摘要：SummaryDespite 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.Graphical abstractDisplay OmittedHighlights•The Mixed Meal Model describes both lipid and carbohydrate metabolism•The Meal Model quantifies insulin resistance, β-cell functionality, and liver fat•The Model reduces meal data to a three-dimensional measure of metabolic health•Physiology-informed regularization produces more reliable and relevant parametersHuman metabolism; Systems biology; In silico biology; Nutrition
