Characterizing SCN1A-Related Disorders Using Real-World Data Across 681 Patient-Years

SCN1A-related disorders are the single most common monogenic cause of epilepsy and represent a major focus of precision medicine efforts. In conjunction with existing prospective studies, the analysis of real-world data obtained during routine clinical care can expand upon the scale and duration of available data and contribute to the development of meaningful outcomes for clinical trials. Here, we leveraged real-world data to delineate the longitudinal disease history of 100 individuals with SCN1A-related disorders using a systematic approach. We mapped a total of 671 unique clinical terms to a standardized framework in monthly increments across 681 patient-years, including 75 terms related to seizure types. Within this cohort, 89 individuals had presumed loss-of-function variants in SCN1A based on variant type and clinical diagnosis, including those with Dravet syndrome (N = 79) and genetic epilepsy with febrile seizures plus (N = 10). Ten individuals had a non-Dravet developmental and epileptic encephalopathy caused by gain-of-function variants in SCN1A. By annotating seizure type and frequency in monthly time-bins, we assessed seizure burden. A median of 17 changes in seizure frequency and ten terms referring to seizure type were identified per participant. Myoclonic seizures occurred with high frequency (median >5 daily), whereas hemiclonic, focal impaired consciousness, and bilateral tonic-clonic seizures occurred more rarely (median monthly). Retrospective analysis of developmental histories showed a range of cognitive abilities. Neurodevelopmental differences were observed in 83% (83/100) of individuals, of whom 83% (69/83) demonstrated delayed language skills. Motor coordination impairments, including gait disturbance, ataxia, hypotonia, and imbalance were annotated in 69% (69/100) of participants. EEG findings varied with age; most were reported as normal before nine months of age, after which the prevalence of abnormal interictal findings increased. Individuals with different clinical syndromes had unique medication landscapes, with 554 prescriptions of 37 unique therapies. Changes in treatment coincided with the diagnosis of an SCN1A-related disorder, with an increase in cannabidiol, clobazam, and fenfluramine and reduction in sodium channel-blocker use following genetic diagnosis. In summary, we reconstructed the longitudinal disease history of SCN1A-related disorders from electronic medical records using a standardized framework for the analysis of real-world clinical data. We refine existing natural history data of SCN1A-related disorders by providing a granular landscape of seizures, comorbidities, and treatment approaches over time.