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Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort
PURPOSE: Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747788/ https://www.ncbi.nlm.nih.gov/pubmed/35023977 http://dx.doi.org/10.2147/NSS.S326818 |
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author | Yao, Yao Jia, Yumeng Wen, Yan Cheng, Bolun Cheng, Shiqiang Liu, Li Yang, Xuena Meng, Peilin Chen, Yujing Li, Chun’e Zhang, Jingxi Zhang, Zhen Pan, Chuyu Zhang, Huijie Wu, Cuiyan Wang, Xi Ning, Yujie Wang, Sen Zhang, Feng |
author_facet | Yao, Yao Jia, Yumeng Wen, Yan Cheng, Bolun Cheng, Shiqiang Liu, Li Yang, Xuena Meng, Peilin Chen, Yujing Li, Chun’e Zhang, Jingxi Zhang, Zhen Pan, Chuyu Zhang, Huijie Wu, Cuiyan Wang, Xi Ning, Yujie Wang, Sen Zhang, Feng |
author_sort | Yao, Yao |
collection | PubMed |
description | PURPOSE: Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents overall sleep traits. PATIENTS AND METHODS: We conducted a genome-wide association study (GWAS) of sleep health score (overall assessment of sleep duration, snoring, insomnia, chronotype, and daytime dozing) using 336,463 participants from the UK Biobank. Proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) were then performed to identify candidate genes at the protein and mRNA level, respectively. We finally used linkage disequilibrium score regression (LDSC) to estimate the genetic correlations between sleep health score and other functionally relevance traits. RESULTS: GWAS identified multiple variants near known candidate genes associated with sleep health score, such as MEIS1, FBXL13, MED20 and SMAD5. HDHD2 (P(PWAS) = 0.0146) and GFAP (P(PWAS) = 0.0236) were identified associated with sleep health score by PWAS. TWAS identified ORC4 (P(TWAS) = 0.0212) and ZNF732 (P(TWAS) = 0.0349) considering mRNA expression level. LDSC found significant genetic correlations of sleep health score with 3 sleep behaviors (including insomnia, snoring, dozing), 4 psychiatry disorders (major depressive disorder, attention deficit/hyperactivity disorder, schizophrenia, autism spectrum disorder), and 9 plasma protein (such as Stabilin-1, Stromelysin-2, Cytochrome c) (all LDSC P(LDSC) < 0.05). CONCLUSION: Our results advance the comprehensive understanding of the aetiology and genetic architecture of the sleep health score, refine the understanding of the relationship of sleep health score with other traits and diseases, and may serve as potential targets for future mechanistic studies of sleep phenotype. |
format | Online Article Text |
id | pubmed-8747788 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-87477882022-01-11 Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort Yao, Yao Jia, Yumeng Wen, Yan Cheng, Bolun Cheng, Shiqiang Liu, Li Yang, Xuena Meng, Peilin Chen, Yujing Li, Chun’e Zhang, Jingxi Zhang, Zhen Pan, Chuyu Zhang, Huijie Wu, Cuiyan Wang, Xi Ning, Yujie Wang, Sen Zhang, Feng Nat Sci Sleep Original Research PURPOSE: Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents overall sleep traits. PATIENTS AND METHODS: We conducted a genome-wide association study (GWAS) of sleep health score (overall assessment of sleep duration, snoring, insomnia, chronotype, and daytime dozing) using 336,463 participants from the UK Biobank. Proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) were then performed to identify candidate genes at the protein and mRNA level, respectively. We finally used linkage disequilibrium score regression (LDSC) to estimate the genetic correlations between sleep health score and other functionally relevance traits. RESULTS: GWAS identified multiple variants near known candidate genes associated with sleep health score, such as MEIS1, FBXL13, MED20 and SMAD5. HDHD2 (P(PWAS) = 0.0146) and GFAP (P(PWAS) = 0.0236) were identified associated with sleep health score by PWAS. TWAS identified ORC4 (P(TWAS) = 0.0212) and ZNF732 (P(TWAS) = 0.0349) considering mRNA expression level. LDSC found significant genetic correlations of sleep health score with 3 sleep behaviors (including insomnia, snoring, dozing), 4 psychiatry disorders (major depressive disorder, attention deficit/hyperactivity disorder, schizophrenia, autism spectrum disorder), and 9 plasma protein (such as Stabilin-1, Stromelysin-2, Cytochrome c) (all LDSC P(LDSC) < 0.05). CONCLUSION: Our results advance the comprehensive understanding of the aetiology and genetic architecture of the sleep health score, refine the understanding of the relationship of sleep health score with other traits and diseases, and may serve as potential targets for future mechanistic studies of sleep phenotype. Dove 2022-01-06 /pmc/articles/PMC8747788/ /pubmed/35023977 http://dx.doi.org/10.2147/NSS.S326818 Text en © 2022 Yao et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Yao, Yao Jia, Yumeng Wen, Yan Cheng, Bolun Cheng, Shiqiang Liu, Li Yang, Xuena Meng, Peilin Chen, Yujing Li, Chun’e Zhang, Jingxi Zhang, Zhen Pan, Chuyu Zhang, Huijie Wu, Cuiyan Wang, Xi Ning, Yujie Wang, Sen Zhang, Feng Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort |
title | Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort |
title_full | Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort |
title_fullStr | Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort |
title_full_unstemmed | Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort |
title_short | Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort |
title_sort | genome-wide association study and genetic correlation scan provide insights into its genetic architecture of sleep health score in the uk biobank cohort |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747788/ https://www.ncbi.nlm.nih.gov/pubmed/35023977 http://dx.doi.org/10.2147/NSS.S326818 |
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