Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep

Modulating social learning-induced evaluation updating during human sleep

People often change their evaluations upon learning about their peers' evaluations, i.e., social learning. Given sleep's vital role in consolidating daytime experiences, sleep may facilitate social learning, thereby further changing people's evaluations. Combining a social learning task and the sleep-based targeted memory reactivation technique, we asked whether social learning-induced evaluation updating can be modulated during sleep. After participants had indicated their initial evaluation of snacks, they learned about their peers' evaluations while hearing the snacks' spoken names. During the post-learning non-rapid-eye-movement sleep, we re-played half of the snack names (i.e., cued snack) to reactivate the associated peers' evaluations. Upon waking up, we found that the social learning-induced evaluation updating further enlarged for both cued and uncued snacks. Examining sleep electroencephalogram (EEG) activity revealed that cue-elicited delta-theta EEG power and the overnight N2 sleep spindle density predicted post-sleep evaluation updating for cued but not for uncued snacks. These findings underscore the role of sleep-mediated memory reactivation and the associated neural activity in supporting social learning-induced evaluation updating.

Using scalp EEG to predict seizure recurrence and electrical status epilepticus in children with idiopathic focal epilepsy

PURPOSE

Some individuals with idiopathic focal epilepsy (IFE) experience recurring seizures accompanied by the evolution of electrical status epilepticus during sleep (ESES). Here, we aimed to develop a predictor for the early detection of seizure recurrence with ESES in children with IFE using resting state electroencephalogram (EEG) data.

METHODS

The study group included 15 IFE patients who developed seizure recurrence with ESES. There were 17 children in the control group who did not experience seizure recurrence with ESES during at least 2-year follow-up. We used the degree value of the partial directed coherence (PDC) from the EEG data to predict seizure recurrence with ESES via 6 machine learning (ML) algorithms.

RESULTS

Among the models, the Xgboost Classifier (XGBC) model achieved the highest specificity of 0.90, and a remarkable sensitivity and accuracy of 0.80 and 0.85, respectively. The CATC showed balanced performance with a specificity of 0.85, sensitivity of 0.73, and an accuracy of 0.80, with an AUC equal to 0.78. For both of these models, F4, Fz and T4 were the overlaps of the top 4 features.

CONCLUSIONS

Considering its high classification accuracy, the XGBC model is an effective and quantitative tool for predicting seizure recurrence with ESES evolution in IFE patients. We developed an ML-based tool for predicting the development of IFE using resting state EEG data. This could facilitate the diagnosis and treatment of patients with IFE.

Factors associated with sleep disturbances in children and adolescents with Angelman Syndrome

BACKGROUND

Angelman Syndrome (AS) is a rare genetic disorder characterised by hyperactivity, overexcitability, developmental delays, and lack of speech.

METHODS

This study used secondary data analysis to investigate sleep disturbances in children and adolescents (n = 212) who are enrolled in the Global Angelman Syndrome Registry. Participants were divided into two groups based on the presence or absence of sleep disturbance. The cut-off score of 40 on the Sleep Disturbance Scale for Children was used to indicate the presence or absence of sleep disturbances. Sleep disturbances and their association with co-occurring conditions were examined regarding challenging behaviour, language and communication, infancy history, gastrointestinal symptoms, and epilepsy. Multiple regression was then conducted to investigate possible predictors for sleep disturbances.

RESULTS

Children and adolescents with AS, with and without sleep disturbances, differed considerably regarding anxiety. Sleep disturbances were significantly associated with an ability to use spoken words and computerised communication devices, and anxiety was a predictor of sleep disturbances.

CONCLUSION

Future research is necessary to replicate this novel research, and to advance the clinical treatment of sleep disturbances in children and adolescents with AS.

Neural hyperexcitability in Angelman syndrome: Genetic factors and pharmacologic treatment approaches

Angelman syndrome (AS) is a rare neurodevelopmental disorder that is typically caused by deletion or a loss-of-function mutation of the maternal copy of the ubiquitin ligase E3A (UBE3A) gene. The disorder is characterized by severe intellectual disability, deficits in speech, motor abnormalities, altered electroencephalography (EEG) activity, spontaneous epileptic seizures, sleep disturbances, and a happy demeanor with frequent laughter. Regarding electrophysiologic abnormalities in particular, enhanced delta oscillatory power and an elevated excitatory/inhibitory (E/I) ratio have been documented in AS, with E/I ratio especially studied in rodent models. These electrophysiologic characteristics appear to relate with the greatly elevated rates of epilepsy in individuals with AS, and associated hypersynchronous neural activity. Here we briefly review findings on EEG, E/I ratio, and epileptic seizures in AS, including data from rodent models of the disorder. We summarize pharmacologic approaches that have been used to treat behavioral aspects of AS, including neuropsychiatric phenomena and sleep disturbances, as well as seizures in the context of the disorder. Antidepressants such as SSRIs and atypical antipsychotics are among the medications that have been used behaviorally, whereas anticonvulsant drugs such as valproic acid and lamotrigine have frequently been used to control seizures in AS. We end by suggesting novel uses for some existing pharmacologic agents in AS, including noradrenergic transmission reducing drugs (alpha2 agonists, beta blockers, alpha1 antagonists) and cholinesterase inhibitors, where these various classes of drugs may have the ability to ameliorate both behavioral disturbances and seizures.

Behavioural sleep problems in children and adults with intellectual disabilities: An integrative literature review

BACKGROUND

People with intellectual disabilities are more likely to experience sleep problems, which can affect quality of life, physical health, mental health and well-being.

METHODS

An integrative literature review was conducted to investigate what is known about behavioural sleep disturbances in people with an intellectual disability. The search used the following databases: Scopus, PsycInfo and Cinahl, to find papers published since 2015.

RESULTS

Within intellectual disability research, sleep appears as a common issue due to its high prevalence, negative relationships with an individual's physical and mental health, their quality of life, and impact of sleep problems on family or carers. The growing evidence base appears to support the use of behavioural, lifestyle and pharmacological interventions to improve sleep in people with an intellectual disability.

CONCLUSION

A wide array of literature provides evidence that people with intellectual disabilities are affected by and need support with their sleep.

Emerging concepts involving inhibitory and activating RNA functionalization towards the understanding of microcephaly phenotypes and brain diseases in humans

Microcephaly is characterized as a small head circumference, and is often accompanied by developmental disorders. Several candidate risk genes for this disease have been described, and mutations in non-coding regions are occasionally found in patients with microcephaly. Various non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), SINEUPs, telomerase RNA component (TERC), and promoter-associated lncRNAs (pancRNAs) are now being characterized. These ncRNAs regulate gene expression, enzyme activity, telomere length, and chromatin structure through RNA binding proteins (RBPs)-RNA interaction. Elucidating the potential roles of ncRNA-protein coordination in microcephaly pathogenesis might contribute to its prevention or recovery. Here, we introduce several syndromes whose clinical features include microcephaly. In particular, we focus on syndromes for which ncRNAs or genes that interact with ncRNAs may play roles. We discuss the possibility that the huge ncRNA field will provide possible new therapeutic approaches for microcephaly and also reveal clues about the factors enabling the evolutionary acquisition of the human-specific "large brain."