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Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium.
Dwyer, Dominic B; Chand, Ganesh B; Pigoni, Alessandro; Khuntia, Adyasha; Wen, Junhao; Antoniades, Mathilde; Hwang, Gyujoon; Erus, Guray; Doshi, Jimit; Srinivasan, Dhivya; Varol, Erdem; Kahn, Rene S; Schnack, Hugo G; Meisenzahl, Eva; Wood, Stephen J; Zhuo, Chuanjun; Sotiras, Aristeidis; Shinohara, Russell T; Shou, Haochang; Fan, Yong; Schaulfelberger, Maristela; Rosa, Pedro; Lalousis, Paris A; Upthegrove, Rachel; Kaczkurkin, Antonia N; Moore, Tyler M; Nelson, Barnaby; Gur, Raquel E; Gur, Ruben C; Ritchie, Marylyn D; Satterthwaite, Theodore D; Murray, Robin M; Di Forti, Marta; Ciufolini, Simone; Zanetti, Marcus V; Wolf, Daniel H; Pantelis, Christos; Crespo-Facorro, Benedicto; Busatto, Geraldo F; Davatzikos, Christos; Koutsouleris, Nikolaos; Dazzan, Paola.
Affiliation
  • Dwyer DB; Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany. domdwyer@gmail.com.
  • Chand GB; Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia. domdwyer@gmail.com.
  • Pigoni A; Orygen, Melbourne, VIC, Australia. domdwyer@gmail.com.
  • Khuntia A; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Wen J; Department of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
  • Antoniades M; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
  • Hwang G; Social and Affective Neuroscience Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy.
  • Erus G; Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany.
  • Doshi J; Max-Planck Institute of Psychiatry, Munich, Germany.
  • Srinivasan D; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Varol E; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Kahn RS; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Schnack HG; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Meisenzahl E; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Wood SJ; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Zhuo C; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Sotiras A; Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA.
  • Shinohara RT; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Shou H; Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands.
  • Fan Y; LVR-Klinikum Düsseldorf, Kliniken der Heinrich-Heine-Universität, Düsseldorf, Germany.
  • Schaulfelberger M; Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia.
  • Rosa P; Orygen, Melbourne, VIC, Australia.
  • Lalousis PA; University of Birmingham, Edgbaston, UK.
  • Upthegrove R; Department of Psychiatric-Neuroimaging-Genetics and Co-morbidity Laboratory (PNGC-Lab), Nankai University Affiliated Tianjin Anding Hospital; Department of Psychiatry, Tianjin Medical University, Tianjin, China.
  • Kaczkurkin AN; Department of Radiology and Institute for Informatics, Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
  • Moore TM; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Nelson B; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Gur RE; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Gur RC; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Ritchie MD; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Satterthwaite TD; Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.
  • Murray RM; Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.
  • Di Forti M; Institute for Mental Health and Centre for Brain Health, University of Birmingham, Birmingham, UK.
  • Ciufolini S; Institute for Mental Health and Centre for Brain Health, University of Birmingham, Birmingham, UK.
  • Zanetti MV; Early Intervention Service, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
  • Wolf DH; Department of Psychology, Vanderbilt University, Nashville, TN, USA.
  • Pantelis C; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Crespo-Facorro B; Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia.
  • Busatto GF; Orygen, Melbourne, VIC, Australia.
  • Davatzikos C; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Koutsouleris N; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Dazzan P; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Mol Psychiatry ; 28(5): 2008-2017, 2023 05.
Article in En | MEDLINE | ID: mdl-37147389
Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Psychotic Disorders / Schizophrenia Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: America do sul / Brasil Language: En Journal: Mol Psychiatry Journal subject: BIOLOGIA MOLECULAR / PSIQUIATRIA Year: 2023 Document type: Article Affiliation country: Germany Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Psychotic Disorders / Schizophrenia Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: America do sul / Brasil Language: En Journal: Mol Psychiatry Journal subject: BIOLOGIA MOLECULAR / PSIQUIATRIA Year: 2023 Document type: Article Affiliation country: Germany Country of publication: United kingdom