4.5 Article

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

Journal

BRAIN IMAGING AND BEHAVIOR
Volume 15, Issue 1, Pages 327-345

Publisher

SPRINGER
DOI: 10.1007/s11682-020-00260-3

Keywords

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

Categories

Funding

  1. Irish Research Council [EPSPG/2017/277]
  2. Science Foundation Ireland [16/ERCD/3797]
  3. Region Calabria
  4. Turkish National Science and Research Council (TUBITAK) [112S459]
  5. Dokuz Eylul University Scientific Research Projects [2018.KB.SAG.084]
  6. Health Research Board, Atlantic Philanthropies
  7. Irish Life
  8. Centre for Advanced Medical Imaging (CAMI) at St. James' Hospital, Dublin
  9. Atlantic Philanthropies
  10. NIA [RF1 AG038465, R01 AG026158]
  11. Irish Research Council (IRC) [EPSPG/2017/277] Funding Source: Irish Research Council (IRC)

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By applying machine learning to predict the relationship between chronological age and grey matter data based on MRI scans, and then applying this model to independent datasets, it was found that increased brain-predicted age differences were significantly negatively correlated with reduced cognitive function in certain domains. This suggests a strong connection between accelerated ageing as predicted by brain age and cognitive decline in specific areas.
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 Eylul 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.

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