Nutrition for Precision Health: The University of North Carolina at Chapel Hill Clinical Center

精准健康营养：北卡罗来纳大学教堂山分校临床中心

• 批准号: 10539342
• 负责人: Elizabeth J Mayer-Davis
• 金额: $ 274.79万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-10 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10539342
• 关键词: Adult; Advisory Committees; Age; All of Us Research Program; American diet; Anti-Inflammatory Agents; Basic Science; Biological; Calories; Carbohydrates; Cardiovascular Diseases; Cardiovascular system; Chronic; Chronic Disease; Clinical; Complex; Creativeness; Crossover Design; Data; Diabetes Mellitus; Diet; Dietary Intervention; Dietary Practices; Disease; Enrollment; Ensure; Epigenetic Process; Fatty acid glycerol esters; Foundations; Funding; Genetic; Genotype; Goals; Health; Heterogeneity; Individual; Inflammation; Inflammatory; Knowledge; Leadership; Literature; Location; Longevity; Malignant Neoplasms; Mediterranean Diet; Metabolic; Molecular; Morbidity - disease rate; Neurodegenerative Disorders; Non-Insulin-Dependent Diabetes Mellitus; North Carolina; Nutritional Science; Nutritional Study; Obesity; Outcome; Participant; Pathogenesis; Phenotype; Physiological; Population; Precision Health; Process; Protocols documentation; Public Health; Recommendation; Research Design; Research Infrastructure; Research Institute; Risk; Risk Reduction; Rural Community; Sampling; Sampling Studies; Site; Subgroup; Testing; United States National Institutes of Health; Universities; Urban Community; Variant; Visit; Weight; clinical center; cohort; dietary; dietary guidelines; experience; feeding; health goals; human old age (65+); improved; individual variation; inflammatory marker; microbiome; mortality; multi-site trial; neoplastic; nutrition; participant enrollment; people of color; precision nutrition; prediction algorithm; public health research; recruit; response; systemic inflammatory response

Project Summary/Abstract – The University of North Carolina at Chapel Hill Clinical Center The need for more precise nutrition advice is widely recognized, yet specific differences in genetic, epigenetic, microbiome and phenotypic drivers of individual variability to diet are not well known. The National Institutes of Health initiative to fund Nutrition for Precision Health (NPH), powered by the All of Us Research Program, will enable major progress in the field of precision nutrition. Here we propose Nutrition for Precision Health: The University of North Carolina at Chapel Hill Clinical Center (UNC-CC). Because chronic inflammation promotes the pathogenesis of a wide range of diseases, including obesity, type 2 diabetes, and cardiovascular, neoplastic, and neurodegenerative disorders, we draw upon the anti-inflammatory Mediterranean diet as a viable strategy to improve systemic inflammation and reduce risk for many chronic diseases and their complications. A body of literature has emerged that demonstrates both genotypically- and phenotypically-driven differential responses to the Mediterranean diet relative to a range of outcomes. Our proposal will address the critical need to understand variability in physiologic responses to diet, anchored by the theme of inflammation. We emphasize inclusion of a highly diverse sample facilitated by two clinical locations with metabolic kitchens: the UNC Nutrition Research Institute (UNC-NRI) in Kannapolis, NC, and the Chapel Hill campus of UNC (UNC-CH). The UNC-NRI draws from relatively rural communities, and UNC-CH draws from relatively urban communities, both with a substantial proportion of people of color. Specific Aims are: Aim 1. To participate actively in the Year 1 planning process and beyond, engaging across the NPH consortium to collaboratively develop and execute the final study protocol. Aim 2. To execute NPH Module 1. Following participant enrollment into All of Us, we will enroll and complete the Module 1 protocol for a total of 2,000 NPH participants (25% at UNC-NRI; 75% at UNC-CH), including two study visits with a 2-week remote data capture period and a mixed meal challenge test. Aim 3. To execute NPH Module 2. A subset of 500 Module 1 participants will complete a free-living, controlled feeding study of three 2-week diet intervention periods, separated by 3-week washout periods. Diets include: the Mediterranean diet adapted for the US (Med-USA; 40% fat calories, 40% carbohydrate), the Med-USA modified for high healthy fat content (60% fat calories, 20% carbohydrate), and Med-USA modified for high healthy carbohydrate content (20% fat calories, 60% carbohydrate). Differential effects of the diets on outcomes comprising inflammatory markers and metabolic parameters from the mixed meal challenge will be tested across genotypic and phenotypic subgroups, focusing on weight status, age, and diabetes status. The UNC-CC team brings impressive interdisciplinary strength in nutrition (basic science to public health) and has the capacity and experience in complex, multi-site trials to ensure the scientific rigor needed to execute this study. Results will generate predictive algorithms to inform individualized dietary guidance to improve health.

项目总结/摘要-北卡罗来纳州大学查佩尔山临床中心 人们广泛认识到需要更精确的营养建议，但遗传、表观遗传、 个体对饮食的变异性的微生物组和表型驱动因素并不为人所知。国家机构 健康倡议，以资助营养的精确健康（NPH），由我们所有的研究计划，将 在精准营养领域取得重大进展。在这里，我们建议营养精准健康： 北卡罗来纳州大学查佩尔山临床中心（UNC-CC）。因为慢性炎症 促进多种疾病的发病机制，包括肥胖、2型糖尿病和心血管， 肿瘤和神经退行性疾病，我们利用抗炎地中海饮食作为一种可行的 改善全身炎症和降低许多慢性疾病及其并发症风险的战略。一 已经出现了大量的文献，证明了基因型和表型驱动的差异 对地中海饮食的反应与一系列结果有关。我们的建议将解决关键的 需要了解对饮食的生理反应的变化，以 炎症我们强调纳入由两个临床地点促进的高度多样化的样本， 代谢厨房：北卡罗来纳州坎纳波利斯的营养研究所（UNC-NRI）和查佩尔山 大学校园（UNC-CH）UNC-NRI从相对农村的社区汲取，UNC-CH从 相对城市化的社区，都有相当大比例的有色人种。具体目标是： 目标1。积极参与第一年及以后的规划过程，参与整个NPH 联合体合作开发和执行最终研究方案。 目标2.执行NPH模块1。在参与者注册到我们所有人之后，我们将注册并完成 共有2,000名NPH参与者（UNC-NRI为25%; UNC-CH为75%）的模块1方案，包括两名 研究访视，包括2周远程数据采集期和混合餐激发试验。 目标3.执行NPH模块2。500名模块1参与者的子集将完成一个自由生活，控制 三个为期2周的饮食干预期的喂养研究，间隔3周的洗脱期。饮食包括： 适合美国的地中海饮食（Med-USA; 40%脂肪热量，40%碳水化合物），Med-USA改良 用于高健康脂肪含量（60%脂肪热量，20%碳水化合物），Med-USA改良用于高健康 碳水化合物含量（20%脂肪热量，60%碳水化合物）。饮食对结果的不同影响 包括来自混合餐挑战的炎性标志物和代谢参数， 基因型和表型亚组，侧重于体重状况、年龄和糖尿病状况。 UNC-CC团队带来了令人印象深刻的跨学科力量营养（基础科学公共卫生） 并具有复杂的多地点试验的能力和经验，以确保执行所需的科学严谨性 本研究结果将生成预测算法，为个性化饮食指导提供信息，以改善健康状况。