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

项目摘要/摘要-北卡罗来纳大学教堂山临床中心 人们普遍认识到，需要更精确的营养建议，但在遗传、表观遗传、 微生物组和个体对饮食变异的表型驱动因素还不是很清楚。美国国立卫生研究院 由我们所有人研究计划支持的为精确健康营养(NPH)提供资金的健康倡议将 使精准营养领域取得重大进展。在这里，我们建议精准健康的营养： 北卡罗来纳大学教堂山临床中心(UNC-CC)。因为慢性炎症 促进一系列疾病的发病，包括肥胖、2型糖尿病和心血管疾病， 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病及其并发症风险的战略。一个 已经出现了大量文献，证明了基因和表型驱动的差异 对地中海饮食的反应与一系列结果相关。我们的建议将解决关键的 需要了解饮食生理反应的变异性，以以下主题为基础 发炎。我们强调纳入高度多样化的样本，由两个临床地点提供便利， 新陈代谢厨房：北卡罗来纳州坎纳波利斯的北卡罗来纳大学营养研究所(UNC-NRI)和教堂山 北卡罗来纳大学校园(UNC-CH)。UNC-NRI来自相对较农村的社区，而UNC-CH来自 相对城市社区，两者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 合作开发和执行最终研究方案的联合体。 目标2.执行NPH模块1。参与者注册到我们所有人后，我们将注册并完成 模块1协议，共有2 000名NPH参与者(UNC-NRI为25%；UNC-CH为75%)，包括两名 为期两周的远程数据采集期和混合膳食挑战测试的研究访问。 目标3.执行NPH模块2。500个模块1参与者的子集将完成自由生活、受控 三个为期两周的饮食干预期的喂养研究，以三周的冲洗期为间隔。饮食包括： 地中海饮食适应美国(地中海-美国；40%脂肪卡路里，40%碳水化合物)，地中海-美国修改 用于高健康脂肪含量(60%脂肪卡路里，20%碳水化合物)，Med-USA修改为高健康 碳水化合物含量(20%脂肪卡路里，60%碳水化合物)。饮食对结局的不同影响 由炎症标志物和混合膳食挑战中的代谢参数组成的测试将在 遗传型和表型亚组，重点关注体重状况、年龄和糖尿病状况。 北卡罗来纳大学-CC团队在营养学(公共卫生的基础科学)方面带来了令人印象深刻的跨学科实力 并有能力和经验在复杂的多地点试验中确保执行所需的科学严谨性 这项研究。结果将生成预测性算法，为个性化饮食指导提供信息，以改善健康。

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.