Analysis of EEG patterns and genotypes in patients with Angelman syndrome.

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 in50% theta and normal posterior rhythm; atypical deletions in patients with \u3e50% theta but abnormal posterior rhythm. EEG patterns are important biomarkers in Angelman syndrome and may suggest the underlying genetic etiology