Brain Dopamine Dynamics in Obesity

About This Grant

Abstract Obesity poses serious health risks and financial burden on healthcare systems. Increased food intake drives obesity, making understanding of overeating mechanisms crucial for developing anti-obesity medications. The brain dopamine (DA) system is a major regulator of food intake, and DA system disruption has been identified in obesity. DA signaling governs reward learning and eating motivation; dysfunction contributes to craving and overeating. While data show differences in striatal DA receptors in human obesity, results are inconsistent. Most human brain DA studies are performed during fasting, yet rodent studies show that DA responses during feeding are more relevant for food intake behavior. The DA response to nutrients consists of an immediate orosensory peak followed by a later post-ingestive peak. High fat/sugar foods reduce nutrient-induced post-ingestive striatal DA release in rodents, and we showed that people with obesity show no measurable striatal DA release upon intragastric lipid infusion. However, which factors drive brain DA responses and whether these responses affect specific food intake behaviors remains unknown in humans. Brain DA dynamics after meals in people with normal versus high BMI are also unknown. Elucidating interactions between brain DA responses to nutrients, metabolic responses to food, and food intake behavior will advance understanding of eating beyond homeostatic need. We propose to study striatal DA responses to milkshake consumption in people with normal and high BMI using a novel ultra-high performance PET system (resolution <1.4 mm), assessing onset, duration, and associations between DA peaks and sex differences. We will determine the metabolic/hormonal factors that drive the DA response and the relationships between DA responses and food intake behavior characteristics. Given complex non-linear relationships between variables, we will use machine learning (ML) approaches. Finally, we will leverage high-resolution and ultrasensitive PET to study extrastriatal DA release. Using independent component analysis and ML, we will define brain DA networks in response to nutrients in both weight groups and assess network determinants and effects on food intake behavior. Overall, our proposed studies will provide fundamental knowledge on overeating mechanisms in obesity.