This is a resubmitted application for a K23 Mentored Patient-Oriented Research Career Development Award. In terms of training, the applicant's goal is to utilize the K23 funding period to complete focused training in functional and image analysis, neuropathology, geriatrics, neuropsychology, and biostatistics. This training will take place through mentorship, a limited number of formal didactics, and through the completion of an ambitious project that will hopefully set the stage for future studies as an independent investigator. Functional connectivity MRI (fcMRI) is a non-invasive method to assess the integrity of anatomically distributed neural networks underlying complex behaviors. In Alzheimer's disease (AD), fcMRI of the default mode network (DMN) has shown great promise as a biomarker in clinical and basic research studies, as (1) profound decreases in DMN fcMRI are seen in prodromal and clinically evident AD and (2) the DMN is among the sites of early amyloid deposition in AD. However, using fcMRI as an early AD biomarker is limited by the overlapping changes in connectivity seen in normal aging, which, in turn, limits the identification of early AD subjects to enroll in clinical trials. To address this limitation, we propose a series f studies that use fcMRI to disambiguate normal aging from early AD by focusing on the pattern of degeneration across six well-described cortical networks in two unique subject populations. The central hypothesis of these studies is that early AD and aging will show distinct patterns of network degradation, with preferential degradation of cognitive networks (especially the Default Mode and Attention Networks) in early AD as compared to aging. We test this hypothesis by comparing young and old subjects with and without evidence of AD pathology, leveraging newly available data from young subjects with dominantly inherited AD (DIAD) drawn from the Dominantly-Inherited Alzheimer's Network (DIAN). Notably, the comparison of the DIAD population and older at-risk and symptomatic patients followed in the Harvard Aging Brain Study represents a unique opportunity to disentangle age and AD pathology, as DIAD carriers have disease onset at a young age (often in the late 30s and early 40s). In addition, using PET data on tau burden in our older subjects (from F18-T807 PET, a newly-developed tau radioligand), we will explore the relative contributions of amyloid and tau pathologies to altered fcMRI. These studies will serve the dual purpose of (1) optimizing the use of fcMRI as an AD biomarker by identifying patterns of fcMRI change that distinguish aging and AD, and (2) provide novel insight into the systems-level pathophysiology that distinguishes aging and AD. Further, these studies will compare the timing and pattern of network degradation in dominantly-inherited vs. sporadic AD and provide critical context for the interpretation of fcMRI data currently being gathered in (a least) three major AD prevention trials in older individuals at-risk for sporadic AD and dominantly-inherited AD.
Alzheimer's disease (AD) is a devastating neurologic disease in which the degradation of brain networks leads to the profound loss of memory. In this project, we use a novel analytic technique and very unique data (comprised of young subjects with dementia due to rare genetic causes and older individuals with signs of preclinical AD) to determine the pattern of network degeneration seen in early AD and contrast this to what is seen with normal aging. In this way, we will investigate how aging and AD differentially weaken the neural networks needed for memory function, and explore how to use this information to identify people in the earliest stages of AD so that we can enroll them in clinical trials prior tothe onset of irreversible loss of neurons and synapses.
|Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A et al. (2018) Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing. Brain 141:1486-1500|
|Buckley, Rachel F; Mormino, Elizabeth C; Amariglio, Rebecca E et al. (2018) Sex, amyloid, and APOE ?4 and risk of cognitive decline in preclinical Alzheimer's disease: Findings from three well-characterized cohorts. Alzheimers Dement 14:1193-1203|
|Gordon, Brian A; Blazey, Tyler M; Su, Yi et al. (2018) Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study. Lancet Neurol 17:241-250|
|Mormino, Elizabeth C; Papp, Kathryn V; Rentz, Dorene M et al. (2017) Early and late change on the preclinical Alzheimer's cognitive composite in clinically normal older individuals with elevated amyloid ?. Alzheimers Dement 13:1004-1012|
|Dumurgier, Julien; Hanseeuw, Bernard J; Hatling, Frances B et al. (2017) Alzheimer's Disease Biomarkers and Future Decline in Cognitive Normal Older Adults. J Alzheimers Dis 60:1451-1459|
|Schultz, Aaron P; Chhatwal, Jasmeer P; Hedden, Trey et al. (2017) Phases of Hyperconnectivity and Hypoconnectivity in the Default Mode and Salience Networks Track with Amyloid and Tau in Clinically Normal Individuals. J Neurosci 37:4323-4331|
|LaPoint, Molly R; Chhatwal, Jasmeer P; Sepulcre, Jorge et al. (2017) The association between tau PET and retrospective cortical thinning in clinically normal elderly. Neuroimage 157:612-622|
|Buckley, Rachel F; Schultz, Aaron P; Hedden, Trey et al. (2017) Functional network integrity presages cognitive decline in preclinical Alzheimer disease. Neurology 89:29-37|
|Dagley, Alexander; LaPoint, Molly; Huijbers, Willem et al. (2017) Harvard Aging Brain Study: Dataset and accessibility. Neuroimage 144:255-258|
|Chhatwal, Jasmeer P; Schultz, Aaron P; Marshall, Gad A et al. (2016) Temporal T807 binding correlates with CSF tau and phospho-tau in normal elderly. Neurology 87:920-6|
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