We hypothesize that Alzheimer's disease (AD) has a preclinical stage in which elevated levels of brain amyloid protein and accumulation of beta-amyloid deposits foreshadow the gradual onset of neuronal dysfunction, cell loss and dementia. While the exact role of amyloid in the initiation of brain damage is still unclear, it is clear that clarifying the exact timing of amyloid plaque deposition that precede AD would be extremely helpful in fully understanding the biological origins of AD and to assist in the design of appropriate interventions. This project will use a new method for the in vivo imaging of amyloid plaques in the human brain. Developed at the University of Pittsburgh, [11C]PIB has very high affinity for amyloid plaques with in vitro preparations and binds rapidly to amyloid plaques in a transgenic mouse model of amyloid deposits. We have implemented this method and demonstrated much greater cortical uptake in older participants diagnosed with DAT compared with nondemented control participants. In this project, 240 participants between the ages of 45 and 74 y will be recruited and undergo baseline imaging with PET and [11C]PIB for calculation of amyloid plaque binding. In each decade (45 - 54 y, 55 - 64 y, and 65 - 74 y) 40 participants with at least one biologic parent with DAT (age at onset, or AAO, <80y) and 40 participants whom neither parent has/had DAT (parents must be >70y) will be studied. In addition, we will re-image subjects with [11C]PIB after a three year interval to determine the longitudinal course of amyloid binding in these two cohorts. With this data we will achieve four specific aims: 1) In Years 01 - 03, we will measure and compare cortical [11C]PIB uptake in 120 ACS participants with a parent with DAT and in 120 participants without a parent with DAT. 2) We will correlate cortical [11C]PIB uptake with specific measures of cognitive performance, including presence and magnitude of learning effects, and with personality measures. 3) We will test for correlations between cortical [11C]PIB uptake and CSF biomarkers (Project 2), and between cortical [11C]PIB uptake and neuroanatomic biomarkers (Project 4). 4) In Years 04 and 05, we will repeat PET [11C]PIB imaging on participants enrolled in Years 01 and 02, respectively. By comparing the cortical [11C]PIB uptake at these two different time-points three years apart, we will be able to assess the ACS cohorts longitudinally to determine the natural history of [11C]PIB binding and its potential for preclinical detection of AD.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
5P01AG026276-02
Application #
7309950
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
2006-07-01
Budget End
2007-06-30
Support Year
2
Fiscal Year
2006
Total Cost
$232,451
Indirect Cost
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Liao, Fan; Li, Aimin; Xiong, Monica et al. (2018) Targeting of nonlipidated, aggregated apoE with antibodies inhibits amyloid accumulation. J Clin Invest 128:2144-2155
Yan, Qi; Nho, Kwangsik; Del-Aguila, Jorge L et al. (2018) Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging. Mol Psychiatry :
Strain, Jeremy F; Smith, Robert X; Beaumont, Helen et al. (2018) Loss of white matter integrity reflects tau accumulation in Alzheimer disease defined regions. Neurology 91:e313-e318
Li, Zeran; Del-Aguila, Jorge L; Dube, Umber et al. (2018) Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structure. Genome Med 10:43
Schindler, Suzanne E; Sutphen, Courtney L; Teunissen, Charlotte et al. (2018) Upward drift in cerebrospinal fluid amyloid ? 42 assay values for more than 10 years. Alzheimers Dement 14:62-70
Sato, Chihiro; Barthélemy, Nicolas R; Mawuenyega, Kwasi G et al. (2018) Tau Kinetics in Neurons and the Human Central Nervous System. Neuron 98:861-864
Babulal, Ganesh M; Chen, Suzie; Williams, Monique M et al. (2018) Depression and Alzheimer's Disease Biomarkers Predict Driving Decline. J Alzheimers Dis 66:1213-1221
Millar, Peter R; Balota, David A; Bishara, Anthony J et al. (2018) Multinomial models reveal deficits of two distinct controlled retrieval processes in aging and very mild Alzheimer disease. Mem Cognit 46:1058-1075
Gangishetti, Umesh; Christina Howell, J; Perrin, Richard J et al. (2018) Non-beta-amyloid/tau cerebrospinal fluid markers inform staging and progression in Alzheimer's disease. Alzheimers Res Ther 10:98
Vlassenko, Andrei G; Gordon, Brian A; Goyal, Manu S et al. (2018) Aerobic glycolysis and tau deposition in preclinical Alzheimer's disease. Neurobiol Aging 67:95-98

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