Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations
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 w...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
eLife Sciences Publications Ltd
2020-03-01
|
Series: | eLife |
Subjects: | |
Online Access: | https://elifesciences.org/articles/52677 |
id |
doaj-aec871cafe71411183c2a93996f14086 |
---|---|
record_format |
Article |
spelling |
doaj-aec871cafe71411183c2a93996f140862021-05-05T20:53:22ZengeLife Sciences Publications LtdeLife2050-084X2020-03-01910.7554/eLife.52677Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associationsStephen M Smith0https://orcid.org/0000-0001-8166-069XLloyd T Elliott1Fidel Alfaro-Almagro2Paul McCarthy3Thomas E Nichols4Gwenaëlle Douaud5https://orcid.org/0000-0003-1981-391XKarla L Miller6https://orcid.org/0000-0002-2511-3189Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United KingdomDepartment of Statistics and Actuarial Science, Simon Fraser University, Vancouver, CanadaWellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United KingdomWellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United KingdomWellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom; Big Data Institute, University of Oxford, Oxford, United KingdomWellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United KingdomWellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United KingdomBrain 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 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.https://elifesciences.org/articles/52677brain agingbrain imagingUK Biobank |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Stephen M Smith Lloyd T Elliott Fidel Alfaro-Almagro Paul McCarthy Thomas E Nichols Gwenaëlle Douaud Karla L Miller |
spellingShingle |
Stephen M Smith Lloyd T Elliott Fidel Alfaro-Almagro Paul McCarthy Thomas E Nichols Gwenaëlle Douaud Karla L Miller Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations eLife brain aging brain imaging UK Biobank |
author_facet |
Stephen M Smith Lloyd T Elliott Fidel Alfaro-Almagro Paul McCarthy Thomas E Nichols Gwenaëlle Douaud Karla L Miller |
author_sort |
Stephen M Smith |
title |
Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations |
title_short |
Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations |
title_full |
Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations |
title_fullStr |
Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations |
title_full_unstemmed |
Brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations |
title_sort |
brain aging comprises many modes of structural and functional change with distinct genetic and biophysical associations |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2020-03-01 |
description |
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 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. |
topic |
brain aging brain imaging UK Biobank |
url |
https://elifesciences.org/articles/52677 |
work_keys_str_mv |
AT stephenmsmith brainagingcomprisesmanymodesofstructuralandfunctionalchangewithdistinctgeneticandbiophysicalassociations AT lloydtelliott brainagingcomprisesmanymodesofstructuralandfunctionalchangewithdistinctgeneticandbiophysicalassociations AT fidelalfaroalmagro brainagingcomprisesmanymodesofstructuralandfunctionalchangewithdistinctgeneticandbiophysicalassociations AT paulmccarthy brainagingcomprisesmanymodesofstructuralandfunctionalchangewithdistinctgeneticandbiophysicalassociations AT thomasenichols brainagingcomprisesmanymodesofstructuralandfunctionalchangewithdistinctgeneticandbiophysicalassociations AT gwenaelledouaud brainagingcomprisesmanymodesofstructuralandfunctionalchangewithdistinctgeneticandbiophysicalassociations AT karlalmiller brainagingcomprisesmanymodesofstructuralandfunctionalchangewithdistinctgeneticandbiophysicalassociations |
_version_ |
1721458528309215232 |