SCN1A-deficient excitatory neuronal networks display mutation-specific phenotypes

Abstract

Abstract Dravet syndrome is a severe epileptic encephalopathy, characterized by (febrile) seizures, behavioral problems and developmental delay. 80% of Dravet syndrome patients have a mutation in SCN1A, encoding NaV1.1. Milder clinical phenotypes, such as GEFS+ (generalized epilepsy with febrile seizures plus), can also arise from SCN1A mutations. Predicting the clinical phenotypic outcome based on the type of mutation remains challenging, even when the same mutation is inherited within one family. Both this clinical and genetic heterogeneity add to the difficulties of predicting disease progression and tailored prescription of anti-seizure medication. A better understanding of the neuropathology of different SCN1A mutations, might give insight in differentiating the expected clinical phenotype and best fit treatment choice. Initially it was recognized that loss of Na+ -current in inhibitory neurons specifically resulted in disinhibition and consequently seizure generation. However, the extent to which excitatory neurons contribute to the pathophysiology is currently debated, and might depend on the patient clinical phenotype or the specific mutation in SCN1A. To examine the genotype-phenotype correlations of SCN1A mutations in relation to excitatory neurons, we investigated a panel of patient-derived excitatory neuronal networks differentiated on multi-electrode arrays. We included patients with different clinical phenotypes, harboring different mutations in SCN1A, plus a family where the same mutation led to febrile seizures, GEFS + or Dravet syndrome. We hitherto describe a previously unidentified functional excitatory neuronal network phenotype in the context of epilepsy, which corresponded to seizurogenic network prediction patterns elicited by proconvulsive compounds. We found that excitatory neuronal networks were differently affected, dependent on the type of SCN1A mutation, but did not segregate by clinical severity. Specifically, loss of function mutations could be distinguished from missense mutations and mutations in the pore domain could be distinguished from mutations in the voltage sensing domain. Furthermore, all patients showed aggravated neuronal network responses upon febrile temperatures compared to controls. Finally, retrospective drug screening revealed that anti-seizure medication affected GEFS + patient-, but not Dravet patient-derived neuronal networks, in a patient-specific and clinically relevant manner. In conclusion, our results indicate a mutation-specific excitatory neuronal network phenotype, which recapitulates the foremost clinically relevant features, providing future opportunities for precision therapies.