Genome-wide association analysis of composite sleep health scores in 413,904 individuals

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Abstract

Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, and together may provide a more complete picture of sleep health, while also illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches. GWASs of these six SHSs identify 28 significant novel loci adjusting for multiple testing on six traits (p<8.3e-9), along with 341 previously reported loci (p<5e-08). The heritability of the first three SHS-PCs equals or exceeds that of SHS-ADD (SNP-h ²=0.094), while revealing sleep-domain-specific genetic discoveries. Significant loci enrich in multiple brain tissues and in metabolic and neuronal pathways. Post GWAS analyses uncover novel genetic mechanisms underlying sleep health and reveal connections to behavioral, psychological, and cardiometabolic traits.

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Proteomics. Tissue-based map of the human proteome.

Mathias Uhlén, Linn Fagerberg, Björn Hallström … (2015)

Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body. Copyright © 2015, American Association for the Advancement of Science.

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UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

Cathie Sudlow, John Gallacher, Naomi Allen … (2017)

Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.

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The UK Biobank resource with deep phenotyping and genomic data

Clare Bycroft, Colin Freeman, Desislava Petkova … (2018)

The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

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Journal

Journal ID (nlm-ta): medRxiv

Journal ID (publisher-id): MEDRXIV

Title: medRxiv

Publisher: Cold Spring Harbor Laboratory

Publication date (Electronic): 03 February 2024

Electronic Location Identifier: 2024.02.02.24302211

Affiliations

[1. ] Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA.

[2. ]Department of Neurology and Medicine, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA.

[3. ]Broad Institute, Cambridge, MA, USA.

[4. ]Instituto de Psicología Clínica, Facultad de Psicología, Universidad de la República, Montevideo, Uruguay.

[5. ]MRC Unit for Lifelong Health & Ageing, Institute of Cardiovascular Science, University College London, London, United Kingdom.

[6. ]Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

[7. ]Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.

[8. ]Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA

[9. ]Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA, USA.

[10. ]Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.

[11. ]Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands

[12. ]School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.

[13. ]Sir Jules Thorn Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

[14. ]Department of Psychiatry and Psychotherapy, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

[15. ]Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK

[16. ]MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK

[17. ]Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK

[18. ]The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.

[19. ]Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.

[20. ]Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

[21. ]Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

[22. ]Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester, UK.

Author notes

Corresponding author: Heming Wang, PhD, Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Harvard Medical, School, 221 Longwood Ave BLI 252, Boston, MA 02115, hwang@ 123456bwh.harvard.edu , Tel: +1 617 732 4440

Author information

Brian E Cade http://orcid.org/0000-0003-1424-0673

Shaun M Purcell http://orcid.org/0000-0002-7402-5812

Heming Wang http://orcid.org/0000-0002-1486-7495

Article

DOI: 10.1101/2024.02.02.24302211

PMC ID: 10863010

PubMed ID: 38352337

SO-VID: 19952d28-e65d-4ffb-8a9e-8de55a90b7f9

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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Genome-wide association analysis of composite sleep health scores in 413,904 individuals

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Most cited references 72

Proteomics. Tissue-based map of the human proteome.

UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

The UK Biobank resource with deep phenotyping and genomic data

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