Neural, hormonal and behavioral mechanisms of long-term weight maintenance

• Applicant: Professor Dr. John-Dylan Haynes
• Subject Area: Pediatric and Adolescent Medicine ; Endocrinology, Diabetology, Metabolism
• Term: from 2012 to 2015
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 101434729

Obesity is a major worldwide health problem due to its high prevalence and severe medical consequences. The key problem in the treatment of obesity is the frequent weight regain following a dietary induced weight loss that can even lead to weight levels above the level of baseline. Such effects will be recognized only with long-term observational studies. The neural mechanisms underlying such weight cycling processes and their relation to hormonal and behavioural parameters of energy homeostasis are largely unknown. The proposed project aims to simultaneously assess neural, hormonal, and behavioural parameters related to body weight in initially obese subjects during an extended interval of 2 to 3 years after they participated in the dietary intervention study. Neural activity will be measured using functional magnetic resonance imaging in combination with magnetic resonance spectroscopy, blood samples, behavioural protocols, and multivariate analysis techniques. The project has two major goals. First, it aims to characterize the mechanisms of weight maintenance based on neural, hormonal, and behavioural parameters. Second, it aims to derive suitable longitudinal predictors for long-term body maintenance from these measures. Regarding brain activity, we hypothesize that body weight changes will be reflected by changes in activity of rewardrelated brain areas involved in the regulation of non-homoeostatic food-intake (e.g., the striatum, the orbitofrontal cortex, and the insula). We assume that activity in these areas will also be predictive of future weight changes. Moreover, we put forward the hypothesis that activity in areas involved in food-related self-control (e.g., the dorsolateral prefrontal cortex) will be related to a given body weight and contain predictive information for future weight changes. To address these goals, highly sensitive multivariate pattern recognition analysis techniques will be applied. These methods can also identify subtle relations between factors that are only accessible by taking into account the co-variation structure of the data (which is ignored by univariate analysis methods applied in most traditional studies). Due to the combination of multimodal data acquisition and state-of-the-art analysis techniques, the project promises to substantially advance our understanding of long-term mechanisms of sustained obesity control.

• DFG Programme: Clinical Research Units
• Subproject of: KFO 218: Hormonal Regulation of Body Weight Maintenance
• Participating Person: Dr. Yvonne Rothemund