1. The Food Environment, Preference, and Experience Modulate the Effects of Exendin-4 on Food Intake and Reward
- Author
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Pierre Paul Romagnoli, Claudio E. Perez-Leighton, Jennifer A. Teske, Camila B. Schmidt, and Ricardo Mella
- Subjects
0301 basic medicine ,Agonist ,Nutrition and Dietetics ,biology ,medicine.drug_class ,Endocrinology, Diabetes and Metabolism ,digestive, oral, and skin physiology ,Medicine (miscellaneous) ,Cafeteria ,biology.organism_classification ,medicine.disease ,Obesity ,Preference ,Conditioned place preference ,03 medical and health sciences ,030104 developmental biology ,0302 clinical medicine ,Endocrinology ,Hypothalamus ,medicine ,Anorectic ,Food science ,Exenatide ,030217 neurology & neurosurgery ,medicine.drug - Abstract
Objective The obesogenic food environment facilitates access to multiple palatable foods. Exendin-4 (EX4) is a glucagon-like peptide 1 receptor (GLP1R) agonist that inhibits food intake and has been proposed as an obesity therapy. This study tested whether the composition of the food environment and experience with palatable foods modulate the effects of EX4 on food intake and reward. Methods Mice fed a cafeteria (CAF) or control diet were tested for the anorectic effects of EX4 when simultaneously offered foods of varying individual preference and in a conditioned place preference (CPP) test for chocolate. Plasma glucagon-like peptide 1 (GLP1) and hypothalamic GLP1R mRNA were analyzed post mortem. Results Mice fed a CAF diet developed individual food preference patterns. Offering mice either novel or highly preferred foods decreased the potency of EX4 to inhibit food intake compared to low preference foods or chow. Compared to the control diet, CAF diet intake blocked the decrease in chocolate CPP caused by EX4 and decreased the expression of hypothalamic GLP1R mRNA without altering the plasma GLP1 concentration. Conclusions The composition of the food environment, food preference, and experience modulate the ability of EX4 to inhibit food intake and reward. These data highlight the significance of modeling the complexity of the human food environment in preclinical obesity studies.
- Published
- 2017