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. 2021 Aug 3;12(1):54.
doi: 10.1186/s13229-021-00460-8.

Abnormal sleep physiology in children with 15q11.2-13.1 duplication (Dup15q) syndrome

Affiliations

Abnormal sleep physiology in children with 15q11.2-13.1 duplication (Dup15q) syndrome

Vidya Saravanapandian et al. Mol Autism. .

Abstract

Background: Sleep disturbances in autism spectrum disorder (ASD) represent a common and vexing comorbidity. Clinical heterogeneity amongst these warrants studies of the mechanisms associated with specific genetic etiologies. Duplications of 15q11.2-13.1 (Dup15q syndrome) are highly penetrant for neurodevelopmental disorders (NDDs) such as intellectual disability and ASD, as well as sleep disturbances. Genes in the 15q region, particularly UBE3A and a cluster of GABAA receptor genes, are critical for neural development, synaptic protein synthesis and degradation, and inhibitory neurotransmission. During awake electroencephalography (EEG), children with Dup15q syndrome demonstrate increased beta band oscillations (12-30 Hz) that likely reflect aberrant GABAergic neurotransmission. Healthy sleep rhythms, necessary for robust cognitive development, are also highly dependent on GABAergic neurotransmission. We therefore hypothesized that sleep physiology would be abnormal in children with Dup15q syndrome.

Methods: To test the hypothesis that elevated beta oscillations persist in sleep in Dup15q syndrome and that NREM sleep rhythms would be disrupted, we computed: (1) beta power, (2) spindle density, and (3) percentage of slow-wave sleep (SWS) in overnight sleep EEG recordings from a cohort of children with Dup15q syndrome (n = 15) and compared them to age-matched neurotypical children (n = 12).

Results: Children with Dup15q syndrome showed abnormal sleep physiology with elevated beta power, reduced spindle density, and reduced or absent SWS compared to age-matched neurotypical controls.

Limitations: This study relied on clinical EEG where sleep staging was not available. However, considering that clinical polysomnograms are challenging to collect in this population, the ability to quantify these biomarkers on clinical EEG-routinely ordered for epilepsy monitoring-opens the door for larger-scale studies. While comparable to other human studies in rare genetic disorders, a larger sample would allow for examination of the role of seizure severity, medications, and developmental age that may impact sleep physiology.

Conclusions: We have identified three quantitative EEG biomarkers of sleep disruption in Dup15q syndrome, a genetic condition highly penetrant for ASD. Insights from this study not only promote a greater mechanistic understanding of the pathophysiology defining Dup15q syndrome, but also lay the foundation for studies that investigate the association between sleep and cognition. Abnormal sleep physiology may undermine healthy cognitive development and may serve as a quantifiable and modifiable target for behavioral and pharmacological interventions.

Keywords: Autism; Biomarkers; Dup15q syndrome; EEG; GABAAR; Sleep; Slow wave sleep; Spindles; UBE3A.

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Conflict of interest statement

Shafali S Jeste serves as a consultant for and has received funding from F. Hoffmann-La Roche Ltd. and Yamo Pharmaceuticals. All the other authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Sleep stages (N1 to N3) in children with Dup15q syndrome. Representative 9-s traces of continuous sleep EEG recording from children with Dup15q syndrome depicting vertex waves (field highlighted by blue rectangle) during stage N1 in a 35-month-old patient (A), K-complexes (broad field highlighted by blue rectangles) during stage N2 juxtaposed with sleep spindles (arrow) in a 19-month-old patient (B), asynchronous spindles in the right (hollow arrow) and left (solid arrow) frontocentral electrodes during stage N2 in a 54-month-old patient (C) and slow-wave sleep during stage N3 in a 35-month-old patient (D)
Fig. 2
Fig. 2
Persistent overnight beta oscillations in Dup15q syndrome. Time–frequency plot derived from 7 h of overnight sleep EEG from a 19-month-old representative Dup15q syndrome participant (A) and a 19-month-old representative neurotypical (NT) participant (B). Beta power (absolute power) dynamics plotted across the night in the 19-month-old participant with Dup15q syndrome (C) and in the 19-month-old NT participant (D)
Fig. 3
Fig. 3
Elevated beta power in sleep in children with Dup15q syndrome. 6 s of continuous sleep EEG recording from a 19-month-old Dup15q participant (A). A scalp map showing standard 10–20 EEG electrode placements on the scalp, with channel groups of interest highlighted (frontal: yellow, central: red and occipital: blue) (B). Dot plots of absolute beta power (12–30 Hz) averaged across overnight sleep EEG, in the Dup15q syndrome group (turquoise: participants with no epilepsy, orange: participants with epilepsy) and the NT group (black), plotted for each channel group (C)
Fig. 4
Fig. 4
Reduced sleep spindle density in children with Dup15q syndrome. Dot plots of average spindle density in participants in the Dup15q syndrome group (turquoise: participants with no epilepsy, orange: participants with epilepsy) and the NT group (black), using automated spindle detection (A) and manual spindle detection (B) methods
Fig. 5
Fig. 5
Reduced SWS in children with Dup15q syndrome. Delta (1–4 Hz) power dynamics across 7 h of overnight EEG from a 19-month-old Dup15q syndrome participant (A) and a 19-month-old NT participant (B), scored for high delta cycles (black) and low delta cycles (blue). Dot plots of percentage of SWS in participants in the Dup15q syndrome group (turquoise: participants with no epilepsy, orange: participants with epilepsy) and the NT group (black), using automated SWS quantification (C) and manual SWS quantification (D) methods. Different channel groups are highlighted in different colors (frontal: yellow, central: red and occipital: blue)

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