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Sodium channels and the neurobiology of epilepsy.

Epilepsia (2012-08-22)
Megan Oliva, Samuel F Berkovic, Steven Petrou
ABSTRACT

Voltage-gated sodium channels (VGSCs) are integral membrane proteins. They are essential for normal neurologic function and are, currently, the most common recognized cause of genetic epilepsy. This review summarizes the neurobiology of VGSCs, their association with different epilepsy syndromes, and the ways in which we can experimentally interrogate their function. The most important sodium channel subunit of relevance to epilepsy is SCN1A, in which over 650 genetic variants have been discovered. SCN1A mutations are associated with a variety of epilepsy syndromes; the more severe syndromes are associated with truncation or complete loss of function of the protein. SCN2A is another important subtype associated with epilepsy syndromes, across a range of severe and less severe epilepsies. This subtype is localized primarily to excitatory neurons, and mutations have a range of functional effects on the channel. SCN8A is the other main adult subtype found in the brain and has recently emerged as an epilepsy gene, with the first human mutation discovered in a severe epilepsy syndrome. Mutations in the accessory β subunits, thought to modulate trafficking and function of the α subunits, have also been associated with epilepsy. Genome sequencing is continuing to become more affordable, and as such, the amount of incoming genetic data is continuing to increase. Current experimental approaches have struggled to keep pace with functional analysis of these mutations, and it has proved difficult to build associations between disease severity and the precise effect on channel function. These mutations have been interrogated with a range of experimental approaches, from in vitro, in vivo, to in silico. In vitro techniques will prove useful to scan mutations on a larger scale, particularly with the advance of high-throughput automated patch-clamp techniques. In vivo models enable investigation of mutation in the context of whole brains with connected networks and more closely model the human condition. In silico models can help us incorporate the impact of multiple genetic factors and investigate epistatic interactions and beyond.