The theme of this ongoing R01 project is that risk factors for Alzheimer's disease (AD) are associated with presymptomatic changes in brain function that can be detected well in advance of symptom onset. Previously we studied an AD risk cohort known as the Wisconsin Registry for Alzheimer's Prevention (WRAP) and have shown functional MRI (fMRI) associated changes due to family history of AD and apolipoprotein E genotype. In this project we will investigate associations that may shed light on explanatory mechanisms of our previously observed findings by measuring amyloid burden using [C11]PiB, regional cerebral metabolic rate of glucose (rCMRglu) using [F18]fluoro-deoxyglucose (FDG) positron emission tomography (PET), neural function, rate of atrophy and ischemic lesion burden using MRI. Our prior study had a cross-sectional design;thus, a second major goal is to investigate the longitudinal course of brain change in a group of at risk subjects who were cognitively normal at baseline;some are now declining toward MCI. This proposed ongoing project represents a unique opportunity to comprehensively follow high-risk patients from cognitively normal to pre-MCI, and eventually to MCI and AD. Our studies are centered around three Specific Aims: A) to examine potential mechanisms (by way of association) of the BOLD risk effect we have observed in the prior funding period;B) To investigate longitudinal presymptomatic evolution of AD related brain changes and cognitive decline in people who are at high risk for AD, and determine whether PiB predicts decline in people at risk;C) Examine the direct relationship between brain changes and the best available known biomarkers consisting of CSF A242, t-tau and p-tau181. We will study 250 subjects longitudinally and use integrated path and regression analyses to accomplish these cross-sectional and longitudinal aims.
By the time a patient exhibits symptomatic dementia, devastating neural loss has already occurred, and the time window for most effective intervention already past. If a preclinical signal can be reliably observed and is predictive of cognitive decline, this will greatly strengthen the rationale for earlier intervention rather than waiting for symptomatic AD to present itself.
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|Kim, Hyunwoo J; Adluru, Nagesh; Bendlin, Barbara B et al. (2014) Canonical Correlation Analysis on Riemannian Manifolds and Its Applications. Comput Vis ECCV 8690:251-267|
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