Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

for the ENIGMA Schizophrenia Working Group(University of California, Irvine), Theo G.M. van Erp(University of Southern California), Derrek P. Hibar(University of Southern California), Jerod M. Rasmussen(University of California, Irvine), David C. Glahn(Yale University), Godfrey D. Pearlson(Yale University), Ole A. Andreassen(Oslo University Hospital), Ingrid Agartz(Oslo University Hospital), Lars T. Westlye(Oslo University Hospital), Unn K. Haukvik(Oslo University Hospital), Anders M. Dale(University of California San Diego), Ingrid Melle(Oslo University Hospital), Cecilie B. Hartberg(Oslo University Hospital), Oliver Gruber(Universitätsmedizin Göttingen), Bernd Kraemer(Universitätsmedizin Göttingen), D Zilles(Universitätsmedizin Göttingen), Gary Donohoe(Ollscoil na Gaillimhe – University of Galway), Sinéad Kelly(University of Southern California), Colm McDonald(Ollscoil na Gaillimhe – University of Galway), Derek W. Morris(Ollscoil na Gaillimhe – University of Galway), Dara M. Cannon(Ollscoil na Gaillimhe – University of Galway), Aiden Corvin(Trinity College), Marise W. J. Machielsen(Amsterdam UMC Location University of Amsterdam), Laura Koenders(Amsterdam UMC Location University of Amsterdam), Lieuwe de Haan(Amsterdam UMC Location University of Amsterdam), Dick J. Veltman(Vrije Universiteit Amsterdam), Theodore D. Satterthwaite(University of Pennsylvania), Daniel H. Wolf(University of Pennsylvania), Ruben C. Gur(University of Pennsylvania), R.E. Gur(University of Pennsylvania), Steven G. Potkin(University of California, Irvine), Daniel H. Mathalon(San Francisco VA Medical Center), Bryon A. Mueller(University of Minnesota), Adrian Preda(University of California, Irvine), Fabìo Macciardi(University of California, Irvine), Stefan Ehrlich(Harvard University), Esther Walton(Technische Universität Dresden), J Hass(Technische Universität Dresden), Vince D. Calhoun(Mind Research Network), H. Jeremy Bockholt(University of Iowa), Scott R. Sponheim(University of Minnesota), Jody M. Shoemaker(Mind Research Network), Neeltje E.M. van Haren(University Medical Center Utrecht), Hilleke E. Hulshoff Pol(University Medical Center Utrecht), R A Ophoff(University of California, Los Angeles), R.S. Kahn(University Medical Center Utrecht), Roberto Roiz‐Santiáñez(Universidad de Cantabria), Benedicto Crespo‐Facorro(Universidad de Cantabria), Lei Wang(Northwestern University), K I Alpert(Northwestern University), E G Jönsson(Oslo University Hospital), Ralica Dimitrova(University of Edinburgh), C. Bois(University of Edinburgh), Heather C. Whalley(University of Edinburgh), Andrew M. McIntosh(University of Edinburgh), Stephen M. Lawrie(University of Edinburgh), R Hashimoto(The University of Osaka), Paul M. Thompson(University of Southern California), Jessica A. Turner(Mind Research Network)
Molecular Psychiatry
June 2, 2015
Cited by 1,183Open Access
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Abstract

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.


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