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Bidirectional genetic overlap between bipolar disorder and intelligence
BACKGROUND: Bipolar disorder (BD) is a highly heritable psychiatric illness exhibiting substantial correlation with intelligence. METHODS: To investigate the shared genetic signatures between BD and intelligence, we utilized the summary statistics from genome-wide association studies (GWAS) to condu...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710050/ https://www.ncbi.nlm.nih.gov/pubmed/36447210 http://dx.doi.org/10.1186/s12916-022-02668-8 |
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author | Shang, Meng-Yuan Wu, Yong Zhang, Chu-Yi Qi, Hao-Xiang Zhang, Qing Huo, Jin-Hua Wang, Lu Wang, Chuang Li, Ming |
author_facet | Shang, Meng-Yuan Wu, Yong Zhang, Chu-Yi Qi, Hao-Xiang Zhang, Qing Huo, Jin-Hua Wang, Lu Wang, Chuang Li, Ming |
author_sort | Shang, Meng-Yuan |
collection | PubMed |
description | BACKGROUND: Bipolar disorder (BD) is a highly heritable psychiatric illness exhibiting substantial correlation with intelligence. METHODS: To investigate the shared genetic signatures between BD and intelligence, we utilized the summary statistics from genome-wide association studies (GWAS) to conduct the bivariate causal mixture model (MiXeR) and conjunctional false discovery rate (conjFDR) analyses. Subsequent expression quantitative trait loci (eQTL) mapping in human brain and enrichment analyses were also performed. RESULTS: Analysis with MiXeR suggested that approximately 10.3K variants could influence intelligence, among which 7.6K variants were correlated with the risk of BD (Dice: 0.80), and 47% of these variants predicted BD risk and intelligence in consistent allelic directions. The conjFDR analysis identified 37 distinct genomic loci that were jointly associated with BD and intelligence with a conjFDR < 0.01, and 16 loci (43%) had the same directions of allelic effects in both phenotypes. Brain eQTL analyses found that genes affected by the “concordant loci” were distinct from those modulated by the “discordant loci”. Enrichment analyses suggested that genes related to the “concordant loci” were significantly enriched in pathways/phenotypes related with synapses and sleep quality, whereas genes associated with the “discordant loci” were enriched in pathways related to cell adhesion, calcium ion binding, and abnormal emotional phenotypes. CONCLUSIONS: We confirmed the polygenic overlap with mixed directions of allelic effects between BD and intelligence and identified multiple genomic loci and risk genes. This study provides hints for the mesoscopic phenotypes of BD and relevant biological mechanisms, promoting the knowledge of the genetic and phenotypic heterogeneity of BD. The essential value of leveraging intelligence in BD investigations is also highlighted. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02668-8. |
format | Online Article Text |
id | pubmed-9710050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-97100502022-12-01 Bidirectional genetic overlap between bipolar disorder and intelligence Shang, Meng-Yuan Wu, Yong Zhang, Chu-Yi Qi, Hao-Xiang Zhang, Qing Huo, Jin-Hua Wang, Lu Wang, Chuang Li, Ming BMC Med Research Article BACKGROUND: Bipolar disorder (BD) is a highly heritable psychiatric illness exhibiting substantial correlation with intelligence. METHODS: To investigate the shared genetic signatures between BD and intelligence, we utilized the summary statistics from genome-wide association studies (GWAS) to conduct the bivariate causal mixture model (MiXeR) and conjunctional false discovery rate (conjFDR) analyses. Subsequent expression quantitative trait loci (eQTL) mapping in human brain and enrichment analyses were also performed. RESULTS: Analysis with MiXeR suggested that approximately 10.3K variants could influence intelligence, among which 7.6K variants were correlated with the risk of BD (Dice: 0.80), and 47% of these variants predicted BD risk and intelligence in consistent allelic directions. The conjFDR analysis identified 37 distinct genomic loci that were jointly associated with BD and intelligence with a conjFDR < 0.01, and 16 loci (43%) had the same directions of allelic effects in both phenotypes. Brain eQTL analyses found that genes affected by the “concordant loci” were distinct from those modulated by the “discordant loci”. Enrichment analyses suggested that genes related to the “concordant loci” were significantly enriched in pathways/phenotypes related with synapses and sleep quality, whereas genes associated with the “discordant loci” were enriched in pathways related to cell adhesion, calcium ion binding, and abnormal emotional phenotypes. CONCLUSIONS: We confirmed the polygenic overlap with mixed directions of allelic effects between BD and intelligence and identified multiple genomic loci and risk genes. This study provides hints for the mesoscopic phenotypes of BD and relevant biological mechanisms, promoting the knowledge of the genetic and phenotypic heterogeneity of BD. The essential value of leveraging intelligence in BD investigations is also highlighted. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02668-8. BioMed Central 2022-11-30 /pmc/articles/PMC9710050/ /pubmed/36447210 http://dx.doi.org/10.1186/s12916-022-02668-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Shang, Meng-Yuan Wu, Yong Zhang, Chu-Yi Qi, Hao-Xiang Zhang, Qing Huo, Jin-Hua Wang, Lu Wang, Chuang Li, Ming Bidirectional genetic overlap between bipolar disorder and intelligence |
title | Bidirectional genetic overlap between bipolar disorder and intelligence |
title_full | Bidirectional genetic overlap between bipolar disorder and intelligence |
title_fullStr | Bidirectional genetic overlap between bipolar disorder and intelligence |
title_full_unstemmed | Bidirectional genetic overlap between bipolar disorder and intelligence |
title_short | Bidirectional genetic overlap between bipolar disorder and intelligence |
title_sort | bidirectional genetic overlap between bipolar disorder and intelligence |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710050/ https://www.ncbi.nlm.nih.gov/pubmed/36447210 http://dx.doi.org/10.1186/s12916-022-02668-8 |
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