Seattle Longitudinal Study: Archiving, Harmonizing and Augmenting Alzheimer's Disease Relevant Data Sets

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The overarching goal of this proposal is to aggregate, harmonize and secure the rich collection of data acquire across all waves of the Seattle Longitudinal Study (SLS) from 1956 to 2012, creating a valuable and accessible resource for epidemiological research on Alzheimer’s Disease (AD), as well as normal aging. Begun in 1956 and now active for 60 years, the SLS is one of the oldest and longest running studies of longitudinal change in cognition and the protective and risk factors associated with normal and pathological aging, involving over 5,000 participants. It represents a population-based, randomized sample recruited from a large health maintenance organization in western Washington. The study is unique in its cohort sequential design that examines cognitive and psychosocial change in birth cohorts from 1889 through 1976, thus providing opportunity to examine cognitive change in multiple birth cohorts over the same chronological age range. The study involves not only extensive cognitive longitudinal data sets but also multiple biomarkers of significance in AD, including blood samples with APOE genotyping, brain tissue at autopsy, and longitudinal multi-occasion neuroimaging data sets. Unlike most prospective AD studies beginning in old age, the SLS (age range: 22-100+ yrs) permits examination of cognitive change from young adulthood to very old age. The Laboratory of Neuro Imaging (LONI) will provide a secure data repository infrastructure for the SLS from which all data and supporting documents will be broadly accessible to the research community worldwide for the first time. Use of innovative approaches will provide an interactive and visual view of the entire SLS data set, harmonizing the multiple waves of SLS data into a uniform data model. A search interface will be provided to permit download of SLS data without extensive preprocessing before incorporating it into subsequent analyses. NCRAD will serve as a repository for blood and brain autopsy biomarkers with linkages to data within the LONI repository. Creation of rich archives can have a positive impact on scientists, research funders and potential for effective reuse of data extending beyond the original intent for which it was collected.