UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

Brain-predicted age in Down syndrome is associated with beta amyloid deposition and cognitive decline

Cole, JH; Annus, T; Wilson, LR; Remtulla, R; Hong, YT; Fryer, TD; Acosta-Cabronero, J; ... Holland, AJ; + view all (2017) Brain-predicted age in Down syndrome is associated with beta amyloid deposition and cognitive decline. Neurobiology of Aging , 56 pp. 41-49. 10.1016/j.neurobiolaging.2017.04.006. Green open access

[img]
Preview
Text
Acosta-Cabronero_brain predicted age in Down Syndrome.pdf - ["content_typename_Published version" not defined]

Download (1MB) | Preview

Abstract

Individuals with Down syndrome (DS) are more likely to experience earlier onset of multiple facets of physiological aging. This includes brain atrophy, beta amyloid deposition, cognitive decline, and Alzheimer's disease-factors indicative of brain aging. Here, we employed a machine learning approach, using structural neuroimaging data to predict age (i.e., brain-predicted age) in people with DS (N = 46) and typically developing controls (N = 30). Chronological age was then subtracted from brain-predicted age to generate a brain-predicted age difference (brain-PAD) score. DS participants also underwent [(11)C]-PiB positron emission tomography (PET) scans to index the levels of cerebral beta amyloid deposition, and cognitive assessment. Mean brain-PAD in DS participants' was +2.49 years, significantly greater than controls (p < 0.001). The variability in brain-PAD was associated with the presence and the magnitude of PiB-binding and levels of cognitive performance. Our study indicates that DS is associated with premature structural brain aging, and that age-related alterations in brain structure are associated with individual differences in the rate of beta amyloid deposition and cognitive impairment.

Type: Article
Title: Brain-predicted age in Down syndrome is associated with beta amyloid deposition and cognitive decline
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neurobiolaging.2017.04.006
Publisher version: http://doi.org/10.1016/j.neurobiolaging.2017.04.00...
Language: English
Additional information: © 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Keywords: Amyloid PET, Brain aging, Cognitive decline, Down syndrome, MRI, Machine learning
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: http://discovery.ucl.ac.uk/id/eprint/1556000
Downloads since deposit
59Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item