Format

Send to

Choose Destination
Brain Imaging Behav. 2020 Mar 5. doi: 10.1007/s11682-020-00260-3. [Epub ahead of print]

Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis.

Author information

1
Trinity College Institute of Neuroscience, Trinity College Dublin, Lloyd Building, Dublin 2, Ireland.
2
Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, München, Germany.
3
Physics Department, University of Calabria, Rende, CS, Italy.
4
Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, İzmir, Turkey.
5
Department of Neurology, Dokuz Eylul University Medical School, İzmir, Turkey.
6
Brain Dynamics Multidisciplinary Research Center, Dokuz Eylul University, İzmir, Turkey.
7
Centre for Advanced Medical Imaging, St. James's Hospital, Dublin 8, Ireland.
8
School of Medicine, Trinity College Dublin, Dublin 2, Ireland.
9
The Irish Longitudinal Study on Ageing, Trinity College Dublin, Dublin 2, Ireland.
10
Department of Medical Gerontology, Trinity College Dublin, Dublin 2, Ireland.
11
Global Brain Health Institute, Trinity College Dublin, Lloyd Building, Dublin 2, Ireland.
12
Department of Psychology, Faculty of Letters, Dokuz Eylul University, İzmir, Turkey.
13
Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, USA.
14
Mercer's Institute for Successful Ageing, St. James's Hospital, Dublin 8, Ireland.
15
Trinity College Institute of Neuroscience, Trinity College Dublin, Lloyd Building, Dublin 2, Ireland. robert.whelan@tcd.ie.
16
Global Brain Health Institute, Trinity College Dublin, Lloyd Building, Dublin 2, Ireland. robert.whelan@tcd.ie.

Abstract

Brain-predicted age difference scores are calculated by subtracting chronological age from 'brain' age, which is estimated using neuroimaging data. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brain-predicted age difference scores and specific cognitive functions has not been systematically examined using appropriate statistical methods. First, applying machine learning to 1359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise grey matter data. This model was then applied to MRI data from three independent datasets, significantly predicting chronological age in each dataset: Dokuz Eylül University (n = 175), the Cognitive Reserve/Reference Ability Neural Network study (n = 380), and The Irish Longitudinal Study on Ageing (n = 487). Each independent dataset had rich neuropsychological data. Brain-predicted age difference scores were significantly negatively correlated with performance on measures of general cognitive status (two datasets); processing speed, visual attention, and cognitive flexibility (three datasets); visual attention and cognitive flexibility (two datasets); and semantic verbal fluency (two datasets). As such, there is firm evidence of correlations between increased brain-predicted age differences and reduced cognitive function in some domains that are implicated in cognitive ageing.

KEYWORDS:

Biomarkers; Brain ageing; Cognitive ageing; Cognitive function; MRI; Machine learning

PMID:
32141032
DOI:
10.1007/s11682-020-00260-3

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center