In the first five years of this project, we initiated work using PiB-PET amyloid imaging along with cognitive evaluations to address the following three fundamental questions: 1) how common is amyloid deposition in clinically unimpaired elderly;2) is the greater variability of cognitive performance in the clinically unimpaired elderly (compared to the young) explained by the presence or absence of amyloid deposition;and 3) will clinically unimpaired elderly who have evidence of amyloid deposition invariably progress to a clinical diagnosis of mild cognitive impairment (MCI) or AD within some reasonable amount of time? As was emphasized in that original application, all of these questions, and most clearly the third, will require more than five years to satisfactorily address. Our goal was to begin this important process and gather a cohort of clinically unimpaired elderly, some of whom we expected to show evidence of amyloid deposition, so we could begin to provide preliminary data on the first two questions and assemble a cohort to follow for a decade or more to address the third question. We now have a cohort of 56 (this number is still growing) clinically unimpaired elderly and ~25% of them show objective evidence of amyloid deposition. For the extension of this MERIT Award, we are proposing to continue the original specific aims, but add enhancements to the project based on new data learned during the first 314 years. They include: a) recruitment ofthe oldest-old (85+) cohort from the existing Cardiovascular Health Study-Cognition Study (CHS-CS);b) addition of a detailed correlational analysis ofthe brain metabolic Imaging data (FDG-PET) with the PiB-PET data based on recent findings that suggest the combination of these measures may provide more precise information regarding impending changes in cognitive status;c) addition of resting- state and activation functional MRI (fMRI) studies to further the amyloid-metabolic correlations and determine the role of the default-mode network and compensatory changes in modulating the effects of brain amyloid deposition;and d) collection of CSF for Ap42 and p-tau181 on a subset of subjects who will volunteer for a lumbar puncture to begin to determine the temporal relationship between PiB-positivity and "abnormal CSF". It should be stressed that there are no major changes to the direction of the research as described in the original proposal. The four additions described above reflect the current state-of-the-art in brain imaging and biomarker studies of normal aging as it blends with the spectrum of cognitive impairment from MCI to AD. This will keep the original project on the cutting edge of imaging research in normal aging and allow it to lead the way for and dovetail with other similar studies being conducted around the world.
; Answers to these questions will help us to understand the significance of amyloid deposition in non- demented individuals. This understanding will become important as anti-amyloid therapies become available. If it becomes clear that pre-clinical amyloid deposition progresses to clinical AD with high frequency, then it will become important to identify and treat non-demented, amyloid-positive individuals. It is at this early stage that anti-amyloid therapies will likely be most effective, or it may even be that they are onlv effective at this stage. It also is at this stage when treatment could actually prevent clinical symptoms before they occur.
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|McDade, Eric; Kim, Albert; James, Jeffrey et al. (2014) Cerebral perfusion alterations and cerebral amyloid in autosomal dominant Alzheimer disease. Neurology 83:710-7|
|Cohen, Ann D; Klunk, William E (2014) Early detection of Alzheimer's disease using PiB and FDG PET. Neurobiol Dis 72 Pt A:117-22|
|Hong, Young T; Veenith, Tonny; Dewar, Deborah et al. (2014) Amyloid imaging with carbon 11-labeled Pittsburgh compound B for traumatic brain injury. JAMA Neurol 71:23-31|
|Lopez, Oscar L; Klunk, William E; Mathis, Chester et al. (2014) Amyloid, neurodegeneration, and small vessel disease as predictors of dementia in the oldest-old. Neurology 83:1804-11|
|Hughes, Timothy M; Kuller, Lewis H; Barinas-Mitchell, Emma J M et al. (2014) Arterial stiffness and ?-amyloid progression in nondemented elderly adults. JAMA Neurol 71:562-8|
|Hughes, Timothy M; Lopez, Oscar L; Evans, Rhobert W et al. (2014) Markers of cholesterol transport are associated with amyloid deposition in the brain. Neurobiol Aging 35:802-7|
|Cohen, Ann D; Mowrey, Wenzhu; Weissfeld, Lisa A et al. (2013) Classification of amyloid-positivity in controls: comparison of visual read and quantitative approaches. Neuroimage 71:207-15|
|Klunk, William E; Perani, Daniela (2013) Amyloid and neurodegeneration: converging and diverging paths. Neurology 81:1728-9|
|D'Angelo, Gina M; Weissfeld, Lisa A (2013) Application of copulas to improve covariance estimation for partial least squares. Stat Med 32:685-96|
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