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Prediction of rapid amyloid and phosphorylated‐Tau accumulation in cognitively healthy individuals
Author(s) -
Koychev Ivan,
Vaci Nemanja,
Bilgel Murat,
An Yang,
Muniz Graciela Terrera,
Wong Dean F.,
Gallacher John,
Mogekhar Abhay,
Albert Marilyn,
Resnick Susan M.
Publication year - 2020
Publication title -
alzheimer's and dementia: diagnosis, assessment and disease monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.497
H-Index - 37
ISSN - 2352-8729
DOI - 10.1002/dad2.12019
Subject(s) - amyloid (mycology) , phosphorylation , neuroscience , psychology , medicine , biology , microbiology and biotechnology , pathology
Objective To test the hypothesis that among cognitively healthy individuals, distinct groups exist in terms of amyloid and phosphorylated‐tau accumulation rates; that if rapid accumulator groups exist, their membership can be predicted by Alzheimer's disease (AD) risk factors, and that time points of significant increase in AD protein accumulation will be evident. Methods The analysis reports data from 263 individuals from the BIOCARD and 184 individuals from the Baltimore Longitudinal Study of Aging with repeated cerebrospinal fluid (CSF) and positron emission tomography (PET) sampling, respectively. We used latent class mixed‐effect models to identify distinct classes of amyloid (CSF and PET) and p‐Tau (CSF) accumulation rates and generalized additive modeling to investigate non‐linear changes to AD biomarkers. Results For both amyloid and p‐Tau latent class models we confirmed the existence of two separate classes: accumulators and non‐accumulators. The accumulator and non‐accumulator groups differed significantly in terms of baseline AD protein levels and slope of change. APOE ε4 carrier status and episodic memory predicted amyloid class membership. Non‐linear models revealed time points of significant increase in the rate of amyloid and p‐Tau accumulation whereby APOE ε4 carrier status associated with earlier age at onset of rapid accumulation. Conclusions The current analysis demonstrates the existence of distinct classes of amyloid and p‐Tau accumulators. Predictors of class membership were identified but the overall accuracy of the models was modest, highlighting the need for additional biomarkers that are sensitive to early disease phenotypes.

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