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Abstracts

Association Between Anti​s​eizure Medication Burden and EEG Spectral Features in SCN2A Developmental ​and ​Epileptic Encephalopathy

Abstract number : 3.276
Submission category : 7. Anti-seizure Medications / 7C. Cohort Studies
Year : 2023
Submission ID : 657
Source : www.aesnet.org
Presentation date : 12/4/2023 12:00:00 AM
Published date :

Authors :
Presenting Author: Jay Pathmanathan, MD, PhD – Beacon Biosignals

Patricia Fogerson, PhD – Beacon Biosignals; Elise Brimble, MS – Invitae Corp.; Melina Tsitsiklis, PhD – Beacon Biosignals; Alex Arslan, MS – Beacon Biosignals; Jayne Nerrie, MA – Beacon Biosignals; Kim Labertino, BSc – Beacon Biosignals; Nasha Fitter, MBA – Invitae Corp.; Jacob Donoghue, MD, PhD – Beacon Biosignals

Rationale: Antiseizure medications (ASMs) are the basis of therapy in epilepsy, although they can impair neurocognitive functioning and cause  central nervous system toxicity. Some classical ASMs are known to cause encephalopathy at high doses, which is reflected in EEG abnormalities such as slowing of the posterior dominant rhythm or increased delta activity. Therefore, it is common clinical practice to avoid excessive polypharmacy where possible. For developmental epileptic encephalopathies (DEEs), toxicity may be more difficult to appreciate due to pathological high-amplitude delta oscillations. In addition, seizures are severe and surgical options are limited, so subjects often receive three or more ASMs at once. Here, we examine the effect of ASM count on background EEG spectral features in children with SCN2A-DEE.

Methods: The Invitae Ciitizen® platform collected clinical metadata and EEG recordings for individuals with SCN2A variants to characterize the natural history of SCN2A-DEE. The Beacon Platform analyzed the associated EEG data. Spectral features were computed for 471 recordings from 31 patients (ages one day to 16 years) using multitaper spectral estimation. Relative spectral power was calculated in traditional EEG bands, excluding periods with artifact and epileptiform discharges, which were detected using a machine learning model. ASM count at the time of each recording was derived from medical records. A mixed-effects linear regression model was built to examine the effect of ASM count on relative delta power, including age and SCN2A phenotype (early onset (EO) vs late onset / late onset with infantile spasms (LO/LOIS)) as covariates. 



Results: Recordings were associated with between zero and eight ASMs based on subjects’ medical records, with an average of four ASMs for EO subject recordings and two for LO/LOIS (Figure 1). Increasing ASM count, regardless of ASM type, correlated with increased relative delta power for both EO and LO/LOIS phenotypes (Figure 2), which is consistent with increasingly severe encephalopathy. The magnitude of this effect increased with age, such that older subjects were predicted to have a greater increase in relative delta power per additional ASM. 

Figure 1. Distribution of relative delta band power by ASM count and phenotype. 
Figure 2. Effect of ASM count on relative delta band power. Lines represent model predictions and shaded bars represent model uncertainty, using the mean age within each bin to show the significant interaction between ASM count and age.


Conclusions: We found that higher ASM counts were associated with more severe encephalopathic EEG changes in SCN2A-DEE, represented by elevated relative delta power. It is unclear whether the positive correlation between ASM count and relative delta power is due to underlying disease burden or ASM toxicity. These results underscore the need for targeted therapies for DEEs, as there may be a balance between standard ASM benefits (reduced epileptic activity) and ASM toxicity (encephalopathy). 

Funding: N/A

Anti-seizure Medications