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Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model. / O'Donovan, Shauna D.; Erdős, Balázs; Jacobs, Doris M. et al.

In: iScience, Vol. 25, No. 11, 105206, 18.11.2022.

Research output: Contribution to journalArticleAcademicpeer-review

Harvard

O'Donovan, SD, Erdős, B, Jacobs, DM, Wanders, AJ, Thomas, EL, Bell, JD, Rundle, M, Frost, G, Arts, ICW, Afman, LA & van Riel, NAW 2022, 'Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model', iScience, vol. 25, no. 11, 105206. https://doi.org/10.1016/j.isci.2022.105206

APA

O'Donovan, S. D., Erdős, B., Jacobs, D. M., Wanders, A. J., Thomas, E. L., Bell, J. D., Rundle, M., Frost, G., Arts, I. C. W., Afman, L. A., & van Riel, N. A. W. (2022). Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model. iScience, 25(11), [105206]. https://doi.org/10.1016/j.isci.2022.105206

Vancouver

O'Donovan SD, Erdős B, Jacobs DM, Wanders AJ, Thomas EL, Bell JD et al. Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model. iScience. 2022 Nov 18;25(11). 105206. https://doi.org/10.1016/j.isci.2022.105206

Author

O'Donovan, Shauna D. ; Erdős, Balázs ; Jacobs, Doris M. et al. / Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model. In: iScience. 2022 ; Vol. 25, No. 11.

BibTeX

@article{143d79bf60d24ee9843c8a51ee875238,
title = "Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model",
abstract = "Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalizable, applying it to meals with diverse macro-nutrient compositions. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity.",
keywords = "Human metabolism, In silico biology, Nutrition, Systems biology",
author = "O'Donovan, {Shauna D.} and Bal{\'a}zs Erd{\H o}s and Jacobs, {Doris M.} and Wanders, {Anne J.} and Thomas, {E. Louise} and Bell, {Jimmy D.} and Milena Rundle and Gary Frost and Arts, {Ilja C. W.} and Afman, {Lydia A.} and {van Riel}, {Natal A. W.}",
note = "Funding Information: The authors would like to thank both the participants and researchers involved in the collection of data in the NutriTech and MetFlex studies. The research presented in this article was supported by a grant from the Dutch Research Council ( NWO )[ https://www.nwo.nl/ ] as part of the Complexity Programme (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. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article. Funding Information: The authors would like to thank both the participants and researchers involved in the collection of data in the NutriTech and MetFlex studies. The research presented in this article was supported by a grant from the Dutch Research Council (NWO)[https://www.nwo.nl/] as part of the Complexity Programme (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. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article. Conceptualization, L.A.A, I.C.W.A, S.D.O'D, and N.A.W.v.R; methodology, B.E. S.D.O'D, and N.A.W.v.R; resources, L.A.A, J.D.B, G.F, D.M.J, M.R. 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, J.D.B. B.E, G.F. D.M.J. S.D.O'D, M.R. E.L.T. N.A.W.v.R, 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. SDOD, BE, ELT, JDB, MR, GF, ICWA, LAA, and NAWvR declare no conflicts of interest. DMJ and AJW are employees of Unilever, which manufactures and markets consumer food products. Publisher Copyright: {\textcopyright} 2022 The Authors",
year = "2022",
month = nov,
day = "18",
doi = "10.1016/j.isci.2022.105206",
language = "English",
volume = "25",
journal = "iScience",
issn = "2589-0042",
publisher = "Elsevier Inc.",
number = "11",

}

RIS

TY - JOUR

T1 - Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model

AU - O'Donovan, Shauna D.

AU - Erdős, Balázs

AU - Jacobs, Doris M.

AU - Wanders, Anne J.

AU - Thomas, E. Louise

AU - Bell, Jimmy D.

AU - Rundle, Milena

AU - Frost, Gary

AU - Arts, Ilja C. W.

AU - Afman, Lydia A.

AU - van Riel, Natal A. W.

N1 - Funding Information: The authors would like to thank both the participants and researchers involved in the collection of data in the NutriTech and MetFlex studies. The research presented in this article was supported by a grant from the Dutch Research Council ( NWO )[ https://www.nwo.nl/ ] as part of the Complexity Programme (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. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article. Funding Information: The authors would like to thank both the participants and researchers involved in the collection of data in the NutriTech and MetFlex studies. The research presented in this article was supported by a grant from the Dutch Research Council (NWO)[https://www.nwo.nl/] as part of the Complexity Programme (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. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article. Conceptualization, L.A.A, I.C.W.A, S.D.O'D, and N.A.W.v.R; methodology, B.E. S.D.O'D, and N.A.W.v.R; resources, L.A.A, J.D.B, G.F, D.M.J, M.R. 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, J.D.B. B.E, G.F. D.M.J. S.D.O'D, M.R. E.L.T. N.A.W.v.R, 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. SDOD, BE, ELT, JDB, MR, GF, ICWA, LAA, and NAWvR declare no conflicts of interest. DMJ and AJW are employees of Unilever, which manufactures and markets consumer food products. Publisher Copyright: © 2022 The Authors

PY - 2022/11/18

Y1 - 2022/11/18

N2 - Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalizable, applying it to meals with diverse macro-nutrient compositions. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity.

AB - Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalizable, applying it to meals with diverse macro-nutrient compositions. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity.

KW - Human metabolism

KW - In silico biology

KW - Nutrition

KW - Systems biology

UR - http://www.scopus.com/inward/record.url?scp=85140798980&partnerID=8YFLogxK

U2 - 10.1016/j.isci.2022.105206

DO - 10.1016/j.isci.2022.105206

M3 - Article

C2 - 36281448

VL - 25

JO - iScience

JF - iScience

SN - 2589-0042

IS - 11

M1 - 105206

ER -

ID: 26637617