrift	iScience
Volume	26
Nummer van het tijdschrift	11
DOI's	https://doi.org/10.1016/j.isci.2023.108324
Status	Gepubliceerd - 17 nov. 2023

Bibliografische nota

Publisher Copyright:
© 2023 The Author(s)

Financiering

This work was supported by a grant by ZonMw with the project number 531003015 . R.Q. also acknowledges the EU Horizon 2020 project TO_AITION ( nr 848146 ). V.Y. received partial support through a personal grant by TUBITAK ( nr 121F278 ). We also thank Albert K. Groen and Richard Bertram for their insightful remarks and helpful suggestions on the manuscript.

Financiers	Financiernummer
ZonMw : Dutch Organisation for Health Research and Development	531003015
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	121F278
Horizon 2020	848146

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10.1016/j.isci.2023.108324

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MATRyOSka: NWO/Complexity/MATRyOSka
van Riel, N. A. W. (Project Manager), O'Donovan, S. (Projectmedewerker), Arts, I. C. W. (Projectmedewerker) & Afman, L. A. (Projectmedewerker)
1/10/17 → 30/06/23
Project: Onderzoek direct
RESOLVE
van Riel, N. A. W. (Project Manager), Sips, F. L. P. (Projectmedewerker), Rozendaal, Y. J. W. (Projectmedewerker), Tiemann, C. A. (Projectmedewerker), Groen, B. (Program Manager) & Kuivenhoven, J. A. (PI)
1/01/13 → 30/06/18
Project: Onderzoek direct

Citeer dit

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abstract = "Obesity is a major risk factor for the development of type 2 diabetes (T2D), where a sustained weight loss may result in T2D remission in individuals with obesity. To design effective and feasible intervention strategies to prevent or reverse T2D, it is imperative to study the progression of T2D and remission together. Unfortunately, this is not possible through experimental and observational studies. To address this issue, we introduce a data-driven computational model and use human data to investigate the progression of T2D with obesity and remission through weight loss on the same timeline. We identify thresholds for the emergence of T2D and necessary conditions for remission. We explain why remission is only possible within a window of opportunity and the way that window depends on the progression history of T2D, individual's metabolic state, and calorie restrictions. These findings can help to optimize therapeutic intervention strategies for T2D prevention or treatment.",

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AU - Crielaard, Loes

AU - Quax, Rick

AU - van Riel, Natal A.W.

AU - Stronks, Karien

AU - Nicolaou, Mary

AU - Sloot, Peter M.A.

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AB - Obesity is a major risk factor for the development of type 2 diabetes (T2D), where a sustained weight loss may result in T2D remission in individuals with obesity. To design effective and feasible intervention strategies to prevent or reverse T2D, it is imperative to study the progression of T2D and remission together. Unfortunately, this is not possible through experimental and observational studies. To address this issue, we introduce a data-driven computational model and use human data to investigate the progression of T2D with obesity and remission through weight loss on the same timeline. We identify thresholds for the emergence of T2D and necessary conditions for remission. We explain why remission is only possible within a window of opportunity and the way that window depends on the progression history of T2D, individual's metabolic state, and calorie restrictions. These findings can help to optimize therapeutic intervention strategies for T2D prevention or treatment.

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A data-driven computational model for obesity-driven diabetes onset and remission through weight loss

Samenvatting

Bibliografische nota

Financiering

Duurzame ontwikkelingsdoelstellingen van de VN

Toegang tot document

Andere bestanden en links

Vingerafdruk

Projecten

MATRyOSka: NWO/Complexity/MATRyOSka

RESOLVE

Citeer dit