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date: 19 January 2019

Sodium Channelopathies of the Central Nervous System

Abstract and Keywords

This chapter presents information about the structure, function, and molecular genetics of voltage-gated sodium channels expressed in the central nervous system. Sodium channels are essential for the generation and propagation of neuronal action potentials. Recent advances in structural biology have provided atomic-scale descriptions of sodium channel structure that can be related to specific functional properties. We further discuss cellular and subcellular localization, as well as the primary physiological functions mediated by sodium channels within the central nervous system. Finally, this chapter examines the association of various sodium channel isoforms with common brain disorders, including epilepsy, autism, and migraine, and explains the range of functional consequences of disease-associated mutations that are correlated with diverse human phenotypes.

Keywords: sodium channel, epilepsy, autism spectrum disorder, migraine, ion channel structure

The Structure of Voltage-Gated Sodium Channels

Evolutionary Origins of Voltage-Gated Sodium Channels

The earliest known life forms on Earth are putative fossilized microorganisms found in hydrothermal vent precipitates. In the genomes of these halophilic archaea is evidence that the first ion channels appeared 3 billion years ago as an evolutionary adaptation to this extreme osmotic condition (Anderson & Greenberg, 2001; Strong, Chandy, & Gutman, 1993). First, a singular domain channel of unknown ion selectivity probably evolved from a common ancestor shared by voltage-gated sodium (NaV) and potassium (KV) channels (Strong et al., 1993). Based on phylogenetic analysis, the lineage of prokaryotic NaV probably diverged from a common progenitor with eukaryotic NaV channels (Liebeskind, Hillis, & Zakon, 2013; Zakon, 2012). At that time, the prokaryotic progenitor gene duplicated, giving rise to a two domain channel topology found in contemporary two-pore channels (TPC), which reside in endosomal and lysosomal compartments (Galione et al., 2009; Liebeskind, Hillis, & Zakon, 2012). Then a second round of gene duplication occurred, creating four domain channels, which provided the topological blueprint for eukaryotic NaV and CaV channels (Cai, 2012). In the first section of this chapter, we will compare the recently resolved high-resolution structures of prokaryotic and eukaryotic NaV channels, and how their intramolecular interactions control their function in the cell membrane.

Assembly of Archetypal Prokaryotic NaV Channel Structures

Although prokaryotic NaV channel structures have garnered considerable interest, the principal value is their relationship to more complex human homologues. These simple NaV archetypes have provided a simple protein platform to investigate the structural basis for Na+ selectivity and the mechanism of channel activation. The simplicity of prokaryotic NaV channels provides a more tractable target than their mammalian counterparts for structural analysis using X-ray crystallography, and thus structures from this family were the first to be solved.

Each subunit of prokaryotic NaV channels has six transmembrane-spanning segments (S1–6) that contain a voltage-sensing module (VSM, S1–4) and pore-forming module (PM, S5–6) (Payandeh, Scheuer, Zheng, & Catterall, 2011; Ren et al., 2001). Each subunit or monomer of prokaryotic NaV channels is viewed as analogous to the four domains of eukaryotic NaV channels (Figure 1A) (Scheuer, 2014; Tang et al., 2014). Four prokaryotic NaV subunits oligomerize to form a homotetramer, where the PM and cytosolic C-terminal coiled-coil motifs form homotypical contacts around a central ion-conducting pathway (Figure 1A, B). Three nearly full-length (NaVCt, NaVAb, and NaVRh) and two complete prokaryotic NaV structures (NaVMs and NaVAb) have been determined (Payandeh et al., 2011; Tsai et al., 2013; Zhang et al., 2012; Lenaeus et al., 2017; Sula et al., 2017). These structures have been captured in unique conformations, which have provided much needed spatial context in which state-dependent interactions may occur during NaV function.

Sodium Channelopathies of the Central Nervous SystemClick to view larger

Figure 1 Structures of prokaryotic NaV channels.

(A) Topology of prokaryotic and eukaryotic sodium channels. Transmembrane pore-forming helices are colored purple. (B) Transmembrane views of the NavAb, NavMs, and NavRh prokaryotic structures depicting three putative states visited during membrane depolarization. Pore-forming helices S5 and S6 are colored purple. Insets, extracellular views of each channel structure.

Relationship of Structure to Function

Voltage-gated sodium channels turn on the flow of ionic current in response to changes in membrane potential. Figure 1A illustrates the “pre-open” state of NaVAb (3.2 Å) and the open state of NaVM channels (2.4 Å), which represent the conformational changes undertaken when the electrical potential of the cell membrane is shifted from negative to zero millivolts (Figure 1B) (Lenaeus et al., 2017; Sula et al., 2017). As discussed in other sections of this book (see Zaleska et al., this volume), and reiterated here, the opening and closing of the pore is mechanically linked to outward movement of the S4 segment that contains a series of positively charged residues (R1–R4) called “gating charges.” Transfer of the S4 gating charges has been measured at 3–4e− per voltage sensor module, which precedes the opening and flow of the ionic current in eukaryotic and prokaryotic NaV channels (Armstrong & Bezanilla, 1974; Keynes, Rojas, & Rudy, 1974; Kuzmenkin, Bezanilla, & Correa, 2004). The movement of gating charges is stabilized by conserved negatively charged resides. The outward trajectory of the S4 has been tracked in a series of disulfide trapping experiments, and the estimated displacement is ≈ 8 Å (DeCaen, Yarov-Yarovoy, Scheuer, & Catterall, 2011; DeCaen, Yarov-Yarovoy, Sharp, Scheuer, & Catterall, 2009; DeCaen, Yarov-Yarovoy, Zhao, Scheuer, & Catterall, 2008; Yarov-Yarovoy et al., 2012). The onset of the trapping effect has led to the proposal that the VSM has at least two activated states (Yarov-Yarovoy et al., 2012). These measurements predicted that the S4 secondary structure must adopt a full or partial 310-helix during activation, an unprecedented feature that was confirmed in each of the prokaryotic (and eukaryotic) NaV structures. After the membrane is depolarized and the VSM has activated, the pore is opened by displacement of the S4–S5 linker that physically interacts with the cytosolic S6 lower gate through a network of hydrogen bonds and charge–counter-charge interactions (Sula et al., 2017). This movement in turn causes each of the four S6 to splay 12° from the center axis, widening the conduction pathway to accommodate the passaging of partially hydrated Na+ ions (Figure 1B).

The mechanism of ion selectivity has become clearer from recent structural revelations. The extracellular mouth of the pore contains the ion selectivity filter. In prokaryotic NaV channels, the filter contains a symmetrical ring of four aspartate residues and two offset rings of backbone carbonyls (Payandeh et al., 2011; Sula et al., 2017). These atoms coordinate a row of three partially hydrated Na+ ions by replacing a square array of oxygen atoms found in first hydration shell. Based on functional analysis, partially hydrated Na+ and the smaller Li+ pass, whereas larger monovalent (e.g., K+) and divalent cations do not (DeCaen, Takahashi, Krulwich, Ito, & Clapham, 2014; Naylor et al., 2016; Zhang et al., 2013). Other cations are proposed to be excluded by size and permeation, and this is dictated by the fit of the filter to the incoming ion hydration shells. After the channel has opened, all NaV channels exhibit slow inactivation, a process wherein the channel is shifted into a non-conductive state that is distinct from the closed state.

Both eukaryotic and prokaryotic NaV channels exhibit slow inactivation that operates with a time constant of tens to hundreds of milliseconds (Ren et al., 2001; Ulmschneider et al., 2013), but eukaryotic NaV channels also exhibit fast inactivation, which is structurally and kinetically distinct from slow inactivation (see Structural Elements of Eukaryotic NaV Channels). Structurally, the slow-inactivated state has been captured as distortions of the selectivity filter and pore domain, which in turn causes occlusion or collapse of the ion coordination sites in the inactivated NaVRh, NaVCt, and NaVAb channel structures (Figure 1B) (Payandeh, Gamal El-Din, Scheuer, Zheng, & Catterall, 2012; Tsai et al., 2013; Zhang et al., 2012). Ironically, the most enigmatic state of the activation cycle of NaV channels is the closed state, which has not been captured in crystal structures because the membrane potential is insufficiently hyperpolarized during the crystallization process. Thus, a complete set of structures that capture prokaryotic NaV channels in the major conformational states occurring during membrane depolarization is not available.

Structural Elements of Eukaryotic NaV Channels

In the human genome, there are ten NaV channel pore-forming subunit genes (SCN1A to SCN11A) that encode nine functional channels (designated NaV1.1 to NaV1 .9) and one atypical homologue (NaV2.1 or NaX). These large (260 kDa) and complex (multiple subunits with heteromeric stoichiometry) transmembrane proteins have posed a major challenge for structural biologists. The structure of the eukaryotic NaV channels is best described as a four-domain pseudoheterotetramer. Each of the four domains (DI–IV) contains six transmembrane segments, which contribute to its total 24-transmembrane-helix assembly (Figure 1A). The first structural view of a eukaryotic NaV channel structure was determined by single-particle cryo-electron microscopy (cryo-EM) applied to the channel purified from the electric organ of Electrophorus electricus (Sato et al., 2001). Although the structure was resolved to only 19 Å, some coarse features of the folded protein were apparent, including a bell-shaped outer surface and several inner cavities. Due to their size and structural complexity, solving the atomic structures of eukaryotic NaV channels has proven to be challenging using X-ray crystallography. However, over the past eight years, the technology to acquire and analyze single-particle cryo-EM data sets has improved immensely, allowing unprecedented structural analysis of macromolecules at atomic resolution. Using this approach, the first two high-resolution structures of a eukaryotic NaV channels were determined (Figure 2).

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Figure 2 Structures of eukaryotic Nav channels.

(A) Transmembrane (top), extracellular (middle), and intracellular (bottom) views of the NavPaS and EeNav1.4-β1 complex. (B) The EeNav1.4 DIII voltage sensor module (top) highlighting gating charge (R1–R5) interactions. The selectivity filter (bottom) highlighting the putative side chains involved in Na ion selectivity. The sites of disease-causing variants (E1034, L1153, and T1242) are underlined.

The first solved eukaryotic NaV channel structure was that of a channel cloned from the cockroach Periplaneta americana at 3.8-Å resolution (Shen et al., 2017). The second structure was of the electric eel channel, EeNaV1.4 at 4.0-Å, which was solved in complex with an accessory β1 subunit (more on these heteromeric interactions in Eukaryotic NaVβ Subunit Complex) (Z. Yan et al., 2017). These channels share 36–66% amino acid sequence identity with human NaV channels and thus provide a structural template to understand disease-causing variants (Huang, Liu, Yan, & Yan, 2017). As expected, each of the NaVPaS and EeNaV1.4 channels exhibits pseudosymmetry, resembling each subunit from prokaryotic NaV channels. However, the functional states of the published NaVPaS and EeNaV1.4 structures are ambiguous. The VSMs from each domain appear to represent a mixture of activated and deactivated conformations. Additionally, the C-terminal gate in NaVPaS is narrow, prohibiting the passage of Na+ ions, whereas this site is more dilated in the EeNaV1.4 structure (Figure 2). Thus, the state of the channel gate was tentatively assigned as “closed” or “open” for NaVPaS or EeNaV1.4, respectively. Many of sequential gating charge interactions sampled by each of the VSMs in the eukaryotic structures were captured in the previously discussed structure-function studies of prokaryotic channels (Figure 2B, top). The moieties proposed to determine Na+ selectivity in NaVPaS and EeNaV1.4 are shared by human NaV channels, including an asymmetrical ring of four amino acids (Asp, Glu, Lys, and Ala) contributed by each of the four domains (Figure 2B, bottom) (Sun, Favre, Schild, & Moczydlowski, 1997). Although it is postulated that eukaryotic channels use a similar mechanism to select for and conduct Na+, it is not clear how or which of the selectivity filter residues are involved because putative ions and protein–ion contacts in the filter were not resolved in these structures. Nonetheless, the structures of NaV selectivity filters have provided a basis to further examine parts of the filter never before considered, such as the role of the intervening pore loops and the impact of the pore-directed negative dipole generated by the eight pore helices.

As mentioned previously, eukaryotic NaV have evolved a fast inactivation mechanism that rapidly (1–2 ms) turns off the flow of ions. NaV channels recover from fast inactivation within a few hundred microseconds after membrane repolarization, which facilitates the rapid frequency of action potentials conducted by nerve and muscle cells (Hodgkin & Huxley, 1952b). Early functional studies demonstrated that fast inactivation can be altered by mutating sites within the DIII–IV linker (e.g., lsoleucine-phenylalanine-methionine (IFM) or leucine-methionine-phenylalanine (LMF) motif) and residues within the C-terminal domain (CTD), and that activation of the VSM domain III is rate-limiting (Capes, Goldschen-Ohm, Arcisio-Miranda, Bezanilla, & Chanda, 2013; Motoike et al., 2004; Stuhmer et al., 1989). However, because these sites are located at seemingly different locations within the channel, the molecular basis for the asynchronous gating model of fast inactivation has been an enigma. Nonetheless, insights into the mechanism of fast inactivation can be gleaned from comparing the NaVPaS and EeNaV1.4 structures. In the NaVPaS structure, the III–IV linker rests on the cytoplasmic side the DIV VSM and physically links this domain with S6 of DIII pore module. This feature is also present in the EeNaV1.4 channel, but here the LMF motif of the III–IV linker engages the corner interface of DIII VSD and DIV S6. Based on these structures, channel inactivation is proposed to be initiated by the LMF–linker association, which in turn causes the DIV S6 to move right-handedly and collapse the ion-conducting pathway at the lower gate. Importantly, the CTD and DIII–DIV linker are hotspots of disease variants, which implicates impairment of fast-inactivation in hyperexcitability of affected cell membranes as a common disease mechanism (e.g., forms of epilepsy) (Huang et al., 2017).

Eukaryotic NaVβ Subunit Complex

In situ, NaV channels form complexes with a small family of accessory proteins called β subunits, which are single-pass transmembrane proteins belonging to the immunoglobulin (Ig) domain superfamily of cell-adhesion molecules. Humans have four genes (SCN1BSCN4B) encoding β1−β4 subunits. Although heterologous expression of any of the mammalian pore-forming subunit genes is sufficient to generate measurable Na+ current, co-expression with β subunits enhances current density and shifts the voltage dependence of activation and inactivation to more negative membrane potentials (Makita, Bennett, & George, 1996; Patino & Isom, 2010; Qu et al., 1999), and as discussed in other sections of this book, may perform non-canonical roles as well as interact with other families of voltage-gated ion channels (see Zaleska et al., this volume). Prior to their structural determination, biochemical analysis of the β subunits determined that β2 and β4 form disulfide bonds with the pore-forming subunits (Yereddi et al., 2013). However, little else was understood regarding the sites of their association and the molecular regulation of NaV function. In the aforementioned EeNaV1.4-β1 structure, the β1 transmembrane helix interacts with the DIII S2 segment through hydrophobic interactions, while the β1 Ig domain interacts with the extracellular S1–S2 loop of DIII through five intermolecular charge–counter-charge interactions (Figure 2B). Thus, it seems that β1 regulates the voltage dependence of activation of NaV1.4 by interactions with the DIII VSM. Future work should validate these putative intersubunit interactions and determine whether the transmembrane portion and/or the Ig motif are responsible for regulating channel function.

In isolation, human β3 and β4 subunit Ig domains have been crystalized at atomic resolution as trimers, which suggests that β subunits may coordinate multimers of NaV channel complexes on the cell membrane (Gilchrist, Das, Van Petegem, & Bosmans, 2013; Namadurai et al., 2014). Thus, it possible that β subunits may be responsible for coordinating the membrane distribution of the NaV alpha subunit in excitable cell membranes, as observed for NaV1.2-β4 and NaV1.6-β1 at the neuronal nodes of Ranvier; and NaV1.5-β2 in the cardiac T-tubule system (Buffington & Rasband, 2013). As the interactome of NaV channels is elucidated, one can envision a time when more protein complexes involving NaV channels will emerge. Recently resolved macromolecular complexes such as the octameric exocyst (>750 kDa) (Mei et al., 2018) and ribosomal Sec-rRNA complexes (>900 kDa) (Frauenfeld et al., 2011) demonstrate the seemingly limitless ability of cryo-EM to undertake a more complete structural view of protein regulation. Thus, it seems that the future of NaV structural biology resides in determining how these proteins associate with endogenous modifiers and how these associations impact electrical and chemical signaling within the cell.

Sodium Channels in the Central Nervous System

In excitable cells, action potential generation and propagation is governed by members of the NaV channel family. Of the ten members of this ion channel family, four (NaV1.1, NaV1.2, NaV1.3, and NaV1.6) reside primarily within the central nervous system (Whitaker et al., 2000; Whitaker et al., 2001). As noted from the structural analysis discussed previously, these proteins have evolved to be highly sensitive to changes in membrane potential, and developed activation and inactivation processes that enable the high-frequency action potential firing associated with normal neuronal function (Catterall, 1992, 2000). Currents mediated by these channels are activated very rapidly, resulting in a large influx of sodium underlying the rising phase of the action potential. Under normal circumstances, channel activation is transient due to fast inactivation, which occurs on the sub-millisecond time scale. Inactivated channels cannot reopen until they recover from inactivation, and the duration of recovery is intimately linked to the refractory period, which limits the maximal firing rate of neuronal cells (Hodgkin & Huxley, 1952a). There is also a persistent component of sodium current that is essential for enhancing synaptic currents, but, as discussed later in this chapter, enhanced persistent current can have pathophysiological consequences (Crill, 1996). As discussed in other chapters of this book, voltage-gated sodium channels may also perform non-canonical functions, and neuronal isoforms are not expressed strictly within the central nervous system (see Zaleska et al., this volume).

Despite the fact that all neuronal NaV channels perform similar functions, they do not share the same developmental expression patterns, cellular localizations, or interacting partners. While this information has been difficult to glean from human tissue, experiments from rodent brain have been informative. Experiments from rodents suggest that NaV1.3 is the predominant NaV channel in embryonic and early postnatal brain, with mRNA expression falling to nearly undetectable levels by postnatal day 30 (P30) (Felts, Yokoyama, Dib-Hajj, Black, & Waxman, 1997). However, NaV1.3 expression has been detected in layer III pyramidal cells in the adult brain (Vacher, Mohapatra, & Trimmer, 2008). The drop in NaV1.3 expression is coordinated with increasing expression of NaV1.1 and NaV1.6, both of which reach steady-state values between P15 and P39. NaV1.2 maintains relatively high expression throughout development, but expression modestly rises from P0 to P9 (Gazina et al., 2010).

In addition to changes in overall expression levels during development, all neuronal NaV channels undergo developmentally regulated alternative mRNA splicing, which leads to the incorporation of an alternate exon-encoding part of S3 and S4 of domain I (Copley, 2004; Kasai et al., 2001). Functionally, alternatively spliced NaV channel proteoforms show differences in channel properties, with subtle differences in voltage dependence of activation or inactivation. For example, the neonatal NaV1.2 proteoform exhibits faster inactivation compared to the adult proteoform, which is predicted to limit the excitability of immature neurons (Gazina et al., 2015; Gazina et al., 2010). Additionally, while rodent Scn1a does not show developmentally regulated alternative mRNA splicing, the human SCN1A gene undergoes alterative splicing at this exon that results in proteoforms with divergent sensitivity to commonly prescribed antiepileptic drugs such as phenytoin and lamotrigine (Thompson, Kahlig, & George, 2011).

As stated before, while these channels perform similar functions, they do not necessarily have overlapping cellular expression. NaV1.1 is strongly localized to the axon initial segment (AIS) of parvalbumin and somatostatin-positive interneurons throughout the neocortex and hippocampus (Ogiwara et al., 2007; Westenbroek, Merrick, & Catterall, 1989). This channel is also strongly expressed in cerebellar Purkinje neurons (Kalume, Yu, Westenbroek, Scheuer, & Catterall, 2007). NaV1.2 is expressed at the AIS and nodes of Ranvier in excitatory cells throughout the neocortex (Hu et al., 2009; Tian, Wang, Ke, Guo, & Shu, 2014). Early in development, NaV1.2 may be found along the entire AIS, but it later becomes restricted to the proximal AIS and is replaced by NaV1.6 at the remaining portions of the AIS and in the nodes of Ranvier (Liao, Deprez, et al., 2010). In addition, some evidence suggests that NaV1.2 is expressed in unmyelinated mossy fibers of hippocampal granule cells and cerebellar granule cells along with NaV1.6, as well as subpopulations of gamma-aminobutyric-acid releasing (GABAergic) interneurons (Gong, Rhodes, Bekele-Arcuri, & Trimmer, 1999; Hu et al., 2009; Miyazaki et al., 2014; Westenbroek et al., 1989; Yamagata, Ogiwara, Mazaki, Yanagawa, & Yamakawa, 2017). NaV1.3 expression appears to be largely somatodendritic in both pyramidal cells and interneuronal populations (Vacher et al., 2008). Thus, mutations in these channels may selectively alter excitatory or inhibitory tone, as discussed later in this chapter.

In addition to the effects of β subunits, which modify the function and trafficking of NaV channels, other proteins may modulate NaV function or are necessary for subcellular localization. As stated, NaV1.1, NaV1.2, and NaV1.6 have been shown to accumulate at the AIS. Guidance to the AIS is promoted by the cytoskeletal proteins ankyrin-G and βIV spectrin as well as FGF14 (Hund et al., 2010; Jenkins & Bennett, 2001; Pablo, Wang, Presby, & Pitt, 2016). In addition to promoting proper subcellular localization, FGF14 also modulates the biophysical properties of NaV1.2 and 1.6, inducing a depolarized shift in voltage dependence of inactivation, which may enhance neuronal excitability (Laezza et al., 2009). FGF12 also promotes a depolarized shift in voltage dependence of inactivation for NaV1.2, but not NaV1.1 (Wang, Wang, Hoch, & Pitt, 2011). Recently, NaV1.2 has been shown to be regulated by CaMKII. Phosphorylation of NaV1.2 by CaMKII induces a depolarized shift in voltage dependence of inactivation and promotes a large increase in the amplitude of persistent sodium current, resulting in greater excitability of hippocampal pyramidal neurons (Thompson, Hawkins, Kearney, & George, 2017). Interestingly, βIV spectrin is important for correct localization of CaMKII to the AIS (Hund et al., 2010). Inactivation parameters of NaV1.2 and NaV1.6 channels are also independently modulated by calmodulin, presumably through interaction with the C-terminal IQ domain or the DIII–DIV linker (Pitt & Lee, 2016; Yan, Wang, Marx, & Pitt, 2017). This interaction suppresses persistent current mediated by these channels. These data suggest that intracellular calcium may regulate sodium channel activity at the AIS. Our knowledge of NaV interacting partners continues to grow, and this will be a critical area of research for interrogation of NaV channel modulation and potential non-canonical functions.

Sodium Channel Diseases of the Central Nervous System

While NaV channels are essential for normal neuronal physiology, the genes encoding these channels have been implicated in many neurological diseases. Most often, mutations in these genes lead to disorders such as epilepsy, autism, and migraine, which have overlapping clinical features (Figure 3). In this section, we will discuss the various diseases affecting the central nervous system that have been associated with genetic variants in NaV channel genes. We will discuss genetic evidence and what we have learned regarding the cellular and network mechanisms underlying these diseases.

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Figure 3 Sodium channelopathies of the central nervous system.

Venn diagram depicting comorbidity of sodium channelopathies of the central nervous system.

Much of the information about pathogenic functions of mutant NaV channels has been gleaned from studies performed in heterologous systems, and it has become customary to assign classifications such as gain of function or loss of function based on these experiments. Therefore, it is important that we define these classifications and how these conclusions are made, based on changes in specific functional properties of NaV channels. As one might expect, “gain of function” and “loss of function” are meant to describe changes in NaV channel properties predicted to either accentuate or dampen Na+ flux, some of which are depicted in Figure 4. Examples of functional effects consistent with gain of function include hyperpolarized voltage dependence of activation, depolarized voltage dependence of inactivation, slowed inactivation kinetics, faster recovery from inactivation, or enhanced persistent sodium current. In contrast, smaller whole-cell current density, depolarized voltage dependence of activation, hyperpolarized voltage dependence of inactivation, faster inactivation kinetics, and slowed recovery from inactivation would be consistent with loss of function. It is important to emphasize that these are only predictions of channel behavior, and the impact of these changes on cell autonomous excitability and on network activity depends upon many factors, including the neuron types expressing the mutant NaV channels.

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Figure 4 Biophysical properties of mutant NaV channels.

Representative gain- and loss-of-function effects associated with (A) abnormal whole-cell current (enhanced persistent current or reduced current density); (B) altered voltage-dependent gating properties; and (C) altered channel inactivation kinetics.


Epilepsy is a neurological disorder affecting approximately 1% of the population. The condition is diagnosed when two or more unprovoked seizures of unknown cause occur (Hauser, Annegers, & Kurland, 1993; Helbig, Scheffer, Mulley, & Berkovic, 2008). The etiology of most epilepsy cases is without an identifiable cause and is thought to have an underlying genetic basis. Over the past decade, mutations in voltage-gated ion channel genes have emerged as a major cause of monogenic epilepsy syndromes, with variants in each predominantly brain-expressed NaV channel genes having associations with one or more syndromes. Recent reports have suggested that variants in SCN1A, SCN2A, and SCN8A account for approximately 40% of pathogenic cases (Butler, da Silva, Alexander, Hegde, & Escayg, 2017; Lindy et al., 2018; Mercimek-Mahmutoglu et al., 2015; Parrini et al., 2017). Sodium channel–related epilepsies range in severity from severe (e.g., Dravet syndrome, Ohtahara syndrome) to relatively benign (e.g., genetic epilepsy with febrile seizures plus benign familial neonatal seizures) (George, 2005; Kaplan, Isom, & Petrou, 2016). In the next section of this chapter, we will discuss various forms of NaV channel–related epilepsies, with an emphasis on disease etiology, underlying functional and cellular mechanisms, and knowledge gleaned from advanced animal and cellular models.

Epileptic Encephalopathy

Dravet syndrome, first described in 1978, is an epileptic encephalopathy with onset during infancy and a poor prognosis (Dravet, 2011). Patients present with generalized tonic-clonic or hemiclonic seizures, often precipitated by fever, within the first year of life. Beginning in the second year of life, patients develop afebrile seizures and show significant developmental delays resulting in permanent cognitive impairment, ataxia, and motor dysfunction. Approximately 80% of Dravet syndrome patients have de novo heterozygous missense or truncating mutations in SCN1A, with currently more than 1400 variants identified (Dravet, 2011; Parihar & Ganesh, 2013; Steel, Symonds, Zuberi, & Brunklaus, 2017). Dravet syndrome is generally not responsive to treatment with most commonly prescribed antiepileptic drugs, and NaV channel blocking drugs are widely considered contraindicated. However, seizure control has been achieved in some patients with the ketogenic diet (Brunklaus, Ellis, Reavey, Forbes, & Zuberi, 2012; Guerrini et al., 1998; Nabbout et al., 2013; Steel et al., 2017) and certain antiepileptic drug combinations (e.g., clobazam and stiripentol). Important advances in understanding the pathogenesis of Dravet syndrome using many experimental platforms have inspired new therapeutic strategies.

Whereas truncating variants are generally predicted to be complete loss-of-function, most missense variants in SCN1A have uncertain functional consequences. Utilizing heterologous expression, a large number of Dravet syndrome–associated NaV1.1 missense mutations have been functionally evaluated. Despite the fact that Dravet syndrome mutations do not show a tendency to cluster within specific functional domains of the channel, most mutations exhibit severe loss of function compared to wild-type NaV1.1, as depicted in Figure 5 (Claes et al., 2003; Claes et al., 2001; Ohmori, Kahlig, Rhodes, Wang, & George, 2006; Rhodes, Lossin, Vanoye, Wang, & George, 2004; Thompson, Porter, Kahlig, Daniels, & George, 2012). Additionally, many mutations exhibit impaired trafficking to the plasma membrane, suggesting that the mutations may evoke protein misfolding (Thompson et al., 2012).

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Figure 5 Loss of function of SCN1A leads to Dravet syndrome.

Whole-cell sodium currents from WT-NaV1.1 and Dravet syndrome-associated mutations G1674R.

Demonstrating loss of function for many mutations was an early clue that haploinsufficiency may be the primary mechanism responsible for Dravet syndrome, but this notion raised the question of how a loss of NaV channel function results in hyperexcitable network activity and epilepsy. An answer was provided in 2006 when two groups independently showed that heterozygous loss of mouse Scn1a recapitulated many of the disease phenotypes associated with Dravet syndrome, including spontaneous generalized seizures, hyperthermia-induced seizures, ataxia, and premature death (Ogiwara et al., 2007; Yu et al., 2006). Whole-cell voltage clamp recording of acutely isolated hippocampal neurons showed lower sodium current density, specifically in GABAergic interneurons (Ogiwara et al., 2007; Yu et al., 2006). This loss of sodium current density resulted in blunted interneuron excitability, suggesting that Dravet syndrome arises from disinhibition of neuronal networks. Cell-type-specific deletion of Scn1a in parvalbumin- or somatostatin-positive interneurons was sufficient to recapitulate many of the behavioral and electrophysiological features identified in the global Scn1a+/– knockout (Cheah et al., 2012; Tai, Abe, Westenbroek, Scheuer, & Catterall, 2014). Interestingly, cerebellar Purkinje neurons from Scn1a+/– mice also exhibit smaller sodium currents and impaired excitability compared to neurons from wild-type animals, a likely explanation for ataxia observed in Dravet syndrome (Kalume et al., 2007). However, it is likely that defects in the basal ganglia also contribute to motor defects of these patients (Gataullina & Dulac, 2017). Other investigations of Scn1a+/– mice suggest that Dravet syndrome may not arise solely from impaired interneuron excitability. Importantly, lower interneuron sodium current density is observable at an age when mice are not observed to have seizures. In addition to finding lower interneuron sodium current density, these is evidence for higher sodium current density and greater excitability of hippocampal pyramidal cells from Scn1a+/– mice, potentially resulting from upregulation of NaV1.6 (Anderson, Hawkins, Thompson, Kearney, & George, 2017; Mistry et al., 2014). This greater sodium current density in excitatory neurons exhibits a strong age dependence, with no difference observed in neurons from P14 mice, and a nearly twofold increase in current density compared to wild-type mice at age P21, which corresponds to the age when seizure frequency rises sharply. Unlike other forms of epilepsy, Dravet syndrome does not remit with age; therefore, an age-dependent increase in excitatory neuron excitability may be a critical contributor to the progression of Dravet syndrome.

Patient-derived induced pluripotent stem cells (iPSCs) have been used recently to interrogate the cellular and network mechanisms of Dravet syndrome. Early experiments examining excitability of glutamatergic neurons derived from SCN1A mutant Dravet syndrome iPSC lines showed greater excitability of these cells compared with neurons from control lines, consistent with the observation of increased excitatory neuron excitability (Liu et al., 2013). More recent work demonstrated reduced excitability of GABAergic interneurons, but it has failed to recapitulate hyperexcitability of excitatory neurons (Jiao et al., 2013; Kim et al., 2018; Liu et al., 2016; Sun et al., 2016). Use of emerging technologies such as brain organoid cultures may offer opportunities to investigate additional behaviors of neural networks in Dravet syndrome.

Mutations in SCN2A are another major cause of epileptic encephalopathies, including Ohtahara syndrome, West syndrome, and epilepsy of infancy with migrating focal seizures. Patients with these syndromes have multiple seizure types, including focal seizures, tonic seizures, generalized tonic-clonic seizures, and infantile spasms. Seizures typically present in the first days or weeks of life, with some reports of seizures occurring on the day of birth (Howell et al., 2015; Nakamura et al., 2013; Wolff et al., 2017). Indeed, Ohtahara syndrome has the earliest age of onset among infantile epileptic encephalopathy associated with NaV channel mutations. In addition to seizures, many SCN2A-related epileptic encephalopathy patients also have significant neurodevelopmental and intellectual disabilities.

Investigations of the electrophysiological properties of SCN2A mutations associated with early onset epilepsy have suggested gain of function as a common pathophysiological mechanism. For example, E1211K (see Fig. 1), which is associated with intractable childhood epilepsy, has been shown to evoke a strongly hyperpolarized voltage dependence of activation (>10 mV) and a depolarized shift in inactivation (<20 mV) (Ogiwara et al., 2009). Computational modeling of this and one other SCN2A mutation (L1473M) demonstrated hyperexcitability of both immature neurons, where NaV1.2 is the sole axonal NaV channel, and mature neurons, where NaV1.2 is restricted to the proximal AIS (Ben-Shalom et al., 2017). Another mutation, A263V, has been shown to have enhanced persistent current, slower inactivation kinetics, and a depolarized shift in the voltage dependence of inactivation, all of which are consistent with promoting a hyperexcitable state (Liao, Anttonen, et al., 2010).

A knock-in mouse model bearing the A263V variant in the Scn2a gene is the only mouse model mimicking a human SCN2A epileptic encephalopathy. Interestingly, while heterozygous mice do not show a severe seizure phenotype, they do have altered neuronal excitability. Because NaV1.2 is largely expressed in excitatory neurons, one can predict that gain-of-function defects in NaV1.2 will cause increased excitability in these cells. Indeed, whole-cell current clamp recording in brain slices from Scn2aA263V+/– mice show hyperexcitability of CA1 pyramidal neurons (Schattling et al., 2016). Interestingly, when A263V mice are bred to homozygosity, the resulting mice have frequent spontaneous seizures and premature death. Unlike Dravet syndrome, many patients with SCN2A-related epileptic encephalopathies respond well to sodium channel blocking antiepileptic drugs, including phenytoin, lamotrigine, and oxcarbazepine, as would be expected from heighted activity of excitatory neurons. However, some evidence suggests that NaV channel blocking drugs are more effective in early onset epilepsy patients, whereas later onset epilepsies exhibit resistance to these drugs. This may reflect diminished expression of NaV1.2 in excitatory neurons as neuronal development progresses, with later onset epilepsy being driven by loss of NaV1.2 function in interneurons (Wolff et al., 2017).

A third severe form of epilepsy termed “early infantile epileptic encephalopathy type 13” (EIEE13) is associated with mutations in SCN8A encoding NaV1.6 (Wagnon & Meisler, 2015). Most patients with EIEE13 have generalized seizures with onset prior to 18 months of age. Following seizure onset, developmental regression occurs, with mild to severe intellectual disability. EIEE13 also typically presents with movement disorders such as mild ataxia, choreoathetosis, and occasionally quadriplegia (Lopez-Santiago et al., 2017; McNally et al., 2016; Meisler et al., 2016; Wagnon et al., 2016; Wagnon & Meisler, 2015). Importantly, most patients with EIEE13 have treatment-refractory seizures, but approximately 40% of patients respond well to antiepileptic drugs that target NaV channels. While the number of variants associated with EIEE13 is growing, functional data are available for only a few of these variants (Barker et al., 2016; de Kovel et al., 2014; Estacion et al., 2014; Patel, Barbosa, Brustovetsky, Brustovetsky, & Cummins, 2016). Due to overlapping expression with NaV1.2, one can predict that epilepsy in patients carrying NaV1.6 mutations may result from overactive excitatory neurons. Functional analysis has revealed that NaV1.6 variants associated with EIEE13 show primarily gain-of-function effects, including enhanced persistent current and slower entry into inactivated states. A mouse model of a prototypical NaV1.6 mutation, N1768D, exhibits infrequent spontaneous seizures and premature death (Lopez-Santiago et al., 2017; Wagnon et al., 2015). However, unlike in humans, seizures do not have early onset in the mice. Brain slice recording performed at P20 shows evidence of increased neuronal excitability, including a greater number of action potentials per degree of electrical stimulation and the occurrence of early afterdepolarizations, which are thought to be derived from the large persistent currents associated with this variant. Like the Scn2aA263V model, Scn8aN1768D mice show a much more severe phenotype when bred to homozygosity, with 100% mortality by three weeks of age.

Finally, de novo SCN3A variants were identified in a small cohort of patients diagnosed with an early onset epileptic encephalopathy. Mutations in NaV1.3 have previously been reported in less severe forms of epilepsy. However, these patients show early onset seizures within the first 18 months of life, with focal, tonic, generalized tonic-clonic, or myoclonic seizures. All patients also show significant developmental delay (Zaman et al., 2018). Functional analysis revealed predominantly gain-of-function phenotypes for these variants, including hyperpolarized voltage dependence of inactivation and large, persistent sodium currents (Zaman et al., 2018). While it is too early to draw definitive conclusions regarding the mechanism of SCN3A-related epileptogenesis, one can speculate that SCN3A-related epileptic encephalopathies arise from abnormal excitability during embryonic development.

While each epileptic encephalopathy stems from mutations in different NaV channels, and the mechanisms underlying epileptogenesis are likely to be different, some common conclusions may be drawn. First, variants that dramatically alter channel function drastically alter neuronal excitability, resulting in either heightened excitability of excitatory neurons or dampened excitability of inhibitory neurons; either mechanism capable of promoting hyperexcitability of neuronal networks. Secondly, this altered network excitability early in development induces long-term impairment of neuronal development that results in severe cognitive disability. This long-term impairment of cognitive development, or in some cases cognitive decline, distinguishes severe epileptic encephalopathies from more benign syndromes that are discussed in the next section.

Other Monogenic Epilepsy Syndromes

In addition to severe epileptic encephalopathy, mutations in SCN1A, SCN2A, and SCN3A are also associated with more benign forms of epilepsy, including genetic epilepsy with febrile seizures plus (GEFS+; SCN1A), benign familial neonatal infantile seizures (BFNIS; SCN2A) and cryptogenic focal epilepsy (SCN3A). Unlike epileptic encephalopathies, patients with these type of epilepsies do not generally have persistent cognitive deficits and in some cases show seizure remission with age. Also, these disorders tend to exhibit genetic transmission and classic Mendelian inheritance (typically autosomal-dominant), as opposed to de novo mutations found in most cases of epileptic encephalopathy.

GEFS+ is an autosomal-dominant familial epilepsy syndrome with febrile seizures presenting in early childhood that often persist beyond six years of age. There is strong phenotypical variability, with clinical phenotypes ranging from only mild febrile seizures to afebrile focal or generalized seizures, including atonic, myoclonic, or absence seizure types (Berkovic & Scheffer, 2001; Scheffer & Berkovic, 1997). This phenotypical variability is further demonstrated within families, wherein family members carrying the same mutations may be asymptomatic, have febrile seizures, or present with febrile seizures and generalized epilepsy (Escayg et al., 2000). GEFS+ typically arises from missense mutations in SCN1A (Brunklaus, Ellis, Reavey, Semsarian, & Zuberi, 2014). Unlike Dravet syndrome, which primarily results from loss of function of NaV1.1, GEFS+ mutations typically show more subtle biophysical defects when measured in heterologous cells. These include enhanced persistent sodium current (R1648H), depolarized shifts in voltage dependence of activation (R859C, I1656M, R1657C), or hyperpolarized shifts in voltage dependence of inactivation (R1916G) (Barela et al., 2006; Lossin et al., 2003; Rusconi et al., 2009; Vanoye, Lossin, Rhodes, & George, 2006). Some mutations also show either moderate or complete loss of whole-cell sodium currents, including V1353L, A1685V, and R1916G (Vanoye et al., 2006; Barela et al., 2006; Bechi et al., 2015; Lossin et al., 2003; Rhodes et al., 2005; Volkers et al., 2011). Computational modeling of the R859C mutation predicted reduced neuronal excitability (Barela et al., 2006). This suggests that GEF+ may arise by cellular mechanisms similar to Dravet syndrome, but with less devastating progression. While it appears that both GEFS+ and Dravet syndrome may arise from similar, but not identical, network mechanisms, one can speculate that complete loss of one functional NaV1.1 allele in Dravet syndrome may result in a more severe phenotype.

A knock-in mouse model of GEFS+, bearing a mutation analogous to human R1648H (Scn1aR1648H+/–), exhibits infrequent spontaneous seizures and reduced seizure threshold to hyperthermia or chemoconvulsant exposure (Martin et al., 2010). Acutely dissociated bipolar neurons from animals homozygous for the mutation show reduced excitability compared to both wild-type and heterozygous animals (Martin et al., 2010). In addition, inhibitory neurons within the thalamic nucleus reticularis (nRt), fast-spiking cortical layer IV interneurons, and CA1 hippocampal stratum oriens interneurons showed impaired excitability, while excitatory neurons were unaffected (Hedrich et al., 2014). Additionally, these animals exhibited disrupted GABA-mediated neurotransmission. Interestingly, if animals were exposed to a prolonged febrile event prior to slice recording, CA3 pyramidal neurons showed greater excitability compared to wild-type or Scn1aR1648H+/– animals that had not been exposed to a febrile event (Dutton et al., 2017). This “priming” with a febrile seizure has also been shown to increase spontaneous seizure frequency in Scn1a+/– mice, and this experimental strategy may represent a more clinically relevant paradigm for studying these animals (Hawkins et al., 2017). Oddly, voltage clamp recording of nucleated patches of neurons from Scn1aR1648H+/– mice did not exhibit enhanced persistent current compared to wild-type neurons and instead showed currents nearly indistinguishable from wild-type neurons, with only a slight slowing of recovery from inactivation. (Hedrich et al., 2014; Martin et al., 2010). This may be due to two possibilities: (1) rundown of persistent current during measurements, or (2) the same variant in mouse and human NaV1.1 behaves differently. The second possibility is intriguing, and not without precedent. The most common mutation in CFTR , the gene associated with cystic fibrosis in the United States (ΔF508) produces a protein that does not properly traffic to the plasma membrane in humans, but traffics and functions properly in rodents (Ostedgaard et al., 2007).

Variants in both SCN2A and SCN3A are also associated with less severe epilepsy phenotypes, including BFNIS (SCN2A), and cryptogenic focal epilepsy (SCN3A) (Wolff et al., 2017; Vanoye, Gurnett, Holland, George, & Kearney, 2014). Functional evaluation of BFNIS-associated NaV1.2 variants has shown a mix of gain- and loss-of-function effects, including enhanced persistent current (M252V), depolarized voltage dependence of inactivation (L1563V), or impaired cell surface expression (L1330M) (Liao, Deprez, et al., 2010; Misra, Kahlig, & George, 2008; Scalmani et al., 2006; Schwarz et al., 2016; Xu et al., 2007). Interestingly, both M252V and L1563V showed biophysical defects only when expressed in the context of the neonatal NaV1.2 alternatively spliced proteoform (Liao, Deprez, et al., 2010; Xu et al., 2007). This suggests that developmentally regulated mRNA splicing of NaV1.2, as well as a developmental switch from NaV1.2 to NaV1.6 in the AIS and nodes of Ranvier, may critically contribute to seizure remission in some patients. While no mouse models have been developed that mimic BFNIS, computational modeling of neurons with L1330M (L1153 in Figure 2) shows modestly increased neuronal excitability that normalizes as the neuron matures (Ben-Shalom et al., 2017). Thus far, it is difficult to make conclusions regarding the mechanisms underlying benign epilepsy associated with variants in SCN3A. Electrophysiological data show both gain and loss of function, though enhanced persistent sodium current appears to be a common feature (Estacion, Gasser, Dib-Hajj, & Waxman, 2010; Vanoye et al., 2014). Transfection of mouse hippocampal neurons with a gain-of-function SCN3A variant, K354Q, increases neuronal excitability (Estacion et al., 2010). However, mice deficient in Scn3a show greater susceptibility to electroconvulsive and chemiconvulsive-induced seizures than wild-type littermates (Lamar et al., 2017).

Although neuronal NaV channels perform similar functions, they do so in specific cell populations. Thus mutations in different NaV channels give rise to epilepsy phenotypes that vary in age of onset, seizure types, and therapeutic outcome. Epilepsy is a major source of disease burden in the United States, and continued research is needed to understand the nature of epileptogenesis so that improvements can be made in currently available treatments.

Autism Spectrum Disorder

Autism spectrum disorders (ASD) are a group of lifelong neurodevelopmental disorders with childhood onset. These disorders are associated with impaired social and communication skills and are characterized by ritualistic, repetitive, and rigid behavioral patterns. ASD has a population prevalence of 1 in 68 individuals in the United States with a male preponderance of 4 to 1 (Srivastava & Sahin, 2017; Weiss et al., 2003; Woodbury-Smith & Scherer, 2018). This represents a stunning rise in prevalence from historical rates of 4/10,000, although it is unknown if this is due to greater awareness, improvements in diagnostic criteria, or increases in environmental factors associated with ASD. ASD is typically diagnosed within the first three years of life, which is a critical period of neurodevelopment when neurite outgrowth and synaptogenesis occur. Post-mortem analysis of ASD brains has demonstrated neuroanatomical abnormalities and cellular-level differences in dendritic branching and spine density (Lin, Frei, Kilander, Shen, & Blatt, 2016).

It is widely accepted that the etiology of ASD has a very strong genetic component, with some estimates of heritability exceeding 90% (Weiss et al., 2003; Woodbury-Smith & Scherer, 2018). While ASD is generally considered to be a complex genetic trait, recent population-based gene discovery efforts have identified several de novo variants associated with the disorder (Codina-Sola et al., 2015; D’Gama et al., 2015; O’Roak et al., 2011; Sanders et al., 2012; Wang et al., 2016). Among the genes identified, SCN2A has been strongly associated with ASD. Interestingly, a significant percentage of ASD patients, 9–22% by some estimates, has comorbid epilepsy (Strasser, Downes, Kung, Cross, & De Haan, 2018).

Voltage-gated sodium channels were first identified as ASD risk genes in 2003 in a study that found missense or in-frame deletion variants in SCN1A, SCN2A, and SCN3A (Weiss et al., 2003). Interestingly, one variant in SCN2A (R1902C) affects a region of the NaV1.2 protein important for calmodulin binding. Analysis of calmodulin-binding affinity to a synthetic peptide encoding either the wildtype (WT) or variant protein sequence showed that the variant peptide exhibits twofold lower affinity for calmodulin. Interestingly, in the presence of 10 μM Ca2+, R1902C showed a hyperpolarized shift in voltage dependence of activation and a depolarized shift of voltage-dependence of inactivation, while WT channel function was not modulated by Ca2+ (Wang et al., 2014). Functional analysis of a number of other NaV1.2 variants, including T1420M (equivalent to T1242 in the NaV1.4 structure), depicted in Figure 2, demonstrated smaller whole-cell sodium currents when measured in heterologous systems (Ben-Shalom et al., 2017). This loss of function was explained by either a loss of cell surface expression or a functionally defective channel. Computational modeling of neurons carrying these variants showed that in simulated immature cortical excitatory neurons, mutant NaV1.2 channels caused impaired neuronal excitability. This is in contrast to epilepsy-associated mutations in NaV1.2, which showed greater neuronal excitability in this model neuron. Importantly, in mature neurons, where NaV1.6 replaces NaV1.2 as the major NaV channel in the proximal AIS, ASD-associated NaV1.2 variants have no impact on neuronal excitability (Ben-Shalom et al., 2017). This led to the hypothesis that loss of NaV1.2 function early in development, associated with impaired neuronal excitability, may be a critical pathophysiological mechanism in ASD. Interestingly, hetero- or homozygous knockout of mouse Scn2a does not produce an epilepsy phenotype (Planells-Cases et al., 2000). Thus, a critical test of this hypothesis will be to determine if Scn2a-deficient mice recapitulate any of the behavioral features associated with ASD.

As discussed, ASD is a commonly observed comorbidity of various epilepsy syndromes, with estimates of comorbid ASD in Dravet syndrome ranging 24–47% (Strasser et al., 2018). One proposed mechanism for development of ASD is an increased excitation:inhibition ratio stemming from a reduction in key inhibitory pathways in the neocortex (Chao et al., 2010; Coghlan et al., 2012; Rubenstein & Merzenich, 2003). Consistent with this hypothesis, Scn1a+/– mice show many autism spectrum behaviors, in addition to the well-documented seizure/premature death phenotype. Specifically, Scn1a+/– mice exhibit hyperactivity, anxiety, and deficits in social interactions compared to wild-type mice (Han et al., 2012; Ito et al., 2012; Tatsukawa, Ogiwara, Mazaki, Shimohata, & Yamakawa, 2018). Conditional deletion of Scn1a in forebrain parvalbumin-positive interneurons recapitulated the autistic-like traits of the global Scn1a+/– model, suggesting that parvalbumin-positive interneurons may be key contributors to the pathogenesis of ASD in this model (Tatsukawa et al., 2018). Furthermore, ASD phenotypes in Scn1a+/– mice could be rescued either by enhancement of GABAergic neurotransmission by treatment with low-dose clonazepam, a positive allosteric modulator of GABAA-receptors, or by treatment with cannabidiol (Han et al., 2012). Thus, ASD associated with mutations in NaV channels may result from a disrupted excitation/inhibition balance, but further work dissecting specific mechanisms of SCN1A- and SCN2A-related ASD will provide valuable insight into ASD disease progression and inform therapeutic decision making.

Familial Hemiplegic Migraine

Migraine is a complex, paroxysmal neurovascular disorder that is characterized by recurring severe headaches lasting one to three days. Migraine has a lifetime incidence of 14–18% worldwide, with more than 30 million migraine suffers in the United States (Lipton et al., 2007; Sutherland & Griffiths, 2017). Approximately 35% of all migraine suffers have aura preceding the headache. The transient neurological symptoms associated with aura correspond to cortical spreading depression, a wave of neuronal depolarization that slowly spreads across the cerebral cortex, generating transient periods of intense neuronal activity followed by long-lasting suppression (Mantegazza & Cestele, 2018). Although migraine is most likely a complex genetic trait, there are monogenic forms. Variants in SCN1A have been identified in patients diagnosed with familial hemiplegic migraine type 3 (FHM3), a rare autosomal-dominant form of migraine with aura characterized by transient motor weakness, visual aura, and speech disturbances.

To date, only 10 SCN1A mutations have been identified in FHM3 families. Like NaV1.1 mutations associated with mild forms of epilepsy, functional evaluation of FHM3 variants has yielded a constellation of biophysical phenotypes, ranging from reduced cell surface expression (Q1489K) to alterations in channel activation or inactivation properties. Some variants, such as L263V and Q1489K, have altered, albeit divergent, inactivation properties compared to wild-type NaV1.1 (Cestele et al., 2008; Kahlig et al., 2008). While L263V shows slower inactivation rate, depolarized voltage dependence of activation, and reduced use-dependent channel rundown, Q1489K exhibits faster inactivation and enhanced use-dependent channel rundown (Kahlig et al., 2008). Still a third variant, T1174S, exhibits depolarized voltage dependence of activation, while both L263V and Q1489K have hyperpolarized activation compared to wild-type channels (Cestele, Labate, et al., 2013; Kahlig et al., 2008). Enhanced persistent sodium current is shared among many of the FHM3-associated mutations. Current clamp recording of neurons transfected with Q1489K, an FHM3 mutation with increased persistent sodium current and faster inactivation kinetics, showed a unique excitability profile. These experiments showed self-limiting hyperexcitability, whereby neurons initially showed increased excitability with weak stimulation, but as stimulation strength increased, excitability converged with wild-type levels (Cestele et al., 2008). Mutant L1649Q also promoted neuronal hyperexcitability (Cestele, Schiavon, Rusconi, Franceschetti, & Mantegazza, 2013). Thus, while epilepsy-associated variants in SCN1A would generally be predicted to reduced interneuron excitability, this variant showed an initial increase in excitability. Work on FHM1 and FHM2, which stem from mutations in CACNA1A encoding the CaV2.1 voltage-gated calcium channel and ATP1A2 encoding a glial-expressed isoform of the Na/K-ATPase, respectively, have suggested that increased intracellular calcium and neurotransmitter release promote a lower threshold for cortical spreading depression (Kahlig et al., 2008; Sutherland & Griffiths, 2017). Future work should be devoted to interrogating the functional and molecular effects of these mutations in order to determine how mutations in the same gene, SCN1A, can result in two different disorders such as migraine and epilepsy.


Over the past few decades, research has provided critical insights into the structure of NaV channels and their function within the central nervous system. Even though we have gained much information into the structural states of the channel, researchers have yet to resolve the closed state of the channel, which may be a critical factor for structure-based drug design. Also, future research should be directed towards understanding the dynamics of structural rearrangements in response to physiological stimuli. It will also be important to devote research efforts to more fully understanding the interactions between NaV channels and their many interacting partners, and determining how these interactions modulate channel function and localization. Sodium channel diseases within the central nervous system significantly overlap. It is clear that variants in neuronal sodium channel that can lead to epilepsy, autism, and migraine may arise from either gain- or loss-of-function effects, and that disruption of the excitatory/inhibitory balance at key stages in development is a critical factor in pathogenesis. However, we do not fully understand how variants with similar functional defects may result in more or less severe forms of epilepsy, for example. Much of the work devoted to cataloging functional defects in sodium channels has been performed in heterologous cells, and future work needs to be devoted to understanding channel dysfunction in native neuronal cells. Future efforts will be needed to determine what factors guide neuronal development down specific pathophysiological pathways. We need to more fully understand which, and when, specific networks are affected in these disorders. Only then can effective treatment strategies be devised.


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