Abstract:
OBJECTIVE: The purpose of the study was to evaluate quantitative sleep electroencephalogram (EEG) frequencies in monozygotic twins discordant for chronic fatigue syndrome.
METHODS: Thirteen pairs of female twins underwent polysomnography. During the first night, they adapted to the sleep laboratory, and during the second night, their baseline sleep was assessed. Visual stage scoring was conducted on sleep electroencephalographic records according to standard criteria, and power spectral analysis was used to quantify delta through beta frequency bands, processed in 6-s blocks. Data were averaged across sleep stage within each twin and coded for sleep stage and the presence or absence of chronic fatigue syndrome (CFS). A completely within-subjects repeated measure multivariate analysis of variance evaluated twin pairs by frequency band by sleep stage interactions and simple effects. The relationship between alpha and delta EEG was also assessed across twin pairs.
RESULTS: No significant differences in spectral power in any frequency band were found between those with CFS and their nonfatigued cotwins. Phasic alpha activity, coupled with delta was noted in five subjects with CFS but was also present in 4/5 healthy twins, indicating this finding likely reflects genetic influences on the sleep electroencephalogram rather than disease-specific sleep pathology.
CONCLUSIONS: The genetic influences on sleep polysomnography and microarchitecture appear to be stronger than the disease influence of chronic fatigue syndrome, despite greater subjective sleep complaint among the CFS twins. EEG techniques that focus on short duration events or paradigms that probe sleep regulation may provide a better description of sleep abnormalities in CFS.
Source: Armitage R, Landis C, Hoffmann R, Lentz M, Watson N, Goldberg J, Buchwald D. Power spectral analysis of sleep EEG in twins discordant for chronic fatigue syndrome. J Psychosom Res. 2009 Jan;66(1):51-7. doi: 10.1016/j.jpsychores.2008.08.004. Epub 2008 Nov 25. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2634600/ (Full article)