Computational Model of Human Energy Metabolism

Abstract

The goal of this research is to create a computational model of nutrient digestion and metabolism to predict energy use and elucidate mechanisms involved in obesity. In the model, nutrient use is dependent on genetic and environmental factors such as body size and body composition, basal metabolic rate, heat production, physical activity, etc. Balance between nutrient intake and nutrient use determines if an individual is obese. The approach uses differential equations representing carbohydrate, amino acid and fatty acid uptake and output by tissues. Uptake is based on nutrient transport into tissues. Nutrients are metabolized for energy and tissue deposition. Equations estimate uptake and metabolism based on aggregated enzyme pathway kinetics. Energy creation and use is based on estimates of ATP/ADP, NADH/NAD, FADH/FAD and NADPH/NADP generation from biochemical pathways. Heat production is estimated from heats of combustion for substrates and heat from ATP use. Protein deposition is a function of maximum genetic potential for protein accretion and adipose deposition is a function of energy balance. Effects of changes in metabolic rate, increases in muscle mass and exercise intensity, or interactions between dietary carbohydrate and fat on nutrient metabolism and body composition are examined using the model. A model of energy and protein metabolism for humans will be a valuable tool for researchers, clinicians and students to explore diet and metabolism interactions and evaluate diets. Since humans are genetically diverse with a range of basal metabolic rates, activity levels and diets, a computational model will quantify diversity and predict metabolic function for a wide range of individuals.