Determining the Functional Brain Networks that Underlie Children’s Overeating and Adiposity Gain

确定导致儿童暴饮暴食和肥胖的大脑功能网络

• 批准号: 10538052
• 负责人: Bari Allison Fuchs
• 金额: $ 3.75万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10538052
• 关键词: 8 year old; Algorithms; Behavior Therapy; Brain; Brain region; COVID-19; Child; Cognitive; Communication; Complex; Cues; Data; Development; Eating; Eating Behavior; Energy Intake; Environment; Exhibits; Experimental Designs; Exposure to; Family; Feeding behaviors; Food; Functional Magnetic Resonance Imaging; Goals; Health; Hyperphagia; Image; Intervention; Laboratories; Measures; Mediating; Mental Health; Mentors; Mentorship; Modeling; Network-based; Neurobiology; Neurocognitive; Nucleic Acid Regulatory Sequences; Obesity; Palate; Pathway Analysis; Pattern; Phenotype; Prevention program; Process; Property; Protocols documentation; Public Health; Research; Research Personnel; Risk; Roentgen Rays; Science; Scientist; Statistical Methods; Subgroup; Sum; System; Techniques; Testing; Training; Weight; Weight Gain; Work; behavioral phenotyping; career; cognitive control; cue reactivity; design; eating in absence of hunger; executive function; follow-up; healthy weight; hedonic; innovation; insight; interest; neural network; neurobiological mechanism; neuroimaging; neuromechanism; novel; obesity development; obesity in children; obesity prevention; obesity risk; obesogenic; pandemic disease; physical conditioning; preadolescence; prevent; psychosocial; public health intervention; relating to nervous system; resilience; response; reward processing; therapy development

Project Summary Childhood obesity is a global pandemic associated with negative physical and psychosocial health outcomes4, and behavioral interventions to prevent childhood obesity produce small and variable effects5. Increased eating in the absence of hunger (EAH) has been identified as an obesogenic eating phenotype in children6, but the mechanisms that contribute to increased EAH prior to the development of obesity are unclear. A better understanding of the mechanisms that engender increased EAH and weight gain in children is critical to the development of more effective obesity prevention programs. Overeating is posited to result from an imbalance in brain regions involved in food cue reactivity and reward processing (i.e., a reactive system) with those involved in inhibition and cognitive control (i.e., a regulatory system)7–12. However, the patterns of functional connectivity between these neural systems which increase overeating and risk for obesity are unclear. Building on my sponsor’s R01 study, which is designed to examine neural and cognitive predictors of adiposity gain in children 7-8 years old who vary by familial risk for obesity, this proposal aims to identify the functional connectivity patterns (i.e., neural network properties) between reactive and regulatory brain systems that underlie EAH and adiposity gain. It is hypothesized that weaker connectivity between the reactive and regulatory system, and stronger connectivity within the reactive system, will be related to greater EAH and adiposity gain in children. To test these hypotheses, neuroimaging (fMRI) data collected during exposure to food cues will be used alongside food intake data from a laboratory assessment of EAH, during which children are offered a variety of palatable snack foods after eating a standard meal to fullness. Anthropomorphic assessments of adiposity will be collected at baseline and 1-year follow-up using dual x-ray absorptiometry (DXA). Innovative network analyses and advanced statistical methods will be used to identify and characterize child-specific neural networks from a priori “reactive” and “regulatory” brain regions of interest. Innovations offered by this proposal are (1) the use of sophisticated quantitative techniques to examine children’s neural networks during exposure to food cues and (2) the integration of network analyses with objectively-assessed hedonic eating and longitudinal measures of adiposity, which together will provide novel insight into the neural factors that promote overeating and risk for weight gain during the vulnerable pre-adolescent period. In addition, the inter-disciplinary mentorship team assembled in this proposal will provide rigorous training in experimental design for ingestive behavior research, neural network analyses, and scientific communication that will help advance my career as an independent researcher. The proposed study will enhance our understanding of the neural mechanisms supporting overeating and adiposity gain, which will inform the development of interventions to mitigate excess energy intake and the development of obesity.

项目摘要 儿童肥胖症是一种全球性流行病，与不良的身体和心理社会健康结果相关4， 行为干预对预防儿童肥胖的影响很小，而且效果不一。增加进食 在没有饥饿的情况下（EAH）已被确定为儿童肥胖饮食表型6，但 在肥胖症发展之前导致EAH增加的机制尚不清楚。更好的 了解导致儿童EAH增加和体重增加的机制对于 制定更有效的预防肥胖计划。暴饮暴食被认为是由于身体的不平衡 在涉及食物线索反应和奖励处理的脑区域（即，反应系统）与那些 参与抑制和认知控制（即，管理系统）7-12.然而，功能模式 这些神经系统之间的联系增加了暴饮暴食和肥胖的风险尚不清楚。建筑 在我的赞助商的R 01研究中，该研究旨在检查肥胖增加的神经和认知预测因素， 7-8岁的儿童因肥胖的家庭风险而异，这项建议旨在确定功能性肥胖， 连接模式（即，神经网络特性）之间的反应和调节大脑系统， 是EAH和肥胖增加的基础。据推测，反应性和非反应性之间的较弱连接性可能是导致反应性和非反应性之间的较弱连接性的原因。 监管系统，以及反应系统内更强的连通性，将与更大的EAH相关， 儿童肥胖增加。为了验证这些假设，神经成像（fMRI）数据收集期间暴露于 食物线索将与来自EAH实验室评估的食物摄入数据一起使用，在此期间， 在饱餐一顿之后，提供各种可口的零食。拟人化 将在基线和1年随访时使用双能X线吸收测定法收集肥胖评估结果 （DXA）的标准曲线。创新的网络分析和先进的统计方法将用于识别和表征 儿童特定的神经网络从先验的“反应”和“调节”感兴趣的大脑区域。创新 该建议提供了（1）使用复杂的定量技术来检查儿童的神经功能， 网络在暴露于食物线索和（2）网络分析与客观评估的整合 享乐主义饮食和肥胖的纵向措施，这将共同提供新的见解，神经 在易受伤害的青春期前，促进暴饮暴食和体重增加的因素。在 此外，本建议书所载的跨学科导师队伍，将提供以下严格训练： 摄食行为研究、神经网络分析和科学交流的实验设计 这将有助于我作为一名独立研究员的职业生涯。建议的研究将加强我们的 了解支持暴饮暴食和肥胖增加的神经机制，这将为 制定干预措施，以减少过量能量摄入和肥胖症的发展。