Electrophysiological Abnormalities in Angelman Syndrome Correlate With Symptom Severity

Electroencephalographic Correlates of Clinical Severity in the Natural history study of RTT and Related Disorders

OBJECTIVE

This study was undertaken to characterize quantitative electroencephalographic (EEG) features in participants from the Natural history study of RTT and Related Disorders and to assess the potential for these features to act as objective measures of cortical function for Rett syndrome (RTT).

METHODS

EEG amplitude and power features were derived from the resting EEG of 60 females with RTT (median age = 10.7 years) and 26 neurotypical females (median age = 10.6 years). Analyses focus on group differences and within the RTT group, associations between the EEG parameters and clinical severity. For a subset of participants (n = 20), follow-up data were available for assessing the reproducibility of the results and the stability in the parameters over 1 year.

RESULTS

Compared to neurotypical participants, participants with RTT had greater amplitude variability and greater low-frequency activity as reflected by greater delta power, more negative 1/f slope, and lower theta/delta, alpha/delta, beta/delta, alpha/theta, and beta/theta ratios. Greater delta power, more negative 1/f slope, and lower power ratios were associated with greater severity. Analyses of year 1 data replicated the associations between 1/f slope and power ratios and clinical severity and demonstrated good within-subject consistency in these measures.

INTERPRETATION

Overall, group comparisons reflected a greater predominance of lower versus higher frequency activity in participants with RTT, which is consistent with prior clinical interpretations of resting EEG in this population. The observed associations between the EEG power measures and clinical assessments and the repeatability of these measures underscore the potential for EEG to provide an objective measure of cortical function and clinical severity for RTT. ANN NEUROL 2024;96:175-186.

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.

Enabling endpoint development for interventional clinical trials in individuals with Angelman syndrome: a prospective, longitudinal, observational clinical study (FREESIAS)

BACKGROUND

Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by the absence of a functional UBE3A gene, which causes developmental, behavioral, and medical challenges. While currently untreatable, comprehensive data could help identify appropriate endpoints assessing meaningful improvements in clinical trials. Herein are reported the results from the FREESIAS study assessing the feasibility and utility of in-clinic and at-home measures of key AS symptoms.

METHODS

Fifty-five individuals with AS (aged < 5 years: n = 16, 5-12 years: n = 27, ≥ 18 years: n = 12; deletion genotype: n = 40, nondeletion genotype: n = 15) and 20 typically developing children (aged 1-12 years) were enrolled across six USA sites. Several clinical outcome assessments and digital health technologies were tested, together with overnight 19-lead electroencephalography (EEG) and additional polysomnography (PSG) sensors. Participants were assessed at baseline (Clinic Visit 1), 12 months later (Clinic Visit 2), and during intermittent home visits.

RESULTS

The participants achieved high completion rates for the clinical outcome assessments (adherence: 89-100% [Clinic Visit 1]; 76-91% [Clinic Visit 2]) and varied feasibility of and adherence to digital health technologies. The coronavirus disease 2019 (COVID-19) pandemic impacted participants' uptake of and/or adherence to some measures. It also potentially impacted the at-home PSG/EEG recordings, which were otherwise feasible. Participants achieved Bayley-III results comparable to the available natural history data, showing similar scores between individuals aged ≥ 18 and 5-12 years. Also, participants without a deletion generally scored higher on most clinical outcome assessments than participants with a deletion. Furthermore, the observed AS EEG phenotype of excess delta-band power was consistent with prior reports.

CONCLUSIONS

Although feasible clinical outcome assessments and digital health technologies are reported herein, further improved assessments of meaningful AS change are needed. Despite the COVID-19 pandemic, remote assessments facilitated high adherence levels and the results suggested that at-home PSG/EEG might be a feasible alternative to the in-clinic EEG assessments. Taken altogether, the combination of in-clinic/at-home clinical outcome assessments, digital health technologies, and PSG/EEG may improve protocol adherence, reduce patient burden, and optimize study outcomes in AS and other rare disease populations.

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.

Antisense oligonucleotide therapy rescues disturbed brain rhythms and sleep in juvenile and adult mouse models of Angelman syndrome

UBE3A encodes ubiquitin protein ligase E3A, and in neurons its expression from the paternal allele is repressed by the UBE3A antisense transcript (UBE3A-ATS). This leaves neurons susceptible to loss-of-function of maternal UBE3A. Indeed, Angelman syndrome, a severe neurodevelopmental disorder, is caused by maternal UBE3A deficiency. A promising therapeutic approach to treating Angelman syndrome is to reactivate the intact paternal UBE3A by suppressing UBE3A-ATS. Prior studies show that many neurological phenotypes of maternal Ube3a knockout mice can only be rescued by reinstating Ube3a expression in early development, indicating a restricted therapeutic window for Angelman syndrome. Here, we report that reducing Ube3a-ATS by antisense oligonucleotides in juvenile or adult maternal Ube3a knockout mice rescues the abnormal electroencephalogram (EEG) rhythms and sleep disturbance, two prominent clinical features of Angelman syndrome. Importantly, the degree of phenotypic improvement correlates with the increase of Ube3a protein levels. These results indicate that the therapeutic window of genetic therapies for Angelman syndrome is broader than previously thought, and EEG power spectrum and sleep architecture should be used to evaluate the clinical efficacy of therapies.

Electrophysiological and Behavioral Evidence for Hyper- and Hyposensitivity in Rare Genetic Syndromes Associated with Autism

Our study reviewed abnormalities in spontaneous, as well as event-related, brain activity in syndromes with a known genetic underpinning that are associated with autistic symptomatology. Based on behavioral and neurophysiological evidence, we tentatively subdivided the syndromes on primarily hyper-sensitive (Fragile X, Angelman) and hypo-sensitive (Phelan–McDermid, Rett, Tuberous Sclerosis, Neurofibromatosis 1), pointing to the way of segregation of heterogeneous idiopathic ASD, that includes both hyper-sensitive and hypo-sensitive individuals. This segmentation links abnormalities in different genes, such as FMR1, UBE3A, GABRB3, GABRA5, GABRG3, SHANK3, MECP2, TSC1, TSC2, and NF1, that are causative to the above-mentioned syndromes and associated with synaptic transmission and cell growth, as well as with translational and transcriptional regulation and with sensory sensitivity. Excitation/inhibition imbalance related to GABAergic signaling, and the interplay of tonic and phasic inhibition in different brain regions might underlie this relationship. However, more research is needed. As most genetic syndromes are very rare, future investigations in this field will benefit from multi-site collaboration with a common protocol for electrophysiological and event-related potential (EEG/ERP) research that should include an investigation into all modalities and stages of sensory processing, as well as potential biomarkers of GABAergic signaling (such as 40-Hz ASSR).

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.

OUP accepted manuscript

Angelman syndrome is a neurodevelopmental disorder caused by deficiency of the maternally inherited UBE3A gene in neurons. Antisense oligonucleotide therapies are under development to reinstate UBE3A protein production. Non-invasive biomarkers to detect target engagement and treatment response are needed to support clinical trials. Delta power measured in the scalp EEG is a reliable biomarker for Angelman syndrome but varies widely across individuals and throughout development, making detection of a treatment effect using single measurements challenging.

We utilized a longitudinal dataset of 204 EEG recordings from 56 subjects with Angelman syndrome to develop a natural history model of delta (2–4 Hz) power, with predictors of age, elapsed time, and relative delta power at an initial recording. Using this model, we computed the sample and effect sizes needed to detect a treatment effect in a human clinical trial with 80% power. We applied the same model structure to a mouse model of Angelman syndrome (n = 41) to detect antisense oligonucleotide-mediated treatment effects on absolute delta activity and Ube3a expression. In humans, delta power at a second time point can be reliably predicted using the natural history model. In mice, a treatment effect can be detected after antisense oligonucleotide treatment targeting the Ube3a-antisense transcript through at least 8 weeks post-treatment (P < 1e-15). Deviations in delta power from the expected natural history correlated with Ube3a expression in the mouse model (P < 0.001). Deviations in delta power from a human natural history model in Angelman syndrome can detect antisense oligonucleotide-mediated improvement in Ube3a expression in Angelman syndrome mice and may be relevant for human clinical trials.