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

描述（由申请人提供）：全基因组关联研究（GWAS）是一种有效且日益负担得起的工具，用于调查遗传对人类健康的贡献。然而，现有的数据受到样本同质性、环境数据有限以及缺乏纵向信息的限制。这些局限性排除了动态的，多层次的综合方法，以健康，捕捉双向生物和上下文的贡献和他们的互动随着时间的推移。为了解决这一差距，本申请提出使用全基因组阵列技术对大约6，000份存档DNA样本进行基因分型，并向全球科学界提供前所未有的丰富的国家资源，纵向环境数据加上全国代表性的种族多样性Add Health样本中12，000多名参与者的综合表型和基因型数据。Add Health已将DNA样本存档以供未来研究，目前正在对GWAS的约6，000个样本进行基因分型。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：目的1）使用Illumina Omni 1-Quad BeadChip（超过100万个遗传标记），对存档的DNA进行基因分型，产生12，000个样本。目标2）通过与dbGaP合作存款添加健康基因型、表型和环境数据，为科学界开发国家和全球资源。目的3）进行初步的GWAS和探索基因x环境（GxE）的相互作用，以确定生物学和上下文的贡献，表型是明确定义的添加健康和与调查小组有实质性的专业知识，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抽样调查，包括家庭、同龄人、学校、邻里、社区和关系二元组，并对这些环境进行了独立和直接的测量。Add Health包含有关健康相关行为的广泛纵向信息，包括身体活动的生活史，参与风险行为，物质使用，性行为，公民行为， 参与、教育和基于自我报告的健康状况的多个指标（例如，一般健康、慢性疾病），直接测量（例如，超重状态和肥胖），和生物标志物（例如，血点）。没有其他的数据资源与这种广泛的基因型和表型数据的一个大的全国代表性的纵向样本与种族，民族，社会经济和地理多样性存在。

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.