Mobile Application to Deliver Personalized Nutrition for the Prevention of Alzheimer's Disease

移动应用程序提供个性化营养以预防阿尔茨海默病

• 批准号: 9254310
• 负责人: Li Shen
• 金额: $ 20.55万
• 依托单位: GENBEN LIFESCIENCES CORPORATION
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9254310
• 关键词: Age; Algorithms; Alleles; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease risk; Americas; Android; Chronic Disease; Clinical; Data; Databases; Dementia; Development; Diet; Dietary Intervention; Dietary intake; Disease; Equilibrium; Family Caregiver; Family history of; Food Preferences; Frequencies; Genetic; Genetic Predisposition to Disease; Genetic Risk; Genome; Genotype; Goals; Guidelines; Health; Life; Life Style; Machine Learning; Mission; Neurodegenerative Disorders; Nutrient; Nutritional; Outcome; Pathology; Pattern; Phase; Phenotype; Physical activity; Population; Prevention Guidelines; Preventive healthcare; Process; Recommendation; Risk; Statistical Models; Symptoms; Translating; base; cost; cost effective; design; digital; evidence base; fighting; fitness; genetic variant; lifestyle intervention; mobile application; mobile computing; mortality; nutrition; nutritional genomics; physical conditioning; prevent; risk variant; tool

Genben Lifesciences (dba GB HealthWatch) is a digital health and nutritional genomics company. Our mission is to help fight common, diet- and lifestyle-related chronic diseases with precision nutrition and advanced mobile technologies. Our company developed the HealthWatch 360 mobile app for tracking dietary intake, physical activity and health-related symptoms. This mobile app has received excellent reviews for both the iOS and Android platforms and has over 70,000 registered users. Health condition- specific goals featured in the app provide refined nutritional recommendations based on clinical guidelines for the prevention of diet-induced, chronic diseases. Alzheimer’s disease (AD) is the leading cause of dementia in the U.S., the 6th leading cause of mortality and a major cost to the nation, families and caregivers. This phase I proposal is for the development of a mobile tool that will deliver personalized nutrition and meal plans based on genetic risk in order to mitigate AD risk. Aim 1: Develop a systematic process to identify specific dietary and nutritional components associated with AD. Using the 1000 Genomes Phase 3 database and nutritional analyses of the traditional diets that correspond with the 26 populations, we will analyze whether specific nutrients correlate with the frequency of genetic variants that predispose risk of AD. We hypothesize that a population’s fitness would be enhanced and AD risk would be lower when the genetic variants that are selected for in a given population are in equilibrium with a diet that is enriched or depleted with the correlated nutrient(s). We will develop statistical models that will quantify these relationships. Aim 2: Translate nutritional patterns to a set of quantitative recommendations for AD prevention. With the nutrient data we obtain from Aim 1, combined with other evidence-based nutrition guidelines for AD, we will synthesize a set of qualitative and quantitative nutritional “rules” based on the app user’s genotypes, family history of AD and other health conditions. These genotype- and/or phenotype - specific rules will estimate ideal ranges for a given nutrient and amend the conventional “rules” (i.e. nutritional recommendations) by the 2015-2020 Dietary Guidelines for America. Aim 3: Mobile app for delivery of personalized meal plan for the prevention of AD. This mobile application is designed for guided, proactive and self-executed prevention of AD, and targeted at those who are at elevated risk. We propose developing machine-learning algorithms to create meal plans that employ the modified nutrient ranges (from Aims 1 and 2) for a given AD risk genotype. Users will be able to modify food preference parameters (for example, “vegetarian”) while maintaining the appropriate nutrient ranges. A key outcome of this project will be a platform that supports population-wide dietary intervention by seamlessly connecting preventive healthcare with daily life in the digital age.

Genben Lifesciences (dba GB HealthWatch) 是一家数字健康和营养基因组学公司。我们的 使命是通过精准营养和帮助对抗常见的、与饮食和生活方式相关的慢性疾病 先进的移动技术。我公司开发了HealthWatch 360移动应用程序用于跟踪 饮食摄入量、体力活动和健康相关症状。这个移动应用程序获得了优秀的 iOS 和 Android 平台都有评论，拥有超过 70,000 名注册用户。健康状况- 该应用程序中的具体目标提供基于临床的精致营养建议 预防饮食引起的慢性疾病的指南。阿尔茨海默病 (AD) 是主要疾病 在美国，痴呆症是导致死亡的第六大原因，也是国家和家庭的主要损失 和护理人员。这一阶段的提案是为了开发一个移动工具，该工具将提供 基于遗传风险的个性化营养和膳食计划，以降低 AD 风险。 目标 1：开发一个系统流程来识别特定的膳食和营养成分 与AD有关。使用 1000 个基因组第 3 阶段数据库和营养分析 与26个人群相对应的传统饮食，我们将分析特定营养素是否 与易患 AD 风险的基因变异频率相关。我们假设一个 当基因变异被 在给定人群中选择的食物与富含或缺乏以下物质的饮食保持平衡 相关营养素。我们将开发统计模型来量化这些关系。 目标 2：将营养模式转化为一套预防 AD 的定量建议。 根据我们从目标 1 获得的营养数据，结合其他循证营养指南 对于AD，我们将根据应用程序用户的情况综合一套定性和定量的营养“规则” 基因型、AD 家族史和其他健康状况。这些基因型和/或表型 具体规则将估计给定营养素的理想范围并修改传统的“规则”（即 营养建议）根据 2015-2020 年美国膳食指南。 目标 3：用于提供预防 AD 的个性化膳食计划的移动应用程序。这款手机 应用程序旨在引导、主动和自我执行 AD 预防，并针对那些 风险较高的人。我们建议开发机器学习算法来创建膳食计划 针对给定的 AD 风险基因型采用修改后的营养范围（来自目标 1 和 2）。用户将能够 修改食物偏好参数（例如“素食”），同时保持适当的饮食偏好 营养范围。 该项目的一个关键成果将是建立一个平台，通过以下方式支持全民饮食干预： 将预防性医疗保健与数字时代的日常生活无缝连接。