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Nat Commun. 2017 Jun 26;8:15930. doi: 10.1038/ncomms15930.

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

Author information

1
Department of Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.
2
Harvard Medical School, Boston, Massachusetts 02115, USA.
3
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
4
Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
5
Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129, USA.
6
Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.
7
Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA.
8
Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215, USA.
9
Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
10
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
11
Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA.
12
Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.
13
Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.

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.

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