Charting brain growth and aging at high spatial precision

Saige Rutherford, Charlotte Fraza, Richard Dinga, Seyed Mostafa Kia, Thomas Wolfers, Mariam Zabihi, Pierre Berthet, Amanda Worker, Serena Verdi, Derek Andrews, Laura K.M. Han, Johanna M.M. Bayer, Paola Dazzan, Phillip McGuire, Roel T. Mocking, Aart Schene, Chandra Sripada, Ivy F. Tso, Elizabeth R. Duval, Soo Eun ChangBrenda W.J.H. Penninx, Mary M. Heitzeg, S. Alexandra Burt, Luke W. Hyde, David Amaral, Christine Wu Nordahl, Ole A. Andreasssen, Lars T. Westlye, Roland Zahn, Henricus G. Ruhe, Christian Beckmann, Andre F. Marquand

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


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 used 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=1985), 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.

Original languageEnglish
Article numbere72904
StatePublished - Feb 2022

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