Charting brain growth and aging at high spatial precision
- Radboud University Medical Center, Netherlands
- University of Oslo, Norway
- King's College London, United Kingdom
- University College London, United Kingdom
- University of California, Davis, United States
- Amsterdam University Medical Center, Netherlands
- University of Melbourne, Australia
- University of Michigan, United States
- Michigan State University, United States
Abstract
Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and use normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1,985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision making.
Data availability
All pre-trained models and code for transferring to new sites are shared online via GitHub (https://github.com/predictive-clinical-neuroscience/braincharts). We have also shared the models on Zenodo (https://zenodo.org/record/5535467#.YVRECmYzZhF).
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ABIDEhttp://fcon_1000.projects.nitrc.org/indi/abide/.
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ADHD200https://fcon_1000.projects.nitrc.org/indi/adhd200/.
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CAMCANhttps://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/.
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CMI-HBNhttp://fcon_1000.projects.nitrc.org/indi/cmi_healthy_brain_network/About.html.
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HCP-Aginghttps://nda.nih.gov/general-query.html?q=query=featured-datasets:HCP%20Aging%20and%20Development.
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HCP-Developmenthttps://nda.nih.gov/general-query.html?q=query=featured-datasets:HCP%20Aging%20and%20Development.
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HCP-Early Psychosishttps://nda.nih.gov/general-query.html?q=query=featured-datasets:Connectomes%20Related%20to%20Human%20Disease.
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NKI-RShttp://fcon_1000.projects.nitrc.org/indi/enhanced/access.html.
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Oasishttps://direct.mit.edu/jocn/article/19/9/1498/4427/Open-Access-Series-of-Imaging-Studies-OASIS-Cross.
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Philadelphia Neurodevelopmental Cohorthttps://www.med.upenn.edu/bbl/philadelphianeurodevelopmentalcohort.html.
Article and author information
Author details
Funding
H2020 European Research Council (10100118)
- Andre F Marquand
Medical Research Council (G0902304)
- Roland Zahn
National Institute of Mental Health (K23MH108823)
- Ivy F Tso
National Institute on Deafness and Other Communication Disorders (R01DC011277)
- Soo-Eun Chang
National Institute of Mental Health (R01MH107741)
- Chandra Sripada
Michigan Institute for Clinical and Health Research (UL1TR002240)
- Elizabeth R Duval
National Institute of Mental Health (UG3MH114249)
- S Alexandra Burt
- Luke Hyde
Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD093334)
- S Alexandra Burt
- Luke Hyde
H2020 European Research Council (802998)
- Lars T Westlye
Wellcome Trust (215698/Z/19/Z)
- Andre F Marquand
Wellcome Trust (098369/Z/12/Z)
- Christian Beckmann
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VIDI grant 016.156.415)
- Andre F Marquand
National Institute of Mental Health (R01MH104438)
- David Amaral
- Christine Wu Nordahl
National Institute of Mental Health (R01MH103371)
- David Amaral
- Christine Wu Nordahl
Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50 HD093079)
- David Amaral
- Christine Wu Nordahl
H2020 Marie Skłodowska-Curie Actions (895011)
- Thomas Wolfers
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Ethical approval for the public data were provided by the relevant local research authorities for the studies contributing data. For full details see the main study publications given in the main text. For all clinical studies, approval was obtained via the local ethical review authorities, i.e.: TOP: Regional Committee for Medical & Health Research Ethics South East Norway. Approval number: 2009/2485- C, KCL: South Manchester NHS National Research Ethics Service. Approval number: 07/H1003/194. Delta: The local ethics committee of the Academic Medical Center of the University of Amsterdam (AMC-METC) Nr.:11/050, UMich_IMPS: University of Michigan Institution Review Board HUM00088188, UMich_SZG: University of Michigan Institution Review Board HUM00080457, UMich_MLS: University of Michigan Institution Review Board HUM00040642, UMich_CWS: MSU Biomedical and Health Institutional Review Board (BIIRB) IRB#09-810, UMich_MTWiNS: University of Michigan Institution Review HUM00163965, UCDavis: University of California Davis Institutional Review Board IRB ID: 220915, 592866, 1097084.
Copyright
© 2022, Rutherford 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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Charting brain growth and aging at high spatial precision
eLife 11:e72904.
https://doi.org/10.7554/eLife.72904
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