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Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA
J. Radua, E. Vieta, R. Shinohara, P. Kochunov, Y. Quidé, MJ. Green, CS. Weickert, T. Weickert, J. Bruggemann, T. Kircher, I. Nenadić, MJ. Cairns, M. Seal, U. Schall, F. Henskens, JM. Fullerton, B. Mowry, C. Pantelis, R. Lenroot, V. Cropley, C....
Language English Country United States
Document type Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S.
Grant support
R01 DA027680
NIDA NIH HHS - United States
P20 GM103472
NIGMS NIH HHS - United States
UL1 TR000153
NCATS NIH HHS - United States
R21 MH097196
NIMH NIH HHS - United States
P50 MH103222
NIMH NIH HHS - United States
R01 MH121246
NIMH NIH HHS - United States
S10 OD023696
NIH HHS - United States
U01 MH108148
NIMH NIH HHS - United States
P41 EB015922
NIBIB NIH HHS - United States
R01 MH112847
NIMH NIH HHS - United States
R01 MH112180
NIMH NIH HHS - United States
R01 EB015611
NIBIB NIH HHS - United States
R01 AA021771
NIAAA NIH HHS - United States
P50 AA022534
NIAAA NIH HHS - United States
R01 EB006841
NIBIB NIH HHS - United States
R01 MH116147
NIMH NIH HHS - United States
R01 MH074797
NIMH NIH HHS - United States
T32 AG058507
NIA NIH HHS - United States
R01 MH094524
NIMH NIH HHS - United States
U54 EB020403
NIBIB NIH HHS - United States
R01 MH085646
NIMH NIH HHS - United States
T32 MH067533
NIMH NIH HHS - United States
G0500092
Medical Research Council - United Kingdom
NLK
Directory of Open Access Journals
from 2020
ProQuest Central
from 1998-05-01 to 2 months ago
Health & Medicine (ProQuest)
from 2002-08-01 to 2 months ago
Psychology Database (ProQuest)
from 2002-08-01 to 2 months ago
ROAD: Directory of Open Access Scholarly Resources
- MeSH
- Algorithms MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Meta-Analysis as Topic MeSH
- Young Adult MeSH
- Cerebral Cortex diagnostic imaging MeSH
- Neuroimaging MeSH
- Image Processing, Computer-Assisted methods MeSH
- Schizophrenia diagnostic imaging MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).
Center for Biomedical Image Computing and Analytics University of Pennsylvania Philadelphia PA USA
Department of Child and Adolescent Psychiatry Technische Universität Dresden Dresden Germany
Department of Mental Health Johns Hopkins Bloomberg School of Public Health Baltimore MD USA
Department of Neuroscience and Physiology Upstate Medical University Syracuse Newyork NY USA
Department of Psychiatry and Human Behavior University of California Irvine Irvine CA USA
Department of Psychiatry and Neuropsychology Maastricht University Maastricht The Netherlands
Department of Psychiatry and Psychotherapy Philipps University Marburg Marburg Germany
Department of Psychiatry and Psychotherapy University Lübeck Germany
Department of Psychiatry Seoul National University College of Medicine Seoul Republic of Korea
Department of Psychiatry University of Basel Basel Switzerland
Department of Psychiatry University of Münster Münster Germany
Department of Psychiatry University of Oxford Oxford UK
Department of Psychiatry University of Pennsylvania Philadelphia PA USA
Department of Radiology Centre Hospitalier Universitaire Vaudois Lausanne Switzerland
Departments of Psychiatry Johns Hopkins School of Medicine Baltimore MD USA
Faculty of Electrical Engineering Czech Technical University Prague Prague Czech Republic
FIDMAG Germanes Hospitalàries Research Foundation Barcelona Spain
Georgia State University Atlanta GA USA
Hunter Medical Research Institute Newcastle NSW Australia
Imaging Genetics Center Department of Neurology University of Southern California Los Angeles CA USA
Imaging of Mood and Anxiety Related Disorders Barcelona Spain
Institut d'Investigacions Biomèdiques August Pi i Sunyer Barcelona Spain
Institute of Computer Science Czech Academy of Sciences Prague Czech Republic
Instituto de Investigación Sanitaria Gregorio Marañón Madrid Spain
IRCCS Casa Sollievo della Sofferenza San Giovanni Rotondo Italy
Lee Kong Chian School of Medicine Nanyang Technological University Singapore Singapore
Maryland Psychiatric Research Center University of Maryland School of Medicine Baltimore MD USA
Melbourne Neuropsychiatry Centre Dept of Psychiatry University of Melbourne Melbourne VIC Australia
Mental Health Research Center Moscow Russia
Montreal Neurological Institute McGill University Montreal Canada
Mood Disorders Program Hospital Universitario San Vicente Fundación Medellin Colombia
Murdoch Children's Research Institute Melbourne VIC Australia
National Institute of Mental Health Klecany Czech Republic
Neuroscience Institute University of Cape Town Cape Town Western Cape South Africa
Neuroscience Research Australia Sydney NSW Australia
North Western Mental Health Melbourne Health Melbourne VIC Australia
Psychiatry Research Center Beijing Huilongguan Hospital Beijing China
Queensland Brain Institute The University of Queensland Brisbane QLD Australia
Queensland Centre for Mental Health Research The University of Queensland Brisbane QLD Australia
School of Medical Sciences University of New South Wales Sydney NSW Australia
School of Medicine Universidad Complutense Madrid Spain
School of Medicine Universitat Internacional de Catalunya Barcelona Spain
School of Psychiatry University of New South Wales Sydney NSW Australia
Seoul National University Hospital Seoul Republic of Korea
Signal Processing Lab École Polytechnique Fédérale de Lausanne Lausanne Switzerland
The University of Melbourne Australia
University of Barcelona Barcelona Spain
University of New Mexico Albuquerque NM USA
University of Newcastle Newcastle NSW Australia
University of Stellenbosch Cape Town Western Province South Africa
Valkenburg Hospital Observatory Cape Town Western Cape South Africa
West Region and Research Division Institute of Mental Health Singapore Singapore
Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore
References provided by Crossref.org
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- $a Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA / $c J. Radua, E. Vieta, R. Shinohara, P. Kochunov, Y. Quidé, MJ. Green, CS. Weickert, T. Weickert, J. Bruggemann, T. Kircher, I. Nenadić, MJ. Cairns, M. Seal, U. Schall, F. Henskens, JM. Fullerton, B. Mowry, C. Pantelis, R. Lenroot, V. Cropley, C. Loughland, R. Scott, D. Wolf, TD. Satterthwaite, Y. Tan, K. Sim, F. Piras, G. Spalletta, N. Banaj, E. Pomarol-Clotet, A. Solanes, A. Albajes-Eizagirre, EJ. Canales-Rodríguez, S. Sarro, A. Di Giorgio, A. Bertolino, M. Stäblein, V. Oertel, C. Knöchel, S. Borgwardt, S. du Plessis, JY. Yun, JS. Kwon, U. Dannlowski, T. Hahn, D. Grotegerd, C. Alloza, C. Arango, J. Janssen, C. Díaz-Caneja, W. Jiang, V. Calhoun, S. Ehrlich, K. Yang, NG. Cascella, Y. Takayanagi, A. Sawa, A. Tomyshev, I. Lebedeva, V. Kaleda, M. Kirschner, C. Hoschl, D. Tomecek, A. Skoch, T. van Amelsvoort, G. Bakker, A. James, A. Preda, A. Weideman, DJ. Stein, F. Howells, A. Uhlmann, H. Temmingh, C. López-Jaramillo, A. Díaz-Zuluaga, L. Fortea, E. Martinez-Heras, E. Solana, S. Llufriu, N. Jahanshad, P. Thompson, J. Turner, T. van Erp, ENIGMA Consortium collaborators
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