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.
This proposal requests funds to complete genome-wide genotyping on the remaining 6,000 Add Health samples using current Illumina chip technology, prepare genotype and phenotype data and documentation for dissemination, and conduct GWAS. Accomplishing these aims will make available to the global scientific community a unique resource of rich, longitudinal environmental data coupled with comprehensive phenotype and genotype data on more than 12,000 nationally representative and ethnically diverse young adults, permitting unprecedented interdisciplinary research opportunities to employ a dynamic, multilevel integrative approach to health that captures bidirectional biological and contextual contributions and their interactions over time.
| Lawrence, Elizabeth M; Hummer, Robert A; Domingue, Benjamin W et al. (2018) Wide educational disparities in young adult cardiovascular health. SSM Popul Health 5:249-256 |
| Domingue, Benjamin W; Belsky, Daniel W; Fletcher, Jason M et al. (2018) The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health. Proc Natl Acad Sci U S A 115:702-707 |
| Belsky, Daniel W; Domingue, Benjamin W; Wedow, Robbee et al. (2018) Genetic analysis of social-class mobility in five longitudinal studies. Proc Natl Acad Sci U S A 115:E7275-E7284 |
| Turley, Patrick; Walters, Raymond K; Maghzian, Omeed et al. (2018) Multi-trait analysis of genome-wide association summary statistics using MTAG. Nat Genet 50:229-237 |
| Guo, Guang; Fu, Yilan; Lee, Hedwig et al. (2014) Genetic bio-ancestry and social construction of racial classification in social surveys in the contemporary United States. Demography 51:141-72 |
| Boardman, Jason D; Domingue, Benjamin W; Blalock, Casey L et al. (2014) Is the gene-environment interaction paradigm relevant to genome-wide studies? The case of education and body mass index. Demography 51:119-39 |
| Conley, Dalton; Siegal, Mark L; Domingue, Benjamin W et al. (2014) Testing the key assumption of heritability estimates based on genome-wide genetic relatedness. J Hum Genet 59:342-5 |
| Harris, Kathleen Mullan; Halpern, Carolyn Tucker; Hussey, Jon et al. (2013) Social, behavioral, and genetic linkages from adolescence into adulthood. Am J Public Health 103 Suppl 1:S25-32 |
| Harris, Kathleen Mullan; Halpern, Carolyn Tucker; Haberstick, Brett C et al. (2013) The National Longitudinal Study of Adolescent Health (Add Health) sibling pairs data. Twin Res Hum Genet 16:391-8 |
| Daw, Jonathan; Shanahan, Michael; Harris, Kathleen Mullan et al. (2013) Genetic sensitivity to peer behaviors: 5HTTLPR, smoking, and alcohol consumption. J Health Soc Behav 54:92-108 |
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