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Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life

Roe, James M. ; Vidal-Piñeiro, Didac ; Sørensen, Øystein ; Grydeland, Håkon ; Leonardsen, Esten H. ; Iakunchykova, Olena ; Pan, Mengyu LU orcid ; Mowinckel, Athanasia ; Strømstad, Marie and Nawijn, Laura , et al. (2024) In Nature Communications 15(1).
Abstract

Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults.... (More)

Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

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type
Contribution to journal
publication status
published
subject
in
Nature Communications
volume
15
issue
1
article number
10651
publisher
Nature Publishing Group
external identifiers
  • pmid:39690174
  • scopus:85212711594
ISSN
2041-1723
DOI
10.1038/s41467-024-53548-z
language
English
LU publication?
yes
id
271da735-9026-4213-ba43-4210daa7ae41
date added to LUP
2025-01-17 11:20:10
date last changed
2025-07-19 02:30:36
@article{271da735-9026-4213-ba43-4210daa7ae41,
  abstract     = {{<p>Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.</p>}},
  author       = {{Roe, James M. and Vidal-Piñeiro, Didac and Sørensen, Øystein and Grydeland, Håkon and Leonardsen, Esten H. and Iakunchykova, Olena and Pan, Mengyu and Mowinckel, Athanasia and Strømstad, Marie and Nawijn, Laura and Milaneschi, Yuri and Andersson, Micael and Pudas, Sara and Bråthen, Anne Cecilie Sjøli and Kransberg, Jonas and Falch, Emilie Sogn and Øverbye, Knut and Kievit, Rogier A. and Ebmeier, Klaus P. and Lindenberger, Ulman and Ghisletta, Paolo and Demnitz, Naiara and Boraxbekk, Carl Johan and Drevon, Christian A. and Petersen, Ronald and Aisen, Paul and Weiner, Michael and Rowe, Christopher C. and Masters, Colin L. and Penninx, Brenda and Bertram, Lars and Nyberg, Lars and Walhovd, Kristine B. and Fjell, Anders M. and Wang, Yunpeng}},
  issn         = {{2041-1723}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Communications}},
  title        = {{Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life}},
  url          = {{http://dx.doi.org/10.1038/s41467-024-53548-z}},
  doi          = {{10.1038/s41467-024-53548-z}},
  volume       = {{15}},
  year         = {{2024}},
}