Research Tools to Enable Widespread Access and Use of Add Health GWAS Data

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ABSTRACT Genetic studies leveraging large-scale genotyping (i.e., “GWAS data”) are increasingly ubiquitous, as demonstrated by the >56,000 unique single nucleotide polymorphism (SNP)-trait associations identified to-date by genome-wide association studies (GWAS). GWAS data also are being used to understand social-genetic effects, control for genetic predispositions in population health and social science studies, and examine genetic correlation between traits. Despite growing adoption, studies leveraging GWAS data remain largely limited to adult populations of European ancestry and tend to ignore the physical and social environment. Studies with GWAS data combined with rich, longitudinal environmental and phenotype data are therefore needed to permit dynamic, multilevel, integrative research approaches to health that capture bidirectional biological and contextual contributions and their interactions over time. The National Longitudinal Study of Adolescent to Adult Health (Add Health) is an ongoing, nationally representative, multiethnic longitudinal study of the social, behavioral, and biological linkages in health and developmental trajectories from early adolescence into adulthood. As the only nationally representative longitudinal study of young adults that contains multilevel social, behavioral, environmental, and biological data (including recently available GWAS data through dbGaP, a NIH-sanctioned repository), Add Health is well positioned to address these research gaps. However, numerous and persistent challenges prevent broad usage of GWAS data by the research community. Specifically, Add Health users may be ill-prepared for conceptualizing, accessing, storing, understanding, analyzing, and interpreting high dimensional (i.e. >30 million SNPs) GWAS data, an impression supported by our recent survey of users. To enable widespread use of this valuable resource, this application aims to: (1) develop resources to aid users in accessing, understanding, analyzing, and interpreting Add Health GWAS data; and (2) initiate and support a scientific community of Add Health GWAS data users. The proposed application builds upon a 25-year commitment of Add Health investigators to user support and data dissemination, which has resulted in prolific research production with unparalleled disciplinary breadth. We are confident that the proposed resources, which will not be developed without dedicated funding, will expedite access to and facilitate high-quality studies of the Add Health GWAS data by a new group of investigators who may have little-to-no experience with GWAS data. Ultimately, we anticipate that this application will multiply the impact of Add Health sociogenomics research throughout the scientific community and provide a stimulus for new scientific discovery.