Our team at the University of Pittsburgh has recently developed a promising, non-invasive, in vivo PET tracer for use in imaging amyloid deposition in living humans. The tracer has become commonly known as Pittsburgh Compound-B (PIB). This Project will exploit this new technology by conducting an exploratory analysis with the overall goals of documenting pre-symptomatic amyloid deposition in living subjects destined to develop Alzheimer's disease (AD) and then determining the natural history of amyloid deposition in these subjects. In order to accomplish these goals within the constraints of an ADRC project, we will focus on early-onset, autosomal dominant, familial AD (eFAD) kindreds. In particular, we will focus on known mutation carriers who have not yet developed symptoms (as determined by the ADRC Clinical Core). We also will study four symptomatic eFAD subjects and four age-matched members of the kindreds who do not carry the mutation (as controls). The PEB retention in these latter groups will be compared to typical sporadic AD cases and typical controls to exclude the possibility of unusual findings in these eFAD families. We plan to identify and follow at least four mutation carriers with no symptoms of dementia who show evidence of amyloid deposition on the initial scan (i.e., increased PIB retention) at yearly intervals to document the natural history of amyloid deposition in these subjects who are on a relatively predictable trajectory toward clinical AD. We also plan to follow at least four other asymptomatic mutation carriers, who show no evidence of amyloid deposition at baseline, at two-year intervals, allowing the possibility of detecting the very onset of amyloid deposition. Although the number of subjects is necessarily small (due to the scarcity of the mutation carriers and budget constraints), the predictable nature of the future clinical course (determined by genotype) will likely allow us to document, for the first time, pre-symptomatic amyloid deposition in a subject known to be on a path toward clinical AD. The follow-up studies proposed will likely provide important information regarding the natural history of amyloid deposition in eFAD subjects. This data is necessary to deepen our understanding of the pathophysiology of AD and to form a foundation for the design and interpretation of anti-amyloid drug trials.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Specialized Center (P50)
Project #
5P50AG005133-24
Application #
7406701
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
2007-04-01
Budget End
2008-03-31
Support Year
24
Fiscal Year
2007
Total Cost
$214,077
Indirect Cost
Name
University of Pittsburgh
Department
Type
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Laymon, Charles M; Minhas, Davneet S; Becker, Carl R et al. (2018) Image-Based 2D Re-Projection for Attenuation Substitution in PET Neuroimaging. Mol Imaging Biol 20:826-834
Jiang, Yun; Sereika, Susan M; Lingler, Jennifer H et al. (2018) Health literacy and its correlates in informal caregivers of adults with memory loss. Geriatr Nurs 39:285-291
Wang, Qi; Guo, Lei; Thompson, Paul M et al. (2018) The Added Value of Diffusion-Weighted MRI-Derived Structural Connectome in Evaluating Mild Cognitive Impairment: A Multi-Cohort Validation1. J Alzheimers Dis 64:149-169
Wilmoth, Kristin; LoBue, Christian; Clem, Matthew A et al. (2018) Consistency of traumatic brain injury reporting in older adults with and without cognitive impairment. Clin Neuropsychol 32:524-529
Minhas, Davneet S; Price, Julie C; Laymon, Charles M et al. (2018) Impact of partial volume correction on the regional correspondence between in vivo [C-11]PiB PET and postmortem measures of A? load. Neuroimage Clin 19:182-189
Ting, Simon Kang Seng; Foo, Heidi; Chia, Pei Shi et al. (2018) Dyslexic Characteristics of Chinese-Speaking Semantic Variant of Primary Progressive Aphasia. J Neuropsychiatry Clin Neurosci 30:31-37
Wang, Tingyan; Qiu, Robin G; Yu, Ming (2018) Predictive Modeling of the Progression of Alzheimer's Disease with Recurrent Neural Networks. Sci Rep 8:9161
Mukherjee, Shubhabrata; Mez, Jesse; Trittschuh, Emily H et al. (2018) Genetic data and cognitively defined late-onset Alzheimer's disease subgroups. Mol Psychiatry :
Brainstorm Consortium (see original citation for additional authors) (2018) Analysis of shared heritability in common disorders of the brain. Science 360:
Hu, Ziheng; Wang, Lirong; Ma, Shifan et al. (2018) Synergism of antihypertensives and cholinesterase inhibitors in Alzheimer's disease. Alzheimers Dement (N Y) 4:542-555

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