TY - JOUR
T1 - Patterns of gray matter abnormalities in schizophrenia based on an international mega-analysis
AU - Gupta, Cota Navin
AU - Calhoun, Vince D.
AU - Rachakonda, Srinivas
AU - Chen, Jiayu
AU - Patel, Veena
AU - Liu, Jingyu
AU - Segall, Judith
AU - Franke, Barbara
AU - Zwiers, Marcel P.
AU - Arias-Vasquez, Alejandro
AU - Buitelaar, Jan
AU - Fisher, Simon E.
AU - Fernandez, Guillen
AU - Van Erp, Theo G M
AU - Potkin, Steven
AU - Ford, Judith
AU - Mathalon, Daniel
AU - McEwen, Sarah
AU - Lee, Hyo Jong
AU - Mueller, Bryon A.
AU - Greve, Douglas N.
AU - Andreassen, Ole
AU - Agartz, Ingrid
AU - Gollub, Randy L.
AU - Sponheim, Scott R.
AU - Ehrlich, Stefan
AU - Wang, Lei
AU - Pearlson, Godfrey
AU - Glahn, David C.
AU - Sprooten, Emma
AU - Mayer, Andrew R.
AU - Stephen, Julia
AU - Jung, Rex E.
AU - Canive, Jose
AU - Bustillo, Juan
AU - Turner, Jessica A.
N1 - Publisher Copyright:
© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved.
PY - 2015/9
Y1 - 2015/9
N2 - 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 sourcebased 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.
AB - 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 sourcebased 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.
KW - Independent component analysis
KW - Schizophrenia
KW - Source-based morphometry
KW - Symptoms
KW - Voxel-based morphometry
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U2 - 10.1093/schbul/sbu177
DO - 10.1093/schbul/sbu177
M3 - Article
C2 - 25548384
AN - SCOPUS:84941923196
SN - 0586-7614
VL - 41
SP - 1133
EP - 1142
JO - Schizophrenia bulletin
JF - Schizophrenia bulletin
IS - 5
ER -