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Mapping cerebellar anatomical heterogeneity in mental and neurological illnesses

Nature Mental Health (2024)Cite this article

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Abstract

The cerebellum is linked to motor coordination, cognitive and affective processing, in addition to a wide range of clinical illnesses. To enable robust quantification of individual cerebellar anatomy relative to population norms, we mapped the normative development and aging of the cerebellum across the lifespan using brain scans of >54,000 participants. We estimated normative models at voxel-wise spatial precision, enabling integration with cerebellar atlases. Applying the normative models in independent samples revealed substantial heterogeneity within five clinical illnesses: autism spectrum disorder, mild cognitive impairment, Alzheimer disease, bipolar disorder, and schizophrenia. Notably, individuals with autism spectrum disorder and mild cognitive impairment exhibited increased positive and negative extreme deviations in cerebellar anatomy, while those with schizophrenia and Alzheimer disease showed predominantly negative deviations. Finally, extreme deviations were associated with cognitive scores. Our results provide a voxel-wise mapping of cerebellar anatomy across the human lifespan demonstrating the cerebellum’s nuanced role in different clinical illnesses.

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Fig. 1: Normative models based on MRI data from >54,000 participants describe the lifespan trajectories of cerebellar lobules and individual voxels.
Fig. 2: The voxel-wise deviations from estimated norms show high levels of heterogeneity within diagnostic groups.
Fig. 3: Voxel-wise normative models can be applied to existing or future cerebellar atlases.
Fig. 4: When applied to different atlases, significant correlations were observed between the percentage of extreme deviations per participant and estimated IQ scores.

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Data availability

In this study, we used brain imaging from ABIDE, ADHD200, AOMIC ID1000, Beijing Enhanced, CAMCAN, CoRR, DLBS, DS000119, DS000202, DS000222, Fcon1000, HBN, HCP, MPI Lemon, NKI-Rockland, OASIS-3, PING, SALD, SLIM, and UK Biobank, ADNI, AIBL, DEMGEN, PNC, and TOP. Publicly available datasets are available on request. The models from this work are available via PCNportal (https://pcnportal.dccn.nl/) (ref. 74) .

Code availability

All code used in this work is publicly available at FreeSurfer (https://surfer.nmr.mgh.harvard.edu), FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation), ACAPULCO (https://gitlab.com/shuohan/acapulco), and SUIT (https://github.com/jdiedrichsen/suit). Code for the normative model is available as an open-source python package, Predictive Clinical Neuroscience (PCN) toolkit (https://github.com/amarquand/PCNtoolkit). Additional codes are available via Github (https://github.com/milinkim/mapping_cerebellar_hetereogeneity).

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Acknowledgments

We are grateful to all the individuals who participated in the studies and acknowledge the contributions of the clinicians and researchers involved in the recruitment and assessment of participants for making this work possible. We gratefully acknowledge the following funding bodies. First, we acknowledge the European Research Council under the European Union’s Horizon 2020 research and Innovation program (ERC StG, grant 802998), the Research Council of Norway (300767, 324499), the South-Eastern Norway Regional Health Authority (2019101). We acknowledge the Norwegian registry of persons assessed for cognitive symptoms (NorCog) for providing access to patient data. We conducted this research using the UK Biobank Resource under application number 27412. T.W. acknowledges funding by the German Research Foundation (DFG; project number: 513851350) as well as starting funding from the faculty of medicine at the University of Tübingen. A.F.M. gratefully acknowledges funding from the European Research Council (‘MENTALPRECISION’ 101001118) and from the Raynor Foundation. We performed this work on the Services for sensitive data (TSD), University of Oslo, Norway, with resources provided by UNINETT Sigma2—the National Infrastructure for High-Performance Computing and Data Storage in Norway. Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann–La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research and Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private-sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. In addition, data used in preparation of this article were obtained from the Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL) databases (adni.loni.usc.edu) and the Pediatric Imaging, Neurocognition and Genetics (PING) study database (chd.ucsd.edu/research/ping-study.html, now shared through the NIMH Data Archive (NDA). This publication is solely the responsibility of the authors and does not necessarily represent the views of the National Institutes of Health or PING investigators. The work was supported by public funds Helse Sør-Øst grant 2021040 (supporting M.K. and T.M.), DFG Emmy Noether 513851350 (supporting T.W.), Research Council of Norway (no. 324499) and NordForsk (no. 164218), and KG Jebsen Foundation. The funders had no role in conception of the study as well as the analyses and/or interpretations of the results.

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Author notes

  1. These authors contributed equally: Thomas Wolfers, Torgeir Moberget.

Authors and Affiliations

  1. Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Milin Kim, Esten Leonardsen, Nils Eiel Steen, Olav B. Smeland, Torill Ueland, Geneviève Richard, Ole A. Andreassen, Lars T. Westlye, Thomas Wolfers & Torgeir Moberget

  2. Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway

    Milin Kim, Esten Leonardsen, Torill Ueland & Lars T. Westlye

  3. Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, Netherlands

    Saige Rutherford

  4. Donders Institute, Radboud University, Nijmegen, Netherlands

    Saige Rutherford, Christian F. Beckmann & Andre F. Marquand

  5. Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA

    Saige Rutherford

  6. Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway

    Geir Selbæk & Karin Persson

  7. The Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway

    Geir Selbæk & Karin Persson

  8. Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway

    Nils Eiel Steen

  9. Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK

    Christian F. Beckmann

  10. Department of Neuroimaging, Centre of Neuroimaging Sciences, Institute of Psychiatry, King’s College London, London, UK

    Andre F. Marquand

  11. KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway

    Ole A. Andreassen & Lars T. Westlye

  12. Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany

    Thomas Wolfers

  13. German Center for Mental Health (DZPG), Tübingen, Germany

    Thomas Wolfers

  14. Department of Behavioral Science, School of Health Sciences, Oslo Metropolitan University—OsloMet, Oslo, Norway

    Torgeir Moberget

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Contributions

T.M., T.W., and M.K. originally conceived of the project. M.K., T.W., T.M., and E.L. performed the analyses. M.K., T.W., and T.M. wrote the initial draft of the manuscript. O.A.A., G.R., K.P., G.S., N.E.S., O.B.S., A.F.M., C.F.B., T.U., T.W., and L.T.W. contributed to data curation. All authors discussed the results and contributed to the final manuscript.

Corresponding author

Correspondence to Milin Kim.

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Competing interests

O.A.A. has received speaker fees from Lundbeck, Janssen, Otsuka, and Sunovion and is a consultant to Cortechs.ai and Precision-Health.ai. The other authors report no competing interests.

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Kim, M., Leonardsen, E., Rutherford, S. et al. Mapping cerebellar anatomical heterogeneity in mental and neurological illnesses. Nat. Mental Health (2024). https://doi.org/10.1038/s44220-024-00297-z

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