Implication of lipid turnover for the control of energy balance.
Samuel BernardKirsty L SpaldingPublished in: Philosophical transactions of the Royal Society of London. Series B, Biological sciences (2023)
The ongoing obesity epidemic is a consequence of a progressive energy imbalance. The energy-balance model (EBM) posits that obesity results from an excess in food intake and circulating fuels. A reversal in causality has been proposed recently in the form of the carbohydrate-insulin model (CIM), according to which fat storage drives energy imbalance. Under the CIM, dietary carbohydrates shift energy use in favour of storage in adipose tissue. The dynamics of lipid storage and mobilization could, therefore, be sensitive to changes in carbohydrate intake and represent a measurable component of the CIM. To characterize potential changes in lipid dynamics induced by carbohydrates, mathematical models were used. Here, we propose a coherent mathematical implementation of the CIM-energy deposition model (CIM-EDM), which includes lipid turnover dynamics. Using lipid turnover data previously obtained by radiocarbon dating, we build two cohorts of virtual patients and simulate lipid dynamics during ageing and weight loss. We identify clinically testable lipid dynamic parameters that discriminate between the CIM-EDM and an energy in, energy out implementation of the EBM (EBM-IOM). Using a clinically relevant two-month virtual trial, we additionally identify scenarios and propose mechanisms whereby individuals may respond differently to low-carbohydrate diets. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.
Keyphrases
- weight loss
- adipose tissue
- insulin resistance
- type diabetes
- fatty acid
- metabolic syndrome
- bariatric surgery
- bone mineral density
- weight gain
- end stage renal disease
- randomized controlled trial
- primary care
- chronic kidney disease
- clinical trial
- body mass index
- roux en y gastric bypass
- newly diagnosed
- study protocol
- postmenopausal women
- high fat diet
- quality improvement
- machine learning
- electronic health record
- skeletal muscle
- phase iii
- artificial intelligence
- open label
- data analysis