Cloud-Based Big Neuroimaging Data Resource for Harmonized Research on Neuropsychiatric Symptoms in Alzheimer's Disease

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PROJECT SUMMARY ABSTRACT More than 6 million Americans suffer from Alzheimer’s disease (AD), the most common age-associated, neurodegenerative dementia. 80% of AD patients also exhibit neuropsychiatric symptoms (NPS), including depression, anxiety, agitation, aggression, and others. NPS in AD respond poorly to conventional treatments and can lead to severe functional impairment, increased caregiver burden, and institutionalization. There is profound disease-related degeneration in neurocircuitry in AD that may be a mechanism for the clinical course and treatment resistance of NPS in AD. The overarching goal of our funded parent grant is to identify relationships between the neurocircuitry underlying NPS and AD neurocircuit degeneration that ultimately may drive worse outcomes in AD with NPS. To probe these relationships, we are conducting secondary analyses of NIMH Research Domain Criteria (RDoC)-related measures from Human Connectome Project (HCP) Young Adult and Aging datasets, and the Connectomes Related to Human Disease (CRHD) on Treatment Resistant Depression, Anxious Misery, Alzheimer’s Disease, and Brain Aging and Dementia. We apply computational methods for big data analysis that inherently embody the principles of RDoC, which treats NPS and AD as extremes from normal values of brain – behavior mappings. We maximize scientific rigor via large sample size of these six combined datasets (N~3,500), and by adopting ReproNim practices designed for reproducible neuroimaging research. In this Administrative Supplement request, we propose to create a cloud-based big neuroimaging data resource for harmonized research on NPS and AD that will allow investigators to leverage cloud-based resources for their research. Our data resource is comprised of: 1) four CRHD datasets used in the parent study, including the fully pre-processed imaging data harmonized with HCP YA and Aging and our novel image- derived phenotypes that will be open access on Amazon Web Service (AWS), and 2) a containerized software tool that leverages AWS cloud computing for complete start-to-finish processing of new datasets so researchers can harmonize their datasets with HCP/CRHD, compute ours or their own novel imaging features, and apply our normative models to their patient data. This Admin Supp will allow us to preserve the overall impact of our study, increase the overall impact of our parent award, exert a sustained high impact influence on AD research, and increase the benefits of our outcomes to the research community and NIH-funded research.