There is a window of time in humans, hypothesized as preclinical Alzheimer's disease (AD) during which amyloid-? (A?) deposition and tauopathy accrues prior to the detection of clinical symptoms and signs of cognitive impairment. By the time of clinical detection of symptomatic AD, there is already significant cell and synaptic loss. An important goal is to determine whether there are changes not only in imaging and fluid biomarkers, but also in brain function, that are associated with preclinical AD that are 1) quantitative;2) predict prognosis;and 3) respond to therapeutic intervention. Sleep in an essential biological function that becomes significantly abnormal during the course of dementia due to AD. We have shown that soluble, monomeric A? in both mice and humans is regulated by the sleep/wake cycle. We have also found that as APP transgenic mice develop A? deposition, sleep, particularly non-REM sleep, is markedly disrupted and that this is secondary to A? accumulation. We have also assessed sleep in a mouse model of tauopathy (P301S Tau transgenic mice) and have noted a marked decline in delta power during non-REM sleep. In recent studies, we have assessed sleep in a cohort of late-middle aged individuals with actigraphy, and found that those with A? deposition have significantly decreased sleep efficiency (% of time sleeping while in bed). Very few of the individuals in our first study had developed neurodegeneration (e.g. increased CSF tau) and we did not assess sleep stages directly by EEG. Herein, we will assess a cohort of individuals who are somewhat older (with mean age ~75);many are cognitively normal with and without different stages of preclinical AD and some have very mild dementia. We hypothesize that decreases in non-REM sleep and delta power will begin during the initial phases of A? deposition and worsen with biomarker evidence of neurodegeneration and tauopathy during preclinical AD and mild cognitive impairment (MCI). In addition, we hypothesize that changes in sleep detected initially and longitudinally will be quantitative diagnostic and prognostic markers of brain injury that have potential to respond to therapeutic intervention (theranostic markers). We predict that progressive changes in sleep will correlate with brain atrophy and dysfunction as assessed by structural MRI, functional connectivity MRI, and certain aspects of longitudinal cognitive performance such as the practice effect.

Public Health Relevance

As instructed by the funding opportunity announcement for this application (PAR-13-329), only the Overall component contains a project narrative. Cores and projects were instructed not to include this section.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
2P01AG003991-31A1
Application #
8739016
Study Section
Special Emphasis Panel (ZAG1-ZIJ-4 (M1))
Project Start
Project End
2019-04-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
31
Fiscal Year
2014
Total Cost
$313,516
Indirect Cost
$107,932
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Lucey, Brendan P; Mawuenyega, Kwasi G; Patterson, Bruce W et al. (2016) Associations Between β-Amyloid Kinetics and the β-Amyloid Diurnal Pattern in the Central Nervous System. JAMA Neurol :
Esparza, Thomas J; Wildburger, Norelle C; Jiang, Hao et al. (2016) Soluble Amyloid-beta Aggregates from Human Alzheimer's Disease Brains. Sci Rep 6:38187
McKee, Ann C; Cairns, Nigel J; Dickson, Dennis W et al. (2016) The first NINDS/NIBIB consensus meeting to define neuropathological criteria for the diagnosis of chronic traumatic encephalopathy. Acta Neuropathol 131:75-86
Reiman, Eric M; Langbaum, Jessica B; Tariot, Pierre N et al. (2016) CAP--advancing the evaluation of preclinical Alzheimer disease treatments. Nat Rev Neurol 12:56-61
Jin, Sheng Chih; Benitez, Bruno A; Deming, Yuetiva et al. (2016) Pooled-DNA Sequencing for Elucidating New Genomic Risk Factors, Rare Variants Underlying Alzheimer's Disease. Methods Mol Biol 1303:299-314
Hohman, Timothy J; Cooke-Bailey, Jessica N; Reitz, Christiane et al. (2016) Global and local ancestry in African-Americans: Implications for Alzheimer's disease risk. Alzheimers Dement 12:233-43
Van Schependom, Jeroen; Jain, Saurabh; Cambron, Melissa et al. (2016) Reliability of measuring regional callosal atrophy in neurodegenerative diseases. Neuroimage Clin 12:825-831
Hohman, Timothy J; Bush, William S; Jiang, Lan et al. (2016) Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium. Neurobiol Aging 38:141-50
Ebbert, Mark T W; Boehme, Kevin L; Wadsworth, Mark E et al. (2016) Interaction between variants in CLU and MS4A4E modulates Alzheimer's disease risk. Alzheimers Dement 12:121-9
Su, Yi; Rubin, Brian B; McConathy, Jonathan et al. (2016) Impact of MR-Based Attenuation Correction on Neurologic PET Studies. J Nucl Med 57:913-7

Showing the most recent 10 out of 756 publications