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. 2020 May 12;10:134. doi: 10.1038/s41398-020-0817-7

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© The Author(s) 2020

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 — a Gene-based aggregation of variant-wise common variant associations was performed using the MAGMA approach for schizophrenia (SZ), along with seven additional psychiatric disorders: bipolar disorder (BIP), attention-deficit/hyperactivity disorder (ADHD), eating disorder (ED), Tourette’s syndrome (TS), obsessive compulsive disorder (OCD), autism-spectrum disorder (ASD) and major depressive disorder (MDD). Genes were firstly selected which survived Bonferroni correction in the schizophrenia dataset along with at least one of the other disorders. Secondly, we identified a subset of genes associated with schizophrenia which did not display uncorrected nominal significance (P > 0.05) with any of the other seven phenotypes. Transcriptomic imputation (TWAS) was leveraged to investigate the correlation between imputed models of genetically regulated expression to explore the functional significance of variation affecting the (i) shared genes and (ii) genes only associated with schizophrenia. b A pairwise gene-based meta-analysis was performed between SZ and each disorder separately to identify significant genes which were not uncovered by analysing the respective phenotypes individually.