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Updated: May 24, 2026

A Scalable, Cell-Based Method for the Functional Assessment of Ube3a Variants
Published on: October 10, 2022
Analysis of EEG patterns and genotypes in patients with Angelman syndrome
Martina Vendrame1, Tobias Loddenkemper, Marcin Zarowski
1Boston University, Neurology Department, C-3, Boston, MA 02118, USA.
Abstract:
We prospectively analyzed EEGs from participants in the ongoing NIH Rare Diseases Clinical Research Network Angelman Syndrome Natural History Study. Of the one-hundred-sixty enrolled patients (2006-2010), 115 had complete data (58 boys, median age 3.6 years). Distinct EEG findings were intermittent rhythmic delta waves (83.5%), interictal epileptiform discharges (74.2%), intermittent rhythmic theta waves (43.5%), and posterior rhythm slowing (43.5%). Centro-occipital and centro-temporal delta waves decreased with age (p=0.01, p=0.03). There were no specific correlations between EEG patterns and genotypes. A classification tree allowed the prediction of deletions class-1 (5.9 Mb) in patients with intermittent theta waves in <50% of EEG and interictal epileptiform abnormalities; UPD, UBE3A mutation or imprinting defects in patients with intermittent theta in <50% of EEG without interictal epileptiform abnormalities; deletions class-2 (5.0 Mb) in patients with >50% theta and normal posterior rhythm; atypical deletions in patients with >50% theta but abnormal posterior rhythm. EEG patterns are important biomarkers in Angelman syndrome and may suggest the underlying genetic etiology.

