Subgrouping autism and ADHD based on structural MRI population modelling centiles.
Authors
Affiliations (33)
Affiliations (33)
- Department of Psychology, University of Cambridge, Cambridge, UK.
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- 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.
- Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada.
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems, Istituto Italiano Di Tecnologia, Rovereto, Italy.
- Centre for Autism, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.
- Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK.
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute Toronto, University of Toronto, Toronto, ON, Canada.
- Department of Pediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
- Program in Neurosciences and Mental Health, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada.
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.
- Department of Psychiatry, University of Western Ontario, London, ON, Canada.
- McMaster University, Hamilton, ON, Canada.
- Genetics & Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
- Department of Psychology, Queen's University, Kingston, ON, Canada.
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
- Department of Psychiatry, Queen's University, Kingston, ON, Canada.
- Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
- Cambridge Lifetime Autism Spectrum Service, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK.
- Department of Psychology, University of Cambridge, Cambridge, UK. [email protected].
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK. [email protected].
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK. [email protected].
- Department of Psychology, University of Cambridge, Cambridge, UK. [email protected].
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK. [email protected].
Abstract
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. 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. 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. 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. 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.