Abstract
Interpretation of clinical genetic testing, which identifies a potential genetic etiology in 25% of children with epilepsy, is limited by variants of uncertain significance. Understanding functional consequences of variants can help distinguish pathogenic from benign alleles. We combined automated patch clamp recording with neurophysiological simulations to discern genotype-function-phenotype correlations in a real-world cohort of children with SCN1A-associated epilepsy. Clinical data were extracted for children with SCN1A variants identified by clinical genetic testing. Functional properties of non-truncating NaV1.1 variant channels were determined using automated patch clamp recording. Functional data were incorporated into a parvalbumin-positive (PV+) interneuron computer model to predict variant effects on neuron firing and were compared with longitudinal clinical data describing epilepsy types, neurocognitive outcomes, and medication response. Twelve SCN1A variants were identified (nine non-truncating). Six non-truncating variants exhibited no measurable sodium current in heterologous cells consistent with complete loss of function (LoF). Two variants caused either partial LoF (L479P) or a mixture of gain and loss of function (I1356M). The remaining non-truncating variant (T1250M) exhibited normal function. Functional data changed classification of pathogenicity for six variants. Complete LoF variants were universally associated with seizure onset before one year of age and febrile seizures, and were often associated with drug resistant epilepsy and below average cognitive outcomes. Simulations demonstrated abnormal firing in heterozygous model neurons containing dysfunctional variants. In SCN1A-associated epilepsy, functional analysis and neuron simulation studies resolved variants of uncertain significance and correlated with aspects of phenotype and medication response.
Published Version
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