Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia

Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia

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J Psychiatry Neurosci 2018;43(3):201-212

Min Tae M. Park, BSc; Armin Raznahan, MD, PhD; Philip Shaw, BM BCh, PhD; Nitin Gogtay, MD; Jason P. Lerch, PhD; M. Mallar Chakravarty, PhD

Abstract

Background: There is evidence suggesting neuropsychiatric disorders share genomic, cognitive and clinical features. Here, we ask if autism-spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and schizophrenia share neuroanatomical variations.

Methods: First, we used measures of cortical anatomy to estimate spatial overlap of neuroanatomical variation using univariate methods. Next, we developed a novel methodology to determine whether cortical deficits specifically target or are “enriched” within functional resting-state networks.

Results: We found cortical anomalies were preferentially enriched across functional networks rather than clustering spatially. Specifically, cortical thickness showed significant enrichment between patients with ASD and those with ADHD in the default mode network, between patients with ASD and those with schizophrenia in the frontoparietal and limbic networks, and between patients with ADHD and those with schizophrenia in the ventral attention network. Networks enriched in cortical thickness anomalies were also strongly represented in functional MRI results (Neurosynth; r = 0.64, p = 0.032).

Limitations: We did not account for variable symptom dimensions and severity in patient populations, and our cross-sectional design prevented longitudinal analyses of developmental trajectories.

Conclusion: These findings suggest that common deficits across neuropsychiatric disorders cannot simply be characterized as arising out of local changes in cortical grey matter, but rather as entities of both local and systemic alterations targeting brain networks.


Submitted May 9, 2017; Revised Sept. 1, 2017; Accepted Sept. 20, 2017; Published online first Feb. 6, 2018

Acknowledgements: The authors thank all groups, as noted in Appendix 1, Table S2, for the generous contribution of their data and indirectly supporting this work. M. Chakravarty is funded by the Canadian Institutes of Health Research, National Sciences and Engineering Research Council of Canada, Brain Canada, Alzheimer’s Society, Michael J. Fox Foundation for Parkinson’s Research, and the Weston Brain Institute. M. Chakravarty also received salary and research support from the Fonds du Recherches Santé Québec.

Affiliations: From the Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Park); the Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Que., Canada (Park, Chakravarty); the Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, USA (Raznahan); the Section on Neurobehavioral Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA (Shaw); the Intramural Program of the National Institute of Mental Health, Bethesda, MD, USA (Shaw); the Program in Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Ont., Canada (Lerch); and the Departments of Psychiatry and Biomedical Engineering, McGill University, Montreal, Que., Canada (Chakravarty).

Competing interests: None declared.

Contributors: M. Park and M. Ckravarty designed the study and acquired the data, which all authors analyzed. All authors wrote and reviewed the article, approved the final version to be published, and can certify that no other individuals not listed as authors have made substantial contributions to the paper.

DOI: 10.1503/jpn.170094

Correspondence to: M.T. Park, Douglas Mental Health University Institute, 6875 LaSalle Blvd, Montreal, Que., Canada H4H 1R3; mtpark89@gmail.com