In vivo, in vitro and in silico correlations of four de novo SCN1A missense mutations

Abstract

Mutations in the SCN1A gene, which encodes for the voltage-gated sodium channel NaV1.1, cause Dravet syndrome, a severe developmental and epileptic encephalopathy. Genetic testing of this gene is recommended early in life. However, predicting the outcome of de novo missense SCN1A mutations is difficult, since milder epileptic syndromes may also be associated. In this study, we correlated clinical severity with functional in vitro electrophysiological testing of channel activity and bioinformatics prediction of damaging mutational effects. Three patients, bearing the mutations p.Gly177Ala, p.Ser259Arg and p.Glu1923Arg, showed frequent intractable seizures that had started early in life, with cognitive and behavioral deterioration, consistent with classical Dravet phenotypes. These mutations failed to produce measurable sodium currents in a mammalian expression system, indicating complete loss of channel function. A fourth patient, who harbored the mutation p.Met1267Ile, though presenting with seizures early in life, showed lower seizure burden and higher cognitive function, matching borderland Dravet phenotypes. In correlation with this, functional analysis demonstrated the presence of sodium currents, but with partial loss of function. In contrast, six bioinformatics tools for predicting mutational pathogenicity suggested similar impact for all mutations. Likewise, homology modeling of the secondary and tertiary structures failed to reveal misfolding. In conclusion, functional studies using patch clamp are suggested as a prognostic tool, whereby detectable currents imply milder phenotypes and absence of currents indicate an unfavorable prognosis. Future development of automated patch clamp systems will facilitate the inclusion of such functional testing as part of personalized patient diagnostic schemes.

SCN1A variants from bench to bedside—improved clinical prediction from functional characterization

“…In contrast, those without any detectable whole‐cell current were often associated with DS only. This is in line with recent work by Nissenkorn et al () who examined four SCN1A variants regarding their functional properties and developmental phenotypes. Three variants had no detectable sodium current and were associated with classical DS, whereas the one variant with detectable current was associated with a milder phenotype with lower seizure burden and better cognitive function.…”

Transfer of SCN1A to the brain of adolescent mouse model of Dravet syndrome improves epileptic, motor, and behavioral manifestations

“… 15 , 16 Furthermore, voltage dependence of activation (Half-activation voltage [V 1/2 )] of 27.7 ± 2 mV) and fast inactivation (V 1/2 of −59.6 ± 2.2 mV) ( Figure 2 D) were similar to previous reports in HEK-293 cells transfected with human Nav1.1 expression plasmids. 17 These vectors were used to infect the neuroblastoma-derived cell line SH-SY5Y, as well as primary neuronal cultures from mouse. In both cases, we found a dose-dependent increase of SCN1A mRNA ( Figure 3 A) and Nav1.1 protein ( Figure 3 B).…”

Dravet syndrome as part of the clinical and genetic spectrum of sodium channel epilepsies and encephalopathies

“…The bioinformatics tools failed to predict the severity of epilepsy or cognitive outcome. These findings indicate that a correlation between the degree of Na v 1.1 loss of function, seizure burden, and cognitive outcome can be predicted by in vitro functional studies and that these studies, simplified by the availability of automated patch clamp systems, could soon be considered part of a personalized prognosis and treatment scheme for patients with de novo SCN1A missense mutations …”

“…Until recently, however, electrophysiological testing has been too laborious, time‐consuming, and costly to be systematically and timely applied with translational clinical purposes. Recently, Nissenkorn et al performed functional studies of four SCN1A missense variants using mammalian expression systems and current bioinformatic tools to predict the severity of the mutations on four variants; three variants had no detectable sodium current and were associated with classical DS, whereas the variant with detectable current was associated with a milder phenotype with lower seizure burden and higher cognitive functioning. The bioinformatics tools failed to predict the severity of epilepsy or cognitive outcome.…”