Open AccessPredicting time to dementia using a quantitative template of disease progression
Author(s) -
Bilgel Murat,
Jedynak Bruno M.
Publication year - 2019
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 - 10.1016/j.dadm.2019.01.005
Subject(s) - dementia , alzheimer's disease neuroimaging initiative , biomarker , neuroimaging , alzheimer's disease , disease , oncology , psychology , neuroscience , medicine , biology , biochemistry
Characterization of longitudinal trajectories of biomarkers implicated in sporadic Alzheimer's disease (AD) in decades before clinical diagnosis is important for disease prevention and monitoring. Methods We used a multivariate Bayesian model to temporally align 1369 Alzheimer's disease Neuroimaging Initiative participants based on the similarity of their longitudinal biomarker measures and estimated a quantitative template of the temporal evolution of cerebrospinal fluid A β 1 − 42, p‐ ta u 181 p, and t‐tau and hippocampal volume, brain glucose metabolism, and cognitive measurements. We computed biomarker trajectories as a function of time to AD dementia and predicted AD dementia onset age in a disjoint sample. Results Quantitative template showed early changes in verbal memory, cerebrospinal fluid Aβ 1–42 and p‐tau 181p , and hippocampal volume. Mean error in predicted AD dementia onset age was < 1.5 years. Discussion Our method provides a quantitative approach for characterizing the natural history of AD starting at preclinical stages despite the lack of individual‐level longitudinal data spanning the entire disease timeline.