Outcome measures and quantitative EEG biomarkers in SYNGAP1-related disorders - PROJECT SUMMARY The proposed research aims to advance clinical trial readiness for SYNGAP1-related disorder (SYNGAP1-RD), a rare monogenic epilepsy associated with severe neurodevelopmental differences including epilepsy, intellectual disability, and autism spectrum disorder. Currently, the absence of natural history data and validated outcome measures hinders the assessment of therapeutic efficacy in clinical trials for SYNGAP1-RD and similar rare genetic epilepsies. This project will bridge this gap by defining disease trajectories and establishing reliable clinical and biomarker-based outcome measures. This study builds on preliminary work to determine disease trajectories, identify developmental and seizure patterns, and explore quantitative EEG (qEEG) features as biomarkers in SYNGAP1-RD. The objectives of the current study will be addressed through two specific aims. In Aim #1, I will follow a cohort of 50 individuals aged 2-10 years with SYNGAP1-RD prospectively to characterize developmental progress and seizure patterns. Regular assessments using tools like the Bayley-4 and Peabody will track motor and cognitive domains to distinguish predictable disease courses from treatment effects in potential future trials. In Aim #2 of this project, I will examine qEEG features as potential biomarkers for SYNGAP1-RD, focusing on specific findings such as the occipital alpha/theta power ratio, which I previously identified to be distinct in SYNGAP1-RD from controls and other genetic epilepsies. qEEG assessments in the study cohort, with comparison against age-matched controls, will clarify whether these features correlate with clinical severity and can predict developmental outcomes, ultimately identifying qEEG-based markers suitable for clinical trials. In addition, I will explore novel qEEG features, using random forest models to select key features to identify novel qEEG markers correlated with SYNGAP1 severity. As an expected outcome, this NIH K23 career development award will support my training in longitudinal study design, outcome measure validation, and advanced qEEG analysis. These efforts aim to provide a foundation for future precision therapies and ensure my progression toward an independent R01-funded career in rare neurological diseases, focusing on tools to evaluate and implement treatments effectively. The anticipated results will address critical gaps in clinical trial readiness, with validated outcome measures and biomarkers that may serve as robust endpoints in SYNGAP1-RD and potentially in other genetic epilepsies.
