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. 2018 Jun 8;8:114. doi: 10.1038/s41398-018-0166-y

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — The first stage of the analysis (Training) was deriving neuroanatomical scores based on case-control data, using a methodology which has been published elsewhere²⁴. The second stage of the analysis (Candidate Region Associations) is the focus of this paper, wherein we directly apply the neuroanatomical scores from large-scale imaging genetic cohorts without further calibration of the model parameters