Measuring energy expenditure in Göttingen Minipigs using indirect calorimetry: validation and methodological...

Obesity affects nearly a billion people globally and is associated with various health consequences. Current anti-obesity medications primarily target appetite, but drug candidates that modulate energy expenditure (EE) and substrate utilization based on respiratory exchange ratio (RER) are also essential to continuously improve the treatment modalities for people living with obesity. Selecting appropriate animal models and methods is crucial to improving translational value in preclinical research. While pig obesity models provide a relevant alternative to rodent models due to their similarities to humans, little is known about the assessment and translatability of EE in pigs. The aim of this study was to evaluate the translatability of minipigs for assessing the effect of EE-modulating drugs using indirect calorimetry and three positive control compounds that have known effects on EE and/or RER in humans. The study consisted of five sub-studies: Sub-study 1 assessed EE and RER based on sex (male/female) and diet (chow/high-fat diet) with and without correction for body composition; Sub-studies 2-4 evaluated changes in EE and RER after treatment with three positive control compounds: 2,4-dinitrophenol, DNP; a glucagon receptor agonist, GCG-RA; and a melanocortin receptor 4 agonist, MC4-RA; and sub-study 5 established three predictive equations for resting metabolic rate.

Sub-study 1 resulted in detectable differences in EE and RER based on diet/body sizes (P-value < 0.0001), while EE adjusted for body composition resulted in differences based on sex (P-value < 0.0001). Sub-studies 2-4 revealed that the three pharmacological interventions known to affect EE in humans, DNP, GCG-RA, and MC4-RA, showed similar effects in the Göttingen Minipigs by significantly increasing EE by 26.1% (P-value: 0.0014), 21.3% (P-value: 0.0491), and 25.4% (P-value: 0.0013), respectively, emphasizing the translational value of the model. In sub-study 5, three predictive equations were established for RMR based on body composition, demographic and anthropometric measurements, and the most accurate equation based on all variables. All three equations demonstrated acceptable accuracy (adjusted R²: 0.73-0.85).

The present study qualifies the use of Göttingen Minipigs for investigating EE in preclinical research and provides a framework for conducting such research.