CORE C – PROJECT SUMMARY/ ABSTRACT Sophisticated informatics is critical to the success of any multisite or coordinated scientific effort and enables subsequent re-use of data and findings in unanticipated ways greatly enhancing the overall value of the project. Core C of the proposed P01 “Vascular Contributions To Dementia And Genetic Risk Factors For Alzheimer’s Disease” will continue providing high quality computational, harmonization, and imaging resources for Projects 1, 2, and 3, Core B, and all P01 investigators, staff, and authorized scientists. The activities of Core C will support the scientific goals of the P01 as well as the broader national Alzheimer’s disease (AD) and dementia research community. Given the multimodality nature of data collected as a part of the P01, robust informatics, data management, and harmonization are critical. Core C will 1) provide an informatics data management framework for Projects 1 and 2 including diagnostic criteria for subtle cognitive decline during preclinical and mild cognitive impairment stages of AD, and harmonized imaging data for all P01 Projects. This centralized web-based data system will be used for registration and documentation of participants, including enrollment at baseline and follow-up, archival and tracking of raw and pre-processed imaging data and open data dissemination; 2) ensure high quality control of all neuroimaging data across P01 Projects using a state-of-the-art workflow for the review and assessment of diffusion tensor imaging (DTI), functional MRI (fMRI), structural magnetic resonance imaging (MRI), dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL) MRI, and dynamic susceptibility contrast (DSC) MRI data; 3) deliver a harmonized analysis workflow for each imaging modality for each Project that can accommodate any computational environment via a user-friendly, uniform data analysis pipeline that is accessible to all investigators; and 4) provide biostatistical support (by working with Core A MPIs, all P01 project and core leaders and co-investigators, and biostatisticians) for our analytic approaches, data harmonization, and modeling of longitudinal data.