Researchers at the Children’s Hospital, Boston, other centers in the US, and Poznan University, Poland, prospectively analyzed EEGs from participants in the NIH Angelman Syndrome Natural History Study. Of 160 enrolled patients (2006-2010), 115 had complete data (58 boys, median age 3.6 years). EEG findings included 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 and 0.03), and EEG patterns are age-dependent. EEG patterns and seizure types were not correlated significantly with genotypes. Using a classification tree to predict specific genotypes based on EEG features, deletions class-2 (5.0Mb) were associated with >50% intermittent rhythmic theta activity, and deletions class-1 (5.9Mb) with <50% intermittent rhythmic theta activity and epileptiform discharges while awake. EEG patterns are important biomarkers in Angelman syndrome and may suggest the underlying genetic etiology. [1]

COMMENT. Boyd SG and colleagues at Great Ormond Street Children’s Hospital, London, UK first described EEG patterns that were considered characteristic of Angelman syndrome: 1) Persistent rhythmic 4-6/s activity (>200mcV) while awake; 2) prolonged runs of rhythmic 2-3/sec activity (200-500 mcV) anteriorly; and 3) spikes mixed with 3-4/s waves (>200 mcV) posteriorly, mainly with eye-closure. Discharges mixed with slow components on eye-closure was the most frequent finding in patients aged 11 months to >12 years [2]. Six children had no history of seizures and the EEG features helped identify patients at an early age.

The EEG findings in the present report are comparable to those of Boyd, and a notched delta pattern, also characteristic of Angelman syndrome, is found in patients presenting <4 years of age. Researchers at the Epilepsy Center, Children’s Memorial Hospital, Chicago, evaluated the notched delta pattern in diagnosis of patients with a suggestive phenotype of Angelman syndrome. A retrospective review of video-EEG recordings with notched delta pattern found 38% specificity for Angelman syndrome. [3]