Unraveling the homeostatic and hedonic circuits underlying feeding behavior and obesity

项目概要 The striking prevalence of obesity and its associated personal and public health consequences highlights the importance of understanding why individuals overeat and gain weight.人们普遍认为暴饮暴食 results from a combination of homeostatic (i.e., nutrient need, hunger) and hedonic (i.e., pleasure, reward) drives. While these homeostatic (e.g., hypothalamic) and hedonic [e.g., midbrain dopamine (DA)] systems have been characterized as discrete drivers of food intake, there is considerable evidence that these systems overlap.对于 example, DA signaling in response to food is potentiated by hunger, increasing the reward value of food during 需要体内平衡的时间。 Our recent findings in rodent models revealed a neural correlate for the interaction 稳态系统和享乐系统之间。饥饿敏感的下丘脑刺鼠相关蛋白的活性 (AgRP)-expressing neurons potentiates the DA response to food.相反，DA 信号增强 AgRP 神经元对食物的稳态反应。 AgRP 和 DA 神经元相互作用的电路是什么 对食物的反应？它们是否有助于解释为什么有些人更有可能暴饮暴食和体重增加？这个 proposal will test the overarching hypotheses that distinct AgRP and DA neuron subpopulations mediate the 稳态和奖励信号之间的相互作用以及 AgRP 和 DA 反应的个体差异 通过食物预测未来的体重增加。 Aim I experiments will determine the AgRP neuron projection subpopulations 增强 DA 对食物的反应。 We will leverage the anatomical organization of AgRP neurons, as well as 光遗传学和化学遗传学技术，单独测试每个 AgRP 投射亚群的情况 影响食物诱发的 DA 信号传导。 Aim II experiments will determine sites of action for DA modulation of AgRP 神经元活动。 We will use genetic and pharmacological approaches to examine how DA projections and neurotransmitter signaling influence AgRP neuron activity.目标 III 将确定 AgRP 和 DA 活性如何 预测未来的暴饮暴食和体重增加。利用体重增加的可变性来响应 高脂肪、高糖饮食，我们将确定瘦小鼠神经活动的个体差异是否可以预测未来 暴饮暴食和肥胖的发展。总的来说，这些实验采用了独特的方法来理解 weight gain by (1) determining the neural intersection of homeostatic and hedonic circuits that have classically 被认为是摄入量的离散驱动因素，并且（2）识别神经活动生物标志物来预测暴饮暴食和 肥胖倾向。最终，拟议研究的结果将揭示细胞和分子靶标 可用于制定肥胖预防和更有效的减肥策略。

PROJECT SUMMARY The striking prevalence of obesity and its associated personal and public health consequences highlights the importance of understanding why individuals overeat and gain weight. It is widely recognized that overeating results from a combination of homeostatic (i.e., nutrient need, hunger) and hedonic (i.e., pleasure, reward) drives. While these homeostatic (e.g., hypothalamic) and hedonic [e.g., midbrain dopamine (DA)] systems have been characterized as discrete drivers of food intake, there is considerable evidence that these systems overlap. For example, DA signaling in response to food is potentiated by hunger, increasing the reward value of food during times of homeostatic need. Our recent findings in rodent models revealed a neural correlate for the interaction between homeostatic and hedonic systems. Activity in hunger-sensitive, hypothalamic agouti-related protein (AgRP)-expressing neurons potentiates the DA response to food. Conversely, DA signaling enhances the homeostatic AgRP neuron response to food. What are the circuits through which AgRP and DA neurons interact in response to food? Do they help explain why some individuals are more likely to overeat and gain weight? This proposal will test the overarching hypotheses that distinct AgRP and DA neuron subpopulations mediate the interaction between homeostatic and reward signaling and that individual differences in AgRP and DA responses to food predict future weight gain. Aim I experiments will determine the AgRP neuron projection subpopulations that potentiate DA responses to food. We will leverage the anatomical organization of AgRP neurons, as well as optogenetic and chemogenetic technologies, to individually test how each AgRP projection subpopulation influences food-evoked DA signaling. Aim II experiments will determine sites of action for DA modulation of AgRP neuron activity. We will use genetic and pharmacological approaches to examine how DA projections and neurotransmitter signaling influence AgRP neuron activity. Aim III will determine how AgRP and DA activity predicts future overeating and weight gain. Taking advantage of the variability in weight gain in response to a high-fat, high-sugar diet, we will determine if individual differences in neural activity in lean mice predict future overeating and the development of obesity. Overall, these experiments take a unique approach to understanding weight gain by (1) determining the neural intersection of homeostatic and hedonic circuits that have classically been considered discrete drivers of intake and (2) identifying neural activity biomarkers to predict overeating and obesity predisposition. Ultimately, results from the proposed studies will reveal cellular and molecular targets that can be leveraged to develop obesity prevention and more effective weight loss strategies.