?PROJECT 4: COGNITION. Given the series of disappointing clinical trial results at symptomatic stages of Alzheimer?s disease (AD), it has become even more urgent to elucidate the temporal relationships between accumulation of the molecular pathology of AD and the emergence of the earliest clinical manifestations. Over the second cycle of Project 4, we found consistent evidence that elevated amyloid-beta (a?) is associated with future cognitive decline; however, there is considerable heterogeneity in rates of decline. It is increasingly clear that a? in isolation is not sufficient for imminent decline, and it is possible that a? becomes much less relevant once tau pathology and neurodegeneration are widespread. Thus, we now seek to better understand the patterns of cognitive change associated with the earliest phases of accumulation of both a? and tau, even below current thresholds for abnormality, and to characterize the ?pre-preclinical? phase of AD, as well as the factors that promote successful aging and resilience to cognitive decline. At the other end of the preclinical AD spectrum, we will investigate whether early cognitive change is predictive of progression to clinical impairment, as we will have up to 15 years of follow-up.
In Aim 1, we strive to further elucidate the temporal association between longitudinal a? and tau accumulation and cognitive trajectories. In addition to our work with the Preclinical Alzheimer Cognitive Composite (PACC), we will go deeper and focus on the specific cognitive processes associated with the earliest accumulation of a? and tau, in the context of the multiple factors that may interact with these pathologies.
In Aim 2, we will utilize digital technology to advance our work to go faster by detecting cognitive change more rapidly and with greater specificity and accuracy. Our initial work using home iPAD testing revealed a marked lack of ?practice effect? despite repeated exposure to face-name pair stimuli every month on the iPad, associated with elevated a?. We now propose to test whether we can detect a similar pattern of diminished practice effect over a period of days. We have also begun working with an Artificial Intelligence (AI) software platform using a digital pen to capture subtle cognitive inefficiencies in non-memory processes.
In Aim 3, we will go broader, beyond cognitive testing, to examine clinically relevant measures that include self- and study-partner report of cognitive function, every day activities, and neurobehavioral alterations to elucidate potential bi-directional relationships and temporal sequence of these changes along the trajectory of preclinical AD. We will use these measures to assess the ?clinical meaningfulness? of early cognitive change, and to improve our predictions of progression to clinical impairment, in combination with imaging AD markers. Project 4 will leverage the rich longitudinal neuropsychological, behavioral, and multi-modality imaging data available on the HABS cohort to improve our understanding of relationships between the accumulation of a? and tau in the aging brain and cognitive trajectories, and ultimately to inform ongoing and future trials aiming to prevent cognitive decline.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
2P01AG036694-11
Application #
9934667
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
2020-04-01
Budget End
2021-03-31
Support Year
11
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114
Properzi, Michael J; Buckley, Rachel F; Chhatwal, Jasmeer P et al. (2018) Nonlinear Distributional Mapping (NoDiM) for harmonization across amyloid-PET radiotracers. Neuroimage 186:446-454
Hanseeuw, Bernard J; Jonas, Victoria; Jackson, Jonathan et al. (2018) Association of anxiety with subcortical amyloidosis in cognitively normal older adults. Mol Psychiatry :
Lee, Catherine; Betensky, Rebecca A; Alzheimer's Disease Neuroimaging Initiative (2018) Time-to-event data with time-varying biomarkers measured only at study entry, with applications to Alzheimer's disease. Stat Med 37:914-932
Jacobs, Heidi I L; Hedden, Trey; Schultz, Aaron P et al. (2018) Structural tract alterations predict downstream tau accumulation in amyloid-positive older individuals. Nat Neurosci 21:424-431
Chiou, Sy Han; Austin, Matthew D; Qian, Jing et al. (2018) Transformation model estimation of survival under dependent truncation and independent censoring. Stat Methods Med Res :962280218817573
Qian, Jing; Chiou, Sy Han; Maye, Jacqueline E et al. (2018) Threshold regression to accommodate a censored covariate. Biometrics :
Orlovsky, Irina; Huijbers, Willem; Hanseeuw, Bernard J et al. (2018) The relationship between recall of recently versus remotely encoded famous faces and amyloidosis in clinically normal older adults. Alzheimers Dement (Amst) 10:121-129
Quiroz, Yakeel T; Sperling, Reisa A; Norton, Daniel J et al. (2018) Association Between Amyloid and Tau Accumulation in Young Adults With Autosomal Dominant Alzheimer Disease. JAMA Neurol 75:548-556
Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A et al. (2018) Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing. Brain 141:1486-1500
Hanseeuw, Bernard J; Betensky, Rebecca A; Mormino, Elizabeth C et al. (2018) PET staging of amyloidosis using striatum. Alzheimers Dement 14:1281-1292

Showing the most recent 10 out of 170 publications