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Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource

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  • S. M. Purcell

    (Brigham and Women’s Hospital
    Harvard Medical School
    Icahn School of Medicine at Mount Sinai)

  • D. S. Manoach

    (Harvard Medical School
    Massachusetts General Hospital
    Athinoula A. Martinos Center for Biomedical Imaging)

  • C. Demanuele

    (Harvard Medical School
    Massachusetts General Hospital
    Athinoula A. Martinos Center for Biomedical Imaging)

  • B. E. Cade

    (Brigham and Women's Hospital
    Harvard Medical School)

  • S. Mariani

    (Brigham and Women's Hospital
    Harvard Medical School)

  • R. Cox

    (Harvard Medical School
    Beth Israel Deaconess Medical Center)

  • G. Panagiotaropoulou

    (Harvard Medical School
    Massachusetts General Hospital
    Athinoula A. Martinos Center for Biomedical Imaging)

  • R. Saxena

    (Center for Human Genetic Research, Massachusetts General Hospital
    Critical Care and Pain Medicine, Massachusetts General Hospital
    Program in Medical and Population Genetics, Broad Institute)

  • J. Q. Pan

    (Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT)

  • J. W. Smoller

    (Harvard Medical School
    Massachusetts General Hospital
    Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital)

  • S. Redline

    (Harvard Medical School
    Brigham and Women's Hospital
    Harvard Medical School)

  • R. Stickgold

    (Harvard Medical School
    Beth Israel Deaconess Medical Center)

Abstract

Sleep spindles are characteristic electroencephalogram (EEG) signatures of stage 2 non-rapid eye movement sleep. Implicated in sleep regulation and cognitive functioning, spindles may represent heritable biomarkers of neuropsychiatric disease. Here we characterize spindles in 11,630 individuals aged 4 to 97 years, as a prelude to future genetic studies. Spindle properties are highly reliable but exhibit distinct developmental trajectories. Across the night, we observe complex patterns of age- and frequency-dependent dynamics, including signatures of circadian modulation. We identify previously unappreciated correlates of spindle activity, including confounding by body mass index mediated by cardiac interference in the EEG. After taking account of these confounds, genetic factors significantly contribute to spindle and spectral sleep traits. Finally, we consider topographical differences and critical measurement issues. Taken together, our findings will lead to an increased understanding of the genetic architecture of sleep spindles and their relation to behavioural and health outcomes, including neuropsychiatric disorders.

Suggested Citation

  • S. M. Purcell & D. S. Manoach & C. Demanuele & B. E. Cade & S. Mariani & R. Cox & G. Panagiotaropoulou & R. Saxena & J. Q. Pan & J. W. Smoller & S. Redline & R. Stickgold, 2017. "Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource," Nature Communications, Nature, vol. 8(1), pages 1-16, August.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15930
    DOI: 10.1038/ncomms15930
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    Cited by:

    1. Xunda Wang & Alex T. L. Leong & Shawn Z. K. Tan & Eddie C. Wong & Yilong Liu & Lee-Wei Lim & Ed X. Wu, 2023. "Functional MRI reveals brain-wide actions of thalamically-initiated oscillatory activities on associative memory consolidation," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    2. Lainey E. Hunnicutt & Makenzie Corgan & Sarah R. Brown & Alyssa Nygaard & George Lesley Meares & Scott R. Collier, 2024. "Sleep Differences in Firefighters: Barracks vs. Home," IJERPH, MDPI, vol. 21(9), pages 1-8, August.

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