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Dataset Information

Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration.


ABSTRACT:

Background

Leveraging Alzheimer's disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomarkers of amyloid, tau and neurodegeneration, to a sample of cognitively unimpaired older adults to identify longitudinal trajectories of CR.

Methods

We identified 200 Harvard Aging Brain Study (HABS) participants (mean age = 71.89 years, SD = 9.41 years, 59% women) who were cognitively unimpaired at baseline with 2 or more timepoints of cognitive assessment following a single amyloid-PET, tau-PET and structural MRI. We examined latent class mixture models with longitudinal cognition as the

SUBMITTER: Boyle R 

PROVIDER: S-EPMC11220971 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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