Abstract
The trait-like nature of electroencephalogram (EEG) is well established. Furthermore, EEG of wake and non-rapid eye movement (non-REM) sleep has been shown to be highly heritable. However, the genetic effects on REM sleep EEG microstructure are as yet unknown. REM sleep is of special interest since animal and human data suggest a connection between REM sleep abnormalities and the pathophysiology of psychiatric and neurological diseases. Here we report the results of a study in monozygotic (MZ) and dizygotic (DZ) twins examining the heritability of REM sleep EEG. We studied the architecture, spectral composition and phasic parameters of REM sleep and identified genetic effects on whole investigated EEG frequency spectrum as well as phasic REM parameters (REM density, REM activity and organization of REMs in bursts). In addition, cluster analysis based on the morphology of the EEG frequency spectrum revealed that the similarity among MZ twins is close to intra-individual stability. The observed strong genetic effects on REM sleep characteristics establish REM sleep as an important source of endophenotypes for psychiatric and neurological diseases.
Highlights
Trait-like characteristics of human electroencephalographic (EEG)recordings have been extensively studied
We observed a significant effect of both age and gender on rapid eye movement (REM) sleep duration
REM sleep was longer in younger subjects and withinpair similarity of REM sleep duration was higher in female twins
Summary
Trait-like characteristics of human electroencephalographic (EEG)recordings have been extensively studied. Seminal work by Feinberg and colleagues on sleep EEG has established substantial inter-individual variability and high intra-individual stability of both non-rapid eye movement (non-REM) and REM sleep spectral composition.[5,6,7] Subsequent studies revealed that after sleep deprivation sleep architecture shows considerable trait inter-individual variability[8] and non-REM sleep power spectrum remains substantially invariant.[9] it was shown that the topography of EEG spectral power during nonREM sleep[10] as well as the EEG spectral pattern during wakefulness,[11] non-REM and REM sleep[12,13] have fingerprint-like characteristics, that is, recordings of each subject cluster together with high accuracy. The duration of slow wave sleep, stage 2 sleep as well as REM density (RD) were shown to be genetically determined, whereas results concerning the duration of REM sleep were inconclusive.[17,18,19]
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