Abstracts

Rationale: Rett Syndrome is a severe neurodevelopmental disease associated with mutations in the methyl-CpG-binding protein 2 gene resulting in X inactivation of the protein. Sleep problems are commonly reported in Rett syndrome; however the electroencephalographic (EEG) biomarkers underlying sleep dysfunction are poorly understood. Previous studies on the characteristics of disturbed sleep/wake patterns in children with RTT have yielded inconsistent findings and age-dependent temporal progressions are not clear. The aim of this study was to analyze the temporal evolution of quantitative EEG (qEEG) biomarkers in overnight EEGs recorded from girls diagnosed with RTT using a non-traditional automated protocol.Methods: EEG spectral analysis identified high delta power cycles representing slow wave sleep (SWS) in 8-9h overnight sleep EEGs from the frontal, central and occipital leads (AP axis), comparing age-matched girls with and without RTT. Algorithms written in R stats quantitated the area under the curve (AUC) within identified SWS cycles for each spectral frequency wave form.Results: Both age-matched RTT and control EEGs showed similar trends for recorded delta wave power in the EEG leads along the antero-posterior axis with occipital leads showing the highest delta wave power for ages 2-9 yrs. RTT EEGs had significantly less number of SWS sleep cycles compared to controls. In contrast, the AUC for delta power within each SWS cycle was significantly heightened in RTT compared to controls. Additionally, consecutive SWS delta-power cycles in age-matched controls showed a significant decline which was lost in RTT. The heightened delta-power remained heightened overnight. When correlated to the clinical syndrome severity, incidence of seizures in girls with RTT was associated with significantly lower number of SWS cycles.Conclusions: This qEEG study demonstrates that in addition to SWS deficits, heightened delta power is a biomarker of the sleep dysfunction associated with RTT. The temporal quantification of this SWS dysfunction may help in evaluating the efficacy of novel interventional treatments for RTT and on the quality and evolution of sleep in RTT.