Abnormal coherence and sleep composition in children with Angelman syndrome: a retrospective EEG study

A clinical-translational review of sleep problems in neurodevelopmental disabilities

Sleep disorders are very common across neurodevelopmental disorders and place a large burden on affected children, adolescents, and their families. Sleep disturbances seem to involve a complex interplay of genetic, neurobiological, and medical/environmental factors in neurodevelopmental disorders. In this review, we discuss animal models of sleep problems and characterize their presence in two single gene disorders, Rett Syndrome, and Angelman Syndrome and two more commonly occurring neurodevelopmental disorders, Down Syndrome, and autism spectrum disorders. We then discuss strategies for novel methods of assessment using wearable sensors more broadly for neurodevelopmental disorders in general, including the importance of analytical validation. An increased understanding of the mechanistic contributions and potential biomarkers of disordered sleep may offer quantifiable targets for interventions that improve overall quality of life for affected individuals and their families.

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.

Sleep disturbance in Angelman syndrome patients

Angelman syndrome (AS) is a neurodevelopmental disorder caused by abnormal expression of the maternal ubiquitin protein ligase E3A gene (UBE3A). As one of the most challenging symptoms and important focuses of new treatment, sleep disturbance is reported to occur in 70-80% of patients with AS and has a serious impact on the lives of patients and their families. Although clinical studies and animal model studies have provided some clues, recent research into sleep disorders in the context of AS is still very limited. It is generally accepted that there is an interaction between neurodevelopment and sleep; however, there is no recognized mechanism for sleep disorders in AS patients. Accordingly, there are no aetiologically specific clinical treatments for AS-related sleep disorders. The most common approaches involve ameliorating symptoms through methods such as behavioural therapy and symptomatic pharmacotherapy. In recent years, preclinical and clinical studies on the targeted treatment of AS have emerged. Although precision therapy for restoring the UBE3A level and the function of its signalling pathways is inevitably hindered by many remaining obstacles, this approach has the potential to address AS-related sleep disturbance.

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.

Enhancing autism spectrum disorder classification in children through the integration of traditional statistics and classical machine learning techniques in EEG analysis

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder hallmarked by challenges in social communication, limited interests, and repetitive, stereotyped movements and behaviors. Numerous research efforts have indicated that individuals with ASD exhibit distinct brain connectivity patterns compared to control groups. However, these investigations, often constrained by small sample sizes, have led to inconsistent results, suggesting both heightened and diminished long-range connectivity within ASD populations. To bolster our analysis and enhance their reliability, we conducted a retrospective study using two different connectivity metrics and employed both traditional statistical methods and machine learning techniques. The concurrent use of statistical analysis and classical machine learning techniques advanced our understanding of model predictions derived from the spectral or connectivity attributes of a subject's EEG signal, while also verifying these predictions. Significantly, the utilization of machine learning methodologies empowered us to identify a unique subgroup of correctly classified children with ASD, defined by the analyzed EEG features. This improved approach is expected to contribute significantly to the existing body of knowledge on ASD and potentially guide personalized treatment strategies.

Injury patterns associated with cognitive motor dissociation

In unconscious appearing patients with acute brain injury, wilful brain activation to motor commands without behavioural signs of command following, known as cognitive motor dissociation (CMD), is associated with functional recovery. CMD can be detected by applying machine learning to EEG recorded during motor command presentation in behaviourally unresponsive patients. Identifying patients with CMD carries clinical implications for patient interactions, communication with families, and guidance of therapeutic decisions but underlying mechanisms of CMD remain unknown. By analysing structural lesion patterns and network level dysfunction we tested the hypothesis that, in cases with preserved arousal and command comprehension, a failure to integrate comprehended motor commands with motor outputs underlies CMD. Manual segmentation of T2-fluid attenuated inversion recovery and diffusion weighted imaging sequences quantifying structural injury was performed in consecutive unresponsive patients with acute brain injury (n = 107) who underwent EEG-based CMD assessments and MRI. Lesion pattern analysis was applied to identify lesion patterns common among patients with (n = 21) and without CMD (n = 86). Thalamocortical and cortico-cortical network connectivity were assessed applying ABCD classification of power spectral density plots and weighted pairwise phase consistency (WPPC) to resting EEG, respectively. Two distinct structural lesion patterns were identified on MRI for CMD and three for non-CMD patients. In non-CMD patients, injury to brainstem arousal pathways including the midbrain were seen, while no CMD patients had midbrain lesions. A group of non-CMD patients was identified with injury to the left thalamus, implicating possible language comprehension difficulties. Shared lesion patterns of globus pallidus and putamen were seen for a group of CMD patients, which have been implicated as part of the anterior forebrain mesocircuit in patients with reversible disorders of consciousness. Thalamocortical network dysfunction was less common in CMD patients [ABCD-index 2.3 (interquartile range, IQR 2.1-3.0) versus 1.4 (IQR 1.0-2.0), P < 0.0001; presence of D 36% versus 3%, P = 0.0006], but WPPC was not different. Bilateral cortical lesions were seen in patients with and without CMD. Thalamocortical disruption did not differ for those with CMD, but long-range WPPC was decreased in 1-4 Hz [odds ratio (OR) 0.8; 95% confidence interval (CI) 0.7-0.9] and increased in 14-30 Hz frequency ranges (OR 1.2; 95% CI 1.0-1.5). These structural and functional data implicate a failure of motor command integration at the anterior forebrain mesocircuit level with preserved thalamocortical network function for CMD patients with subcortical lesions. Amongst patients with bilateral cortical lesions preserved cortico-cortical network function is associated with CMD detection. These data may allow screening for CMD based on widely available structural MRI and resting EEG.

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.

Electroencephalographic (EEG) Biomarkers in Genetic Neurodevelopmental Disorders

Collectively, neurodevelopmental disorders are highly prevalent, but more than a third of neurodevelopmental disorders have an identifiable genetic etiology, each of which is individually rare. The genes associated with neurodevelopmental disorders are often involved in early brain development, neuronal signaling, or synaptic plasticity. Novel treatments for many genetic neurodevelopmental disorders are being developed, but disease-relevant clinical outcome assessments and biomarkers are limited. Electroencephalography (EEG) is a promising noninvasive potential biomarker of brain function. It has been used extensively in epileptic disorders, but its application in neurodevelopmental disorders needs further investigation. In this review, we explore the use of EEG in 3 of the most prevalent genetic neurodevelopmental disorders-Angelman syndrome, Rett syndrome, and fragile X syndrome. Quantitative analyses of EEGs, such as power spectral analysis or measures of connectivity, can quantify EEG signatures seen on qualitative review and potentially correlate with phenotypes. In both Angelman syndrome and Rett syndrome, increased delta power on spectral analysis has correlated with clinical markers of disease severity including developmental disability and seizure burden, whereas spectral power analysis on EEG in fragile X syndrome tends to demonstrate abnormalities in gamma power. Further studies are needed to establish reliable relationships between quantitative EEG biomarkers and clinical phenotypes in rare genetic neurodevelopmental disorders.

The potential of electroencephalography coherence to predict the outcome of repetitive transcranial magnetic stimulation in insomnia disorder

BACKGROUND

It is unknown whether repetitive Transcranial Magnetic Stimulation (rTMS) could improve sleep quality by modulating electroencephalography (EEG) connectivity of insomnia disorder (ID) patients. Great heterogeneity had been found in the clinical outcomes of rTMS for ID. The study aimed to investigate the potential mechanisms of rTMS therapy for ID and develop models to predict clinical outcomes.

METHODS

In Study 1, 50 ID patients were randomly divided into active and sham groups, and subjected to 20 sessions of treatment with 1 Hz rTMS over the left dorsolateral prefrontal cortex. EEG during awake, Polysomnography, and clinical assessment were collected and analyzed before and after rTMS. In Study 2, 120 ID patients were subjected to active rTMS stimulation and were then separated into optimal and sub-optimal groups due to the median of Pittsburgh Sleep Quality Index reduction rate. Machine learning models were developed based on baseline EEG coherence to predict rTMS treatment effects.

RESULTS

In Study 1, decreased EEG coherence in theta and alpha bands were observed after rTMS treatment, and changes in theta band (F7-O1) coherence were correlated with changes in sleep efficiency. In Study 2, baseline EEG coherence in theta, alpha, and beta bands showed the potential to predict the treatment effects of rTMS for ID.

CONCLUSION

rTMS improved sleep quality of ID patients by modulating the abnormal EEG coherence. Baseline EEG coherence between certain channels in theta, alpha, and beta bands could act as potential biomarkers to predict the therapeutic effects.

Quantitative EEG Analysis in Angelman Syndrome: Candidate Method for Assessing Therapeutics

The goal of these studies was to use quantitative (q)EEG techniques on data from children with Angelman syndrome (AS) using spectral power analysis, and to evaluate this as a potential biomarker and quantitative method to evaluate therapeutics. Although characteristic patterns are evident in visual inspection, using qEEG techniques has the potential to provide quantitative evidence of treatment efficacy. We first assessed spectral power from baseline EEG recordings collected from children with AS compared to age-matched neurotypical controls, which corroborated the previously reported finding of increased total power driven by elevated delta power in children with AS. We then retrospectively analyzed data collected during a clinical trial evaluating the safety and tolerability of minocycline (3 mg/kg/d) to compare pretreatment recordings from children with AS (4-12 years of age) to EEG activity at the end of treatment and following washout for EEG spectral power and epileptiform events. At baseline and during minocycline treatment, the AS subjects demonstrated increased delta power; however, following washout from minocycline treatment the AS subjects had significantly reduced EEG spectral power and epileptiform activity. Our findings support the use of qEEG analysis in evaluating AS and suggest that this technique may be useful to evaluate therapeutic efficacy in AS. Normalizing EEG power in AS therefore may become an important metric in screening therapeutics to gauge overall efficacy. As therapeutics transition from preclinical to clinical studies, it is vital to establish outcome measures that can quantitatively evaluate putative treatments for AS and neurological disorders with distinctive EEG patterns.

Systematic Review on EEG Analysis to Diagnose and Treat Autism by Evaluating Functional Connectivity and Spectral Power

An abnormality in neural connectivity is linked to autism spectrum disorder (ASD). There is no way to test the concept of neural connectivity empirically. According to recent network theory and time series analysis findings, electroencephalography (EEG) can assess neural network architecture, a sign of activity in the brain. This systematic review aims to evaluate functional connectivity and spectral power using EEG signals. EEG records the brain activity of an individual by displaying wavy lines that depict brain cells' communication through electrical impulses. EEG can diagnose various brain disorders, including epilepsy and related seizure illness, brain dysfunction, tumors, and damage. We found 21 studies using two of the most common EEG analysis methods: functional connectivity and spectral power. ASD and non-ASD individuals were found to differ significantly in all selected papers. Due to high heterogeneity in the outcomes, generalizations cannot be drawn, and no single method is currently beneficial as a diagnostic tool. For ASD subtype delineation, the lack of research prevented the evaluation of these techniques as diagnostic tools. These findings confirm the presence of abnormalities in the EEG in ASD, but they are insufficient to diagnose. Our study suggests that EEG is useful in diagnosing ASD by evaluating entropy in the brain. Researchers may be able to develop new diagnostic methods for ASD which focuses on particular stimuli and brainwaves if they conduct more extensive studies with higher numbers and more rigorous study designs.

Questionnaires based on natural language processing elicit immersive ruminative thinking in ruminators: Evidence from behavioral responses and EEG data

Rumination is closely related to mental disorders and can thus be used as a marker of their presence or a predictor of their development. The presence of masking and fabrication in psychological selection can lead to inaccurate detection of psychological disorders. Human language is considered crucial in eliciting specific conscious activities, and the use of natural language processing (NLP) in the development of questionnaires for psychological tests has the potential to elicit immersive ruminative thinking, leading to changes in neural activity. Electroencephalography (EEG) is commonly used to detect and record neural activity in the human brain and is sensitive to changes in brain activity. In this study, we used NLP to develop a questionnaire to induce ruminative thinking and then recorded the EEG signals in response to the questionnaire. The behavioral results revealed that ruminators exhibited higher arousal rates and longer reaction times, specifically in response to the ruminative items of the questionnaire. The EEG results showed no significant difference between the ruminators and the control group during the resting state; however, a significant alteration in the coherence of the entire brain of the ruminators existed while they were answering the ruminative items. No differences were found in the control participants while answering the two items. These behavioral and EEG results indicate that the questionnaire elicited immersive ruminative thinking, specifically in the ruminators. Therefore, the questionnaire designed using NLP is capable of eliciting ruminative thinking in ruminators, offering a promising approach for the early detection of mental disorders in psychological selection.

Circadian Rhythms and Sleep Are Dependent Upon Expression Levels of Key Ubiquitin Ligase Ube3a

Normal neurodevelopment requires precise expression of the key ubiquitin ligase gene Ube3a. Comparing newly generated mouse models for Ube3a downregulation (models of Angelman syndrome) vs. Ube3a upregulation (models for autism), we find reciprocal effects of Ube3a gene dosage on phenotypes associated with circadian rhythmicity, including the amount of locomotor activity. Consistent with results from neurons in general, we find that Ube3a is imprinted in neurons of the suprachiasmatic nuclei (SCN), the pacemaking circadian brain locus, despite other claims that SCN neurons were somehow exceptional to these imprinting rules. In addition, Ube3a-deficient mice lack the typical drop in wake late in the dark period and have blunted responses to sleep deprivation. Suppression of physical activity by light in Ube3a-deficient mice is not due to anxiety as measured by behavioral tests and stress hormones; quantification of stress hormones may provide a mechanistic link to sleep alteration and memory deficits caused by Ube3a deficiency, and serve as an easily measurable biomarker for evaluating potential therapeutic treatments for Angelman syndrome. We conclude that reduced Ube3a gene dosage affects not only neurodevelopment but also sleep patterns and circadian rhythms.

Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep

Angelman syndrome (AS) is a neurodevelopmental disorder caused by loss‐of‐function mutations in the maternal copy of the UBE3A gene. AS is characterized by intellectual disability, impaired speech and motor skills, epilepsy, and sleep disruptions. Multiple treatment strategies to re‐express functional neuronal UBE3A from the dormant paternal allele were successful in rodent models of AS and have now moved to early phase clinical trials in children. Developing reliable and objective AS biomarkers is essential to guide the design and execution of current and future clinical trials. Our prior work quantified short daytime electroencephalograms (EEGs) to define promising biomarkers for AS. Here, we asked whether overnight sleep is better suited to detect AS EEG biomarkers. We retrospectively analyzed EEGs from 12 overnight sleep studies from individuals with AS with age and sex‐matched Down syndrome and neurotypical controls, focusing on low frequency (2–4 Hz) delta rhythms and sleep spindles. Delta EEG rhythms were increased in individuals with AS during all stages of overnight sleep, but overnight sleep did not provide additional benefit over wake in the ability to detect increased delta. Abnormal sleep spindles were not reliably detected in EEGs from individuals with AS during overnight sleep, suggesting that delta rhythms represent a more reliable biomarker. Overall, we conclude that periods of wakefulness are sufficient, and perhaps ideal, to quantify delta EEG rhythms for use as AS biomarkers.

Abnormal brain state distribution and network connectivity in a SYNGAP1 rat model

Mutations in the SYNGAP1 gene are one of the common predictors of neurodevelopmental disorders, commonly resulting in individuals developing autism, intellectual disability, epilepsy, and sleep deficits. EEG recordings in neurodevelopmental disorders show potential to identify clinically translatable biomarkers to both diagnose and track the progress of novel therapeutic strategies, as well as providing insight into underlying pathological mechanisms. In a rat model of SYNGAP1 haploinsufficiency in which the exons encoding the calcium/lipid binding and GTPase-activating protein domains have been deleted (Syngap^+/Δ-GAP ), we analysed the duration and occurrence of wake, non-rapid eye movement and rapid eye movement brain states during 6 h multi-electrode EEG recordings. We find that although Syngap^+/Δ-GAP animals spend an equivalent percent time in wake and sleep states, they have an abnormal brain state distribution as the number of wake and non-rapid eye movement bouts are reduced and there is an increase in the average duration of both wake and non-rapid eye movement epochs. We perform connectivity analysis by calculating the average imaginary coherence between electrode pairs at varying distance thresholds during these states. In group averages from pairs of electrodes at short distances from each other, a clear reduction in connectivity during non-rapid eye movement is present between 11.5 Hz and 29.5 Hz, a frequency range that overlaps with sleep spindles, oscillatory phenomena thought to be important for normal brain function and memory consolidation. Sleep abnormalities were mostly uncorrelated to the electrophysiological signature of absence seizures, spike and wave discharges, as was the imaginary coherence deficit. Sleep spindles occurrence, amplitude, power and spread across multiple electrodes were not reduced in Syngap^+/Δ-GAP rats, with only a small decrease in duration detected. Nonetheless, by analysing the dynamic imaginary coherence during sleep spindles, we found a reduction in high-connectivity instances between short-distance electrode pairs. Finally comparing the dynamic imaginary coherence during sleep spindles between individual electrode pairs, we identified a group of channels over the right somatosensory, association and visual cortices that have a significant reduction in connectivity during sleep spindles in mutant animals. This matched a significant reduction in connectivity during spindles when averaged regional comparisons were made. These data suggest that Syngap^+/Δ-GAP rats have altered brain state dynamics and EEG connectivity, which may have clinical relevance for SYNGAP1 haploinsufficiency in humans.

Right Anterior Theta Hypersynchrony as a Quantitative Measure Associated with Autistic Traits and K-Cl Cotransporter KCC2 Polymorphism

Our aim was to use theta coherence as a quantitative trait to investigate the relation of the polymorphisms in NKCC1 (rs3087889) and KCC2 (rs9074) channel protein genes to autistic traits (AQ) in neurotypicals. Coherence values for candidate connection regions were calculated from eyes-closed resting EEGs in two independent groups. Hypersynchrony within the right anterior region was related to AQ in both groups (p < 0.05), and variability in this hypersynchrony was related to the rs9074 polymorphism in the total group (p < 0.05). In conclusion, theta hypersynchrony within the right anterior region during eyes-closed rest can be considered a quantitative measure for autistic traits. Replicating our findings in two independent populations with different backgrounds strengthens the validity of the current study.

Insulin-like growth factor-2 does not improve behavioral deficits in mouse and rat models of Angelman Syndrome

BACKGROUND

Angelman Syndrome (AS) is a rare neurodevelopmental disorder for which there is currently no cure or effective therapeutic. Since the genetic cause of AS is known to be dysfunctional expression of the maternal allele of ubiquitin protein ligase E3A (UBE3A), several genetic animal models of AS have been developed. Both the Ube3a maternal deletion mouse and rat models of AS reliably demonstrate behavioral phenotypes of relevance to AS and therefore offer suitable in vivo systems in which to test potential therapeutics. One promising candidate treatment is insulin-like growth factor-2 (IGF-2), which has recently been shown to ameliorate behavioral deficits in the mouse model of AS and improve cognitive abilities across model systems.

METHODS

We used both the Ube3a maternal deletion mouse and rat models of AS to evaluate the ability of IGF-2 to improve electrophysiological and behavioral outcomes.

RESULTS

Acute systemic administration of IGF-2 had an effect on electrophysiological activity in the brain and on a metric of motor ability; however the effects were not enduring or extensive. Additional metrics of motor behavior, learning, ambulation, and coordination were unaffected and IGF-2 did not improve social communication, seizure threshold, or cognition.

LIMITATIONS

The generalizability of these results to humans is difficult to predict and it remains possible that dosing schemes (i.e., chronic or subchronic dosing), routes, and/or post-treatment intervals other than that used herein may show more efficacy.

CONCLUSIONS

Despite a few observed effects of IGF-2, our results taken together indicate that IGF-2 treatment does not profoundly improve behavioral deficits in mouse or rat models of AS. These findings shed cautionary light on the potential utility of acute systemic IGF-2 administration in the treatment of AS.

Consciousness and complexity: a consilience of evidence

Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

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

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 GABA_A 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.

Emerging Gene and Small Molecule Therapies for the Neurodevelopmental Disorder Angelman Syndrome

Angelman syndrome (AS) is a rare (~1:15,000) neurodevelopmental disorder characterized by severe developmental delay and intellectual disability, impaired communication skills, and a high prevalence of seizures, sleep disturbances, ataxia, motor deficits, and microcephaly. AS is caused by loss-of-function of the maternally inherited UBE3A gene. UBE3A is located on chromosome 15q11-13 and is biallelically expressed throughout the body but only maternally expressed in the brain due to an RNA antisense transcript that silences the paternal copy. There is currently no cure for AS, but advancements in small molecule drugs and gene therapies offer a promising approach for the treatment of the disorder. Here, we review AS and how loss-of-function of the maternal UBE3A contributes to the disorder. We also discuss the strengths and limitations of current animal models of AS. Furthermore, we examine potential small molecule drug and gene therapies for the treatment of AS and associated challenges faced by the therapeutic design. Finally, gene therapy offers the opportunity for precision medicine in AS and advancements in the treatment of this disorder can serve as a foundation for other single-gene neurodevelopmental disorders.

Electrophysiological Biomarkers in Genetic Epilepsies

Precision treatments for epilepsy targeting the underlying genetic diagnoses are becoming a reality. Historically, the goal of epilepsy treatments was to reduce seizure frequency. In the era of precision medicine, however, outcomes such as prevention of epilepsy progression or even improvements in cognitive functions are both aspirational targets for any intervention. Developing methods, both in clinical trial design and in novel endpoints, will be necessary for measuring, not only seizures, but also the other neurodevelopmental outcomes that are predicted to be targeted by precision treatments. Biomarkers that quantitatively measure disease progression or network level changes are needed to allow for unbiased measurements of the effects of any gene-level treatments. Here, we discuss some of the promising electrophysiological biomarkers that may be of use in clinical trials of precision therapies, as well as the difficulties in implementing them.

Functional rescue in an Angelman syndrome model following treatment with lentivector transduced hematopoietic stem cells

Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by impaired communication skills, ataxia, motor and balance deficits, intellectual disabilities, and seizures. The genetic cause of AS is the neuronal loss of UBE3A expression in the brain. A novel approach, described here, is a stem cell gene therapy which uses lentivector-transduced hematopoietic stem and progenitor cells to deliver functional UBE3A to affected cells. We have demonstrated both the prevention and reversal of AS phenotypes upon transplantation and engraftment of human CD34+ cells transduced with a Ube3a lentivector in a novel immunodeficient Ube3a^mat−/pat+ IL2rg^−/y mouse model of AS. A significant improvement in motor and cognitive behavioral assays as well as normalized delta power measured by electroencephalogram was observed in neonates and adults transplanted with the gene modified cells. Human hematopoietic profiles observed in the lymphoid organs by detection of human immune cells were normal. Expression of UBE3A was detected in the brains of the adult treatment group following immunohistochemical staining illustrating engraftment of the gene-modified cells expressing UBE3A in the brain. As demonstrated with our data, this stem cell gene therapy approach offers a promising treatment strategy for AS, not requiring a critical treatment window.

Consciousness among delta waves: a paradox?

A common observation in EEG research is that consciousness vanishes with the appearance of delta (1 - 4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are very frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalised epileptic seizures, and disorders of consciousness such as coma and vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the "down states" or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and nonconvulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalogram or MEG signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.

Abnormal electrophysiological phenotypes and sleep deficits in a mouse model of Angelman Syndrome

Background

Angelman Syndrome (AS) is a rare genetic disorder characterized by impaired communication, motor and balance deficits, intellectual disabilities, recurring seizures and abnormal sleep patterns. The genetic cause of AS is neuronal-specific loss of expression of UBE3A (ubiquitin-protein ligase E6-AP), an imprinted gene. Seizure and sleep disorders are highly prevalent (> 80%) in the AS population. The present experiments were designed to identify translational, neurophysiological outcome measures in a model of AS.

Methods

We used the exon-2 deletion mouse (Ube3a-del) on a C57BL/6J background to assess seizure, sleep and electrophysiological phenotypes. Seizure susceptibility has been reported in Ube3a-del mice with a variety of seizure induction methods. Here, we provoked seizures by a single high-dose injection of 80 mg/kg pentylenetetrazole. Novel experiments included the utilization of wireless telemetry devices to acquire global electroencephalogram (EEG) and neurophysiological data on electrographic seizures, power spectra, light–dark cycles, sleep stages and sleep spindles in Ube3a-del and WT mice.

Results

Ube3a-del mice exhibited reduced seizure threshold compared to WT. EEG illustrated that Ube3a-del mice had increased epileptiform spiking activity and delta power, which corroborates findings from other laboratories and recapitulates clinical reports in AS. This is the first report to use a cortical surface-based recording by a wireless telemetry device over tethered/fixed head-mount depth recordings. Less time in both paradoxical and slow-wave sleep, longer latencies to paradoxical sleep stages and total less sleep time in Ube3a-del mice were observed compared to WT. For the first time, we detected fewer sleep spindles in the AS mouse model.

Limitations

This study was limited to the exon 2 deletion mouse model, and future work will investigate the rat model of AS, containing a complete Ube3a deletion and pair EEG with behavior.

Conclusions

Our data enhance rigor and translatability as our study provides important corroboration of previous reports on epileptiform and elevated delta power. For the first time we report neurophysiological phenotypes collected via translational methodology. Furthermore, this is the first report of reduced sleep spindles, a critical marker of memory consolidation during sleep, in an AS model. Our results are useful outcomes for therapeutic testing.

Resting state EEG biomarkers of cognitive decline associated with Alzheimer's disease and mild cognitive impairment

In this paper, we explore the utility of resting-state EEG measures as potential biomarkers for the detection and assessment of cognitive decline in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Neurophysiological biomarkers of AD derived from EEG and FDG-PET, once characterized and validated, would expand the set of existing diagnostic molecular biomarkers of AD pathology with associated biomarkers of disease progression and neural dysfunction. Since symptoms of AD often begin to appear later in life, successful identification of EEG-based biomarkers must account for age-related neurophysiological changes that occur even in healthy individuals. To this end, we collected EEG data from individuals with AD (n = 26), MCI (n = 53), and cognitively normal healthy controls stratified by age into three groups: 18-40 (n = 129), 40-60 (n = 62) and 60-90 (= 55) years old. For each participant, we computed power spectral density at each channel and spectral coherence between pairs of channels. Compared to age matched controls, in the AD group, we found increases in both spectral power and coherence at the slower frequencies (Delta, Theta). A smaller but significant increase in power of slow frequencies was observed for the MCI group, localized to temporal areas. These effects on slow frequency spectral power opposed that of normal aging observed by a decrease in the power of slow frequencies in our control groups. The AD group showed a significant decrease in the spectral power and coherence in the Alpha band consistent with the same effect in normal aging. However, the MCI group did not show any significant change in the Alpha band. Overall, Theta to Alpha ratio (TAR) provided the largest and most significant differences between the AD group and controls. However, differences in the MCI group remained small and localized. We proposed a novel method to quantify these small differences between Theta and Alpha bands' power using empirically derived distributions of spectral power across the time domain as opposed to averaging power across time. We defined Power Distribution Distance Measure (PDDM) as a distance measure between probability distribution functions (pdf) of Theta and Alpha power. Compared to average TAR, using PDDF enhanced the statistical significance, the effect size, and the spatial distribution of significant effects in the MCI group. We designed classifiers for differentiating individual MCI and AD participants from age-matched controls. The classification performance measured by the area under ROC curve after cross-validation were AUC = 0.85 and AUC = 0.6, for AD and MCI classifiers, respectively. Posterior probability of AD, TAR, and the proposed PDDM measure were all significantly correlated with MMSE score and neuropsychological tests in the AD group.

Angelman syndrome and melatonin: What can they teach us about sleep regulation

In 1965, Dr Harry Angelman reported a neurodevelopmental disorder affecting three unrelated children who had similar symptoms: brachycephaly, mental retardation, ataxia, seizures, protruding tongues, and remarkable paroxysms of laughter. Over the past 50 years, the disorder became Angelman's namesake and symptomology was expanded to include hyper-activity, stereotypies, and severe sleep disturbances. The sleep disorders in many Angelman syndrome (AS) patients are broadly characterized by difficulty falling and staying asleep at night. Some of these patients sleep less than 4 hours a night and, in most cases, do not make up this lost sleep during the day-leading to the speculation that AS patients may "need" less sleep. Most AS patients also have severely reduced levels of melatonin, a hormone produced by the pineal gland exclusively at night. This nightly pattern of melatonin production is thought to help synchronize internal circadian rhythms and promote nighttime sleep in humans and other diurnal species. It has been proposed that reduced melatonin levels contribute to the sleep problems in AS patients. Indeed, emerging evidence suggests melatonin replacement therapy can improve sleep in many AS patients. However, AS mice show sleep problems that are arguably similar to those in humans despite being on genetic backgrounds that do not make melatonin. This suggests the hypothesis that the change in nighttime melatonin may be a secondary factor rather than the root cause of the sleeping disorder. The goals of this review article are to revisit the sleep and melatonin findings in both AS patients and animal models of AS and discuss what AS may tell us about the underlying mechanisms of, and interplay between, melatonin and sleep.

Behavioral Evaluation of Angelman Syndrome Mice at Older Ages

Angelman syndrome is a neurodevelopmental disorder presenting with severe deficits in motor, speech, and cognitive abilities. The primary genetic cause of Angelman syndrome is a maternally transmitted mutation in the Ube3a gene, which has been successfully modeled in Ube3a mutant mice. Phenotypes have been extensively reported in young adult Ube3a mice. Because symptoms continue throughout life in Angelman syndrome, we tested multiple behavioral phenotypes of male Ube3a mice and WT littermate controls at older adult ages. Social behaviors on both the 3-chambered social approach and male-female social interaction tests showed impairments in Ube3a at 12 months of age. Anxiety-related scores on both the elevated plus-maze and the light ↔ dark transitions assays indicated anxiety-like phenotypes in 12 month old Ube3a mice. Open field locomotion parameters were consistently lower at 12 months. Reduced general exploratory locomotion at this age prevented the interpretation of an anxiety-like phenotype, and likely impacted social tasks. Robust phenotypes in middle-aged Ube3a mice appear to result from continued motor decline. Motor deficits may provide the best outcome measures for preclinical testing of pharmacological targets, towards reductions of symptoms in adults with Angelman syndrome.

Evaluation of a TrkB agonist on spatial and motor learning in the Ube3a mouse model of Angelman syndrome

Angelman syndrome is a rare neurodevelopmental disorder caused by a mutation in the maternal allele of the gene Ube3a The primary symptoms of Angelman syndrome are severe cognitive deficits, impaired motor functions, and speech disabilities. Analogous phenotypes have been detected in young adult Ube3a mice. Here, we investigate cognitive phenotypes of Ube3a mice as compared to wild-type littermate controls at an older adult age. Water maze spatial learning, swim speed, and rotarod motor coordination and balance were impaired at 6 mo of age, as predicted. Based on previous findings of reduced brain-derived neurotrophic factor in Ube3a mice, a novel therapeutic target, the TrkB agonist 7,8-DHF, was interrogated. Semichronic daily treatment with 7,8-DHF, 5 mg/kg i.p., did not significantly improve the impairments in performance during the acquisition of the water maze hidden platform location in Ube3a mice, after training with either massed or spaced trials, and had no effect on the swim speed and rotarod deficits. Robust behavioral phenotypes in middle-aged Ube3a mice appear to result from continued motor decline. Our results suggest that motor deficits could offer useful outcome measures for preclinical testing of many pharmacological targets, with the goal of reducing symptoms in adults with Angelman syndrome.

High-voltage, diffuse delta rhythms coincide with wakeful consciousness and complexity in Angelman syndrome

Abundant evidence from slow wave sleep, anesthesia, coma, and epileptic seizures links high-voltage, slow electroencephalogram (EEG) activity to loss of consciousness. This well-established correlation is challenged by the observation that children with Angelman syndrome (AS), while fully awake and displaying volitional behavior, display a hypersynchronous delta (1–4 Hz) frequency EEG phenotype typical of unconsciousness. Because the trough of the delta oscillation is associated with down-states in which cortical neurons are silenced, the presence of volitional behavior and wakefulness in AS amidst diffuse delta rhythms presents a paradox. Moreover, high-voltage, slow EEG activity is generally assumed to lack complexity, yet many theories view functional brain complexity as necessary for consciousness. Here, we use abnormal cortical dynamics in AS to assess whether EEG complexity may scale with the relative level of consciousness despite a background of hypersynchronous delta activity. As characterized by multiscale metrics, EEGs from 35 children with AS feature significantly greater complexity during wakefulness compared with sleep, even when comparing the most pathological segments of wakeful EEG to the segments of sleep EEG least likely to contain conscious mentation and when factoring out delta power differences across states. These findings (i) warn against reverse inferring an absence of consciousness solely on the basis of high-amplitude EEG delta oscillations, (ii) corroborate rare observations of preserved consciousness under hypersynchronization in other conditions, (iii) identify biomarkers of consciousness that have been validated under conditions of abnormal cortical dynamics, and (iv) lend credence to theories linking consciousness with complexity.

Angelman Syndrome: From Mouse Models to Therapy

The UBE3A gene is part of the chromosome 15q11-q13 region that is frequently deleted or duplicated, leading to several neurodevelopmental disorders (NDD). Angelman syndrome (AS) is caused by the absence of functional maternally derived UBE3A protein, while the paternal UBE3A gene is present but silenced specifically in neurons. Patients with AS present with severe neurodevelopmental delay, with pronounced motor deficits, absence of speech, intellectual disability, epilepsy, and sleep problems. The pathophysiology of AS is still unclear and a treatment is lacking. Animal models of AS recapitulate the genotypic and phenotypic features observed in AS patients, and have been invaluable for understanding the disease process as well as identifying apropriate drug targets. Using these AS mouse models we have learned that loss of UBE3A probably affects many areas of the brain, leading to increased neuronal excitability and a loss of synaptic spines, along with changes in a number of distinct behaviours. Inducible AS mouse models have helped to identify the critical treatment windows for the behavioral and physiological phenotypes. Additionally, AS mouse models indicate an important role for the predominantly nuclear UBE3A isoform in generating the characteristic AS pathology. Last, but not least, the AS mice have been crucial in guiding Ube3a gene reactivation treatments, which present a very promising therapy to treat AS.

Multielectrode array analysis of EEG biomarkers in a mouse model of Fragile X Syndrome

Fragile X Syndrome (FXS) is a leading known genetic cause of intellectual disability with symptoms that include increased anxiety and social and sensory processing deficits. Recent EEG studies in humans with FXS have identified neural oscillation deficits that include increased resting state gamma power, increased amplitude of auditory evoked potentials, and reduced inter-trial phase coherence of sound-evoked gamma oscillations. Identification of comparable EEG biomarkers in mouse models of FXS could facilitate the pre-clinical to clinical therapeutic pipeline. However, while human EEG studies have involved 128-channel scalp EEG acquisition, no mouse studies have been performed with more than three EEG channels. In the current study, we employed a recently developed 30-channel mouse multielectrode array (MEA) system to record and analyze resting and stimulus-evoked EEG signals in WT vs. Fmr1 KO mice. Using this system, we now report robust MEA-derived phenotypes including higher resting EEG power, altered event-related potentials (ERPs) and reduced inter-trial phase coherence to auditory chirp stimuli in Fmr1 KO mice that are remarkably similar to those reported in humans with FXS. We propose that the MEA system can be used for: (i) derivation of higher-level EEG parameters; (ii) EEG biomarkers for drug testing; and (ii) mechanistic studies of FXS pathophysiology.

Sleep in the United States Military

The military lifestyle often includes continuous operations whether in training or deployed environments. These stressful environments present unique challenges for service members attempting to achieve consolidated, restorative sleep. The significant mental and physical derangements caused by degraded metabolic, cardiovascular, skeletomuscular, and cognitive health often result from insufficient sleep and/or circadian misalignment. Insufficient sleep and resulting fatigue compromises personal safety, mission success, and even national security. In the long-term, chronic insufficient sleep and circadian rhythm disorders have been associated with other sleep disorders (e.g., insomnia, obstructive sleep apnea, and parasomnias). Other physiologic and psychologic diagnoses such as post-traumatic stress disorder, cardiovascular disease, and dementia have also been associated with chronic, insufficient sleep. Increased co-morbidity and mortality are compounded by traumatic brain injury resulting from blunt trauma, blast exposure, and highly physically demanding tasks under load. We present the current state of science in human and animal models specific to service members during- and post-military career. We focus on mission requirements of night shift work, sustained operations, and rapid re-entrainment to time zones. We then propose targeted pharmacological and non-pharmacological countermeasures to optimize performance that are mission- and symptom-specific. We recognize a critical gap in research involving service members, but provide tailored interventions for military health care providers based on the large body of research in health care and public service workers.

Circadian biology and sleep in monogenic neurological disorders and its potential application in drug discovery

Sleep disturbances are common in people with monogenic neurological disorders and they dramatically affect the life of individuals with the disorders and their families. The associated sleep problems are probably caused by multiple factors that have not been elucidated. Study of the underlying molecular cause, behavioral phenotypes, and reciprocal interactions in several single-gene disorders (Angelman Syndrome, Fragile X Syndrome, Rett Syndrome, and Huntington's Disease) leads to the suggestion that sleep disruption and other symptoms may directly result from abnormal operation of circadian systems due to genetic alteration and/or conflicting environmental cues for clock entrainment. Therefore, because circadian patterns modify the symptoms of neurological disorders, treatments that modulate our daily rhythms may identify heretofore unappreciated therapies for the underlying disorders.

Sleep in children with neurodevelopmental difficulties

Sleep disorders in children with neurodevelopmental disorders are complex and reflect underlying genetic/biological and behavioural components. The sleep disorders are the same as in the typically developing child, although there may be some modifications to the presentation or the frequency depending on the phenotype. Consideration of the known phenotypes and environmental issues are important in defining management strategies. Despite this complexity, defined behavioural strategies with good sleep hygiene can have a significant effect on the sleep problem and on parental management of the behaviours.