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

Shauna D. O'Donovan*, Balázs Erdős, Doris M. Jacobs, Anne J. Wanders, E.L. Thomas, Jimmy D. Bell, Milena Rundle, Gary Frost, Ilja C.W. Arts, Lydia A. Afman, Natal A.W. van Riel

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Article number105206
Issue number11
Publication statusPublished - 18 Nov 2022


  • Human metabolism
  • In silico biology
  • Nutrition
  • Systems biology


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