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The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function
Genome-wide association studies (GWAS) of psychiatric phenotypes have tended to focus on categorical diagnoses, but to understand the biology of mental illness it may be more useful to study traits which cut across traditional boundaries. Here we report the results of a GWAS of mood instability as a...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116257/ https://www.ncbi.nlm.nih.gov/pubmed/31168069 http://dx.doi.org/10.1038/s41380-019-0439-8 |
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author | Ward, Joey Tunbridge, Elizabeth M. Sandor, Cynthia Lyall, Laura M. Ferguson, Amy Strawbridge, Rona J. Lyall, Donald M. Cullen, Breda Graham, Nicholas Johnston, Keira J.A. Webber, Caleb Escott-Price, Valentina O’Donovan, Michael Pell, Jill P. Bailey, Mark E.S. Harrison, Paul J. Smith, Daniel J. |
author_facet | Ward, Joey Tunbridge, Elizabeth M. Sandor, Cynthia Lyall, Laura M. Ferguson, Amy Strawbridge, Rona J. Lyall, Donald M. Cullen, Breda Graham, Nicholas Johnston, Keira J.A. Webber, Caleb Escott-Price, Valentina O’Donovan, Michael Pell, Jill P. Bailey, Mark E.S. Harrison, Paul J. Smith, Daniel J. |
author_sort | Ward, Joey |
collection | PubMed |
description | Genome-wide association studies (GWAS) of psychiatric phenotypes have tended to focus on categorical diagnoses, but to understand the biology of mental illness it may be more useful to study traits which cut across traditional boundaries. Here we report the results of a GWAS of mood instability as a trait in a large population cohort (UK Biobank, n = 363,705). We also assess the clinical and biological relevance of the findings, including whether genetic associations show enrichment for nervous system pathways. Forty six unique loci associated with mood instability were identified with a SNP heritability estimate of 9%. Linkage Disequilibrium Score Regression (LDSR) analyses identified genetic correlations with Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizophrenia, anxiety and Post Traumatic Stress Disorder (PTSD). Gene-level and gene set analyses identified 244 significant genes and 6 enriched gene sets. Tissue expression analysis of the SNP-level data found enrichment in multiple brain regions, and eQTL analyses highlighted an inversion on chromosome 17 plus two brain-specific eQTLs. Additionally, we used a Phenotype Linkage Network (PLN) analysis and community analysis to assess for enrichment of nervous system gene sets using mouse orthologue databases. The PLN analysis found enrichment in nervous system PLNs for a community containing serotonin and melatonin receptors. In summary, this work has identified novel loci, tissues and gene sets contributing to mood instability. These findings may be relevant for the identification of novel trans-diagnostic drug targets and could help to inform future precision medicine innovations in mental health. |
format | Online Article Text |
id | pubmed-7116257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71162572020-10-23 The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function Ward, Joey Tunbridge, Elizabeth M. Sandor, Cynthia Lyall, Laura M. Ferguson, Amy Strawbridge, Rona J. Lyall, Donald M. Cullen, Breda Graham, Nicholas Johnston, Keira J.A. Webber, Caleb Escott-Price, Valentina O’Donovan, Michael Pell, Jill P. Bailey, Mark E.S. Harrison, Paul J. Smith, Daniel J. Mol Psychiatry Article Genome-wide association studies (GWAS) of psychiatric phenotypes have tended to focus on categorical diagnoses, but to understand the biology of mental illness it may be more useful to study traits which cut across traditional boundaries. Here we report the results of a GWAS of mood instability as a trait in a large population cohort (UK Biobank, n = 363,705). We also assess the clinical and biological relevance of the findings, including whether genetic associations show enrichment for nervous system pathways. Forty six unique loci associated with mood instability were identified with a SNP heritability estimate of 9%. Linkage Disequilibrium Score Regression (LDSR) analyses identified genetic correlations with Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizophrenia, anxiety and Post Traumatic Stress Disorder (PTSD). Gene-level and gene set analyses identified 244 significant genes and 6 enriched gene sets. Tissue expression analysis of the SNP-level data found enrichment in multiple brain regions, and eQTL analyses highlighted an inversion on chromosome 17 plus two brain-specific eQTLs. Additionally, we used a Phenotype Linkage Network (PLN) analysis and community analysis to assess for enrichment of nervous system gene sets using mouse orthologue databases. The PLN analysis found enrichment in nervous system PLNs for a community containing serotonin and melatonin receptors. In summary, this work has identified novel loci, tissues and gene sets contributing to mood instability. These findings may be relevant for the identification of novel trans-diagnostic drug targets and could help to inform future precision medicine innovations in mental health. 2020-11-01 2019-06-05 /pmc/articles/PMC7116257/ /pubmed/31168069 http://dx.doi.org/10.1038/s41380-019-0439-8 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Ward, Joey Tunbridge, Elizabeth M. Sandor, Cynthia Lyall, Laura M. Ferguson, Amy Strawbridge, Rona J. Lyall, Donald M. Cullen, Breda Graham, Nicholas Johnston, Keira J.A. Webber, Caleb Escott-Price, Valentina O’Donovan, Michael Pell, Jill P. Bailey, Mark E.S. Harrison, Paul J. Smith, Daniel J. The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function |
title | The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function |
title_full | The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function |
title_fullStr | The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function |
title_full_unstemmed | The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function |
title_short | The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function |
title_sort | genomic basis of mood instability: identification of 46 loci in 363,705 uk biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116257/ https://www.ncbi.nlm.nih.gov/pubmed/31168069 http://dx.doi.org/10.1038/s41380-019-0439-8 |
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