BACKGROUND Variants in SCN2A that disrupt the encoded neuronal sodium channel NaV1.2 are important risk factors for autism spectrum disorder (ASD), developmental delay, and infantile seizures. Variants observed in infantile seizures are predominantly missense, leading to a gain of function and increased neuronal excitability. How variants associated with ASD affect NaV1.2 function and neuronal excitability are unclear. METHODS We examined the properties of 11 ASD-associated SCN2A variants in heterologous expression systems using whole-cell voltage-clamp electrophysiology and immunohistochemistry. Resultant data were incorporated into computational models of developing and mature cortical pyramidal cells that express NaV1.2. RESULTS In contrast to gain of function variants that contribute to seizure, we found that all ASD-associated variants dampened or eliminated channel function. Incorporating these electrophysiological results into a compartmental model of developing excitatory neurons demonstrated that all ASD variants, regardless of their mechanism of action, resulted in deficits in neuronal excitability. Corresponding analysis of mature neurons predicted minimal change in neuronal excitability. CONCLUSIONS This functional characterization thus identifies SCN2A mutation and NaV1.2 dysfunction as the most frequently observed ASD risk factor detectable by exome sequencing and suggests that associated changes in neuronal excitability, particularly in developing neurons, may contribute to ASD etiology.

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Highlights d Conditional deletion of Na V 1.2 channels increases action potential (AP) excitability d Na V 1.2 regulates somatodendritc excitability, and Na V 1.6 regulates axonal action potential initiation d Lack of Na V 1.2 channels impairs AP repolarization by reducing K V activation d Reduced K V -mediated AP after hyperpolarization increases AP output

Epileptic encephalopathies are severe forms of infantile-onset epilepsy often complicated by severe neurodevelopmental impairments. Some forms of early-onset epileptic encephalopathy (EOEE) have been associated with variants in SCN2A, which encodes the brain voltage-gated sodium channel NaV1.2. Many voltage-gated sodium channel genes, including SCN2A, undergo developmentally regulated mRNA splicing. The early onset of these disorders suggests that developmentally regulated alternative splicing of NaV1.2 may be an important consideration when elucidating the pathophysiological consequences of epilepsy-associated variants. We hypothesized that EOEE-associated NaV1.2 variants would exhibit greater dysfunction in a splice isoform that is prominently expressed during early development. We engineered five EOEE-associated NaV1.2 variants (T236S, E999K, S1336Y, T1623N, and R1882Q) into the adult and neonatal splice isoforms of NaV1.2 and performed whole-cell voltage clamp to elucidate their functional properties. All variants exhibited functional defects that could enhance neuronal excitability. Three of the five variants (T236S, E999K, and S1336Y) exhibited greater dysfunction in the neonatal isoform compared with those observed in the adult isoform. Computational modeling of a developing cortical pyramidal neuron indicated that T236S, E999K, S1336Y, and R1882Q showed hyperexcitability preferentially in immature neurons. These results suggest that both splice isoform and neuronal developmental stage influence how EOEE-associated NaV1.2 variants affect neuronal excitability.

G-protein coupled receptors (GPCRs) initiate a variety of signaling cascades depending on effector coupling. β-arrestins, which were initially characterized by their ability to “arrest” GPCR signaling by uncoupling receptor and G protein, have recently emerged as important signaling effectors for GPCRs. β-arrestins engage signaling pathways that are distinct from those mediated by G-protein. As such, arrestin-dependent signaling can play a unique role in regulating cell function, but whether neuromodulatory GPCRs utilize β-arrestin-dependent signaling to regulate neuronal excitability remains unclear. Here, we find that D3 dopamine receptors (D3R) regulate axon initial segment (AIS) excitability through β-arrestin-dependent signaling, modifying CaV3 voltage dependence to suppress high frequency action potential generation. This non-canonical D3R signaling thereby gates AIS excitability via pathways distinct from classical GPCR signaling pathways.

The medial prefrontal cortex plays a key role in higher order cognitive functions like decision making and social cognition. These complex behaviors emerge from the coordinated firing of prefrontal neurons. Fast-spiking interneurons (FSIs) control the timing of excitatory neuron firing via somatic inhibition and generate gamma (30–100 Hz) oscillations. Therefore, factors that regulate how FSIs respond to gamma-frequency input could affect both prefrontal circuit activity and behavior. Here, we show that serotonin (5HT), which is known to regulate gamma power, acts via 5HT2A receptors to suppress an inward-rectifying potassium conductance in FSIs. This leads to depolarization, increased input resistance, enhanced spiking, and slowed decay of excitatory post-synaptic potentials (EPSPs). Notably, we found that slowed EPSP decay preferentially enhanced temporal summation and firing elicited by gamma frequency inputs. These findings show how changes in passive membrane properties can affect not only neuronal excitability but also the temporal filtering of synaptic inputs.

Genetic variants in SCN2A, encoding the NaV1.2 voltage-gated sodium channel, are associated with a range of neurodevelopmental disorders with overlapping phenotypes. Some variants fit into a framework wherein gain-of-function missense variants that increase neuronal excitability lead to developmental and epileptic encephalopathy, while loss-of-function variants that reduce neuronal excitability lead to intellectual disability and/or autism spectrum disorder with or without co-morbid seizures. One unique case less easily classified using this framework is the de novo missense variant SCN2A-p.K1422E, associated with infant-onset developmental delay, infantile spasms, and features of autism spectrum disorder. Prior structure–function studies demonstrated that K1422E substitution alters ion selectivity of NaV1.2, conferring Ca2+ permeability, lowering overall conductance, and conferring resistance to tetrodotoxin (TTX). Based on heterologous expression of K1422E, we developed a compartmental neuron model incorporating variant channels that predicted reductions in peak action potential speed. We generated Scn2aK1422E mice and characterized effects on neurons and neurological/neurobehavioral phenotypes. Cultured cortical neurons from heterozygous Scn2aK1422E/+ mice exhibited lower current density with a TTX-resistant component and reversal potential consistent with mixed ion permeation. Recordings from Scn2aK1442E/+ cortical slices demonstrated impaired action potential initiation and larger Ca2+ transients at the axon initial segment during the rising phase of the action potential, suggesting complex effects on channel function. Scn2aK1422E/+ mice exhibited rare spontaneous seizures, interictal EEG abnormalities, altered induced seizure thresholds, reduced anxiety-like behavior and alterations in olfactory-guided social behavior. Overall, Scn2aK1422E/+ mice present with phenotypes similar yet distinct from other Scn2a models, consistent with complex effects of K1422E on NaV1.2 channel function.

Compartmental modeling is a widely used tool in neurophysiology but the detail and scope of such models is frequently limited by lack of computational resources. Here we implement compartmental modeling on low cost Graphical Processing Units (GPUs), which significantly increases simulation speed compared to NEURON. Testing two methods for solving the current diffusion equation system revealed which method is more useful for specific neuron morphologies. Regions of applicability were investigated using a range of simulations from a single membrane potential trace simulated in a simple fork morphology to multiple traces on multiple realistic cells. A runtime peak 150-fold faster than the CPU was achieved. This application can be used for statistical analysis and data fitting optimizations of compartmental models and may be used for simultaneously simulating large populations of neurons. Since GPUs are forging ahead and proving to be more cost-effective than CPUs, this may significantly decrease the cost of computation power and open new computational possibilities for laboratories with limited budgets.