- Title
- Pairwise common variant meta-analyses of schizophrenia with other psychiatric disorders reveals shared and distinct gene and gene-set associations
- Creator
- Reay, William R.; Cairns, Murray J.
- Relation
- NHMRC.1188493 http://purl.org/au-research/grants/nhmrc/1128493
- Relation
- Translational Psychiatry Vol. 10, no. 134
- Publisher Link
- http://dx.doi.org/10.1038/s41398-020-0817-7
- Publisher
- Nature Publishing Group
- Resource Type
- journal article
- Date
- 2020
- Description
- The complex aetiology of schizophrenia is postulated to share components with other psychiatric disorders. We investigated pleiotropy amongst the common variant genomics of schizophrenia and seven other psychiatric disorders using a multimarker association test. Transcriptomic imputation was then leveraged to investigate the functional significance of variation mapped to these genes, prioritising several interesting functional candidates. Gene-based analysis of common variation revealed 67 schizophrenia-associated genes shared with other psychiatric phenotypes, including bipolar disorder, major depressive disorder, ADHD and autism-spectrum disorder. In addition, we uncovered 78 genes significantly enriched with common variant associations for schizophrenia that were not linked to any of these seven disorders (P > 0.05). Multivariable gene-set association suggested that common variation enrichment within biologically constrained genes observed for schizophrenia also occurs across several psychiatric phenotypes. Pairwise meta-analysis of schizophrenia and each psychiatric phenotype was implemented and identified 330 significantly associated genes (PMeta < 2.7 × 10−6) that were only nominally associated with each disorder individually (P < 0.05). These analyses consolidate the overlap between the genomic architecture of schizophrenia and other psychiatric disorders, uncovering several candidate pleiotropic genes which warrant further investigation.
- Subject
- schizophrenia; psychiatric disorders; pleiotropy; gene-based analysis
- Identifier
- http://hdl.handle.net/1959.13/1456297
- Identifier
- uon:45203
- Identifier
- ISSN:2158-3188
- Rights
- © 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/.
- Language
- eng
- Full Text
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