Predicting time to dementia using a quantitative template of disease progression.

ABSTRACT:

Introduction

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 β1-42 , p- tau181p , 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 chan

SUBMITTER: Bilgel M 

PROVIDER: S-EPMC6396328 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature