EEG Phenotype in Angelman Syndrome Differs between Genotypes

Background:: Angelman syndrome (AS) is a neurodevelopmental disorder characterized by a specific set of clinical features including intellectual disability, movement disorders, limited speech, and epilepsy [Angelman et al., 1965], and confers increased risk for autism spectrum disorder. Loss of function of UBE3A is necessary and sufficient for AS. This paternally imprinted (i.e., silenced) gene encodes ubiquitin-protein ligase and is critical for normal neuronal development. There are several AS genotypes that present with different clinical severity [Moncla et al., 1999]: 1) deletions of 15q11.2-q13.1 on the maternal allele, which includes UBE3A and several other genes, most notably three non-imprinted gamma-aminobutyric acid (GABA)-A receptor subunit genes GABRA5, GABRB3, GABRG3, and 2) mutations that affect the maternal copy of UBE3A (e.g., loss of function UBE3A mutations, unipaternal disomy, and imprinting mutations). Biomarkers reflecting the disease pathophysiology are crucial for the development of pharmacological treatments of AS. Electroencephalography (EEG) is a promising candidate biomarker and functional readout of neuronal activity in AS, characterized by excessive delta oscillations [Sidorov et al, 2017]. However, it remains unknown if this EEG phenotype differs between genotypes. Such knowledge is important for both understanding AS pathophysiology and informing the design of possible future intervention studies.

Objectives: To examine EEG characteristics of AS patients by genotype and, specifically, to compare spontaneous EEG spectral power between 1) AS genotype groups and 2) AS patients and typical developing (TD) controls.

Methods: Clinical EEG recordings were obtained from a National Institutes of Health (NIH) natural history study of AS. A total of 66 datasets, including longitudinal data, were obtained from 43 unique subjects (13 non-deletion, 30 deletion) ranging in age from infancy to adulthood. Age-matched control data were recorded with the same EEG system from 51 TD children. Data were recorded in the awake state and preprocessed to remove physiological artifacts. Power spectral densities (PSDs, 1-32 Hz) were computed using a Morlet wavelet transform. PSDs where averaged across electrodes and across visits for subjects with multiple visits. A between-group analysis examined spectral power differences between AS subjects and controls; a within-group analysis examined spectral power differences between AS subjects with different genotypes. Statistical analysis compared log-transformed PSDs using t-test.

Results: Individuals with AS are characterized by excessive delta-band power compared to controls (p < 0.05, Bonferroni corrected across all frequencies; peak frequency 2.7 Hz). Deletion and non-deletion groups both show excess delta-band power — however, delta power is significantly greater in the deletion genotype (p < 0.05).

Conclusions: Differences in EEG delta power between deletion and non-deletion AS genotypes suggest a role in AS pathogenesis for non-imprinted 15q11.2-q13.1 genes or regulatory elements within this region. For instance, given the relevance of GABAergic signaling for electrophysiological oscillations, deletions of the genes GABRA5, GABRB3, GABRG3 may contribute to greater delta power in some patients. These findings suggest differences in disease pathophysiology between AS patients with different genotypes, and, moreover, support the use of EEG as a stratification biomarker and functional readout in AS.