The Framingham Heart Study (FHS), initiated by the National Heart, Lung, Blood Institute (NHLBI) to identify determinants of cardiovascular disease (CVD) and stroke in 1948, has created a rich source of comprehensive data, including demographic, health, lifestyle, social networks, genetic, serum, plasma biomarkers, cognitive and neuroimaging data that together can be evaluated to deeply and longitudinally characterize CVD, stroke and Alzheimer's disease (AD) risk. While these data present an unprecedented opportunity to address scientific questions of AD risk across the entire disease spectrum (e.g., asymptomatic, preclinical, clinical) as well as factors associated with cognitive resilience, management and sharing of all these data have relied on ad-hoc operations funded through multiple National Institute on Aging (NIA) R01 grants that have become more difficult to administrate as clinical data collection and data sharing efforts expanded. Further, due to the extremely complex structure of FHS data, it has been difficult for external (and internal) investigators to understand the characteristics of the data and the most appropriate use of the data even after they receive them. The proposed Data Core will (1) establish a comprehensive and secure database of FHS AD-related phenotypic data that will integrate all existing AD data available to date as well as new data collected from the Clinical and Neuropathology Cores and Projects 1-3 (Aim 1); (2) review, modify and direct quality control pipelines for all data assembled in Aim 1 and harmonize and curate all data to produce a centralized set of data that is ready for analysis and sharing (Aim 2); (3) accelerate data sharing by transferring data from Clinical and Neuropathology cores and Projects 1-3 to the FHS National Heart Lung Blood Institute (NHLBI) funded data repository on a quarterly basis; prepare data to deposit in the publicly available National Center for Biotechnology Information (NCBI) Database of Genotypes and Phenotypes (dbGaP) and NHLBI's Data Repository Information Coordinating Center (BioLINCC); and facilitate data sharing with collaborators by pre-prepping all phenotypic data for FHS NHLBI funded contract staff to disseminate (Aim 3); and (4) support the proposed Projects 1-3 by updating datasets with newly acquired data from Clinical and Neuropathology Cores and providing statistical design and analytical support, including explaining data, structures, recommending methods for combining different data formats for analyses, and assisting with the development of computer scripts that are needed to perform the proposed statistical analyses, particularly longitudinal and trajectory analyses (Aim 4).
