ArticleiScience2022
Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Integrating Sensory Perception and Wearable Monitoring to Promote Healthy Aging: A New Frontier in Nutritional Personalization.Nutrients · 2026Review
- The mediating effect of triglycerides and related indices on the association between polycyclic aromatic hydrocarbons and oral health in adults aged ≥ 45 years from the national health and nutrition examination survey 2003-2016.Lipids in health and disease · 2026Article
- Understanding metabolic resilience by unraveling temporal dynamics of cellular responses.Trends in endocrinology and metabolism: TEM · 2025Review
- Physiology-informed regularisation enables training of universal differential equation systems for biological applications.PLoS computational biology · 2025Article
- Mathematical model of the inflammatory response to acute and prolonged lipopolysaccharide exposure in humans.NPJ systems biology and applications · 2024Article
- Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models.iScience · 2024Article
- Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism.Scientific reports · 2024Article
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Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.