. 2025 Jun 4;16(1):33.

doi: 10.1186/s13229-025-00667-z.

Subgrouping autism and ADHD based on structural MRI population modelling centiles

Clara Pecci-Terroba¹, Meng-Chuan Lai^{2

3

4

5

6}, Michael V Lombardo⁷, Bhismadev Chakrabarti⁸, Amber N V Ruigrok^{2

9}, John Suckling¹⁰, Evdokia Anagnostou^{11

12}, Jason P Lerch^{13

14

15}, Margot J Taylor^{13

16}, Rob Nicolson¹⁷, Stelios Georgiades¹⁸, Jennifer Crosbie^{4

5

13

19}, Russell Schachar^{4

5

13

19}, Elizabeth Kelley^{20

21

22}, Jessica Jones^{21

22}, Paul D Arnold^{23

24}, Jakob Seidlitz^{25

26

27}, Aaron F Alexander-Bloch^{25

26

27}, Edward T Bullmore¹⁰, Simon Baron-Cohen^{2

28}, Saashi A Bedford^{29

30

31}, Richard A I Bethlehem^{32

33}

Affiliations

¹ Department of Psychology, University of Cambridge, Cambridge, UK.
² Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
³ Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.
⁴ Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada.
⁵ Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
⁶ Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.
⁷ Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems, Istituto Italiano Di Tecnologia, Rovereto, Italy.
⁸ Centre for Autism, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.
⁹ Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK.
¹⁰ Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
¹¹ Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute Toronto, University of Toronto, Toronto, ON, Canada.
¹² Department of Pediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
¹³ Program in Neurosciences and Mental Health, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.
¹⁴ Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada.
¹⁵ Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
¹⁶ Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.
¹⁷ Department of Psychiatry, University of Western Ontario, London, ON, Canada.
¹⁸ McMaster University, Hamilton, ON, Canada.
¹⁹ Genetics & Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
²⁰ Department of Psychology, Queen's University, Kingston, ON, Canada.
²¹ Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
²² Department of Psychiatry, Queen's University, Kingston, ON, Canada.
²³ Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
²⁴ Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
²⁵ Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
²⁶ Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
²⁷ Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
²⁸ Cambridge Lifetime Autism Spectrum Service, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK.
²⁹ Department of Psychology, University of Cambridge, Cambridge, UK. ajb349@cam.ac.uk.
³⁰ Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK. ajb349@cam.ac.uk.
³¹ Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK. ajb349@cam.ac.uk.
³² Department of Psychology, University of Cambridge, Cambridge, UK. rb643@cam.ac.uk.
³³ Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK. rb643@cam.ac.uk.

PMID: 40468437
PMCID: PMC12135403
DOI: 10.1186/s13229-025-00667-z

Subgrouping autism and ADHD based on structural MRI population modelling centiles

Clara Pecci-Terroba et al. Mol Autism. 2025.

. 2025 Jun 4;16(1):33.

doi: 10.1186/s13229-025-00667-z.

Authors

Affiliations

¹ Department of Psychology, University of Cambridge, Cambridge, UK.
² Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
³ Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.
⁴ Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada.
⁵ Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
⁶ Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.
⁷ Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems, Istituto Italiano Di Tecnologia, Rovereto, Italy.
⁸ Centre for Autism, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.
⁹ Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK.
¹⁰ Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
¹¹ Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute Toronto, University of Toronto, Toronto, ON, Canada.
¹² Department of Pediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
¹³ Program in Neurosciences and Mental Health, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.
¹⁴ Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada.
¹⁵ Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
¹⁶ Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.
¹⁷ Department of Psychiatry, University of Western Ontario, London, ON, Canada.
¹⁸ McMaster University, Hamilton, ON, Canada.
¹⁹ Genetics & Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
²⁰ Department of Psychology, Queen's University, Kingston, ON, Canada.
²¹ Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
²² Department of Psychiatry, Queen's University, Kingston, ON, Canada.
²³ Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
²⁴ Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
²⁵ Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
²⁶ Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
²⁷ Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
²⁸ Cambridge Lifetime Autism Spectrum Service, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK.
²⁹ Department of Psychology, University of Cambridge, Cambridge, UK. ajb349@cam.ac.uk.
³⁰ Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK. ajb349@cam.ac.uk.
³¹ Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK. ajb349@cam.ac.uk.
³² Department of Psychology, University of Cambridge, Cambridge, UK. rb643@cam.ac.uk.
³³ Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK. rb643@cam.ac.uk.

PMID: 40468437
PMCID: PMC12135403
DOI: 10.1186/s13229-025-00667-z

Abstract

Background: Autism and attention deficit hyperactivity disorder (ADHD) are two highly heterogeneous neurodevelopmental conditions with variable underlying neurobiology. Imaging studies have yielded varied results, and it is now clear that there is unlikely to be one characteristic neuroanatomical profile of either condition. Parsing this heterogeneity could allow us to identify more homogeneous subgroups, either within or across conditions, which may be more clinically informative. This has been a pivotal goal for neurodevelopmental research using both clinical and neuroanatomical features, though results thus far have again been inconsistent with regards to the number and characteristics of subgroups.

Methods: Here, we use population modelling to cluster a multi-site dataset based on global and regional centile scores of cortical thickness, surface area and grey matter volume. We use HYDRA, a novel semi-supervised machine learning algorithm which clusters based on differences to controls and compare its performance to a traditional clustering approach.

Results: We identified distinct subgroups within autism and ADHD, as well as across diagnosis, often with opposite neuroanatomical alterations relatively to controls. These subgroups were characterised by different combinations of increased or decreased patterns of morphometrics. We did not find significant clinical differences across subgroups.

Limitations: Crucially, however, the number of subgroups and their membership differed vastly depending on chosen features and the algorithm used, highlighting the impact and importance of careful method selection.

Conclusions: We highlight the importance of examining heterogeneity in autism and ADHD and demonstrate that population modelling is a useful tool to study subgrouping in autism and ADHD. We identified subgroups with distinct patterns of alterations relative to controls but note that these results rely heavily on the algorithm used and encourage detailed reporting of methods and features used in future studies.

Keywords: ADHD; Autism; Neuroimaging; Population modelling; Structural MRI; Subgrouping.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Ethical approval and informed consent were obtained for each primary study. The Cambridge Psychology Research Ethics Committee (PRE.2020.104) deemed that secondary analysis of deidentified data did not require ethical oversight. Consent for publication: Not applicable. Competing interests: RAIB, MVL, and M-CL are Associate Editors, and EA and BC are Editorial Board members of Molecular Autism. SBC is a former Editor-in-Chief of the journal. ETB reports consultancy work for Boehringer Ingelheim, Sosei Heptares, SR One, and GlaxoSmithKline. ETB, RAIB, JS, and AFA-B are cofounders of Centile Bioscience. PDA receives research support from Biohaven Pharmaceuticals. M-CL has received editorial honorarium from SAGE Publications. RN reported receiving grants from Brain Canada, Hoffman La Roche, Otsuka Pharmaceuticals, and Maplight Therapeutics outside the submitted work. EA reported receiving grants from Roche and Anavex; receiving nonfinancial support from AMO Pharma and CRA-Simons Foundation; and receiving personal fees from Roche, Impel, Ono, and Quadrant outside the submitted work.

Figures

**Fig. 1**
Scatter plot showing distribution of individuals across UMAP embeddings (X1 and X2), coloured by subgroup. Each row corresponds to a different set of features: a global, b regional uncorrected, c regional corrected. Scatter plots for the combined dataset are also coloured in by diagnostic

**Fig. 2**
Violin plots showing the difference between controls and subgroups for the main global features: total grey matter volume (GMV), mean cortical thickness (CT), total surface area (SA), white matter volume (WMV), subcortical grey matter volume (sGMV), ventricular volume (V). Each row corresponds to a different dataset. a HYDRA, b UMAP and K-medoids

**Fig. 3**
Autism regional features results. a Differences in regional features between controls and autism subgroups, both uncorrected and corrected for global effects. The brain plots show Cohen’s d effect size, where red represents a positive effect size (subgroup > control), and blue a negative effect size (subgroup < control). Significant regions are outlined in black. b Alluvial showing flow of participants across techniques for the uncorrected and corrected cases. The colour indicates the subgroups identified by HYDRA

**Fig. 4**
ADHD regional features results. a Differences in regional features between controls and ADHD subgroups, both uncorrected and corrected for global effects. The brain plots show Cohen’s d effect size, where red represents a positive effect size (subgroup > control), and blue a negative effect size (subgroup < control). Significant regions are outlined in black. b Alluvial showing flow of participants across techniques for the uncorrected and corrected cases. The colour indicates the subgroups identified by HYDRA

**Fig. 5**
Combined dataset regional features results. a Differences in regional features between controls and Autism and ADHD Subgroups, both uncorrected and corrected for global effects. The brain plots show Cohen’s d effect size, where red represents a positive effect size (subgroup > control), and blue a negative effect size (subgroup < control). Significant regions are outlined in black. b Alluvial showing flow of participants across techniques for the uncorrected and corrected cases. The colour indicates the subgroups identified by HYDRA

See this image and copyright information in PMC

References

1. Lenroot RK, Yeung PK. Heterogeneity within autism spectrum disorders: what have we learned from neuroimaging studies? Front Hum Neurosci. 2013;7:733. - PMC - PubMed
1. Karalunas SL, Nigg JT. Heterogeneity and subtyping in attention-deficit/hyperactivity disorder—considerations for emerging research using person-centered computational approaches. Biol Psychiatry. 2020;88:103–10. - PMC - PubMed
1. Lombardo MV, Lai MC, Baron-Cohen S. Big data approaches to decomposing heterogeneity across the autism spectrum. Mol Psychiatry. 2019;24:1435–50. - PMC - PubMed
1. Lai MC, Lombardo MV, Chakrabarti B, Baron-Cohen S. Subgrouping the Autism “Spectrum": Reflections on DSM-5. PLoS Biol. 2013;11: e1001544. - PMC - PubMed
1. Courchesne E. Brain development in autism: Early overgrowth followed by premature arrest of growth. Ment Retard Dev Disabil Res Rev. 2004;10:106–11. - PubMed

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Subgrouping autism and ADHD based on structural MRI population modelling centiles

Affiliations

Subgrouping autism and ADHD based on structural MRI population modelling centiles

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

MeSH terms

LinkOut - more resources

Full Text Sources

Medical