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Publications

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural Epublish 2 citations

PubMed: 39690174 DOI: 10.1038/s41467-024-53548-z

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

Nat Commun 15(1):10651

Authors: James M Roe, Didac Vidal-Piñeiro, Øystein Sørensen, Håkon Grydeland, Esten H Leonardsen, Olena Iakunchykova, Mengyu Pan, Athanasia Mowinckel, Marie Strømstad, Laura Nawijn, Yuri Milaneschi, Micael Andersson, Sara Pudas, Anne Cecilie Sjøli Bråthen, Jonas Kransberg, Emilie Sogn Falch, Knut Øverbye, Rogier A Kievit, Klaus P Ebmeier, Ulman Lindenberger, Paolo Ghisletta, Naiara Demnitz, Carl-Johan Boraxbekk, Christian A Drevon, Brenda Penninx, Lars Bertram, Lars Nyberg, Kristine B Walhovd, Anders M Fjell, Yunpeng Wang

Affiliations

  • Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway.
  • Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway.
  • Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
  • Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.
  • Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry and Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Department of Medical and Translational Biology, Umeå University, Umeå, Sweden.
  • Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden.
  • Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Department of Psychiatry and Wellcome Centre for Integrative Neuroimaging, University of Oxford, Warneford Hospital, Oxford, United Kingdom.
  • Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
  • Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
  • Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland.
  • Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
  • Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Department of Radiation Sciences, Diagnostic Radiology, and Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden.
  • Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark.
  • Department of Nutrition, Institute of Basic Medical Science, Faculty of Medicine, University of Oslo, Oslo, Norway.
  • Vitas Ltd, Oslo Science Park, Oslo, Norway.
  • Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.
  • Department of Diagnostics and Intervention, Umeå University, Umeå, Sweden.
  • Department of Health, Education and Technology, Luleå University of Technology, Luleå, Sweden.
  • Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.

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. 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.

MeSH

Genetic Variation, Brain, Memory

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