Quantitative EEG Analysis in Angelman Syndrome: Candidate Method for Assessing Therapeutics

Quantitative EEG Analysis in Angelman Syndrome: Candidate Method for Assessing Therapeutics, Clinical EEG and Neuroscience, Ahead of Print. The goal of these studies was to use quantitative (q)EEG techniques on data from children with Angelman syndrome (AS) using spectral power analysis, and to evaluate this as a potential biomarker and quantitative method to evaluate therapeutics., Clinical EEG and Neuroscience, Ahead of Print.
The goal of these studies was to use quantitative (q)EEG techniques on data from children with Angelman syndrome (AS) using spectral power analysis, and to evaluate this as a potential biomarker and quantitative method to evaluate therapeutics. Although characteristic patterns are evident in visual inspection, using qEEG techniques has the potential to provide quantitative evidence of treatment efficacy. We first assessed spectral power from baseline EEG recordings collected from children with AS compared to age-matched neurotypical controls, which corroborated the previously reported finding of increased total power driven by elevated delta power in children with AS. We then retrospectively analyzed data collected during a clinical trial evaluating the safety and tolerability of minocycline (3 mg/kg/d) to compare pretreatment recordings from children with AS (4-12 years of age) to EEG activity at the end of treatment and following washout for EEG spectral power and epileptiform events. At baseline and during minocycline treatment, the AS subjects demonstrated increased delta power; however, following washout from minocycline treatment the AS subjects had significantly reduced EEG spectral power and epileptiform activity. Our findings support the use of qEEG analysis in evaluating AS and suggest that this technique may be useful to evaluate therapeutic efficacy in AS. Normalizing EEG power in AS therefore may become an important metric in screening therapeutics to gauge overall efficacy. As therapeutics transition from preclinical to clinical studies, it is vital to establish outcome measures that can quantitatively evaluate putative treatments for AS and neurological disorders with distinctive EEG patterns., admin,