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Elife. 2020 Mar 5;9. pii: e52677. doi: 10.7554/eLife.52677. [Epub ahead of print]

Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations.

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Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, Canada.
Wellcome Centre For Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom.


Brain imaging can be used to study how individuals' brains are aging, compared against population norms. This can inform on aspects of brain health; for example, smoking and blood pressure can be seen to accelerate brain aging. Typically, a single 'brain age' is estimated per subject, whereas here we we identified 62 modes of subject variability, from 21,407 subjects' multimodal brain imaging data in UK Biobank. The modes represent different aspects of brain aging, showing distinct patterns of functional and structural brain change, and distinct patterns of association with genetics, lifestyle, cognition, physical measures and disease. While conventional brain-age modelling found no genetic associations, 34 modes had genetic associations. We suggest that it is important not to treat brain aging as a single homogeneous process, and that modelling of distinct patterns of structural and functional change will reveal more biologically meaningful markers of brain aging in health and disease.


human; neuroscience

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