Type

Journal Article

Authors

Aiden Corvin

Subjects

Psychology

Topics
health board biomedical research mental health meta analysis high performance computing research and development brain structural abnormalities data analysis

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium (2015)

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. The AMC study was supported by grants from ZonMW (grant numbers: 3160007, 91676084, 31160003, 31180002, 31000056, 2812412, 100001002, 100002034), NWO (grant numbers: 90461193, 40007080, 48004004, 40003330), and grants from the Amsterdam Brain Imaging Platform, Neuroscience Campus Amsterdam and the Dutch Brain foundation. The processing with Freesurfer was performed on the Dutch e-Science Grid through BiG Grid project and COMMIT project “e-Biobanking with imaging for healthcare”, which are funded by the Netherlands Organization for Scientific Research (NWO). The CLiNG study and the HMS studies were partially supported by a research grant from the Competence Network Schizophrenia to Oliver Gruber. The Dublin study was supported by grant funding from the Irish Health Research Board (grant number HRA_POR/2012/54) and Science Foundation Ireland (grant numbers 12/IP/1359 and 08/IN.1/B1916). The Edinburgh study was supported by the Medical Research Council through a Clinical Training Fellowship (Ref G84/5699). Further funding was also provided by the Mortimer and Theresa Sackler Foundation. The FBIRN study was supported by the National Center for Research Resources at the National Institutes of Health (grant numbers: NIH 1 U24 RR021992 (Function Biomedical Informatics Research Network) and NIH 1 U24 RR025736-01 (Biomedical Informatics Research Network Coordinating Center; http://www.birncommunity.org). FBIRN data was processed by the UCI High Performance Computing cluster supported by Joseph Farran, Harry Mangalam, and Adam Brenner and the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1 TR000153. FBIRN thanks Mrs. Liv McMillan for overall study coordination. The Galway study was supported by grant funding from the Health Research Board (grant number HRA_POR/2011/100) and the Wellcome Trust (grant number 072894/2/03/Z) The HUBIN study was supported by the Swedish Research Council (grant numbers K2009-62X-15077-06-3 and K2012-61X-15077-09-3), the Karolinska Institutet and the Knut and Alice Wallenberg Foundation. The MCIC study was supported by the National Institutes of Health (NIH/NCRR P41RR14075 and R01EB005846 (to Vince D. Calhoun)), the Department of Energy (DE-FG02-99ER62764), the Mind Research Network, the Morphometry BIRN (1U24, RR021382A), the Function BIRN (U24RR021992-01, NIH.NCRR MO1 RR025758-01, NIMH 1RC1MH089257 to Vince D. Calhoun), the Deutsche Forschungsgemeinschaft (research fellowship to Stefan Ehrlich), and a NARSAD Young Investigator Award (to Stefan Ehrlich). The NU study was supported by NIH grants P50 MH071616, R01 MH056584, 1R01 MH084803 (Wang PI) and 1U01 MH097435 (Wang, Turner, Ambite, Potkin PIs). The PAFIP study was supported by Instituto de Salud Carlos III, FIS 00/3095, 01/3129, PI020499, PI060507, PI10/00183, the SENY Fundació Research Grant CI 2005‐0308007, and the Fundación Marqués de Valdecilla API07/011. The TOP study was supported by the Research Council of Norway (#213837, #217776, #223273), the South-East Norway Health Authority (2013-123), and the KG Jebsen Foundation. The Olin study was supported by R37MH43375 and R01MH074797. The UMCU study was supported by the Netherlands Organization forHealth Research and Development Zon-Mw grants 90802123 and 91746370 (to Hilleke E. Hulshoff Pol) and 10-000-1001 (to René S. Kahn). The UPENN study was supported by National Institute of Mental Health grants MH064045, MH 60722, MH019112, and MH085096 (DHW). Theodore D. Satterthwaite was supported by MH098130 and by the Marc Rapport Family through NARSAD. The authors thank Mrs. Liv McMillan for assistance with manuscript submission. Research reported in this publication was supported by the National Institute Of Biomedical Imaging And Bioengineering (NIBIB) of the National Institutes of Health under Award Number U54EB020403. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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Aiden Corvin

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Aiden Corvin
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