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Abstract

SCN2A-related disorders result from pathogenic variants in the gene encoding for the voltage-gated sodium channel Nav1.2. Collectively, these disorders result in variable age of onset epilepsy, autism spectrum disorder, and epileptic encephalopathies. While the mechanisms of haploinsufficiency resulting in autism spectrum disorder have been explored in detail, few studies report the impact of pathogenic missense variants in human neurons. In this work, we combined conventional electrophysiology and high-throughput all-optical electrophysiology assays to analyze the SCN2A p.M1879T pathogenic variant associated with early-onset epilepsy and developmental delay. In both platforms, iPSC-derived excitatory neurons expressing the disease variant showed greater firing at higher stimuli compared to the isogenic control neurons (corrected by CRISPR/Cas9), as well as changes to action potential shape (steeper slope and larger amplitude) with evoked firing. We used machine learning techniques on the optical physiology dataset to classify the two genotypes, finding that sodium channel blocking anti-seizure drugs could restore an isogenic phenotype. This work demonstrates proof of sodium channel blocker efficacy in a human neuronal model of SCN2A-related epilepsy and highlights the power of leveraging high-throughput all-optical electrophysiology for testing drug efficacy.

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