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

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 and R. Stickgold
Additional contact information
S. M. Purcell: Brigham and Women’s Hospital
D. S. Manoach: Harvard Medical School
C. Demanuele: Harvard Medical School
B. E. Cade: Brigham and Women's Hospital
S. Mariani: Brigham and Women's Hospital
R. Cox: Harvard Medical School
G. Panagiotaropoulou: Harvard Medical School
R. Saxena: Center for Human Genetic Research, Massachusetts General Hospital
J. Q. Pan: Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT
J. W. Smoller: Harvard Medical School
S. Redline: Harvard Medical School
R. Stickgold: Harvard Medical School

Nature Communications, 2017, vol. 8, issue 1, 1-16

Abstract: 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.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15930

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DOI: 10.1038/ncomms15930

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