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Genome-wide association analysis of insomnia using data from Partners Biobank

Insomnia is one of the most prevalent and burdensome mental disorders worldwide, affecting between 10–20% of adults and up to 48% of the geriatric population. It is further associated with substance usage and dependence, as well other psychiatric disorders. In this study, we combined electronic heal...

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Autores principales: Song, Wenyu, Torous, John, Kossowsky, Joe, Chen, Chia-Yen, Huang, Hailiang, Wright, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7181749/
https://www.ncbi.nlm.nih.gov/pubmed/32332799
http://dx.doi.org/10.1038/s41598-020-63792-0
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author Song, Wenyu
Torous, John
Kossowsky, Joe
Chen, Chia-Yen
Huang, Hailiang
Wright, Adam
author_facet Song, Wenyu
Torous, John
Kossowsky, Joe
Chen, Chia-Yen
Huang, Hailiang
Wright, Adam
author_sort Song, Wenyu
collection PubMed
description Insomnia is one of the most prevalent and burdensome mental disorders worldwide, affecting between 10–20% of adults and up to 48% of the geriatric population. It is further associated with substance usage and dependence, as well other psychiatric disorders. In this study, we combined electronic health record (EHR) derived phenotypes and genotype information to conduct a genome wide analysis of insomnia in a 18,055 patient cohort. Diagnostic codes were used to identify 3,135 patients with insomnia. Our genome-wide association study (GWAS) identified one novel genomic risk locus on chromosome 8 (lead SNP rs17052966, p = 4.53 × 10(−9), odds ratio = 1.28, se = 0.04). The heritability analysis indicated that common SNPs accounts for 7% (se = 0.02, p = 0.015) of phenotypic variation. We further conducted a large-scale meta-analysis of our results and summary statistics of two recent insomnia GWAS and 13 significant loci were identified. The genetic correlation analysis yielded a strong positive genetic correlation between insomnia and alcohol use (rG = 0.56, se = 0.14, p < 0.001), nicotine use (rG = 0.50, se = 0.12, p < 0.001) and opioid use (rG = 0.43, se = 0.18, p = 0.02) disorders, suggesting a significant common genetic risk factors between insomnia and substance use.
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spelling pubmed-71817492020-04-29 Genome-wide association analysis of insomnia using data from Partners Biobank Song, Wenyu Torous, John Kossowsky, Joe Chen, Chia-Yen Huang, Hailiang Wright, Adam Sci Rep Article Insomnia is one of the most prevalent and burdensome mental disorders worldwide, affecting between 10–20% of adults and up to 48% of the geriatric population. It is further associated with substance usage and dependence, as well other psychiatric disorders. In this study, we combined electronic health record (EHR) derived phenotypes and genotype information to conduct a genome wide analysis of insomnia in a 18,055 patient cohort. Diagnostic codes were used to identify 3,135 patients with insomnia. Our genome-wide association study (GWAS) identified one novel genomic risk locus on chromosome 8 (lead SNP rs17052966, p = 4.53 × 10(−9), odds ratio = 1.28, se = 0.04). The heritability analysis indicated that common SNPs accounts for 7% (se = 0.02, p = 0.015) of phenotypic variation. We further conducted a large-scale meta-analysis of our results and summary statistics of two recent insomnia GWAS and 13 significant loci were identified. The genetic correlation analysis yielded a strong positive genetic correlation between insomnia and alcohol use (rG = 0.56, se = 0.14, p < 0.001), nicotine use (rG = 0.50, se = 0.12, p < 0.001) and opioid use (rG = 0.43, se = 0.18, p = 0.02) disorders, suggesting a significant common genetic risk factors between insomnia and substance use. Nature Publishing Group UK 2020-04-24 /pmc/articles/PMC7181749/ /pubmed/32332799 http://dx.doi.org/10.1038/s41598-020-63792-0 Text en © 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/.
spellingShingle Article
Song, Wenyu
Torous, John
Kossowsky, Joe
Chen, Chia-Yen
Huang, Hailiang
Wright, Adam
Genome-wide association analysis of insomnia using data from Partners Biobank
title Genome-wide association analysis of insomnia using data from Partners Biobank
title_full Genome-wide association analysis of insomnia using data from Partners Biobank
title_fullStr Genome-wide association analysis of insomnia using data from Partners Biobank
title_full_unstemmed Genome-wide association analysis of insomnia using data from Partners Biobank
title_short Genome-wide association analysis of insomnia using data from Partners Biobank
title_sort genome-wide association analysis of insomnia using data from partners biobank
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7181749/
https://www.ncbi.nlm.nih.gov/pubmed/32332799
http://dx.doi.org/10.1038/s41598-020-63792-0
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