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.