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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023001%3A_____%2F20%3A00079967" target="_blank" >RIV/00023001:_____/20:00079967 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21230/20:00345952

  • Result on the web

    <a href="https://reader.elsevier.com/reader/sd/pii/S1053811920304420?token=8D4792AE38534068CAC843B09705B00560796751D8DD7F9203716189AF538F21E8FA30D58D6C9B954C1F199FABF5CA4B" target="_blank" >https://reader.elsevier.com/reader/sd/pii/S1053811920304420?token=8D4792AE38534068CAC843B09705B00560796751D8DD7F9203716189AF538F21E8FA30D58D6C9B954C1F199FABF5CA4B</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.neuroimage.2020.116956" target="_blank" >10.1016/j.neuroimage.2020.116956</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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 het-erogeneity 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).

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30103 - Neurosciences (including psychophysiology)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    NeuroImage

  • ISSN

    1053-8119

  • e-ISSN

  • Volume of the periodical

    218

  • Issue of the periodical within the volume

    September

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    14

  • Pages from-to

    "art. no. 116956"

  • UT code for WoS article

    000555460300009

  • EID of the result in the Scopus database

    2-s2.0-85086881765