The ENIGMA Toolbox: multiscale neural contextualization of multisite neuroimaging datasets

To the Editor— Among big-data neuroscience initiatives, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium—a worldwide alliance of over 2,000 scientists

diversified into over 50 working groups—has yielded some of the largest studies of the healthy and diseased human brain. Through harmonized procedures and by sharing site-specific brain

metrics (for example, cortical thickness) or aggregated statistical maps, ENIGMA has set the stage for large-scale analyses comparing findings across different topics or disorders1,2. In

parallel, increasingly available resources offer opportunities to contextualize findings across multiscale brain organization. Examples include the Allen Human Brain Atlas3

(microarray-derived postmortem gene expression), the BigBrain Project4 (three-dimensional postmortem human brain histology) and the Human Connectome Project5 (high-definition in vivo

functional and structural connectomics). Here we introduce the ENIGMA Toolbox, an open ecosystem for integration and visualization of multisite ENIGMA results and their multiscale neural

contextualization. Our Toolbox relies on an efficient codebase for exploring and analyzing big data, aiming to facilitate and homogenize follow-up analyses of ENIGMA or other magnetic

resonance imaging (MRI) datasets around the globe.

As of release v1.1.0, our Toolbox includes 100+ case–control summary statistics from several ENIGMA Working Groups, including 22.q11.2 deletion syndrome, attention deficit hyperactivity

disorder, autism spectrum disorder, bipolar disorder, epilepsy, major depressive disorder, obsessive–compulsive disorder and schizophrenia. These datasets, obtained from standardized and

quality-controlled protocols, represent morphological (for example, subcortical volume, cortical thickness, surface area) case–control effect sizes from previously published meta- and

mega-analyses. Summary statistics from other working groups will be continually added to the Toolbox as they are published.

Our Toolbox is available in Python and Matlab and complemented with expandable online documentation (http://enigma-toolbox.readthedocs.io). Derivative data (for example, summary statistics

from published ENIGMA studies) and codes are openly accessible under the terms of the BSD-3-Clause license at http://github.com/MICA-MNI/ENIGMA. Requests to work on a project with

subject-level data can be proposed to the working group via the chairs (http://enigma.ini.usc.edu/). Users seeking help are encouraged to subscribe and post their questions to the ENIGMA

Toolbox mailing list at https://groups.google.com/g/enigma-toolbox.

Many scientists around the world contributed to ENIGMA but did not take part in the writing of this report. A full list of contributors to ENIGMA is available at

http://enigma.ini.usc.edu/about-2/consortium/members/. The authors would like to express their gratitude to the open science initiatives that made this work possible: (i) the ENIGMA

Consortium (core funding for ENIGMA was provided by the NIH Big Data to Knowledge (BD2K) program under consortium grant U54 EB020403 to P.M.T.), (ii) The Allen Human Brain Atlas and the

abagen toolbox (https://doi.org/10.5281/zenodo.4984124), (iii) BigBrain/HIBALL, and (iv) the Human Connectome Project (principal investigators David Van Essen and Kamil Ugurbil;

1U54MH091657), funded by the 16 NIH institutes and centers that support the NIH Blueprint for Neuroscience Research and by the McDonnell Center for Systems Neuroscience at Washington

University. S.L. acknowledges funding from Fonds de la Recherche du Québec – Santé (FRQ-S) and the Canadian Institutes of Health Research (CIHR). C.P. was funded through a postdoctoral FRQ-S

fellowship. O.B. was funded by a Healthy Brains for Healthy Lives (HBHL) postdoctoral fellowship. B.-y.P. was funded by the National Research Foundation of Korea (NRF-2020R1A6A3A03037088),

a Molson Neuro-Engineering fellowship from the Montreal Neurological Institute and Hospital, and FRQ-S. J.R. was supported by CIHR. R.V.d.W. was funded by studentships from the Savoy

Foundation for Epilepsy and the Richard and Ann Sievers award. S.L.V. was supported by the Otto Hahn award of the Max Planck Society. M.K. acknowledges funding from the Swiss National

Science Foundation (P2SKP3_178175). S.M.S. was supported by the Epilepsy Society, UK. Part of this work was undertaken at University College London Hospitals, which received a proportion of

funding from the NIHR Biomedical Research Centres funding scheme. C.R.M. acknowledges funding from the National Institutes of Health (NINDS R01NS065838 and R21 NS107739). B.C.B. acknowledges

research funding from the SickKids Foundation (NI17-039), the Natural Sciences and Engineering Research Council of Canada (NSERC; Discovery-1304413), CIHR (FDN-154298, PJT-174995), the

Azrieli Center for Autism Research (ACAR), an MNI-Cambridge collaboration grant, salary support from FRQ-S (Chercheur-Boursier), BrainCanada, the Helmholtz BigBrain Analytics and Learning

Lab (Hiball) and the Canada Research Chairs (CRC) Program.

Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada

Sara Larivière, Casey Paquola, Bo-yong Park, Jessica Royer, Yezhou Wang, Oualid Benkarim, Reinder Vos de Wael & Boris C. Bernhardt

Institute of Neuroscience and Medicine (INM-1), Research Center, Jülich, Jülich, Germany

Department of Data Science, Inha University, Incheon, South Korea

Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany

Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA

Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland

McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada

McGill Centre for Integrative Neuroscience, McGill University, Montreal, Quebec, Canada

Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK

Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA

Core developers: S.L., B.C.B. Toolbox beta testing: B.-Y.P., J.R., C.P., S.L.V., Y.W, M.K. Writing: S.L., B.C.B.; revised and approved by other listed co-authors.

P.M.T. received partial grant support from Biogen, Inc., and consulting payments from Kairos Venture Capital, Inc., for work unrelated to ENIGMA and this manuscript.

Peer review information Nature Methods thanks Oscar Esteban, David Van Essen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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