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: 10663196
• 负责人: Bari Allison Fuchs
• 金额: $ 2.69万
• 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 2024-02-25
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10663196
• 关键词: 8 year old; Algorithms; Behavior Therapy; Body mass index; Brain; Brain region; COVID-19 pandemic; 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; Outcome; 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; neural network; neurobiological mechanism; neuroimaging; neuromechanism; neuroregulation; novel; obesity development; obesity in children; obesity prevention; obesity risk; obesogenic; pandemic disease; physical conditioning; preadolescence; prevent; psychosocial; public health intervention; 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 儿童肥胖是与负面的身体和社会心理健康结果相关的全球大流行。4， 以及预防儿童肥胖症的行为干预措施会产生较小和可变的影响5。饮食增加 在没有饥饿的情况下（EAH）已被确定为儿童的肥胖饮食表型6，但是 在肥胖发展之前导致EAH增加的机制尚不清楚。更好 了解儿童增加EAH和体重增加的机制对 制定更有效的预防肥胖计划。暴饮暴食是由于失衡而导致的 在参与食物提示反应性和奖励处理（即反应性系统）的大脑区域中 参与抑制和认知对照（即监管系统）7-12。但是，功能的模式 这些神经系统之间增加了暴饮暴食和物体风险之间的连通性尚不清楚。建筑 在我的赞助商的R01研究中，该研究旨在检查肥胖增长的神经和认知预测指标 该提议旨在确定功能性 反应性和调节性脑系统之间的连通性模式（即神经网络属性） EAH的基础和肥胖增长。假设反应性和 监管系统以及反应性系统内的更强连通性将与更大的EAH和 儿童的肥胖增长。为了检验这些假设，在暴露期间收集的神经影像学（fMRI）数据 食品提示将与EAH实验室评估的食物摄入数据一起使用，在此期间 吃一顿标准的饭菜后，可以提供各种可口的零食食品。拟人化 使用双X射线绝对持久性图将在基线和1年随访时收集肥胖的评估 （DXA）。创新的网络分析和高级统计方法将用于识别和表征 来自先验的“反应性”和“调节性”脑部区域的儿童特异性神经网络。创新 该建议提供的是（1）使用复杂的定量技术检查儿童神经 接触食物提示期间的网络，（2）网络分析与客观评估的集成 享乐饮食和肥胖纵向测量，这将共同提供对神经的新见解 在脆弱的青春期前时期，促进暴饮暴食和体重增加风险的因素。在 此外，本提案中组装的跨学科心态团队将提供严格的培训 摄入行为研究，神经网络分析和科学沟通的实验设计 这将有助于发展我作为独立研究人员的职业。拟议的研究将增强我们的 了解支持暴饮暴食和肥胖增长的神经机制，这将为 开发减轻能量摄入的干预措施和肥胖的发展。