Diet-induced Weight Loss and Phenotypic Flexibility Among Healthy Overweight Adults: A Randomized Trial

Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models

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 (ρ = 0.67, p < 0.05) and the gold-standard hyperinsulinemic-euglycemic clamp. The model is also shown to quantify liver fat accumulation and β-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.

Large metabolic swings: when feeding exceeds its goals

Exaggerated blood excursions of nutrients and endogenous molecules in response to food intake may have health consequences if they repeatedly exceed the capacity of homeostatic mechanisms. Here, I discuss the significance of abnormally high postprandial metabolic fluctuations, the role of some influencing factors, and suggest ways to avoid them.