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GWAS identifies 14 loci for device-measured physical activity and sleep duration

Author

Listed:
  • Aiden Doherty

    (University of Oxford
    University of Oxford
    University of Oxford
    Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital)

  • Karl Smith-Byrne

    (University of Oxford)

  • Teresa Ferreira

    (University of Oxford
    University of Oxford)

  • Michael V. Holmes

    (Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital
    University of Oxford
    University of Oxford)

  • Chris Holmes

    (University of Oxford
    University of Oxford)

  • Sara L. Pulit

    (University of Oxford
    University of Oxford
    University Medical Center Utrecht
    Broad Institute)

  • Cecilia M. Lindgren

    (University of Oxford
    Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital
    University of Oxford
    Broad Institute)

Abstract

Physical activity and sleep duration are established risk factors for many diseases, but their aetiology is poorly understood, partly due to relying on self-reported evidence. Here we report a genome-wide association study (GWAS) of device-measured physical activity and sleep duration in 91,105 UK Biobank participants, finding 14 significant loci (7 novel). These loci account for 0.06% of activity and 0.39% of sleep duration variation. Genome-wide estimates of ~ 15% phenotypic variation indicate high polygenicity. Heritability is higher in women than men for overall activity (23 vs. 20%, p = 1.5 × 10−4) and sedentary behaviours (18 vs. 15%, p = 9.7 × 10−4). Heritability partitioning, enrichment and pathway analyses indicate the central nervous system plays a role in activity behaviours. Two-sample Mendelian randomisation suggests that increased activity might causally lower diastolic blood pressure (beta mmHg/SD: −0.91, SE = 0.18, p = 8.2 × 10−7), and odds of hypertension (Odds ratio/SD: 0.84, SE = 0.03, p = 4.9 × 10−8). Our results advocate the value of physical activity for reducing blood pressure.

Suggested Citation

  • Aiden Doherty & Karl Smith-Byrne & Teresa Ferreira & Michael V. Holmes & Chris Holmes & Sara L. Pulit & Cecilia M. Lindgren, 2018. "GWAS identifies 14 loci for device-measured physical activity and sleep duration," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-07743-4
    DOI: 10.1038/s41467-018-07743-4
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    Cited by:

    1. Xinyue Li & Hongyu Zhao, 2020. "Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms," PLOS Genetics, Public Library of Science, vol. 16(10), pages 1-22, October.
    2. Thomas G. Brooks & Nicholas F. Lahens & Gregory R. Grant & Yvette I. Sheline & Garret A. FitzGerald & Carsten Skarke, 2023. "Diurnal rhythms of wrist temperature are associated with future disease risk in the UK Biobank," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Alyse Davies & Margaret Allman-Farinelli & Katherine Owen & Louise Signal & Cameron Hosking & Leanne Wang & Adrian Bauman, 2020. "Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data," IJERPH, MDPI, vol. 17(24), pages 1-13, December.

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