Introduction: Down syndrome (DS) is associated with elevated risk for Alzheimer's disease (AD) due to amyloid beta (Aβ) lifelong accumulation. We hypothesized that the spatial distribution of brain Aβ predicts future dementia conversion in individuals with DS.
Methods: We acquired 18F-florbetapir positron emission tomography scans from 19 nondemented individuals with DS at baseline and monitored them for 4 years, with five individuals transitioning to dementia. Machine learning classification using an independent test set determined features on 18F-florbetapir standardized uptake value ratio maps that predicted transition.
Results: In addition to "AD signature" regions including the inferior parietal cortex, temporal lobes, and the cingulum, we found that Aβ cortical binding in the prefrontal and superior frontal cortices distinguished subjects who transitioned to dementia. Classification did well in predicting transitioners.
Discussion: Our study suggests that specific regional profiles of brain amyloid in older adults with DS may predict cognitive decline and are informative in evaluating the risk for dementia.
Keywords: Alzheimer's; Down syndrome; amyloid; classification; dementia; positron emission tomography; predict; standardized uptake value ratio; transition.
© 2020 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.