PROJECT SUMMARY/ABSTRACT Early-onset Alzheimer’s disease (EOAD) is a critically understudied form of AD associated with a more aggressive clinical course, more “atypical” non-amnestic clinical presentations, more severe neuropathology (particularly neurofibrillary tangles), and increased heritability compared with its late-onset counterpart. At present, little is known about the mechanisms underlying the spread of tau pathology and genetic risk factors that predispose it. Candidate Development and Environment: The candidate’s career goal is to become an independent investigator with deep knowledge of multimodal neuroimaging techniques to elucidate the mechanisms underlying cognitive dysfunction in AD and related dementias and to develop tools that help improve individual patients’ well-being. With this K award, the candidate will extend his expertise in multimodal neuroimaging by gaining critical training in longitudinal positron emission tomography (PET) imaging, diffusion tensor imaging (DTI), graph theory, and analysis of gene expression in the brain. This new skill set will allow him to characterize the mechanisms of disease progression in EOAD with unprecedented specificity. The candidate will analyze the rich multimodal neuroimaging dataset collected in the Longitudinal Early-onset Alzheimer’s Disease Study (LEADS), the largest and best characterized cohort of patients with sporadic EOAD to date. His mentor/advisory team consists of world-renowned scientists throughout the United States with broad expertise spanning behavioral neurology, cognitive, systems, and network neurosciences, and imaging genetics. The state-of-the-art resources and facilities at Massachusetts General Hospital and Harvard Medical School will provide an ideal environment for the candidate’s training and will foster his growth toward scientific independence. Research Project: The proposed project aims to investigate the role of large-scale brain network connectivity in the longitudinal spread of tau pathology in EOAD using novel graph theoretical methods, and to identify specific genetic biomarkers that may confer vulnerability to the cortical spread of tau in this population via integrative neuroimaging-transcriptomic analyses. Specific gaps in the literature will be filled by cross-sectionally establishing the relationships between tau accumulation and intrinsic brain functional and structural connectivity (Aim 1), validating the utility of brain connectivity in predicting longitudinal tau spread using directional graph theory regression analysis (Aim 2), and identifying specific genes whose cortical expression is associated with the topography of longitudinal tau spread (Aim 3) in EOAD. Knowledge gained from this project will facilitate the inclusion of patients with EOAD in clinical trials by identifying novel imaging and genetic biomarkers sensitive to clinical progression in this population.