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Schizophr Bull. 2015 Sep;41(5):1133-42. doi: 10.1093/schbul/sbu177. Epub 2014 Dec 28.

Patterns of Gray Matter Abnormalities in Schizophrenia Based on an International Mega-analysis.

Author information

1
The Mind Research Network, Albuquerque, NM;
2
The Mind Research Network, Albuquerque, NM; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM;
3
Department of Psychiatry and Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands;
4
Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands;
5
Department of Psychiatry and Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands;
6
Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands; Department of Language and Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands;
7
Department of Psychiatry & Human Behavior, School of Medicine, University of California, Irvine, CA;
8
Department of Psychiatry, School of Medicine, University of California, San Francisco, CA;
9
Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, CA;
10
Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Korea;
11
Department of Psychiatry, University of Minnesota, Minneapolis, MN;
12
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA;
13
NORMENT, KG Jebsen Center for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;
14
NORMENT, KG Jebsen Center for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Research, Diakonhjemmet Hospital, Oslo, Norway;
15
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA; Department of Psychiatry, Massachusetts General Hospital, HMS, Boston, MA;
16
Department of Psychiatry, University of Minnesota, Minneapolis, MN; Minneapolis VA Healthcare System, Minneapolis, MN;
17
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA; Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany;
18
Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL; Department of Radiology, Northwestern University, Chicago, IL;
19
Department of Psychiatry, School of Medicine, Yale University, New Haven, CT; Institute of Living, Hartford Healthcare Corporation, Hartford, CT; Department of Neurobiology, School of Medicine, Yale University, New Haven, CT;
20
Department of Psychiatry, School of Medicine, Yale University, New Haven, CT; Institute of Living, Hartford Healthcare Corporation, Hartford, CT;
21
Department of Neurosurgery, University of New Mexico Health Sciences Center, Albuquerque, NM;
22
University of New Mexico Health Sciences Center, Albuquerque, NM; Department of Psychiatry, University of New Mexico, Albuquerque, NM; Raymond G. Murphy VA Medical Center, Albuquerque, NM;
23
University of New Mexico Health Sciences Center, Albuquerque, NM; Department of Psychiatry, University of New Mexico, Albuquerque, NM;
24
The Mind Research Network, Albuquerque, NM; Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, GA jturner@mrn.org.

Abstract

Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both source-based morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects.

KEYWORDS:

independent component analysis; schizophrenia; source-based morphometry; symptoms; voxel-based morphometry

PMID:
25548384
PMCID:
PMC4535628
DOI:
10.1093/schbul/sbu177
[Indexed for MEDLINE]
Free PMC Article

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