Biological brain age prediction using machine learning on structural neuroimaging data: multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex

  1. Irene Cumplido-Mayoral
  2. Marina García-Prat
  3. Grégory Operto
  4. Carles Falcon
  5. Mahnaz Shekari
  6. Raffaele Cacciaglia
  7. Marta Milà-Alomà
  8. Luigi Lorenzini
  9. Silvia Ingala
  10. Alle Meije Wink
  11. Henk JMM Mutsaerts
  12. Carolina Minguillón
  13. Karine Fauria
  14. José Luis Molinuevo
  15. Sven Haller
  16. Gael Chetelat
  17. Adam Waldman
  18. Adam J Schwarz
  19. Frederik Barkhof
  20. Ivonne Suridjan
  21. Gwendlyn Kollmorgen
  22. Anna Bayfield
  23. Henrik Zetterberg
  24. Kaj Blennow
  25. Marc Suárez-Calvet
  26. Verónica Vilaplana
  27. Juan Domingo Gispert López  Is a corresponding author
  1. Pasqual Maragall Foundation, Spain
  2. Amsterdam University Medical Centers, Netherlands
  3. CIRD Centre d'Imagerie Rive Droite, Switzerland
  4. Normandie Univ, UNICAEN, INSERM, U1237, France
  5. University of Edinburgh, United Kingdom
  6. Takeda Pharmaceutical Company Ltd, United States
  7. Roche Diagnostics International Ltd, Switzerland
  8. Roche Diagnostics GmbH, Germany
  9. University of Gothenburg, Sweden
  10. Universitat Politècnica de Catalunya, Spain

Abstract

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-b, more advanced stages (AT) of AD pathology and APOE-e4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.

Data availability

UKBiobank data availability at www.ukbiobank.ac.ukADNI data availability at https://adni.loni.usc.edu/EPAD data availability at www.ep-ad.org/ALFA: data availability through GAAIN at https://www.gaaindata.org/partners/online.htmlFully steps and instructions on data access can be found in the following links:UKBiobank: https://www.ukbiobank.ac.uk/enable-your-research/apply-for-accessADNI: https://adni.loni.usc.edu/data-samples/access-data/EPAD: https://ep-ad.org/open-access-data/access/ALFA: https://www.gaaindata.org/partner/ALFA

Article and author information

Author details

  1. Irene Cumplido-Mayoral

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  2. Marina García-Prat

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  3. Grégory Operto

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  4. Carles Falcon

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  5. Mahnaz Shekari

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  6. Raffaele Cacciaglia

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  7. Marta Milà-Alomà

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  8. Luigi Lorenzini

    Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
    Competing interests
    No competing interests declared.
  9. Silvia Ingala

    Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
    Competing interests
    No competing interests declared.
  10. Alle Meije Wink

    Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
    Competing interests
    No competing interests declared.
  11. Henk JMM Mutsaerts

    Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0894-0307
  12. Carolina Minguillón

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  13. Karine Fauria

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    No competing interests declared.
  14. José Luis Molinuevo

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    José Luis Molinuevo, JL.M is currently a full-time employee of H. Lundbeck A/S and previously has served as a consultant or on advisory boards for the following for-profit companies or has given lectures in symposia sponsored by the following for-profit companies: Roche Diagnostics, Genentech, Novartis, Lundbeck, Oryzon, Biogen, Lilly, Janssen, Green Valley, MSD, Eisai, Alector, BioCross, GE Healthcare, and ProMIS Neurosciences..
  15. Sven Haller

    CIRD Centre d'Imagerie Rive Droite, Geneva, Switzerland
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7433-0203
  16. Gael Chetelat

    Normandie Univ, UNICAEN, INSERM, U1237, Caen, France
    Competing interests
    No competing interests declared.
  17. Adam Waldman

    Centre for Dementia Prevention, University of Edinburgh, Edinburgh, United Kingdom
    Competing interests
    No competing interests declared.
  18. Adam J Schwarz

    Takeda Pharmaceutical Company Ltd, Cambridge, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9743-6171
  19. Frederik Barkhof

    Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
    Competing interests
    No competing interests declared.
  20. Ivonne Suridjan

    Roche Diagnostics International Ltd, Rotkreuz, Switzerland
    Competing interests
    Ivonne Suridjan, is a full-time employee and shareholder of Roche Diagnostics International Ltd.
  21. Gwendlyn Kollmorgen

    Roche Diagnostics GmbH, Penzberg, Germany
    Competing interests
    Gwendlyn Kollmorgen, is a full-time employee of Roche Diagnostics GmbH.
  22. Anna Bayfield

    Roche Diagnostics GmbH, Penzberg, Germany
    Competing interests
    Anna Bayfield, is a full-time employee and shareholder of Roche Diagnostics GmbH..
  23. Henrik Zetterberg

    Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
    Competing interests
    No competing interests declared.
  24. Kaj Blennow

    Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
    Competing interests
    No competing interests declared.
  25. Marc Suárez-Calvet

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    Competing interests
    Marc Suárez-Calvet, has served as a consultant and at advisory boards for Roche Diagnostics International Ltd and has given lectures in symposia sponsored by Roche Diagnostics, S.L.U, Roche Farma, S.A and Roche Sistemas de Diagnósticos, Sociedade Unipessoal, Lda..
  26. Verónica Vilaplana

    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Spain
    Competing interests
    No competing interests declared.
  27. Juan Domingo Gispert López

    Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
    For correspondence
    jdgispert@barcelonabeta.org
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6155-0642

Funding

European Union's Horizon 2020 Research and Innovation (948677)

  • Marc Suárez-Calvet

Instituto de Salud Carlos III (PI19/00155)

  • Marc Suárez-Calvet

La Caixa Foundation (100010434)

  • Marc Suárez-Calvet

European Union's Horizon 2020 Research and Innovation (847648)

  • Marc Suárez-Calvet

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

Ethics

Human subjects: ALFA ethics: All participants were enrolled in the ALFA (ALzheimer and FAmilies) study (Clinicaltrials.gov Identifier: NCT01835717. The study was approved by the Independent Ethics Committee "Parc de Salut Mar," Barcelona, and all participants gave written informed consent.

Copyright

© 2023, Cumplido-Mayoral 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. Irene Cumplido-Mayoral
  2. Marina García-Prat
  3. Grégory Operto
  4. Carles Falcon
  5. Mahnaz Shekari
  6. Raffaele Cacciaglia
  7. Marta Milà-Alomà
  8. Luigi Lorenzini
  9. Silvia Ingala
  10. Alle Meije Wink
  11. Henk JMM Mutsaerts
  12. Carolina Minguillón
  13. Karine Fauria
  14. José Luis Molinuevo
  15. Sven Haller
  16. Gael Chetelat
  17. Adam Waldman
  18. Adam J Schwarz
  19. Frederik Barkhof
  20. Ivonne Suridjan
  21. Gwendlyn Kollmorgen
  22. Anna Bayfield
  23. Henrik Zetterberg
  24. Kaj Blennow
  25. Marc Suárez-Calvet
  26. Verónica Vilaplana
  27. Juan Domingo Gispert López
(2023)
Biological brain age prediction using machine learning on structural neuroimaging data: multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex
eLife 12:e81067.
https://doi.org/10.7554/eLife.81067

Share this article

https://doi.org/10.7554/eLife.81067

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