Interaction of circulating GLP-1 and the response of the dorsolateral prefrontal cortex to food-cues predicts body weight development

OBJECTIVES: This study evaluated the impact of the interaction between the anorexigenic incretin hormone glucagon-like peptide-1 (GLP-1) and reward-related brain activity in the dorsolateral prefrontal cortex (DLPFC), a key area of behavioral control, on future weight loss in obese individuals. METHODS: We performed a weight loss-weight maintenance intervention study over 27 months. We applied an fMRI food-cue reactivity paradigm during which the participants were passively exposed to food pictures to evaluate neuronal activity in the DLPFC. Additionally, we measured concentrations of circulating GLP-1 levels during a standard oral glucose tolerance test. Phenotyping was performed consecutively before and after a 3-month low-calorie diet as well as after a randomized 12-month trial, investigating the effect of a combined behavioral intervention on body weight maintenance. Participants were then followed-up for another 12 months without further intervention. RESULTS: Using voxel-wise linear mixed-effects regression analyses, we evaluated 56 measurements and identified a strong interaction between circulating, endogenous GLP-1 levels and DLPFC activity predicting body weight change over the total observation period (t = −6.17, p = 1.6 · 10(−7)). While neither the GLP-1 nor the DLPFC response individually predicted the subsequent weight change, participants achieved body weight loss when the GLP-1 and the DLPFC responses occurred concurrently. CONCLUSIONS: Our data demonstrate an interaction between a peripheral hormonal signal and central nervous activity as robust predictor of body weight change throughout the different periods of a long-term life-style intervention. The preeminent role of their interdependency compared to the partly ambivalent effects of the single components argues for integrative approaches to improve sensitivity and reliability of weight prediction conventionally based on individual biomarkers.