The ENIGMA Consortium: Large-scale collaborative analyses of neuroimaging and genetic data

Brain Imaging and Behavior (Impact Factor: 4.6). 01/2014; 8(2). DOI: 10.1007/s11682-013-9269-5


This article reviews work published by the ENIGMA Consortium and its Working Groups ( It was written collaboratively; P.T. wrote the first draft and all listed authors revised and edited the document for important intellectual content, using Google Docs for parallel editing, and approved it. Some ENIGMA investigators contributed to the design and implementation of ENIGMA or provided data but did not participate in the analysis or writing of this report. A complete listing of ENIGMA investigators is available at For ADNI, some investigators contributed to the design and implementation of ADNI or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators is available at ADNI_Acknowledgement_List.pdf The work reviewed here was funded by a large number of federal and private agencies worldwide, listed in Stein et al. (2012); the funding for listed consortia is also itemized in Stein et al. (2012).

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    • "Meyer-Lindenberg (2012) has indicated that the future of imaging genetics will recognize the importance of the sizeable amount of variation in CNVs. Given the low incidence of individual CNVs, in particular large and rare CNVs, such studies are more likely from multi-site collaborations, where increasing numbers of imaging genetic studies are heading for (Schumann et al., 2010; Thompson et al., 2014). Methods to encompass data from multi-sites, controlling for not only different equipments or experiments but also different local populations or environments, are in great need, which have to consider both computational feasibility and mathematical (model) validity. "
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    Frontiers in Neuroinformatics 03/2014; 8:29. DOI:10.3389/fninf.2014.00029 · 3.26 Impact Factor
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    • "Many neuroimaging studies of genetic polymorphisms and their effects on the brain are barely powered to detect effects, which may contribute to differences in what effects are found. To address this, imaging genetics consortia such as ENIGMA are meta-analyzing data worldwide with the goal of understanding the consistency and credibility of effects seen in smaller cohorts (Thompson et al. 2014). "
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