Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA

Autor: Raquel E. Gur, Geor Bakker, Erick J. Canales-Rodríguez, Edith Pomarol-Clotet, Cynthia Shannon Weickert, Neda Jahanshad, Ulrich Schall, Theodore D. Satterthwaite, Vince D. Calhoun, Aleix Solanes, Frans Henskens, Antonin Skoch, Sara Llufriu, Anthony A. James, Michael Stäblein, Aurora Bonvino, Kun Yang, Cyril Höschl, Christos Pantelis, Carlos López-Jaramillo, Stefan Ehrlich, S. Sarró, Stefan Kaiser, Udo Dannlowski, Fengmei Fan, Wenhao Jiang, Paul E. Rasser, Patricia T. Michie, Julian A Pineda-Zapata, Zhiren Wang, Russell T. Shinohara, Eduard Vieta, Rodney J. Scott, Tilo Kircher, Andrea Weideman, Melissa J. Green, Nicola G. Cascella, Jason M. Bruggemann, Dominik Grotegerd, Viola Oertel, Janice M. Fullerton, Theo G.M. van Erp, Stanley V. Catts, Hong Xiang, Murray J. Cairns, Jingxu Chen, Paul M. Thompson, Adrian Preda, Elisabeth Solana, Fleur M. Howells, Godfrey D. Pearlson, Anne Uhlmann, Peter Kochunov, Christian Knöchel, Fabrizio Piras, Fude Yang, Je-Yeon Yun, Yunlong Tan, Henk Temmingh, Covadonga M. Díaz-Caneja, Peter J. McKenna, Carmel M. Loughland, Alexander Tomyshev, Kang Sim, Joost Janssen, Kaleda Vg, Ruben C. Gur, Akira Sawa, Ana M. Díaz-Zuluaga, Annabella Di Giorgio, Nerisa Banaj, Jessica A. Turner, Vanessa Cropley, Gavin Cooper, Raymond Salvador, Marc L. Seal, Rhoshel K. Lenroot, Stefan S. du Plessis, Yoichiro Takayanagi, Federica Piras, Jun Soo Kwon, Dan J. Stein, Anton Albajes-Eizagirre, David C. Glahn, Vaughan J. Carr, Thomas W. Weickert, Francesca Assogna, Lydia Fortea, Joaquim Radua, Igor Nenadic, Alessandro Bertolino, Margaret D. King, Eloy Martinez-Heras, Gianfranco Spalletta, Paul A. Tooney, Tim Hahn, Hua Guo, Stefan Borgwardt, Yann Quidé, Bryan J. Mowry, Shuping Tan, Axel Krug, Therese van Amelsvoort, Elliot Hong, Irina V. Lebedeva, David Tomecek, Daniel H. Wolf, Celso Arango, Clara Alloza, Matthias Kirschner, Dana Nguyen
Přispěvatelé: Kaiser, Stefan, Psychiatrie & Neuropsychologie, MUMC+: MA Med Staf Spec Psychiatrie (9), RS: MHeNs - R2 - Mental Health
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Male
Computer science
Image Processing
Medical and Health Sciences
0302 clinical medicine
Computer-Assisted
Image Processing
Computer-Assisted
ENIGMA Consortium collaborators
Cerebral Cortex
05 social sciences
Brain
Middle Aged
Magnetic Resonance Imaging
3. Good health
Mental Health
Neurology
Schizophrenia
Biomedical Imaging
Female
Algorithms
Adult
medicine.medical_specialty
Mega-analysis
Cognitive Neuroscience
Neuroimaging
SURFACE-BASED ANALYSIS
050105 experimental psychology
Article
Cortical thickness
lcsh:RC321-571
03 medical and health sciences
Young Adult
Physical medicine and rehabilitation
Meta-Analysis as Topic
medicine
Humans
0501 psychology and cognitive sciences
Cortical surface
ddc:610
Gray matter
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Neurology & Neurosurgery
Volume
Psychology and Cognitive Sciences
Neurosciences
medicine.disease
Brain Disorders
Data set
030217 neurology & neurosurgery
Diagnosis of schizophrenia
Zdroj: NeuroImage, Vol 218, Iss, Pp 116956-(2020)
Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
NeuroImage, Vol. 218 (2020) P. 116956
Neuroimage, 218:116956. Elsevier Science
NeuroImage
ISSN: 1095-9572
1053-8119
Popis: Altres ajuts: SRB: The Australian Schizophrenia Research Bank (ASRB) was supported by the National Health and Medical Research Council of Australia (NHMRC) (Enabling Grant, ID 386500), the Pratt Foundation, Ramsay Health Care, the Viertel Charitable Foundation and the Schizophrenia Research Institute. Chief Investigators for ASRB were Carr, V., Schall, U., Scott, R., Jablensky, A., Mowry, B., Michie, P., Catts, S., Henskens, F., Pantelis, C. We thank Loughland, C., the ASRB Manager, and acknowledge the help of Jason Bridge for ASRB database queries. CP was supported by NHMRC Senior Principal Research Fellowships (IDs: 628386 & 1105825); GC was supported by the Schizophrenia Research Institute utilizing infrastructure funding from the New South Wales Ministry of Health and New South Wales Ministry of Trade and Investment (Australia); JMF was supported by NHMRC project grant (1063960) and the Janette Mary O'Neil Research Fellowship; MJG was supported by NHMRC as an R.D. Wright Biomedical Career Development Fellow (1061875). MJC was supported by NHMRC Senior Research Fellowship (1121474). CASSI: CSW is funded by the NSW Ministry of Health, Office of Health and Medical Research. CSW is a recipient of a National Health and Medical Research Council (Australia) Principal Research Fellowship (PRF) (#1117079). CIAM: The CIAM study (FMH - PI) was supported by the University Research Committee, University of Cape Town and South African funding bodies National Research Foundation and Medical Research Council. COBRE: The COBRE dataset and investigators were supported by NIH grants R01EB006841 & P20GM103472, as well as NSF grant 1539067. JT (senior author) and VDC are supported by 5R01MH094524. JMS is supported by R01 AA021771 and P50 AA022534. EONCKS: This work was supported by a New Partnership for Africa's Development (NEPAD) grant through the Department of Science and Technology of South Africa, the Medical Research Council of South Africa (grant number 65174). ESO: The ESO study was funded by NPU I - LO1611 and Ministry of Health, Czech Republic - Conceptual Development of Research Organization 00023001 (IKEM). FIDMAG/Project: This work was supported by the Catalan Government and several grants from the Instituto de Salud Carlos III and co-funded by European Union (ERDF/ESF, 'Investing in your future'): Miguel Servet Research Contracts and Research Project Grants. FOR2107 Marburg: The FOR2107 Marburg study was funded by the German Research Foundation (DFG), Tilo Kircher (speaker FOR2107; DFG grant numbers KI588/14-1, KI588/14-2), Axel Krug (KR 3822/5-1, KR 3822/7-2), Igor Nenadic (NE 2254/1-2), Carsten Konrad (KO 4291/3-1). FOR2107 Muenster: The FOR2107 Muenster study was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). TH was supported by grants from the German Research Foundation (DFG grants HA7070/2-2, HA7070/3, HA7070/4). Frankfurt: MRI was performed at the Frankfurt Brain Imaging Center, supported by the German Research Council (DFG) and the German Ministry for Education and Research (BMBF; Brain Imaging Center Frankfurt/Main, DLR 01GO0203). GIPSI: This study was supported by Colciencias PRISMA-U.T. Huilong1 & Huilong2: This study was funded by the National Natural Science Foundation of China (81761128021; 31671145; 81401115; 81401133), Beijing Municipal Science and Technology Commission grant (Z141107002514016) and Beijing Natural Science Foundation(7162087, Beijing Municipal Administration of Hospitals Clinical medicine Development of special funding (XMLX201609; zylx201409). IGP: This study was funded by Project Grants from the Australian National Health and Medical Research Council of Australia (NHMRC; APP630471 and APP1081603), the Macquarie University's Australian Research Council Centre of Excellence in Cognition and its Disorders (CE110001021). Johns Hopkins: Supported by National Institutes of Health Grant Nos. MH-092443, MH-094268 (Silvio O. Conte Center), MH-105660, and MH-107730; foundation grants from Stanley, RUSK/S-R, and NARSAD/Brain and Behavior Research Foundation. Madrid: Supported by the Spanish Ministry of Science, Innovation and Universities, Instituto de Salud Carlos III, co-financed by ERDF Funds from the European Commission, "A way of making Europe", CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds and European Union Seventh Framework Program and H2020 Program; Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. MPRC1 & MPRC2: Support was received from NIH grants U01MH108148, 2R01EB015611, R01MH112180, R01DA027680, R01MH085646, P50MH103222 and T32MH067533, a State of Maryland contract (M00B6400091) and NSF grant (1620457). OLIN: The Olin study was supported by NIH grants R37MH43375 and R01MH074797. Oxford: The Oxford study MRC G0500092. SLF Rome: Support from the Italian Ministry of Health grants RC-12-13-14-15-16-17-18-19/A. RSCZ: RSCZ data collection was supported by RFBR 15-06-05758 grant. SCORE: This study was supported in part by grant 3232BO_119382 from the Swiss National Science Foundation. We thank the FePsy (Frueherkennung von Psychosen; early detection of psychosis) Study Group from the University of Basel, Department of Psychiatry, Switzerland, for the recruitment of the study participants. The FePsy Study was supported in part by grant No. SNF 3200-057216/1, ext./2, ext./3. Singapore: This study was supported by research grants from the National Healthcare Group, Singapore (SIG/05004; SIG/11003), and the Singapore Bioimaging Consortium (RP C-009/2006) research grants awarded to KS. SNUH: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (Grant no. 2013R1A2A1A03071089 and 2017M3C7A1029610). UCISZ: The UCISZ study was supported by the National Institutes of Mental Health grant number R21MH097196 to TGMvE. UCISZ data were 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. UNIBA: The UNIBA study was supported by grant funding from the Italian Ministry of Health (PE-2011-02347951). UNIMAAS: The study was supported by Dutch Organization for Health Research and Development (ZonMw 91112002) and a personal grant to Thérèse van Amelsvoort (ZonMw-VIDI: 91712394). The data was collected in a clinical trial registered in the Dutch clinical trial registry under ID: NTR5094 (http://www.trialregister.nl). UPenn: This study was supported by the National Institute of Mental Health grants MH064045, MH 60722, MH019112, MH085096 (DHW), and R01MH112847 (RTS and TDS). Zurich: This study was supported by the Swiss National Science Foundation (105314_140351 to S.K.). Matthias Kirschner acknowledges support from the National Bank Fellowship (McGill University) and the Swiss National Foundation (P2SKP3_178175). Research reported in this publication was also supported by the following National Institutes of Health grants: U54 EB020403 to PMT, R01 MH116147, U24 RR21992, R21MH097196, and TR000153 to TGMvE, S10 OD023696 and R01EB015611 to PK, T32 AG058507and 5T32 MH073526 to CRKC, R01 MH117601 to NJ, ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, ENIGMA Sex Differences R01MH116147, and ENIGMA-COINSTAC: Advanced World-wide Transdiagnostic Analysis of Valence System Brain Circuits R01MH121246. 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).
Databáze: OpenAIRE
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