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Research Paper

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

Min Tae M. Park, Armin Raznahan, Philip Shaw, Nitin Gogtay, Jason P. Lerch and M. Mallar Chakravarty
J Psychiatry Neurosci May 01, 2018 43 (3) 201-212; DOI: https://doi.org/10.1503/jpn.170094
Min Tae M. Park
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).
BSc
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Armin Raznahan
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).
MD, PhD
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Philip Shaw
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).
BM BCh, PhD
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Nitin Gogtay
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).
MD
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Jason P. Lerch
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).
PhD
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M. Mallar Chakravarty
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).
PhD
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    Fig. 1

    Graphical representation of network-set enrichment analysis (NSEA) using 2 hypothetical disorders and corresponding arrays. In both disorders, vertices are ordered using the ranking metric described: −log(p value) × sign(Cohen d), derived from case–control meta-analysis statistics within each disorder. Examining the enrichment score (ES) curves of the default mode network across Disorders A and B: A shows an initially decreasing ES due to default mode network vertices lacking enrichment (clustering) near the top of the ranked list, whereas B shows increasing ES due to highly enriched arrangement in ranked list L near the top.

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    Fig. 2

    Cross-disorder comparisons and combined meta-analysis. (A) Distribution of Cohen d effects across single- and combined-disorder analyses. (B) Meta-analysis of combined-disorder effects (all 3) relative to healthy controls. Colour bars indicate the direction of effect (Cohen d), with warmer colours (red) indicating increased cortical thickness/surface area (CT/SA) and cooler colours (blue) indicating decreased CT/SA compared with controls. Significance levels after false-discovery rate (FDR) correction (or lack thereof) are noted in the second panels. ADHD = attention-deficit/hyperactivity disorder; ASD = autism-spectrum disorder; SCZ = schizophrenia.

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    Fig. 3

    Conjunction analysis examining overlap between disorders by thresholding p values to the top 20%, 15%, 10% and 5% significant vertices within each disorder for (A) cortical thickness, with p value thresholds as follows: p = 0.004 at 20%, p = 0.002 at 15%, and p < 0.001 at both the 10% and 5% thresholds for patients with autism-spectrum disorders (ASD); p = 0.07 at 20%, p = 0.06 at 15%, p = 0.040 at 10% and p = 0.023 at the 5% threshold for patients with attention-deficit/hyperactivity disorder (ADHD); and p < 0.001 at all thresholds for patients with schizophrenia (SCZ), and (B) surface area, with p value thresholds as follows: ASD p = 0.20 at 20%, p = 0.14 at 15%, p = 0.09 at 10% and p = 0.032 at the 5% threshold for patients with ASD; p = 0.12 at 20%, p = 0.09 at 15%, p = 0.05 at 10% and p = 0.028 at the 5% threshold for patients with ADHD; and p < 0.001 at all thresholds for patients with schizophrenia.

  • Fig. 4
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    Fig. 4

    Assessing cross-modal homology comparing structural MRI to Neurosynth functional MRI (fMRI) findings at the network level. (A) Network-set enrichment analysis (NSEA) applied to single-disorder analyses for cortical thickness (CT) and surface area (SA), with Neurosynth comparisons. The Y axis indicates the normalized enrichment score (NES) for all meta-analysis results. Venn diagrams show networks that were significantly enriched across disorders. Correlations of Venn diagrams between CT and Neurosynth was significant (r = 0.64, p = 0.032), whereas the correlation between SA and Neurosynth was not significant (r = −0.48, p = 0.11). (B) The NSEA applied to combined disorder analyses and was compared with Neurosynth results. (C) Examining the dorsal attention SA network ES curves between patients with autism-spectrum disorder (ASD) and schizophrenia (SCZ). The Y axis indicates ES, and the X axis indicates ranked vertices from both hemispheres.

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Journal of Psychiatry and Neuroscience: 43 (3)
J Psychiatry Neurosci
Vol. 43, Issue 3
1 May 2018
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Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia
Min Tae M. Park, Armin Raznahan, Philip Shaw, Nitin Gogtay, Jason P. Lerch, M. Mallar Chakravarty
J Psychiatry Neurosci May 2018, 43 (3) 201-212; DOI: 10.1503/jpn.170094

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Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia
Min Tae M. Park, Armin Raznahan, Philip Shaw, Nitin Gogtay, Jason P. Lerch, M. Mallar Chakravarty
J Psychiatry Neurosci May 2018, 43 (3) 201-212; DOI: 10.1503/jpn.170094
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