@article{ef17ffbb382c4adf84bbf380276b98a3,
title = "Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models",
abstract = "The manifestation of metabolic deteriorations that accompany overweight and obesity can differ greatly between individuals, giving rise to a highly heterogeneous population. This inter-individual variation can impede both the provision and assessment of nutritional interventions as multiple aspects of metabolic health should be considered at once. Here, we apply the Mixed Meal Model, a physiology-based computational model, to characterize an individual's metabolic health in silico. A population of 342 personalized models were generated using data for individuals with overweight and obesity from three independent intervention studies, demonstrating a strong relationship between the model-derived metric of insulin resistance (? = 0.67, p < 0.05) and the gold-standard hyperinsulinemic-euglycemic clamp. The model is also shown to quantify liver fat accumulation and {\ss}-cell functionality. Moreover, we show that personalized Mixed Meal Models can be used to evaluate the impact of a dietary intervention on multiple aspects of metabolic health at the individual level.",
keywords = "Human metabolism, Nutrition",
author = "O'Donovan, {Shauna D.} and Milena Rundle and Thomas, {E. Louise} and Bell, {Jimmy D.} and Gary Frost and Jacobs, {Doris M.} and Anne Wanders and {de Vries}, Ryan and Mariman, {Edwin C.M.} and {van Baak}, {Marleen A.} and Luc Sterkman and Max Nieuwdorp and Groen, {Albert K.} and Arts, {Ilja C.W.} and {van Riel}, {Natal A.W.} and Afman, {Lydia A.}",
note = "Funding Information: The authors would like to thank both the participants and researchers involved in the collection of data in the NutriTech, BellyFat, and MetFlex studies. The research presented in this manuscript was supported by a grant from the Dutch Research Council (NWO) [https://www.nwo.nl/] as part of the Complexity Program (project number 645.001.003) with contributions from the Unilever Food Innovation Center, Wageningen, the Netherlands [https://hive.unilever.com/] and Caelus Health, Amsterdam, the Netherlands [https://caelushealth.com/] awarded to N.A.W.v.R. I.C.W.A. and L.A.A. M.N. is supported by a personal ZonMw-VICI grant 2020 [09150182010020]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Conceptualization, L.A.A. I.C.W.A. S.D.O'D. and N.A.W.v.R.; Methodology, S.D.O'D. and N.A.W.v.R.; Resources, L.A.A. M.v.B. J.D.B. G.F. A.K.G. D.M.J. E.C.M.M. M.N. M.R. L.S. E.L.T. and A.J.W.; Software, S.D.O'D.; Formal Analysis, S.D.O'D.; Writing – Original Draft, S.D.O'D; Writing – Review & Editing, L.A.A, I.C.W.A, M.v.B. J.D.B. G.F. A.K.G. D.M.J. E.C.M.M. M.N. S.D.O'D. M.R. L.S. E.L.T. N.A.W.v.R. R.d.V. and A.J.W.; Funding Acquisition, L.A.A. I.C.W.A. and N.A.W.v.R.; Supervision, L.A.A. I.C.W.A. and N.A.W.v.R. D.M.J. and A.J.W. are employees of Unilever, which manufactures and markets consumer food products. L.S. is CEO and M.N. is in the scientific board of Caelus Pharmaceuticals, the Netherlands. However, these positions are not directly relevant for the content of this current paper. S.D.O'D. M.R. E.L.T. J.D.B. G.F. R.d.V. E.C.M.M. M.v.B. L.S. M.N. A.K.G. I.C.W.A. N.A.W.v.R. and L.A.A. declare no conflicts of interest. Funding Information: The research presented in this manuscript was supported by a grant from the Dutch Research Council (NWO)[ https://www.nwo.nl/ ] as part of the Complexity Program (project number 645.001.003) with contributions from the Unilever Food Innovation Center, Wageningen, the Netherlands [ https://hive.unilever.com/ ] and Caelus Health, Amsterdam, the Netherlands [ https://caelushealth.com/ ] awarded to N.A.W.v.R., I.C.W.A., and L.A.A. M.N. is supported by a personal ZonMw-VICI grant 2020 [ 09150182010020 ]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} 2024 The Author(s)",
year = "2024",
month = apr,
day = "19",
doi = "10.1016/j.isci.2024.109362",
language = "English",
volume = "27",
journal = "iScience",
issn = "2589-0042",
publisher = "Elsevier Inc.",
number = "4",
}