Add Health: A Genotype and Phenotype Resource for the Global Scientific Community

添加健康：全球科学界的基因型和表型资源

• 批准号: 8514413
• 负责人: Kathleen Mullan Harris
• 金额: $ 70.59万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-24 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8514413
• 关键词: Address; Adolescence; Adolescent; Adult; Age; Alcohol or Other Drugs use; Archives; Behavior; Behavioral; Biological; Biological Markers; Blood; Candidate Disease Gene; Cardiovascular Diseases; Chronic Disease; Collection; Communities; Consent; Cost Savings; Coupled; DNA; Data; Data Collection; Deposition; Development; Documentation; Education; Environment; Family; Funding; Future; Genes; Genetic; Genetic Markers; Genome; Genotype; Health; Health Status Indicators; Home environment; Human; Institute of Medicine (U.S.); Interdisciplinary Study; Interview; Journals; Knowledge; Life; Life Cycle Stages; Longitudinal Studies; Measurement; Medical; Neighborhoods; Obesity; Overweight; Participant; Patient Self-Report; Peer Review; Phenotype; Physical activity; Program Research Project Grants; Public Health; Publishing; Race; Request for Proposals; Research; Research Personnel; Resources; Respondent; Risk Behaviors; Sampling; Schools; Science; Sex Behavior; Specimen; Spottings; Technology; Time; United States; Work; aged; base; cost; database of Genotypes and Phenotypes; design; genetic linkage; genome wide association study; genome-wide; life history; multidisciplinary; peer; prevent; programs; social; socioeconomics; tool; young adult

DESCRIPTION (provided by applicant): Genome-wide association studies (GWAS) are an effective and increasingly affordable tool to investigate genetic contributions to human health. However, existing data are limited by homogeneity of samples, modest environmental data, and absence of longitudinal information. These limitations preclude a dynamic, multilevel integrative approach to health that captures bidirectional biological and contextual contributions and their interactions over time. To address this gap, this application proposes to complete genotyping on approximately 6,000 archived DNA samples using whole genome array technology, and make available to the global scientific community an unprecedented national resource of rich, longitudinal environmental data coupled with comprehensive phenotype and genotype data on more than 12,000 participants in the nationally representative, ethnically diverse Add Health sample. Add Health has archived DNA specimens for future research and is currently genotyping approximately 6,000 samples for GWAS. This project will complete genotyping on the entire sample, disseminate these data and conduct preliminary GWAS. We have three specific aims: Aim 1) Using the Illumina Omni1-Quad BeadChip (more than 1 million genetic markers), complete genotyping on the archived DNA, yielding a sample of 12,000. Aim 2) Develop a national and global resource for the scientific community by collaborating with dbGaP to deposit Add Health genotype, phenotype, and environmental data. Aim 3) Conduct preliminary GWAS and explore gene x environment (GxE) interactions to identify biological and contextual contributions to phenotypes that are well-defined in Add Health and with which the investigative team has substantive expertise, including obesity, substance use, and cardiovascular disease. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers (e.g., blood spots). No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists.

描述（由申请人提供）：全基因组关联研究（GWAS）是一种有效且日益实惠的工具，用于研究遗传对人类健康的贡献。然而，现有数据受到样本同质性、环境数据有限和缺乏纵向信息的限制。这些限制阻碍了动态、多层次的综合健康方法，无法捕获双向生物和背景贡献及其随时间的相互作用。为了弥补这一差距，本申请建议使用全基因组阵列技术对大约 6,000 个存档的 DNA 样本完成基因分型，并向全球科学界提供前所未有的国家资源，其中包含丰富的纵向环境数据以及更多的综合表型和基因型数据。 Add Health 样本中有超过 12,000 名具有全国代表性、种族多样化的参与者。 Add Health 已将 DNA 样本存档以供未来研究使用，目前正在对大约 6,000 个样本进行 GWAS 基因分型。该项目将完成整个样本的基因分型，传播这些数据并进行初步的GWAS。我们有三个具体目标： 目标 1) 使用 Illumina Omni1-Quad BeadChip（超过 100 万个遗传标记），对存档的 DNA 完成基因分型，产生 12,000 个样本。目标 2) 与 dbGaP 合作，存储 Add Health 基因型、表型和环境数据，为科学界开发国家和全球资源。目标 3) 进行初步 GWAS 并探索基因 x 环境 (GxE) 相互作用，以确定对表型的生物学和背景贡献，这些表型在 Add Health 中明确定义，并且调查团队拥有实质性专业知识，包括肥胖、物质使用和心血管疾病。 Add Health 对年轻人生活的多种环境进行了采样，包括家庭、同龄人、学校、邻里、社区和关系二元体，并随着时间的推移提供对这些环境的独立和直接测量。 Add Health 包含有关健康相关行为的广泛纵向信息，包括体力活动的生活史、参与危险行为、物质使用、性行为、公民行为 参与度、教育以及基于自我报告（例如一般健康状况、慢性疾病）、直接测量（例如超重状况和肥胖）和生物标志物（例如血斑）的多种健康状况指标。没有其他数据资源能够在具有种族、民族、社会经济和地理多样性的全国代表性大型纵向样本中提供如此广泛的基因型和表型数据。