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Dwyer DB, Chand GB, Pigoni A, Khuntia A, Wen J, Antoniades M, Hwang G, Erus G, Doshi J, Srinivasan D, Varol E, Kahn RS, Schnack HG, Meisenzahl E, Wood SJ, Zhuo C, Sotiras A, Shinohara RT, Shou H, Fan Y, Schaulfelberger M, Rosa P, Lalousis PA, Upthegrove R, Kaczkurkin AN, Moore TM, Nelson B, Gur RE, Gur RC, Ritchie MD, Satterthwaite TD, Murray RM, Di Forti M, Ciufolini S, Zanetti MV, Wolf DH, Pantelis C, Crespo-Facorro B, Busatto GF, Davatzikos C, Koutsouleris N, Dazzan P. Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium. Mol Psychiatry 2023; 28:2008-2017. [PMID: 37147389 PMCID: PMC10575777 DOI: 10.1038/s41380-023-02069-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 03/15/2023] [Accepted: 04/05/2023] [Indexed: 05/07/2023]
Abstract
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.
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Affiliation(s)
- Dominic B Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany.
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia.
- Orygen, Melbourne, VIC, Australia.
| | - Ganesh B Chand
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Alessandro Pigoni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Social and Affective Neuroscience Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Adyasha Khuntia
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Max-Planck Institute of Psychiatry, Munich, Germany
| | - Junhao Wen
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mathilde Antoniades
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gyujoon Hwang
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Guray Erus
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jimit Doshi
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dhivya Srinivasan
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Erdem Varol
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA
| | - Rene S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hugo G Schnack
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
| | - Eva Meisenzahl
- LVR-Klinikum Düsseldorf, Kliniken der Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Stephen J Wood
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
- Orygen, Melbourne, VIC, Australia
- University of Birmingham, Edgbaston, UK
| | - Chuanjun Zhuo
- 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
| | - Aristeidis Sotiras
- Department of Radiology and Institute for Informatics, Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Haochang Shou
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yong Fan
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Pedro Rosa
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Paris A Lalousis
- Institute for Mental Health and Centre for Brain Health, University of Birmingham, Birmingham, UK
| | - Rachel Upthegrove
- Institute for Mental Health and Centre for Brain Health, University of Birmingham, Birmingham, UK
- Early Intervention Service, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | | | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Barnaby Nelson
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
- Orygen, Melbourne, VIC, Australia
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Robin M Murray
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Marta Di Forti
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Simone Ciufolini
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Marcus V Zanetti
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
- Hospital Sírio-Libanês, São Paulo, Brazil
| | - Daniel H Wolf
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Benedicto Crespo-Facorro
- Mental Health Service, Hospital Universitario Virgen del Rocío, Seville, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III (CIBERSAM), Madrid, Spain
- Instituto de Biomedicina de Sevilla (IBiS), Seville, Spain
- Department of Psychiatry, Universidad de Sevilla, Seville, Spain
| | - Geraldo F Busatto
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany.
- Max-Planck Institute of Psychiatry, Munich, Germany.
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
| | - Paola Dazzan
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
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Differential diagnosis of delusional symptoms in schizophrenia: Brain tractography data. COGN SYST RES 2023. [DOI: 10.1016/j.cogsys.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Zhao Q, Cao H, Zhang W, Li S, Xiao Y, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Hill SK, Keedy SK, Ivleva EI, Lencer R, Sweeney JA, Gong Q, Lui S. A subtype of institutionalized patients with schizophrenia characterized by pronounced subcortical and cognitive deficits. Neuropsychopharmacology 2022; 47:2024-2032. [PMID: 35260788 PMCID: PMC9556672 DOI: 10.1038/s41386-022-01300-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 01/28/2022] [Accepted: 02/19/2022] [Indexed: 02/05/2023]
Abstract
Some patients with schizophrenia have severe cognitive impairment and functional deficits that require long-term institutional care. The patterns of brain-behavior alterations in these individuals, and their differences from patients living successfully in the community, remain poorly understood. Previous cognition-based studies for stratifying schizophrenia patients highlight the importance of subcortical structures in the context of illness heterogeneity. In the present study, subcortical volumes from 96 institutionalized patients with long-term schizophrenia were evaluated using cluster analysis to test for heterogeneity. These data were compared to those from two groups of community-dwelling individuals with schizophrenia for comparison purposes, including 68 long-term ill and 126 first-episode individuals. A total of 290 demographically matched healthy participants were included as normative references at a 1:1 ratio for each patient sample. A subtype of institutionalized patients was identified based on their pattern of subcortical alterations. Using a machine learning algorithm developed to discriminate the two groups of institutionalized patients, all three patient samples were found to have similar rates of patients assigned to the two subtypes (approximately 50% each). In institutionalized patients, only the subtype with the identified pattern of subcortical alterations had greater neocortical and cognitive abnormalities than those in the similarity classified community-dwelling patients with long-term illness. Thus, for the subtype of patients with a distinctive pattern of subcortical alterations, when the distinct pattern of subcortical alterations is present and particularly severe, it is associated with cognitive impairments that may contribute to persistent disability and institutionalization.
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Affiliation(s)
- Qiannan Zhao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Hengyi Cao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Wenjing Zhang
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Siyi Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Yuan Xiao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Scot Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
| | - Su Lui
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
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Nelson EA, Kraguljac NV, Maximo JO, Armstrong W, Lahti AC. Dorsal striatial hypoconnectivity predicts antipsychotic medication treatment response in first-episode psychosis and unmedicated patients with schizophrenia. Brain Behav 2022; 12:e2625. [PMID: 36237115 PMCID: PMC9660417 DOI: 10.1002/brb3.2625] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/28/2022] [Accepted: 04/24/2022] [Indexed: 01/10/2023] Open
Abstract
INTRODUCTION The dorsal striatum, comprised of the caudate and putamen, is implicated in the pathophysiology of psychosis spectrum disorders. Given the high concentration of dopamine receptors in the striatum, striatal dopamine imbalance is a likely cause in cortico-striatal dysconnectivity. There is great interest in understanding the relationship between striatal abnormalities in psychosis and antipsychotic treatment response, but few studies have considered differential involvement of the caudate and putamen. This study's goals were twofold. First, identify patterns of dorsal striatal dysconnectivity for the caudate and putamen separately in patients with a psychosis spectrum disorder; second, determine if these dysconnectivity patterns were predictive of treatment response. METHODS Using resting state functional connectivity, we evaluated dorsal striatal connectivity using separate bilateral caudate and putamen seed regions in two cohorts of subjects: a cohort of 71 medication-naïve first episode psychosis patients and a cohort of 42 unmedicated patients with schizophrenia (along with matched controls). Patient and control connectivity maps were contrasted for each cohort. After receiving 6 weeks of risperidone treatment, patients' clinical response was calculated. We used regression analyses to determine the relationship between baseline dysconnectivity and treatment response. RESULTS This dysconnectivity was also predictive of treatment response in both cohorts. DISCUSSION These findings suggest that the caudate may be more of a driving factor than the putamen in early cortico-striatal dysconnectivity.
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Affiliation(s)
- Eric A Nelson
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Nina V Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Jose O Maximo
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - William Armstrong
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
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Gurholt TP, Lonning V, Nerland S, Jørgensen KN, Haukvik UK, Alloza C, Arango C, Barth C, Bearden CE, Berk M, Bohman H, Dandash O, Díaz‐Caneja CM, Edbom CT, van Erp TGM, Fett AJ, Frangou S, Goldstein BI, Grigorian A, Jahanshad N, James AC, Janssen J, Johannessen C, Karlsgodt KH, Kempton MJ, Kochunov P, Krabbendam L, Kyriakopoulos M, Lundberg M, MacIntosh BJ, Rund BR, Smelror RE, Sultan A, Tamnes CK, Thomopoulos SI, Vajdi A, Wedervang‐Resell K, Myhre AM, Andreassen OA, Thompson PM, Agartz I. Intracranial and subcortical volumes in adolescents with early-onset psychosis: A multisite mega-analysis from the ENIGMA consortium. Hum Brain Mapp 2022; 43:373-384. [PMID: 33017498 PMCID: PMC8675418 DOI: 10.1002/hbm.25212] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/11/2020] [Accepted: 09/13/2020] [Indexed: 12/27/2022] Open
Abstract
Early-onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early-onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early-onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early-onset schizophrenia (n = 183), affective psychosis (n = 39), or other psychotic disorders (n = 41). We used linear mixed-effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen's d = -0.39) and hippocampal (d = -0.25) volumes, and higher caudate (d = 0.25) and pallidum (d = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early-onset schizophrenia (d = -0.34) and affective psychosis (d = -0.42), and early-onset schizophrenia showed lower hippocampal (d = -0.24) and higher pallidum (d = 0.29) volumes. Patients who were currently treated with antipsychotic medication (n = 193) had significantly lower intracranial volume (d = -0.42). The findings demonstrate a similar pattern of brain alterations in early-onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early-onset psychosis.
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Affiliation(s)
- Tiril P. Gurholt
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Vera Lonning
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Stener Nerland
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Kjetil N. Jørgensen
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Unn K. Haukvik
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
- Department of Adult Mental Health, Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental HealthHospital General Universitario Gregorio Marañón, IiSGM, CIBERSAMMadridSpain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental HealthHospital General Universitario Gregorio Marañón, IiSGM, CIBERSAMMadridSpain
- School of MedicineUniversidad ComplutenseMadridSpain
| | - Claudia Barth
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Carrie E. Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUCLALos AngelesCaliforniaUSA
- Department of PsychologyUCLALos AngelesCaliforniaUSA
| | - Michael Berk
- IMPACT, The Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin UniversityGeelongVictoriaAustralia
- Orygen Youth Health Research CenterThe Florey Institute for Neuroscience and Department of PsychiatryParkvilleVictoriaAustralia
| | - Hannes Bohman
- Center for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, SwedenStockholmSweden
- Department of Neuroscience, Child and Adolescent PsychiatryUppsala UniversityUppsalaSweden
- Department of Clinical Science and Education SödersjukhusetKarolinska InstitutetStockholmSweden
| | - Orwa Dandash
- IMPACT, The Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin UniversityGeelongVictoriaAustralia
| | - Covadonga M. Díaz‐Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental HealthHospital General Universitario Gregorio Marañón, IiSGM, CIBERSAMMadridSpain
- School of MedicineUniversidad ComplutenseMadridSpain
| | - Carl T. Edbom
- Center for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, SwedenStockholmSweden
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of LearningUniversity of California Irvine and MemoryIrvineCaliforniaUSA
| | - Anne‐Kathrin J. Fett
- Department of PsychologyCity, University of LondonLondonUK
- Department of Psychosis StudiesIoPPNLondonUK
- Department of Clinical, Neuro and Developmental PsychologyVU AmsterdamAmsterdamNetherlands
| | - Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Benjamin I. Goldstein
- Center for Youth Bipolar Disorder, Sunnybrook Health Science CenterTorontoOntarioCanada
- Department of Psychiatry and PharmacologyUniversity of TorontoCanada
| | - Anahit Grigorian
- Center for Youth Bipolar Disorder, Sunnybrook Health Science CenterTorontoOntarioCanada
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Anthony C. James
- Department of PsychiatryUniversity of OxfordOxfordUK
- Oxford Health Foundation NHS TrustOxfordUK
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental HealthHospital General Universitario Gregorio Marañón, IiSGM, CIBERSAMMadridSpain
- School of MedicineUniversidad ComplutenseMadridSpain
| | - Cecilie Johannessen
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Katherine H. Karlsgodt
- Department of PsychologyUCLALos AngelesCaliforniaUSA
- Department Psychiatry and Biobehavioral SciencesUCLALos AngelesCaliforniaUSA
| | | | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Lydia Krabbendam
- Department of Clinical, Neuro and Developmental PsychologyVU AmsterdamAmsterdamNetherlands
| | - Marinos Kyriakopoulos
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUK
- National and Specialist Children's Inpatient Unit (Acorn Lodge), South London and Maudsley NHS Foundation TrustBeckenhamUK
| | - Mathias Lundberg
- Center for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, SwedenStockholmSweden
- Department of Neuroscience, Child and Adolescent PsychiatryUppsala UniversityUppsalaSweden
- Department of Clinical Science and Education SödersjukhusetKarolinska InstitutetStockholmSweden
- The Department of Clinical Science and EducationKI SÖSStockholmSweden
| | - Bradley J. MacIntosh
- Hurvitz Brain Sciences, Sunnybrook Research InstituteTorontoOntarioCanada
- Department of Medical BiophysicsUniversity of TorontoOntarioCanada
| | - Bjørn Rishovd Rund
- Department of PsychologyUniversity of OsloOsloNorway
- Department of ResearchVestre Viken Hospital TrustDrammenNorway
| | - Runar E. Smelror
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Alysha Sultan
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of PharmacologyUniversity of TorontoTorontoOntarioCanada
| | - Christian K. Tamnes
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- PROMENTA Research Center, Department of PsychologyUniversity of OsloOsloNorway
| | | | - Ariana Vajdi
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human BehaviorUCLALos AngelesCaliforniaUSA
| | - Kirsten Wedervang‐Resell
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Anne M. Myhre
- Child and Adolescent Psychiatry Unit, Division of Mental Health and Addiction, Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric Research and Development, Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Ole A. Andreassen
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Paul M. Thompson
- Department of Psychiatry and PharmacologyUniversity of TorontoCanada
| | - Ingrid Agartz
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- Center for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, SwedenStockholmSweden
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Zang J, Huang Y, Kong L, Lei B, Ke P, Li H, Zhou J, Xiong D, Li G, Chen J, Li X, Xiang Z, Ning Y, Wu F, Wu K. Effects of Brain Atlases and Machine Learning Methods on the Discrimination of Schizophrenia Patients: A Multimodal MRI Study. Front Neurosci 2021; 15:697168. [PMID: 34385901 PMCID: PMC8353157 DOI: 10.3389/fnins.2021.697168] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 07/07/2021] [Indexed: 11/24/2022] Open
Abstract
Recently, machine learning techniques have been widely applied in discriminative studies of schizophrenia (SZ) patients with multimodal magnetic resonance imaging (MRI); however, the effects of brain atlases and machine learning methods remain largely unknown. In this study, we collected MRI data for 61 first-episode SZ patients (FESZ), 79 chronic SZ patients (CSZ) and 205 normal controls (NC) and calculated 4 MRI measurements, including regional gray matter volume (GMV), regional homogeneity (ReHo), amplitude of low-frequency fluctuation and degree centrality. We systematically analyzed the performance of two classifications (SZ vs NC; FESZ vs CSZ) based on the combinations of three brain atlases, five classifiers, two cross validation methods and 3 dimensionality reduction algorithms. Our results showed that the groupwise whole-brain atlas with 268 ROIs outperformed the other two brain atlases. In addition, the leave-one-out cross validation was the best cross validation method to select the best hyperparameter set, but the classification performances by different classifiers and dimensionality reduction algorithms were quite similar. Importantly, the contributions of input features to both classifications were higher with the GMV and ReHo features of brain regions in the prefrontal and temporal gyri. Furthermore, an ensemble learning method was performed to establish an integrated model, in which classification performance was improved. Taken together, these findings indicated the effects of these factors in constructing effective classifiers for psychiatric diseases and showed that the integrated model has the potential to improve the clinical diagnosis and treatment evaluation of SZ.
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Affiliation(s)
- Jinyu Zang
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
| | - Yuanyuan Huang
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
| | - Lingyin Kong
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
| | - Bingye Lei
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
| | - Pengfei Ke
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
| | - Hehua Li
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
| | - Jing Zhou
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
| | - Dongsheng Xiong
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
| | - Guixiang Li
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
- National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Jun Chen
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
- National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Xiaobo Li
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Zhiming Xiang
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
- Department of Radiology, Panyu Central Hospital of Guangzhou, Guangzhou, China
| | - Yuping Ning
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
| | - Fengchun Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
| | - Kai Wu
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
- National Engineering Research Center for Healthcare Devices, Guangzhou, China
- Key Laboratory of Biomedical Engineering of Guangdong Province, South China University of Technology, Guangzhou, China
- Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
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7
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The effect of second-generation antipsychotics on basal ganglia and thalamus in first-episode psychosis patients. Eur Neuropsychopharmacol 2019; 29:1408-1418. [PMID: 31708330 DOI: 10.1016/j.euroneuro.2019.10.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 07/29/2019] [Accepted: 10/15/2019] [Indexed: 01/14/2023]
Abstract
Patients who have recently experienced a first of episode psychosis (FEP) exhibit considerable heterogeneity in subcortical brain volumes. These results become even more divergent when exploring the effect of antipsychotic medication among other clinical and cognitive features. We aimed to contrast volumetric measures in basal ganglia and thalamus in patients with a FEP treated with different second-generation antipsychotics. T1-weighted magnetic resonance images were obtained and subcortical structures were extracted with MAGeT-Brain. Relationships with cognitive functioning were also explored with a Global Cognitive Index obtained, on average, within one month from the scan. Subgroups included: risperidone (n = 26), aripiprazole (n = 22), olanzapine (n = 19) and controls (n = 80). The olanzapine subgroup displayed significant enlargement of the right globus pallidus volume compared with all other groups. Moreover, despite not exhibiting poorer cognitive capacity than the rest of patients, results from a stepwise multiple-regression linear regression analysis identified a significant negative association between right globus pallidus volume and scores on the Global Cognitive Index among these patients. To our knowledge, this is the first study to associate treatment with olanzapine with an increase in globus pallidus volume in a sample of FEP patients with a relatively short time of antipsychotic monotherapy. Such enlargement was also found to be associated with poorer global cognitive functioning. Exploration of the biological underpinnings of this early medication-induced enlargement should be the focus of future investigations since it may lend insight towards achieving a better clinical outcome for these patients.
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8
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Di Sero A, Jørgensen KN, Nerland S, Melle I, Andreassen OA, Jovicich J, Agartz I. Antipsychotic treatment and basal ganglia volumes: Exploring the role of receptor occupancy, dosage and remission status. Schizophr Res 2019; 208:114-123. [PMID: 31006616 DOI: 10.1016/j.schres.2019.04.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 03/27/2019] [Accepted: 04/02/2019] [Indexed: 12/13/2022]
Abstract
Antipsychotic treatment may affect brain morphology, and enlargement of the basal ganglia (BG) is a replicated finding. Here we investigated associations between antipsychotic treatment and BG volumes in patients with psychotic and bipolar disorders. We hypothesized that current treatment and, among those medicated, higher dosage, estimated D2R occupancy and being in remission would predict larger BG volumes. Structural covariance analysis was performed to examine if correlations between BG volumes and cortical thickness differed by treatment status. 224 patients treated with antipsychotics; 26 previously treated, 29 never treated and 301 healthy controls (HC) were included from the TOP study cohort (NORMENT, Norway). T1-weighted MR images were processed using FreeSurfer. D2R occupancy was estimated based on serum concentration measurements for patients receiving stable monotherapy. Statistical analyses were adjusted for age, gender and estimated intracranial volume (ICV). We found larger right (p < 0.003) and left putamen (p < 0.02) and right globus pallidus (GP) (p < 0.03) in currently medicated patients compared to HC. Bilateral regional cortical thinning was also observed in currently and previously medicated patients compared to HC. In medicated patients, higher chlorpromazine equivalent dose (CPZ) was associated with larger left GP (p < 0.04). There was no association with estimated D2R occupancy (n = 47) or remission status. Lower positive correlation between left putamen volume and cortical thickness of the left lateral occipital cortex was found in medicated patients compared to HC. We replicated the BG enlargement in medicated patients, but found no association with estimated D2R occupancy. Further studies are needed to clarify the underlying mechanisms.
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Affiliation(s)
- Alessia Di Sero
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Center for Mind and Brain Sciences, University of Trento, Trento, Italy; Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Norway
| | - Kjetil N Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Norway.
| | - Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Norway
| | - Ingrid Melle
- Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Norway; Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Norway; Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jorge Jovicich
- Center for Mind and Brain Sciences, University of Trento, Trento, Italy
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Norwegian Centre for Research on Mental Disorders, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Norway; Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
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9
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Do Antipsychotics "Thin" the Brain?: It Is a Rather Gray Matter. J Clin Psychopharmacol 2018; 38:167-169. [PMID: 29620691 DOI: 10.1097/jcp.0000000000000879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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10
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Eggins PS, Hatton SN, Hermens DF, Hickie IB, Lagopoulos J. Subcortical volumetric differences between clinical stages of young people with affective and psychotic disorders. Psychiatry Res Neuroimaging 2018; 271:8-16. [PMID: 29216557 DOI: 10.1016/j.pscychresns.2017.11.015] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Revised: 11/20/2017] [Accepted: 11/20/2017] [Indexed: 11/19/2022]
Abstract
The aim of this study was to investigate differences in subcortical and hippocampal volumes between healthy controls, young people at an early stage of affective and psychotic disorders and those in more advanced stages, to identify markers associated with functional outcomes and illness severity. Young people presenting to youth mental health services with admixtures of depressive, manic and psychotic symptoms (n = 141), and healthy counterparts (n = 49), aged 18-25 were recruited. Participants underwent magnetic resonance imaging, clinical assessments and were rated as to their current clinical stage. Eighty-four patients were classified at the attenuated syndrome stage (Stage 1b) and 57 were classified as having discrete and persistent disorders (Stage 2+). Automated segmentation was performed using NeuroQuant® to determine volumes of subcortical and hippocampus structures which were compared between groups and correlated with clinical and functional outcomes. Compared to healthy controls, Stage 2+ patients showed significantly reduced right amygdala volumes. Whereas Stage 1b patients showed significantly reduced left caudate volumes compared to healthy controls. Smaller left caudate volume correlated with greater psychological distress and impaired functioning. This study shows a clinical application for an automated program to identify and track subcortical changes evident in young people with emerging psychopathology.
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Affiliation(s)
- Peta S Eggins
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Australia.
| | - Sean N Hatton
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Australia
| | - Daniel F Hermens
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Australia
| | - Ian B Hickie
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Australia
| | - Jim Lagopoulos
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Australia
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11
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Nørbak-Emig H, Pinborg LH, Raghava JM, Svarer C, Baaré WFC, Allerup P, Friberg L, Rostrup E, Glenthøj B, Ebdrup BH. Extrastriatal dopamine D 2/3 receptors and cortical grey matter volumes in antipsychotic-naïve schizophrenia patients before and after initial antipsychotic treatment. World J Biol Psychiatry 2017; 18:539-549. [PMID: 27782768 DOI: 10.1080/15622975.2016.1237042] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
OBJECTIVES Long-term dopamine D2/3 receptor blockade, common to all antipsychotics, may underlie progressive brain volume changes observed in patients with chronic schizophrenia. In the present study, we examined associations between cortical volume changes and extrastriatal dopamine D2/3 receptor binding potentials (BPND) in first-episode schizophrenia patents at baseline and after antipsychotic treatment. METHODS Twenty-two initially antipsychotic-naïve patients underwent magnetic resonance imaging (MRI), [123I]epidepride single-photon emission computerised tomography (SPECT), and psychopathology assessments before and after 3 months of treatment with either risperidone (N = 13) or zuclopenthixol (N = 9). Twenty healthy controls matched on age, gender and parental socioeconomic status underwent baseline MRI and SPECT. RESULTS Neither extrastriatal D2/3 receptor BPND at baseline, nor blockade at follow-up, was related to regional cortical volume changes. In post-hoc analyses excluding three patients with cannabis use we found that higher D2/3 receptor occupancy was significantly associated with an increase in right frontal grey matter volume. CONCLUSIONS The present data do not support an association between extrastriatal D2/3 receptor blockade and extrastriatal grey matter loss in the early phases of schizophrenia. Although inconclusive, our exclusion of patients tested positive for cannabis use speaks to keeping attention to potential confounding factors in imaging studies.
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Affiliation(s)
- Henrik Nørbak-Emig
- a Centre for Neuropsychiatric Schizophrenia Research, CNSR & Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre, Glostrup, University of Copenhagen , Denmark.,b Faculty of Health and Medical Sciences, Department of Clinical Medicine , University of Copenhagen , Denmark
| | - Lars H Pinborg
- c Neurobiology Research Unit and Epilepsy Clinic, Rigshospitalet, University of Copenhagen , Denmark
| | - Jayachandra M Raghava
- a Centre for Neuropsychiatric Schizophrenia Research, CNSR & Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre, Glostrup, University of Copenhagen , Denmark.,d Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet - Glostrup , University of Copenhagen , Denmark
| | - Claus Svarer
- c Neurobiology Research Unit and Epilepsy Clinic, Rigshospitalet, University of Copenhagen , Denmark
| | - William F C Baaré
- e Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Hvidovre Hospital, University of Copenhagen , Denmark
| | - Peter Allerup
- f Institute for Education (DPU), Aarhus University , Denmark
| | - Lars Friberg
- g Department of Clinical Physiology and Nuclear Medicine , Bispebjerg Hospital, University of Copenhagen , Denmark
| | - Egill Rostrup
- d Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet - Glostrup , University of Copenhagen , Denmark
| | - Birte Glenthøj
- a Centre for Neuropsychiatric Schizophrenia Research, CNSR & Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre, Glostrup, University of Copenhagen , Denmark.,b Faculty of Health and Medical Sciences, Department of Clinical Medicine , University of Copenhagen , Denmark
| | - Bjørn H Ebdrup
- a Centre for Neuropsychiatric Schizophrenia Research, CNSR & Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre, Glostrup, University of Copenhagen , Denmark
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12
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Shah C, Zhang W, Xiao Y, Yao L, Zhao Y, Gao X, Liu L, Liu J, Li S, Tao B, Yan Z, Fu Y, Gong Q, Lui S. Common pattern of gray-matter abnormalities in drug-naive and medicated first-episode schizophrenia: a multimodal meta-analysis. Psychol Med 2017; 47:401-413. [PMID: 27776571 DOI: 10.1017/s0033291716002683] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Studies of schizophrenia at drug-naive state and on antipsychotic medication have reported a number of regions of gray-matter (GM) abnormalities but the reports have been inconsistent. The aim of this study was to conduct multimodal meta-analysis to compare the cross-sectional voxel-based morphometry studies of brain GM in antipsychotic-naive first-episode schizophrenia (AN-FES) and those with antipsychotic treatment within 1 year (AT-FES) to determine the similarities and differences in these groups. We conducted two separate meta-analyses containing 24 studies with a sample size of 801 patients and 957 healthy controls. A multimodal meta-analysis method was used to compare the findings between AN-FES and AT-FES. Meta-regression analyses were done to determine the influence of different variables including age, duration of illness, and positive and negative symptom scores. Finally, jack-knife analyses were done to test the robustness of the results. AN-FES and AT-FES showed common patterns of GM abnormalities in frontal (gyrus rectus), superior temporal, left hippocampal and insular cortex. GM in the left supramarginal gyrus and left middle temporal gyrus were found to be increased in AN-FES but decreased in AT-FES, whereas left median cingulate/paracingulate gyri and right hippocampus GM was decreased in AN-FES but increased in AT-FES. Findings suggest that both AN-FES and AT-FES share frontal, temporal and insular regions as common anatomical regions to be affected indicating these to be the primary regions of GM abnormalities in both groups.
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Affiliation(s)
- C Shah
- Radiology Department,The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University,Wenzhou,Zhejiang,China
| | - W Zhang
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - Y Xiao
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - L Yao
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - Y Zhao
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - X Gao
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - L Liu
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - J Liu
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - S Li
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - B Tao
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - Z Yan
- Radiology Department,The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University,Wenzhou,Zhejiang,China
| | - Y Fu
- Radiology Department,The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University,Wenzhou,Zhejiang,China
| | - Q Gong
- Department of Radiology,Huaxi MR Research Center (HMRRC), the Center for Medical Imaging, West China Hospital of Sichuan University,Chengdu,Sichuan,China
| | - S Lui
- Radiology Department,The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University,Wenzhou,Zhejiang,China
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13
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Jørgensen KN, Nesvåg R, Gunleiksrud S, Raballo A, Jönsson EG, Agartz I. First- and second-generation antipsychotic drug treatment and subcortical brain morphology in schizophrenia. Eur Arch Psychiatry Clin Neurosci 2016; 266:451-60. [PMID: 26547434 DOI: 10.1007/s00406-015-0650-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2015] [Accepted: 10/26/2015] [Indexed: 01/22/2023]
Abstract
Antipsychotic medication may influence brain structure, but to what extent effects of first-generation antipsychotics (FGAs) and second-generation antipsychotics (SGAs) differ is still not clear. Here we aimed to disentangle the effects of FGA and SGA on variation in volumes of subcortical structures in patients with long-term treated schizophrenia. Magnetic resonance images were obtained from 95 patients with schizophrenia and 106 healthy control subjects. Among the patients, 40 received only FGA and 42 received only SGA. FreeSurfer 5.3.0 was used to obtain volumes of 27 subcortical structures as well as total brain volume and estimated intracranial volume. Findings of reduced total brain volume, enlarged ventricular volume and reduced hippocampal volume bilaterally among patients were replicated, largely independent of medication class. In the basal ganglia, FGA users had larger putamen bilaterally and right caudate volume compared to healthy controls, and the right putamen was significantly larger than among SGA users. FGA and SGA users had similar and larger globus pallidus volumes compared to healthy controls. Post hoc analyses revealed that the difference between FGA and SGA could be attributed to smaller volumes in the clozapine users specifically. We therefore conclude that basal ganglia volume enlargements are not specific to FGA.
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Affiliation(s)
- Kjetil N Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, P.O. Box 85, 0319, Vinderen, Oslo, Norway. .,NORMENT and K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Ragnar Nesvåg
- Department of Psychiatric Research, Diakonhjemmet Hospital, P.O. Box 85, 0319, Vinderen, Oslo, Norway.,Department of Genetics, Environment and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Sindre Gunleiksrud
- Department of Psychiatric Research, Diakonhjemmet Hospital, P.O. Box 85, 0319, Vinderen, Oslo, Norway
| | - Andrea Raballo
- Department of Psychiatric Research, Diakonhjemmet Hospital, P.O. Box 85, 0319, Vinderen, Oslo, Norway.,NORMENT and K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Erik G Jönsson
- NORMENT and K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Clinical Neuroscience, HUBIN Project, Karolinska Institutet and Hospital, Stockholm, Sweden
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, P.O. Box 85, 0319, Vinderen, Oslo, Norway.,NORMENT and K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Clinical Neuroscience, HUBIN Project, Karolinska Institutet and Hospital, Stockholm, Sweden
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14
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Schmaal L, Veltman DJ, van Erp TGM, Sämann PG, Frodl T, Jahanshad N, Loehrer E, Tiemeier H, Hofman A, Niessen WJ, Vernooij MW, Ikram MA, Wittfeld K, Grabe HJ, Block A, Hegenscheid K, Völzke H, Hoehn D, Czisch M, Lagopoulos J, Hatton SN, Hickie IB, Goya-Maldonado R, Krämer B, Gruber O, Couvy-Duchesne B, Rentería ME, Strike LT, Mills NT, de Zubicaray GI, McMahon KL, Medland SE, Martin NG, Gillespie NA, Wright MJ, Hall GB, MacQueen GM, Frey EM, Carballedo A, van Velzen LS, van Tol MJ, van der Wee NJ, Veer IM, Walter H, Schnell K, Schramm E, Normann C, Schoepf D, Konrad C, Zurowski B, Nickson T, McIntosh AM, Papmeyer M, Whalley HC, Sussmann JE, Godlewska BR, Cowen PJ, Fischer FH, Rose M, Penninx BWJH, Thompson PM, Hibar DP. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Mol Psychiatry 2016; 21:806-12. [PMID: 26122586 PMCID: PMC4879183 DOI: 10.1038/mp.2015.69] [Citation(s) in RCA: 744] [Impact Index Per Article: 82.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2014] [Revised: 03/13/2015] [Accepted: 04/01/2015] [Indexed: 11/09/2022]
Abstract
The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen's d=-0.14, % difference=-1.24). This effect was driven by patients with recurrent MDD (Cohen's d=-0.17, % difference=-1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen's d=-0.20, % difference=-1.85) and a trend toward smaller amygdala (Cohen's d=-0.11, % difference=-1.23) and larger lateral ventricles (Cohen's d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.
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Affiliation(s)
- L Schmaal
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands,Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, P.O. Box 74077, Amsterdam 1070 BB, The Netherlands. E-mail:
| | - D J Veltman
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - T G M van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - P G Sämann
- Max Planck Institute of Psychiatry, Munich, Germany
| | - T Frodl
- Department of Psychiatry, University of Regensburg, Regensburg, Germany,Department of Psychiatry, University of Dublin, Trinity College, Dublin, Ireland
| | - N Jahanshad
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - E Loehrer
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Department of Psychiatry, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - W J Niessen
- Departments of Radiology and Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Imaging Science and Technology, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - M W Vernooij
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Departments of Radiology and Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Departments of Radiology and Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - K Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - H J Grabe
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany,Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany,Helios Hospital Stralsund, Stralsund, Germany
| | - A Block
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - K Hegenscheid
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - H Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - D Hoehn
- Max Planck Institute of Psychiatry, Munich, Germany
| | - M Czisch
- Max Planck Institute of Psychiatry, Munich, Germany
| | - J Lagopoulos
- Clinical Research Unit, Brain and Mind Research Institute, University of Sydney, Camperdown, Australia
| | - S N Hatton
- Clinical Research Unit, Brain and Mind Research Institute, University of Sydney, Camperdown, Australia
| | - I B Hickie
- Clinical Research Unit, Brain and Mind Research Institute, University of Sydney, Camperdown, Australia
| | - R Goya-Maldonado
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen, Germany
| | - B Krämer
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen, Germany
| | - O Gruber
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen, Germany
| | - B Couvy-Duchesne
- NeuroImaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,School of Psychology, University of Queensland, Brisbane, QLD, Australia,Center for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - M E Rentería
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - L T Strike
- NeuroImaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,School of Psychology, University of Queensland, Brisbane, QLD, Australia,Center for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - N T Mills
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - G I de Zubicaray
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
| | - K L McMahon
- Center for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - S E Medland
- Quantitative Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - N G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - N A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - M J Wright
- NeuroImaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - G B Hall
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - G M MacQueen
- Department of Psychiatry, Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - E M Frey
- Department of Psychiatry, University of Regensburg, Regensburg, Germany
| | - A Carballedo
- Department of Psychiatry and Institute of Neuroscience, University of Dublin, Trinity College Dublin, Dublin, Ireland
| | - L S van Velzen
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - M J van Tol
- University of Groningen, University Medical Center Groningen, NeuroImaging Center, Groningen, The Netherlands
| | - N J van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden University, Leiden, The Netherlands,Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - I M Veer
- Department of Psychiatry and Psychotherapy, Division of Mind and Brain Research, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - H Walter
- Department of Psychiatry and Psychotherapy, Division of Mind and Brain Research, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - K Schnell
- Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany
| | - E Schramm
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - C Normann
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - D Schoepf
- Department of Psychiatry, University of Bonn, Bonn, Germany
| | - C Konrad
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - B Zurowski
- Center for Integrative Psychiatry, University of Lübeck, Lübeck, Germany
| | - T Nickson
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - M Papmeyer
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - H C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - J E Sussmann
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - B R Godlewska
- University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - P J Cowen
- University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - F H Fischer
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin, Berlin, Germany,Institute for Social Medicine, Epidemology and Health Economics, Charité Universitätsmedizin, Berlin, Germany
| | - M Rose
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin, Berlin, Germany,Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - B W J H Penninx
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - P M Thompson
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - D P Hibar
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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15
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Tao H, Wong GHY, Zhang H, Zhou Y, Xue Z, Shan B, Chen EYH, Liu Z. Grey matter morphological anomalies in the caudate head in first-episode psychosis patients with delusions of reference. Psychiatry Res 2015; 233:57-63. [PMID: 26025014 DOI: 10.1016/j.pscychresns.2015.04.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2014] [Revised: 11/18/2014] [Accepted: 04/30/2015] [Indexed: 11/26/2022]
Abstract
Delusions of reference (DOR) are theoretically linked with aberrant salience and associative learning. Previous studies have shown that the caudate nucleus plays a critical role in the cognitive circuits of coding prediction errors and associative learning. The current study aimed at testing the hypothesis that abnormalities in the caudate nucleus may be involved in the neuroanatomical substrate of DOR. Structural magnetic resonance imaging of the brain was performed in 44 first-episode psychosis patients (with diagnoses of schizophrenia or schizophreniform disorder) and 25 healthy controls. Patients were divided into three groups according to symptoms: patients with DOR as prominent positive symptom; patients with prominent positive symptoms other than DOR; and patients with minimal positive symptoms. All groups were age-, gender-, and education-matched, and patient groups were matched for diagnosis, duration of illness, and antipsychotic treatment. Voxel-based morphometric analysis was performed to identify group differences in grey matter density. Relationships were explored between grey matter density and DOR. Patients with DOR were found to have reduced grey matter density in the caudate compared with patients without DOR and healthy controls. Grey matter density values of the left and right caudate head were negatively correlated with DOR severity. Decreased grey matter density in the caudate nucleus may underlie DOR in early psychosis.
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Affiliation(s)
- Haojuan Tao
- Mental Health Institute of The Second Xiangya Hospital, National Technology Institute of Psychiatry, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan, China.
| | - Gloria H Y Wong
- Department of Psychiatry, The University of Hong Kong, Hong Kong; Sau Po Centre on Ageing, The University of Hong Kong, Hong Kong.
| | - Huiran Zhang
- Mental Health Institute of The Second Xiangya Hospital, National Technology Institute of Psychiatry, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan, China
| | - Yuan Zhou
- Key Laboratory of Behavioural Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Zhimin Xue
- Mental Health Institute of The Second Xiangya Hospital, National Technology Institute of Psychiatry, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan, China
| | - Baoci Shan
- Key Laboratory of Nuclear Analysis Techniques, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Eric Y H Chen
- Department of Psychiatry, The University of Hong Kong, Hong Kong
| | - Zhening Liu
- Mental Health Institute of The Second Xiangya Hospital, National Technology Institute of Psychiatry, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan, China
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16
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Goodkind M, Eickhoff SB, Oathes DJ, Jiang Y, Chang A, Jones-Hagata LB, Ortega BN, Zaiko YV, Roach EL, Korgaonkar MS, Grieve SM, Galatzer-Levy I, Fox PT, Etkin A. Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry 2015; 72:305-15. [PMID: 25651064 PMCID: PMC4791058 DOI: 10.1001/jamapsychiatry.2014.2206] [Citation(s) in RCA: 932] [Impact Index Per Article: 93.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
IMPORTANCE Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness. OBJECTIVE To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret structural findings in the meta-analysis. DATA SOURCES PubMed was searched to identify voxel-based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta-analysis. The 3 parallel healthy participant data sets included resting-state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data. DATA EXTRACTION AND SYNTHESIS Studies were included in the meta-analysis if they reported voxel-based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses). The meta-analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach. MAIN OUTCOMES AND MEASURES We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow-up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta-analysis and the relationship of gray matter volume to cognition. RESULTS Based on the voxel-based morphometry meta-analysis of 193 studies comprising 15 892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety), we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis-specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow-up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning. CONCLUSIONS AND REVELANCE We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate-based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.
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Affiliation(s)
- Madeleine Goodkind
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Simon B. Eickhoff
- Institute for Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany4Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Desmond J. Oathes
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Ying Jiang
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Andrew Chang
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Laura B. Jones-Hagata
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Brissa N. Ortega
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Yevgeniya V. Zaiko
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Erika L. Roach
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
| | - Mayuresh S. Korgaonkar
- Brain Dynamics Centre, Westmead Millennium Institute and Sydney Medical School–Westmead, Sydney, Australia6Sydney Translational Imaging Laboratory, Sydney Medical School, University of Sydney, Sydney, Australia
| | - Stuart M. Grieve
- Brain Dynamics Centre, Westmead Millennium Institute and Sydney Medical School–Westmead, Sydney, Australia6Sydney Translational Imaging Laboratory, Sydney Medical School, University of Sydney, Sydney, Australia
| | | | - Peter T. Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio9South Texas Veterans Health Care System, San Antonio10School of Humanities, University of Hong Kong, Hong Kong, China11State Key Laboratory for Brain and Cognitive Scienc
| | - Amit Etkin
- Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, California2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford
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17
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Keedy SK, Reilly JL, Bishop JR, Weiden PJ, Sweeney JA. Impact of antipsychotic treatment on attention and motor learning systems in first-episode schizophrenia. Schizophr Bull 2015; 41:355-65. [PMID: 24894883 PMCID: PMC4332935 DOI: 10.1093/schbul/sbu071] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
BACKGROUND Antipsychotic medications have established clinical benefit, but there are few neuroimaging studies before and after initiating antipsychotic medication to assess drug influence on brain circuitry. Attention and motor learning tasks are promising approaches for examining treatment-related changes in frontostriatal systems. METHODS Twenty-one unmedicated first-episode schizophrenia patients (14 antipsychotic-naïve) participated in functional imaging studies while performing visual attention (prosaccades) and motor learning tasks (predictive saccades). Posttreatment testing was completed in 14 patients after 4-6 weeks of antipsychotic treatment. Matched healthy controls were studied in parallel. RESULTS Pretreatment, patients had reduced activation in the dorsal neocortical visual attention network. Activation deficits were significantly reduced posttreatment. Higher medication dose was associated with greater caudate activation at follow-up. For the motor learning task, patients' dorsolateral prefrontal cortex (DLPFC) was unimpaired prior to treatment but showed significantly reduced activation after treatment. CONCLUSION Impairments in dorsal cortical attention networks are present in untreated first-episode schizophrenia patients. These impairments are reduced after antipsychotic treatment, suggesting a beneficial effect on neural systems for attention. Treatment-emergent decreases in DLPFC activation observed for the motor learning task are consistent with other clinical and preclinical evidence suggesting that antipsychotics can have adverse effects on prefrontal function.
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Affiliation(s)
- Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL;
| | - James L Reilly
- Department of Psychiatry, Northwestern University, Chicago, IL
| | - Jeffrey R Bishop
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, IL
| | - Peter J Weiden
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL
| | - John A Sweeney
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
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18
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Chakravarty MM, Rapoport JL, Giedd JN, Raznahan A, Shaw P, Collins DL, Lerch JP, Gogtay N. Striatal shape abnormalities as novel neurodevelopmental endophenotypes in schizophrenia: a longitudinal study. Hum Brain Mapp 2014; 36:1458-69. [PMID: 25504933 DOI: 10.1002/hbm.22715] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Revised: 11/15/2014] [Accepted: 11/30/2014] [Indexed: 01/04/2023] Open
Abstract
There are varying, often conflicting, reports with respect to altered striatal volume and morphometry in the major psychoses due to the influences of antipsychotic medications on striatal volume. Thus, disassociating disease effects from those of medication become exceedingly difficult. For the first time, using a longitudinally studied sample of structural magnetic resonance images from patients with childhood onset schizophrenia (COS; neurobiologically contiguous with the adult onset form of schizophrenia), their nonpsychotic siblings (COSSIBs), and novel shape mapping algorithms that are volume independent, we report the familial contribution of striatal morphology in schizophrenia. The results of our volumetric analyses demonstrate age-related increases in overall striatal volumes specific only to COS. However, both COS and COSSIBs showed overlapping shape differences in the striatal head, which normalized in COSSIBs by late adolescence. These results mirror previous studies from our group, demonstrating cortical thickness deficits in COS and COSSIBs as these deficits normalize in COSSIBs in the same age range as our striatal findings. Finally, there is a single region of nonoverlapping outward displacement in the dorsal aspect of the caudate body, potentially indicative of a response to medication. Striatal shape may be considered complimentary to volume as an endophenotype, and, in some cases may provide information that is not detectable using standard volumetric techniques. Our striatal shape findings demonstrate the striking localization of abnormalities in striatal the head. The neuroanatomical localization of these findings suggest the presence of abnormalities in the striatal-prefrontal circuits in schizophrenia and resilience mechanisms in COSSIBs with age dependent normalization.
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Affiliation(s)
- M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; Department of Psychiatry, McGill University, Montreal, Canada; Department of Biomedical Engineering, McGill University, Montreal, Canada
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19
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Zhuo C, Zhu J, Qin W, Qu H, Ma X, Tian H, Xu Q, Yu C. Functional connectivity density alterations in schizophrenia. Front Behav Neurosci 2014; 8:404. [PMID: 25477799 PMCID: PMC4237131 DOI: 10.3389/fnbeh.2014.00404] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Accepted: 11/05/2014] [Indexed: 11/30/2022] Open
Abstract
Background: Schizophrenia is characterized by altered resting-state functional connectivity. Most previous studies have focused on changes in connectivity strengths; however, the alterations in connectivity density in schizophrenia remain largely unknown. Here, we aimed to investigate changes in resting-state functional connectivity density (rsFCD) in schizophrenia. Methods: A total of 95 schizophrenia patients and 93 sex- and age-matched healthy controls (HCs) underwent resting-state functional MRI examinations. The rsFCD, which reflects the total number of functional connections between a given brain voxel and all other voxels in the entire brain, was calculated for each voxel of each subject. Voxel-based comparisons were performed to identify brain regions with significant rsFCD differences between patients and controls (P < 0.05, corrected). Results: Compared with HCs, patients with schizophrenia showed significantly increased rsFCD in the bilateral striatum and hippocampus and significantly decreased rsFCD in the bilateral sensorimotor cortices and right occipital cortex. However, the rsFCD values of these brain regions were not correlated with antipsychotic dosage, illness duration, or clinical symptom severity. Conclusions: The striatal and hippocampal regions and parietal-occipital regions exhibited completely different changes in rsFCD in schizophrenia, which roughly correspond to dopamine activity in these regions in schizophrenia. These findings support the connectivity disorder hypothesis of schizophrenia and increase our understanding of the neural mechanisms of schizophrenia.
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Affiliation(s)
- Chuanjun Zhuo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital Tianjin, China ; Functional Neuroimaging Laboratory, Department of Psychiatry, Tianjin Mental Health Center, Tianjin Anding Hospital Tianjin, China ; Tianjin Anning Hospital Tianjin, China
| | - Jiajia Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital Tianjin, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital Tianjin, China
| | - Hongru Qu
- Tianjin Anning Hospital Tianjin, China
| | | | - Hongjun Tian
- Functional Neuroimaging Laboratory, Department of Psychiatry, Tianjin Mental Health Center, Tianjin Anding Hospital Tianjin, China
| | | | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital Tianjin, China
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20
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Huo M, Heyvaert M, Van den Noortgate W, Onghena P. Permutation Tests in the Educational and Behavioral Sciences. METHODOLOGY-EUROPEAN JOURNAL OF RESEARCH METHODS FOR THE BEHAVIORAL AND SOCIAL SCIENCES 2014. [DOI: 10.1027/1614-2241/a000067] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Over the past two decades, permutation tests (PTs) have received much attention in the educational and behavioral sciences. The aim of this article is to review the theoretical developments of PTs, the active areas in the educational and behavioral research using PTs, and the types of analysis under which PTs have been applied. We obtained 224 published articles, which included 141 theoretical articles and 83 application articles. After scrutinizing each article, we are happy to see that (1) some researchers began to advocate introducing PTs into basic statistics training; (2) computing load for PTs may be reduced dramatically by some intelligent algorithms; (3) PTs began to be applied in new areas such as studies on the relationship between brain and behavior and the relationship between gene and behavior; (4) besides simple types of analysis such as independent two-group comparison, PTs can also be carried out under more complex situations such as multivariate analysis. However, we should also notice that PTs are still mostly used for simple analyses (e.g., randomness analysis).
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Affiliation(s)
- Ming Huo
- Faculty of Psychology and Educational Sciences, Methodology of Educational Science Research Group, Katholieke Universiteit Leuven, Belgium
| | - Mieke Heyvaert
- Faculty of Psychology and Educational Sciences, Methodology of Educational Science Research Group, Katholieke Universiteit Leuven, Belgium
| | - Wim Van den Noortgate
- Faculty of Psychology and Educational Sciences, Methodology of Educational Science Research Group, Katholieke Universiteit Leuven, Belgium
| | - Patrick Onghena
- Faculty of Psychology and Educational Sciences, Methodology of Educational Science Research Group, Katholieke Universiteit Leuven, Belgium
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21
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Hutcheson NL, Clark DG, Bolding MS, White DM, Lahti AC. Basal ganglia volume in unmedicated patients with schizophrenia is associated with treatment response to antipsychotic medication. Psychiatry Res 2014; 221:6-12. [PMID: 24210948 PMCID: PMC3947916 DOI: 10.1016/j.pscychresns.2013.10.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2013] [Revised: 07/31/2013] [Accepted: 10/16/2013] [Indexed: 02/08/2023]
Abstract
We investigated the relationship between basal ganglia volume and treatment response to the atypical antipsychotic medication risperidone in unmedicated patients with schizophrenia. Basal ganglia volumes included the bilateral caudate, putamen, and pallidum and were measured using the Freesurfer automated segmentation pipeline in 23 subjects. Also, baseline symptom severity, duration of illness, age, gender, time off medication, and exposure to previous antipsychotic were measured. Treatment response was significantly correlated with all three regions of the bilateral basal ganglia (caudate, putamen, and pallidum), baseline symptom severity, duration of illness, and age but not gender, time off antipsychotic medication, or exposure to previous antipsychotic medication. The caudate volume was the basal ganglia region that demonstrated the strongest correlation with treatment response and was significantly negatively correlated with patient age. Caudate volume was not significantly correlated with any other measure. We demonstrated a novel finding that the caudate volume explains a significant amount of the variance in treatment response over the course of 6 weeks of risperidone pharmacotherapy even when controlling for baseline symptom severity and duration of illness.
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Affiliation(s)
- Nathan L. Hutcheson
- Department of Graduate Biomedical Sciences, Neuroscience, University of Alabama at Birmingham, Birmingham, AL, USA,Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - David G. Clark
- Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL
| | - Mark S. Bolding
- Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL,Department of Vision Sciences, The University of Alabama at Birmingham, Birmingham, AL. USA
| | - David M. White
- Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Adrienne C. Lahti
- Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, Birmingham, AL, USA,Corresponding author. Tel.: +1 205 996 6776; fax: +1 205 975 4879.
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22
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Ebdrup BH, Nørbak H, Borgwardt S, Glenthøj B. Volumetric changes in the basal ganglia after antipsychotic monotherapy: a systematic review. Curr Med Chem 2014; 20:438-47. [PMID: 23157636 PMCID: PMC3715891 DOI: 10.2174/0929867311320030015] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2012] [Revised: 09/09/2012] [Accepted: 09/26/2012] [Indexed: 11/22/2022]
Abstract
Introduction: Exposure to antipsychotic medication has been extensively associated with structural brain changes in the basal ganglia (BG). Traditionally antipsychotics have been divided into first and second generation antipsychotics (FGAs and SGAs) however, the validity of this classification has become increasingly controversial. To address if specific antipsychotics induce differential effects on BG volumes or whether volumetric effects are explained by FGA or SGA classification, we reviewed longitudinal structural magnetic resonance imaging (MRI) studies investigating effects of antipsychotic monotherapy. Material and Methods: We systematically searched PubMed for longitudinal MRI studies of patients with schizophrenia or non-affective psychosis who had undergone a period of antipsychotic monotherapy. We used specific, predefined search terms and extracted studies were hand searched for additional studies. Results: We identified 13 studies published in the period from 1996 to 2011. Overall six compounds (two classified as FGAs and four as SGAs) have been investigated: haloperidol, zuclophentixol, risperidone, olanzapine, clozapine, and quetiapine. The follow-up period ranged from 3-24 months. Unexpectedly, no studies found that specific FGAs induce significant BG volume increases. Conversely, both volumetric increases and decreases in the BG have been associated with SGA monotherapy. Discussion: Induction of striatal volume increases is not a specific feature of FGAs. Except for clozapine treatment in chronic patients, volume reductions are not restricted to specific SGAs. The current review adds brain structural support to the notion that antipsychotics should no longer be classified as either FGAs or SGAs. Future clinical MRI studies should strive to elucidate effects of specific antipsychotic drugs.
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Affiliation(s)
- B H Ebdrup
- Center for Neuropsychiatric Schizophrenia Research, CNSR & Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Psychiatric Center Glostrup, University Hospital DK-Glostrup, Denmark.
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Torres US, Portela-Oliveira E, Borgwardt S, Busatto GF. Structural brain changes associated with antipsychotic treatment in schizophrenia as revealed by voxel-based morphometric MRI: an activation likelihood estimation meta-analysis. BMC Psychiatry 2013; 13:342. [PMID: 24359128 PMCID: PMC3878502 DOI: 10.1186/1471-244x-13-342] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2013] [Accepted: 12/09/2013] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND The results of multiple studies on the association between antipsychotic use and structural brain changes in schizophrenia have been assessed only in qualitative literature reviews to date. We aimed to perform a meta-analysis of voxel-based morphometry (VBM) studies on this association to quantitatively synthesize the findings of these studies. METHODS A systematic computerized literature search was carried out through MEDLINE/PubMed, EMBASE, ISI Web of Science, SCOPUS and PsycINFO databases aiming to identify all VBM studies addressing this question and meeting predetermined inclusion criteria. All studies reporting coordinates representing foci of structural brain changes associated with antipsychotic use were meta-analyzed by using the activation likelihood estimation technique, currently the most sophisticated and best-validated tool for voxel-wise meta-analysis of neuroimaging studies. RESULTS Ten studies (five cross-sectional and five longitudinal) met the inclusion criteria and comprised a total of 548 individuals (298 patients on antipsychotic drugs and 250 controls). Depending on the methodologies of the selected studies, the control groups included healthy subjects, drug-free patients, or the same patients evaluated repeatedly in longitudinal comparisons (i.e., serving as their own controls). A total of 102 foci associated with structural alterations were retrieved. The meta-analysis revealed seven clusters of areas with consistent structural brain changes in patients on antipsychotics compared to controls. The seven clusters included four areas of relative volumetric decrease in the left lateral temporal cortex [Brodmann area (BA) 20], left inferior frontal gyrus (BA 44), superior frontal gyrus extending to the left middle frontal gyrus (BA 6), and right rectal gyrus (BA 11), and three areas of relative volumetric increase in the left dorsal anterior cingulate cortex (BA 24), left ventral anterior cingulate cortex (BA 24) and right putamen. CONCLUSIONS Our results identify the specific brain regions where possible associations between antipsychotic drug usage and structural brain changes in schizophrenia patients are more consistently reported. Additional longitudinal VBM studies including larger and more homogeneous samples of schizophrenia patients may be needed to further disentangle such alterations from those possibly linked to the intrinsic pathological progressive process in schizophrenia.
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Affiliation(s)
- Ulysses S Torres
- Post-Graduate Program in Radiology, Institute of Radiology (INRAD), University of Sao Paulo Medical School, Sao Paulo, Brazil.
| | - Eduardo Portela-Oliveira
- Department of Radiology, Hospital de Base, São José do Rio Preto Medical School, Sao Paulo, Brazil
| | - Stefan Borgwardt
- Department of Psychiatry, University of Basel, Basel, Switzerland,Department of Psychosis Studies, Institute of Psychiatry, King’s College, London, UK
| | - Geraldo F Busatto
- Post-Graduate Program in Radiology, Institute of Radiology (INRAD), University of Sao Paulo Medical School, Sao Paulo, Brazil,Laboratory of Neuroimaging in Psychiatry (LIM-21), Institute of Psychiatry, University of Sao Paulo Medical School, Centro de Medicina Nuclear, 3º andar, Rua Dr. Ovídio Pires Campos, s/n, Sao Paulo, Sao Paulo, 05403-010, Brazil,Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Sao Paulo, Brazil
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Malchow B, Hasan A, Schneider-Axmann T, Jatzko A, Gruber O, Schmitt A, Falkai P, Wobrock T. Effects of cannabis and familial loading on subcortical brain volumes in first-episode schizophrenia. Eur Arch Psychiatry Clin Neurosci 2013; 263 Suppl 2:S155-68. [PMID: 24085610 DOI: 10.1007/s00406-013-0451-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2013] [Accepted: 09/16/2013] [Indexed: 02/06/2023]
Abstract
Schizophrenia is a severe neuropsychiatric disorder with familial loading as heritable risk factor and cannabis abuse as the most relevant environmental risk factor up to date. Cannabis abuse has been related to an earlier onset of the disease and persisting cannabis consumption is associated with reduced symptom improvement. However, the underlying morphological and biochemical brain alterations due to these risk factors as well as the effects of gene-environmental interaction are still unclear. In this magnetic resonance imaging (MRI) study in 47 first-episode schizophrenia patients and 30 healthy control subjects, we investigated effects of previous cannabis abuse and increased familial risk on subcortical brain regions such as hippocampus, amygdala, caudate nucleus, putamen, thalamus and subsegments of the corpus callosum (CC). In a subsequent single-volume (1)H-magnetic resonance spectroscopy study, we investigated spectra in the left hippocampus and putamen to detect metabolic alterations. Compared to healthy controls, schizophrenia patients displayed decreased volumes of the left hippocampus, bilateral amygdala and caudate nucleus as well as an increased area of the midsagittal CC1 segment of the corpus callosum. Patients fulfilling the criteria for cannabis abuse at admission showed an increased area of the CC2 segment compared to those who did not fulfill the criteria. Patients with a family history of schizophrenia combined with previous cannabis abuse showed lower volumes of the bilateral caudate nucleus compared to all other patients, implicating an interaction between the genetic background and cannabis abuse as environmental factor. Patients with cannabis abuse also had higher ratios of N-acetyl aspartate/choline in the left putamen, suggesting a possible neuroprotective effect in this area. However, antipsychotic medication prior to MRI acquisition and gender effects may have influenced our results. Future longitudinal studies in first-episode patients with quantification of cannabis abuse and assessment of schizophrenia risk genes are warranted.
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Affiliation(s)
- Berend Malchow
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University (LMU) Munich, Nußbaumstraße 7, 80336, Munich, Germany,
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Wang Q, Cheung C, Deng W, Li M, Huang C, Ma X, Wang Y, Jiang L, Sham PC, Collier DA, Gong Q, Chua SE, McAlonan GM, Li T. White-matter microstructure in previously drug-naive patients with schizophrenia after 6 weeks of treatment. Psychol Med 2013; 43:2301-2309. [PMID: 23442742 DOI: 10.1017/s0033291713000238] [Citation(s) in RCA: 76] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND It is not clear whether the progressive changes in brain microstructural deficits documented in previous longitudinal magnetic resonance imaging (MRI) studies might be due to the disease process or to other factors such as medication. It is important to explore the longitudinal alterations in white-matter (WM) microstructure in antipsychotic-naive patients with first-episode schizophrenia during the very early phase of treatment when relatively 'free' from chronicity. METHOD Thirty-five patients with first-episode schizophrenia and 22 healthy volunteers were recruited. High-resolution diffusion tensor imaging (DTI) was obtained from participants at baseline and after 6 weeks of treatment. A 'difference map' for each individual was calculated from the 6-week follow-up fractional anisotropy (FA) of DTI minus the baseline FA. Differences in Positive and Negative Syndrome Scale (PANSS) scores and Global Assessment of Functioning (GAF) scores between baseline and 6 weeks were also evaluated and expressed as a 6-week/baseline ratio. RESULTS Compared to healthy controls, there was a significant decrease in absolute FA of WM around the bilateral anterior cingulate gyrus and the right anterior corona radiata of the frontal lobe in first-episode drug-naive patients with schizophrenia following 6 weeks of treatment. Clinical symptoms improved during this period but the change in FA did not correlate with the changes in clinical symptoms or the dose of antipsychotic medication. CONCLUSIONS During the early phase of treatment, there is an acute reduction in WM FA that may be due to the effects of antipsychotic medications. However, it is not possible to entirely exclude the effects of underlying progression of illness.
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Affiliation(s)
- Q Wang
- Mental Health Centre and Psychiatric Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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26
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Fervaha G, Remington G. Neuroimaging findings in schizotypal personality disorder: a systematic review. Prog Neuropsychopharmacol Biol Psychiatry 2013; 43:96-107. [PMID: 23220094 DOI: 10.1016/j.pnpbp.2012.11.014] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2012] [Revised: 11/10/2012] [Accepted: 11/28/2012] [Indexed: 11/30/2022]
Abstract
BACKGROUND Schizotypal personality disorder is the prototypical schizophrenia-spectrum condition, sharing similar phenomenological, cognitive, genetic, physiological, neurochemical, neuroanatomical and neurofunctional abnormalities with schizophrenia. Investigations into SPD circumvent many confounds inherent to schizophrenia such as medication and institutionalization. Hence, SPD offers a unique vantage point from which to study schizophrenia-spectrum conditions. METHODS We systematically reviewed the neuroimaging literature in SPD to establish: (1) whether there are concordant findings in SPD and schizophrenia, possibly reflective of core pathology between the two conditions and (2) whether there are discordant findings in SPD and schizophrenia, possibly reflecting protective factors in the former. The findings are synthesized across structural and functional neuroimaging domains. RESULTS A total of 54 studies were identified. Medial temporal lobe structures seem to be compromised in both SPD and schizophrenia. In schizophrenia prefrontal structures are further compromised, whereas in SPD these seem to be larger-than-normal, possibly reflecting a compensatory mechanism. Additional pathology is discussed, including evidence of aberrant subcortical dopaminergic functioning. CONCLUSIONS SPD is a schizophrenia-spectrum condition that shares pathology with schizophrenia, but is distinct in showing unique neural findings. Future studies are needed to confirm and localize regions of common and disparate pathology between SPD and schizophrenia.
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Affiliation(s)
- Gagan Fervaha
- Schizophrenia Program, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada.
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Yang Y, Nuechterlein KH, Phillips OR, Gutman B, Kurth F, Dinov I, Thompson PM, Asarnow RF, Toga AW, Narr KL. Disease and genetic contributions toward local tissue volume disturbances in schizophrenia: a tensor-based morphometry study. Hum Brain Mapp 2012; 33:2081-91. [PMID: 22241649 DOI: 10.1002/hbm.21349] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Structural brain deficits, especially frontotemporal volume reduction and ventricular enlargement, have been repeatedly reported in patients with schizophrenia. However, it remains unclear whether brain structural deformations may be attributable to disease-related or genetic factors. In this study, the structural magnetic resonance imaging data of 48 adult-onset schizophrenia patients, 65 first-degree nonpsychotic relatives of schizophrenia patients, 27 community comparison (CC) probands, and 73 CC relatives were examined using tensor-based morphometry (TBM) to isolate global and localized differences in tissue volume across the entire brain between groups. We found brain tissue contractions most prominently in frontal and temporal regions and expansions in the putamen/pallidum, and lateral and third ventricles in schizophrenia patients when compared with unrelated CC probands. Results were similar, though less prominent when patients were compared with their nonpsychotic relatives. Structural deformations observed in unaffected patient relatives compared to age-similar CC relatives were suggestive of schizophrenia-related genetic liability and were pronounced in the putamen/pallidum and medial temporal regions. Schizophrenia and genetic liability effects for the putamen/pallidum were confirmed by regions-of-interest analysis. In conclusion, TBM findings complement reports of frontal, temporal, and ventricular dysmorphology in schizophrenia and further indicate that putamen/pallidum enlargements, originally linked mainly with medication exposure in early studies, also reflect a genetic predisposition for schizophrenia. Thus, brain deformation profiles revealed in this study may help to clarify the role of specific genetic or environmental risk factors toward altered brain morphology in schizophrenia.
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Affiliation(s)
- Yaling Yang
- Laboratory of Neuro Imaging, Geffen School of Medicine at UCLA, Los Angeles, CA 90024, USA.
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Narayanaswamy JC, Venkatasubramanian G, Gangadhar BN. Neuroimaging studies in schizophrenia: an overview of research from Asia. Int Rev Psychiatry 2012; 24:405-16. [PMID: 23057977 DOI: 10.3109/09540261.2012.704872] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Neuroimaging studies in schizophrenia help clarify the neural substrates underlying the pathogenesis of this neuropsychiatric disorder. Contemporary brain imaging in schizophrenia is predominated by magnetic resonance imaging (MRI)-based research approaches. This review focuses on the various imaging studies from India and their relevance to the understanding of brain abnormalities in schizophrenia. The existing studies are predominantly comprised of structural MRI reports involving region-of-interest and voxel-based morphometry approaches, magnetic resonance spectroscopy and single-photon emission computed tomography/positron emission tomography (SPECT/PET) studies. Most of these studies are significant in that they have evaluated antipsychotic-naïve schizophrenia patients--a relatively difficult population to obtain in contemporary research. Findings of these studies offer robust support to the existence of significant brain abnormalities at very early stages of the disorder. In addition, theoretically relevant relationships between these brain abnormalities and developmental aberrations suggest possible neurodevelopmental basis for these brain deficits.
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Affiliation(s)
- Janardhanan C Narayanaswamy
- Schizophrenia Clinic, Department of Psychiatry, Translational Psychiatry Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neurosciences, Bangalore, India
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29
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Li M, Chen Z, Deng W, He Z, Wang Q, Jiang L, Ma X, Wang Y, Chua SE, Cheung C, McAlonan GM, Sham PC, Collier DA, Gong Q, Li T. Volume increases in putamen associated with positive symptom reduction in previously drug-naive schizophrenia after 6 weeks antipsychotic treatment. Psychol Med 2012; 42:1475-1483. [PMID: 22030695 DOI: 10.1017/s0033291711002157] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
BACKGROUND Brain structure appears to alter after antipsychotic administration, but it is unknown whether these alterations are associated with improvement of psychopathology in patients with schizophrenia. In this study, the authors explore this relationship. METHOD Altogether, 66 first-episode, drug-naive patients with schizophrenia and 23 well-matched healthy controls underwent brain magnetic resonance imaging scans at baseline. All 23 healthy controls and 42 of the patients were rescanned after 6 weeks follow-up. The patients received regular antipsychotic treatment during the 6-week period and their psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS) at baseline and 6 weeks. The difference in PANSS scores between baseline and 6 weeks was expressed as a ratio of the scores at baseline - 'PANSS reduction ratio'. A modified tensor-based morphometry procedure was applied to analyse longitudinal images. Correlations between regional volume changes, PANSS reduction ratio and antipsychotic drug dosages were explored. RESULTS Compared with healthy controls, there was a significant increase in grey-matter volume of the right putamen in patients after 6 weeks treatment. This volume change was positively correlated with a positive PANSS reduction score but not related to drug dosages. CONCLUSIONS Putaminal volume increased after 6 weeks antipsychotic treatment in first-episode schizophrenia. The increased volume was closely correlated with improved psychopathology, suggesting the putamen might be a biomarker to predict the treatment response in schizophrenia.
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Affiliation(s)
- M Li
- The Mental Health Center & Psychiatric Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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30
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Szeszko PR, Narr KL, Phillips OR, McCormack J, Sevy S, Gunduz-Bruce H, Kane JM, Bilder RM, Robinson DG. Magnetic resonance imaging predictors of treatment response in first-episode schizophrenia. Schizophr Bull 2012; 38:569-78. [PMID: 21084552 PMCID: PMC3329996 DOI: 10.1093/schbul/sbq126] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Identifying neurobiological predictors of response to antipsychotics in patients with schizophrenia is a critical goal of translational psychiatry. Few studies, however, have investigated the relationship between indices of brain structure and treatment response in the context of a controlled clinical trial. In this study, we sought to identify magnetic resonance (MR) imaging measures of the brain that predict treatment response in patients experiencing a first-episode of schizophrenia. Structural MR imaging scans were acquired in 39 patients experiencing a first-episode of schizophrenia with minimal or no prior exposure to antipsychotics participating in a double-blind 16-week clinical trial comparing the efficacy of risperidone vs olanzapine. Twenty-five patients were classified as responders by meeting operationally defined treatment response criteria on 2 consecutive study visits. Fourteen patients never responded to antipsychotic medication at any point during the clinical trial. MR imaging scans were also acquired in 45 age- and sex-matched healthy volunteers. Cortical pattern matching methods were used to compare cortical thickness and asymmetry measures among groups. Statistical mapping results, confirmed by permutation testing, indicated that responders had greater cortical thickness in occipital regions and greater frontal cortical asymmetry compared with nonresponders. Moreover, among responders, greater thickness in temporal regions was associated with less time to respond. Our findings are consistent with the hypothesis that plasticity and cortical thickness may be more preserved in responders and that MR imaging may assist in the prediction of antipsychotic drug response in patients experiencing a first-episode of schizophrenia.
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Affiliation(s)
- Philip R. Szeszko
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY,Division of Psychiatry Research, Zucker Hillside Hospital, North Shore-LIJ Health System, Glen Oaks, NY,Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY,To whom correspondence should be addressed; Division of Psychiatry Research, Zucker Hillside Hospital, 75-59 263rd Street, Glen Oaks, NY 11004, USA; tel: 718-470-8489, fax: 718-343-1659, e-mail:
| | - Katherine L. Narr
- Laboratory of Neuroimaging, Department of Neurology, David Geffen School of Medicine at Los Angeles, CA
| | - Owen R. Phillips
- Laboratory of Neuroimaging, Department of Neurology, David Geffen School of Medicine at Los Angeles, CA
| | - Joanne McCormack
- Division of Psychiatry Research, Zucker Hillside Hospital, North Shore-LIJ Health System, Glen Oaks, NY
| | - Serge Sevy
- Division of Psychiatry Research, Zucker Hillside Hospital, North Shore-LIJ Health System, Glen Oaks, NY,Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY
| | | | - John M. Kane
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY,Division of Psychiatry Research, Zucker Hillside Hospital, North Shore-LIJ Health System, Glen Oaks, NY,Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY
| | - Robert M. Bilder
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, and Department of Psychology, College of Letters & Science, and Jane and Terry Semel Institute for Neuroscience and Human Behavior at University of California at Los Angeles, Los Angeles, CA
| | - Delbert G. Robinson
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY,Division of Psychiatry Research, Zucker Hillside Hospital, North Shore-LIJ Health System, Glen Oaks, NY,Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY
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Is there an anatomical endophenotype for neurodevelopmental disorders? A review of dual disorder anatomical likelihood estimation (ALE) meta-analyses of grey matter volumes. CHINESE SCIENCE BULLETIN-CHINESE 2011. [DOI: 10.1007/s11434-011-4743-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Waters-Metenier S, Toulopoulou T. Putative structural neuroimaging endophenotypes in schizophrenia: a comprehensive review of the current evidence. FUTURE NEUROLOGY 2011. [DOI: 10.2217/fnl.11.35] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The genetic contribution to schizophrenia etiopathogenesis is underscored by the fact that the best predictor of developing schizophrenia is having an affected first-degree relative, which increases lifetime risk by tenfold, as well as the observation that when both parents are affected, the risk of schizophrenia increases to approximately 50%, compared with 1% in the general population. The search to elucidate the complex genetic architecture of schizophrenia has employed various approaches, including twin and family studies to examine co-aggregation of brain abnormalities, studies on genetic linkage and studies using genome-wide association to identify genetic variations associated with schizophrenia. ‘Endophenotypes’, or ‘intermediate phenotypes’, are potentially narrower constructs of genetic risk. Hypothetically, they are intermediate in the pathway between genetic variation and clinical phenotypes and can supposedly be implemented to assist in the identification of genetic diathesis for schizophrenia and, possibly, in redefining clinical phenomenology.
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Affiliation(s)
- Sheena Waters-Metenier
- Department of Psychosis Studies, King’s College London, King’s Health Partners, Institute of Psychiatry, London, UK
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Cheung V, Chiu CPY, Law CW, Cheung C, Hui CLM, Chan KKS, Sham PC, Deng MY, Tai KS, Khong PL, McAlonan GM, Chua SE, Chen E. Positive symptoms and white matter microstructure in never-medicated first episode schizophrenia. Psychol Med 2011; 41:1709-1719. [PMID: 20809999 DOI: 10.1017/s003329171000156x] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND We investigated cerebral structural connectivity and its relationship to symptoms in never-medicated individuals with first-onset schizophrenia using diffusion tensor imaging (DTI). METHOD We recruited subjects with first episode DSM-IV schizophrenia who had never been exposed to antipsychotic medication (n=34) and age-matched healthy volunteers (n=32). All subjects received DTI and structural magnetic resonance imaging scans. Patients' symptoms were assessed on the Positive and Negative Syndrome Scale. Voxel-based analysis was performed to investigate brain regions where fractional anisotropy (FA) values significantly correlated with symptom scores. RESULTS In patients with first-episode schizophrenia, positive symptoms correlated positively with FA scores in white matter associated with the right frontal lobe, left anterior cingulate gyrus, left superior temporal gyrus, right middle temporal gyrus, right middle cingulate gyrus, and left cuneus. Importantly, FA in each of these regions was lower in patients than controls, but patients with more positive symptoms had FA values closer to controls. We found no significant correlations between FA and negative symptoms. CONCLUSIONS The newly-diagnosed, neuroleptic-naive patients had lower FA scores in the brain compared with controls. There was positive correlation between FA scores and positive symptoms scores in frontotemporal tracts, including left fronto-occipital fasciculus and left inferior longitudinal fasciculus. This implies that white matter dysintegrity is already present in the pre-treatment phase and that FA is likely to decrease after clinical treatment or symptom remission.
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Affiliation(s)
- V Cheung
- Department of Psychiatry, University of Hong Kong, Pokfulam, SAR China
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Vernon AC, Natesan S, Modo M, Kapur S. Effect of chronic antipsychotic treatment on brain structure: a serial magnetic resonance imaging study with ex vivo and postmortem confirmation. Biol Psychiatry 2011; 69:936-44. [PMID: 21195390 DOI: 10.1016/j.biopsych.2010.11.010] [Citation(s) in RCA: 119] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2010] [Revised: 11/03/2010] [Accepted: 11/03/2010] [Indexed: 11/26/2022]
Abstract
BACKGROUND There is increasing evidence that antipsychotic (APD) may affect brain structure directly. To examine this, we developed a rodent model that uses clinically relevant doses and serial magnetic resonance imaging (MRI), followed by postmortem histopathological analysis to study the effects of APD on brain structures. METHODS Antipsychotic , haloperidol, and olanzapine were continuously administered to rats via osmotic minipumps to maintain clinic-like steady state levels for 8 weeks. Longitudinal in vivo MRI scanning (T₂-weighted) was carried out at baseline, 4 weeks, and 8 weeks, after which animals were perfused and their brains preserved for ex vivo MRI scanning. Region of interest analyses were performed on magnetic resonance images (both in vivo as well as ex vivo) along with postmortem stereology using the Cavalieri estimator probe. RESULTS Chronic (8 weeks) exposure to both haloperidol and olanzapine resulted in significant decreases in whole-brain volume (6% to 8%) compared with vehicle-treated control subjects, driven mainly by a decrease in frontal cerebral cortex volume (8% to 12%). Hippocampal, corpus striatum, lateral ventricles, and corpus callosum volumes were not significantly different from control subjects, suggesting a differential effect of APD on the cortex. These results were corroborated by ex vivo MRI scans and decreased cortical volume was confirmed postmortem by stereology. CONCLUSIONS This is the first systematic whole-brain MRI study of the effects of APD, which highlights significant effects on the cortex. Although caution needs to be exerted when extrapolating results from animals to patients, the approach provides a tractable method for linking in vivo MRI findings to their histopathological origins.
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Affiliation(s)
- Anthony C Vernon
- Department of Psychosis Studies, Institute of Psychiatry, King's College London, London, United Kingdom
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35
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Brain volume changes after withdrawal of atypical antipsychotics in patients with first-episode schizophrenia. J Clin Psychopharmacol 2011; 31:146-53. [PMID: 21346618 DOI: 10.1097/jcp.0b013e31820e3f58] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
The influence of antipsychotic medication on brain morphology in schizophrenia may confound interpretation of brain changes over time. We aimed to assess the effect of discontinuation of atypical antipsychotic medication on change in brain volume in patients. Sixteen remitted, stable patients with first-episode schizophrenia, schizoaffective or schizophreniform disorder and 20 healthy controls were included. Two magnetic resonance imaging brain scans were obtained from all subjects with a 1-year interval. The patients either discontinued (n = 8) their atypical antipsychotic medication (olanzapine, risperidone, or quetiapine) or did not (n = 8) discontinue during the follow-up period. Intracranial volume and volumes of total brain, cerebral gray and white matter, cerebellum, third and lateral ventricle, nucleus caudatus, nucleus accumbens, and putamen were obtained. Multiple linear regression analyses were used to assess main effects for group (patient-control) and discontinuation (yes-no) for brain volume (change) while correcting for age, sex, and intracranial volume. Decrease in cerebral gray matter and caudate nucleus volume over time was significantly more pronounced in patients relative to controls. Our data suggest decreases in the nucleus accumbens and putamen volumes during the interval in patients who discontinued antipsychotic medication, whereas increases were found in patients who continued their antipsychotics. We confirmed earlier findings of excessive gray matter volume decrements in patients with schizophrenia compared with normal controls. We found evidence suggestive of decreasing volumes of the putamen and nucleus accumbens over time after discontinuation of medication. This might suggest that discontinuation reverses effects of atypical medication.
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Chan RCK, Di X, McAlonan GM, Gong QY. Brain anatomical abnormalities in high-risk individuals, first-episode, and chronic schizophrenia: an activation likelihood estimation meta-analysis of illness progression. Schizophr Bull 2011; 37:177-88. [PMID: 19633214 PMCID: PMC3004195 DOI: 10.1093/schbul/sbp073] [Citation(s) in RCA: 250] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
OBJECTIVE The present study reviewed voxel-based morphometry (VBM) studies on high-risk individuals with schizophrenia, patients experiencing their first-episode schizophrenia (FES), and those with chronic schizophrenia. We predicted that gray matter abnormalities would show progressive changes, with most extensive abnormalities in the chronic group relative to FES and least in the high-risk group. METHOD Forty-one VBM studies were reviewed. Eight high-risk studies, 14 FES studies, and 19 chronic studies were analyzed using anatomical likelihood estimation meta-analysis. RESULTS Less gray matter in the high-risk group relative to controls was observed in anterior cingulate regions, left amygdala, and right insula. Lower gray matter volumes in FES compared with controls were also found in the anterior cingulate and right insula but not the amygdala. Lower gray matter volumes in the chronic group were most extensive, incorporating similar regions to those found in FES and high-risk groups but extending to superior temporal gyri, thalamus, posterior cingulate, and parahippocampal gryus. Subtraction analysis revealed less frontotemporal, striatal, and cerebellar gray matter in FES than the high-risk group; the high-risk group had less gray matter in left subcallosal gyrus, left amygdala, and left inferior frontal gyrus compared with FES. Subtraction analysis confirmed lower gray matter volumes through ventral-dorsal anterior cingulate, right insula, left amygdala and thalamus in chronic schizophrenia relative to FES. CONCLUSIONS Frontotemporal brain structural abnormalities are evident in nonpsychotic individuals at high risk of developing schizophrenia. The present meta-analysis indicates that these gray matter abnormalities become more extensive through first-episode and chronic illness. Thus, schizophrenia appears to be a progressive cortico-striato-thalamic loop disorder.
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Affiliation(s)
- Raymond C. K. Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory,Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 4A Datun Road, Beijing 100101, China,Department of Psychiatry, University of Hong Kong, Hong Kong Special Administrative Region, China,To whom correspondence should be addressed;
| | - Xin Di
- Department of Psychology, Sun Yat-Sen University, Guangzhou, China
| | - Grainne M. McAlonan
- Department of Psychiatry, University of Hong Kong, Hong Kong Special Administrative Region, China,State key laboratory for Brain and Cognitive Sciences, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Qi-yong Gong
- Huaxi MR Research Centre, Department of Radiology, West China Hospital / West China School of Medicine, Sichuan University, Chengdu, China
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Spoletini I, Cherubini A, Banfi G, Rubino IA, Peran P, Caltagirone C, Spalletta G. Hippocampi, thalami, and accumbens microstructural damage in schizophrenia: a volumetry, diffusivity, and neuropsychological study. Schizophr Bull 2011; 37:118-30. [PMID: 19542526 PMCID: PMC3004185 DOI: 10.1093/schbul/sbp058] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Volumetric abnormalities in the subcortical structures have been described in schizophrenia. However, it still has to be clarified if subtle microstructural damage is also present. Thus, we aimed to detect subcortical volume and mean diffusivity (MD) alterations in 45 patients with diagnosis of schizophrenia compared with 45 age-, gender-, and educational attainment-matched healthy comparison (HC) participants, by using a combined volumetry and diffusion tensor imaging (DTI) method. A secondary aim was to identify the neuropsychological correlates of subcortical abnormalities in the schizophrenic group. We found thalami and hippocampi bilaterally and left accumbens to show MD increase in the schizophrenic group. No volumetric decrease was found. Moreover, significant correlations between the MD values in subcortical structures (right thalamus and hippocampus and left accumbens) and working memory performance were found. Thus, subcortical microstructural alterations are present in schizophrenia even in absence of volumetric abnormalities. Furthermore, microstructural damage in subcortical areas is linked to working memory, suggesting the presence of a subtle microstructural subcortical dysfunction in the pathoetiological mechanism underlying high cognitive load performances in schizophrenia. Finally, our findings indicate that MD is a more sensitive marker of brain tissue deficits than signal intensity variations measured in T1-weighted imaging data, consistently with previous reports. Thus, DTI appears to be an invaluable tool to investigate subcortical pathology in schizophrenia, greatly enhancing the ability to detect subtle brain changes in this complex disorder.
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Affiliation(s)
- Ilaria Spoletini
- Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Andrea Cherubini
- Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Giulia Banfi
- Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Ivo Alex Rubino
- Department of Neuroscience, Tor Vergata University, Rome, Italy
| | - Patrice Peran
- Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Carlo Caltagirone
- Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy,Department of Neuroscience, Tor Vergata University, Rome, Italy
| | - Gianfranco Spalletta
- Department of Neuroscience, Tor Vergata University, Rome, Italy,To whom correspondence should be addressed; Laboratory of Clinical and Behavioural Neurology, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Via Ardeatina 306. 00179 Rome, Italy; tel: +39-06-51501575, fax: +39-06-51501575, e-mail:
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Leung M, Cheung C, Yu K, Yip B, Sham P, Li Q, Chua S, McAlonan G. Gray matter in first-episode schizophrenia before and after antipsychotic drug treatment. Anatomical likelihood estimation meta-analyses with sample size weighting. Schizophr Bull 2011; 37:199-211. [PMID: 19759093 PMCID: PMC3004197 DOI: 10.1093/schbul/sbp099] [Citation(s) in RCA: 109] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Cerebral morphological abnormalities in schizophrenia may be modulated by treatment, chronicity, and duration of illness. Comparing brain imaging studies of individuals with first-episode schizophrenia and neuroleptic naive (NN-FES) with that of their neuroleptic-treated counterparts (NT-FES) can help to dissect out the effect of these potential confounders. METHODS We used the anatomical likelihood estimation method to compare voxel-based morphometric studies of NN-FES (n = 162 patients) and NT-FES (n = 336 patients) studies. The analysis included a sample size weighting step based on the Liptak-Stouffer method to reflect the greater power of larger studies. RESULTS Patient samples were matched for age, gender, and duration of illness. An extensive network of gray matter deficits in frontal, temporal, insular, striatal, posterior cingulate, and cerebellar regions was detected in the NN-FES samples as compared with healthy controls. Major deficits were detected in the frontal, superior temporal, insular, and parahippocampal regions for the NT-FES group compared with the NN-FES group. In addition, the NT-FES group showed minor deficits in the caudate, cingulate, and inferior temporal regions compared with the NN-FES group. There were no regions with gray matter volumetric excess in the NT-FES group. CONCLUSION Frontal, striato-limbic, and temporal morphological abnormalities are present in the early stage of schizophrenia and are unrelated to the effects of neuroleptic treatment, chronicity, and duration of illness. There may be dynamic effects of treatment on striato-limbic and temporal, but not frontal, regional gray matter volumes of the brain.
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Affiliation(s)
- Meikei Leung
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - Charlton Cheung
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - Kevin Yu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - Benjamin Yip
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - Pak Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong,Centre for Reproduction, Development and Growth, The University of Hong Kong
| | - Qi Li
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong,Centre for Reproduction, Development and Growth, The University of Hong Kong
| | - Siew Chua
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong,Centre for Reproduction, Development and Growth, The University of Hong Kong
| | - Grainne McAlonan
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong,Centre for Reproduction, Development and Growth, The University of Hong Kong,To whom correspondence should be addressed; tel: +852-28199564, fax: +852-28551345, e-mail:
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McAlonan GM, Li Q, Cheung C. The timing and specificity of prenatal immune risk factors for autism modeled in the mouse and relevance to schizophrenia. Neurosignals 2010; 18:129-39. [PMID: 21042002 DOI: 10.1159/000321080] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2010] [Accepted: 09/09/2010] [Indexed: 12/13/2022] Open
Abstract
Autism is a highly heritable condition, but there is strong epidemiological evidence that environmental factors, especially prenatal exposure to immune challenge, contribute to it. This evidence is largely indirect, and experimental testing is necessary to directly examine causal mechanisms. Mouse models reveal that prenatal immune perturbation disrupts postnatal brain maturation with alterations in gene and protein expression, neurotransmitter function, brain structure and behavioral indices reminiscent of, but not specific to, autism. This likely reflects a neurodevelopmental spectrum in which autism and schizophrenia share numerous genetic and environmental risk factors for difficulties in social interaction, communication, emotion processing and executive function. Recent epidemiological studies find that early rather than late pregnancy infection confers the greater risk of schizophrenia. The autism literature is more limited, but exposures in the 2nd half of pregnancy may be important. Mouse models of prenatal immune challenge help dissect these observations and show some common consequences of early and late gestational exposures, as well as distinct ramifications potentially relevant to schizophrenia and autism. Although nonspecificity of immune-stimulated mouse models could be considered a disadvantage, we propose a broadened perspective, exploiting the possibility that advances made investigating a target condition can contribute towards the understanding of related conditions.
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Affiliation(s)
- Gráinne M McAlonan
- Department of Psychiatry, The University of Hong Kong, Hong Kong, SAR, China.
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Yu K, Cheung C, Leung M, Li Q, Chua S, McAlonan G. Are Bipolar Disorder and Schizophrenia Neuroanatomically Distinct? An Anatomical Likelihood Meta-analysis. Front Hum Neurosci 2010; 4:189. [PMID: 21103008 PMCID: PMC2987512 DOI: 10.3389/fnhum.2010.00189] [Citation(s) in RCA: 70] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2010] [Accepted: 09/22/2010] [Indexed: 11/13/2022] Open
Abstract
Objective: There is renewed debate on whether modern diagnostic classification should adopt a dichotomous or dimensional approach to schizophrenia and bipolar disorder. This study synthesizes data from voxel-based studies of schizophrenia and bipolar disorder to estimate the extent to which these conditions have a common neuroanatomical phenotype. Methods: A post-hoc meta-analytic estimation of the extent to which bipolar disorder, schizophrenia, or both conditions contribute to brain gray matter differences compared to controls was achieved using a novel application of the conventional anatomical likelihood estimation (ALE) method. 19 schizophrenia studies (651 patients and 693 controls) were matched as closely as possible to 19 bipolar studies (540 patients and 745 controls). Result: Substantial overlaps in the regions affected by schizophrenia and bipolar disorder included regions in prefrontal cortex, thalamus, left caudate, left medial temporal lobe, and right insula. Bipolar disorder and schizophrenia jointly contributed to clusters in the right hemisphere, but schizophrenia was almost exclusively associated with additional gray matter deficits (left insula and amygdala) in the left hemisphere. Limitation: The current meta-analytic method has a number of constraints. Importantly, only studies identifying differences between controls and patient groups could be included in this analysis. Conclusion: Bipolar disorder shares many of the same brain regions as schizophrenia. However, relative to neurotypical controls, lower gray matter volume in schizophrenia is more extensive and includes the amygdala. This fresh application of ALE accommodates multiple studies in a relatively unbiased comparison. Common biological mechanisms may explain the neuroanatomical overlap between these major disorders, but explaining why brain differences are more extensive in schizophrenia remains challenging.
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Affiliation(s)
- Kevin Yu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong Pokfulam, Hong Kong
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Cheung C, Yu K, Fung G, Leung M, Wong C, Li Q, Sham P, Chua S, McAlonan G. Autistic disorders and schizophrenia: related or remote? An anatomical likelihood estimation. PLoS One 2010; 5:e12233. [PMID: 20805880 PMCID: PMC2923607 DOI: 10.1371/journal.pone.0012233] [Citation(s) in RCA: 147] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2010] [Accepted: 07/19/2010] [Indexed: 01/06/2023] Open
Abstract
Shared genetic and environmental risk factors have been identified for autistic spectrum disorders (ASD) and schizophrenia. Social interaction, communication, emotion processing, sensorimotor gating and executive function are disrupted in both, stimulating debate about whether these are related conditions. Brain imaging studies constitute an informative and expanding resource to determine whether brain structural phenotype of these disorders is distinct or overlapping. We aimed to synthesize existing datasets characterizing ASD and schizophrenia within a common framework, to quantify their structural similarities. In a novel modification of Anatomical Likelihood Estimation (ALE), 313 foci were extracted from 25 voxel-based studies comprising 660 participants (308 ASD, 352 first-episode schizophrenia) and 801 controls. The results revealed that, compared to controls, lower grey matter volumes within limbic-striato-thalamic circuitry were common to ASD and schizophrenia. Unique features of each disorder included lower grey matter volume in amygdala, caudate, frontal and medial gyrus for schizophrenia and putamen for autism. Thus, in terms of brain volumetrics, ASD and schizophrenia have a clear degree of overlap that may reflect shared etiological mechanisms. However, the distinctive neuroanatomy also mapped in each condition raises the question about how this is arrived in the context of common etiological pressures.
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Affiliation(s)
- Charlton Cheung
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
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Caudate nucleus volume in individuals at ultra-high risk of psychosis: a cross-sectional magnetic resonance imaging study. Psychiatry Res 2010; 182:223-30. [PMID: 20488675 DOI: 10.1016/j.pscychresns.2010.02.006] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2009] [Revised: 12/24/2009] [Accepted: 02/11/2010] [Indexed: 11/24/2022]
Abstract
The aim of the present study was to investigate whether volumetric abnormalities of the caudate nuclei predate the onset of psychotic illness. Caudate nuclei volume (CNVs), excluding the tail, were measured using region-of-interest (ROI) tracing of magnetic resonance imaging (MRI) scans acquired on a 1.5T scanner. Subjects included 39 individuals deemed at ultra-high risk of psychosis who converted to psychosis (UHR-P) after initial MRI scanning; 39 matched individuals at ultra-high risk who did not convert to psychosis (UHR-NP); and 39 matched healthy controls. All subjects were neuroleptic-naïve. After adjusting CNVs for intracranial volume (ICV), univariate analyses of variance and repeated measures analyses of variance were undertaken to examine the relationship of CNVs to psychosis transition and to family history of psychosis. Pearson's correlations were used to investigate the relationship of psychopathological scores to CNVs. CNVs did not differ significantly between UHR individuals and healthy controls, and there was no significant difference between converters and non-converters to psychosis. In the UHR group, presence of family history of psychosis was not related to CNVs. There was no correlation between CNVs and either positive or negative symptoms of schizophrenia. Significant associations were found between larger CNV and increased errors on a spatial working memory task but better verbal fluency performance. These data suggest that the caudate is macroscopically normal prior to illness onset, while the relationship to tasks of executive function may implicate the caudate together with its connections to prefrontal regions. Future research should examine changes longitudinally together with analysis of shape to assess subregions of the caudate that connect with prefrontal cortex.
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Deng MY, McAlonan GM, Cheung C, Chiu CPY, Law CW, Cheung V, Sham PC, Chen EYH, Chua SE. A naturalistic study of grey matter volume increase after early treatment in anti-psychotic naïve, newly diagnosed schizophrenia. Psychopharmacology (Berl) 2009; 206:437-46. [PMID: 19641900 DOI: 10.1007/s00213-009-1619-z] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2009] [Accepted: 07/10/2009] [Indexed: 10/20/2022]
Abstract
BACKGROUND Anti-psychotic treatment appears to be associated with striatal volume increase, but how early this change occurs is still unknown. METHODS A single prospective cohort of 20 anti-psychotic-naïve patients, newly diagnosed with schizophrenia, underwent magnetic resonance imaging brain scan at baseline. This was repeated following up to 8 weeks of anti-psychotic treatment. Ten patients had repeat scan within only 3 weeks. The choice of anti-psychotic medication was naturalistic, i.e., clinician-led. Well-matched healthy individuals were also scanned to control for non-specific changes over a 3-week period. RESULTS After 3 weeks of anti-psychotic treatment, significant grey matter volume increase in the right caudate, superior and inferior frontal gyrus, precentral gyrus, and left inferior parietal lobule was noted. However, after 8 weeks of anti-psychotic treatment, volume increase in the right thalamus and bilateral cerebellum was observed. Significant grey matter reduction was detected in the left medial frontal gyrus at both 3- and 8-week intervals. CONCLUSIONS Early increase in striatal volume change occurs as early as 3 weeks after anti-psychotic treatment, whilst thalamic volume increase is apparent later, by 8 weeks of treatment. We speculate that drug-mediated neuroplasticity may provide a biomarker for clinical recovery.
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Affiliation(s)
- Michelle Y Deng
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, Queen Mary Hospital, The University of Hong Kong, Pokfulam Road, Hong Kong, Hong Kong
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Chua SE, McAlonan G. Is there core diffusion tensor imaging pathology in schizophrenia? Br J Psychiatry 2009; 195:86-7; author reply 87. [PMID: 19567906 DOI: 10.1192/bjp.195.1.86b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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