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

  1. Stephen M Smith  Is a corresponding author
  2. Lloyd T Elliott
  3. Fidel Alfaro-Almagro
  4. Paul McCarthy
  5. Thomas E Nichols
  6. Gwenaëlle Douaud
  7. Karla L Miller
  1. University of Oxford, United Kingdom
  2. Simon Fraser University, Canada

Abstract

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.

Data availability

All source data is available from UK Biobank, as described in Section 5. That section also describes the full availability of all of our code used for this work, and additional supplementary materials. https://www.fmrib.ox.ac.uk/ukbiobank/BrainAgingModes/

The following previously published data sets were used

Article and author information

Author details

  1. Stephen M Smith

    Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    For correspondence
    steve@fmrib.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8166-069X
  2. Lloyd T Elliott

    Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Fidel Alfaro-Almagro

    Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Paul McCarthy

    Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Thomas E Nichols

    Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Gwenaëlle Douaud

    Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1981-391X
  7. Karla L Miller

    Wellcome Centre For Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2511-3189

Funding

Wellcome (203139/Z/16/Z)

  • Stephen M Smith
  • Karla L Miller

Wellcome (098369/Z/12/Z)

  • Stephen M Smith

Wellcome (215573/Z/19/Z)

  • Stephen M Smith

Wellcome (202788/Z/16/Z)

  • Karla L Miller

Medical Research Council (MR/K006673/1)

  • Gwenaëlle Douaud

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Jonathan Erik Peelle, Washington University in St. Louis, United States

Ethics

Human subjects: The UK Biobank has approval from the North West Multi-centre Research Ethics Committee (MREC) to obtain and disseminate data and samples from the participants (http://www.ukbiobank.ac.uk/ethics/), and these ethical regulations cover the work in this study. Written informed consent was obtained from all participants.

Version history

  1. Received: October 11, 2019
  2. Accepted: March 2, 2020
  3. Accepted Manuscript published: March 5, 2020 (version 1)
  4. Version of Record published: April 16, 2020 (version 2)

Copyright

© 2020, Smith et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Stephen M Smith
  2. Lloyd T Elliott
  3. Fidel Alfaro-Almagro
  4. Paul McCarthy
  5. Thomas E Nichols
  6. Gwenaëlle Douaud
  7. Karla L Miller
(2020)
Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations
eLife 9:e52677.
https://doi.org/10.7554/eLife.52677

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https://doi.org/10.7554/eLife.52677

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