Functional correlates of clinical phenotype and severity in recurrent SCN2A variants

Molecular and cellular context influences SCN8A variant function

Pathogenic variants in SCN8A, which encodes the voltage-gated sodium (NaV) channel NaV1.6, associate with neurodevelopmental disorders, including developmental and epileptic encephalopathy. Previous approaches to determine SCN8A variant function may be confounded by use of a neonatally expressed, alternatively spliced isoform of NaV1.6 (NaV1.6N) and engineered mutations rendering the channel tetrodotoxin (TTX) resistant. We investigated the impact of SCN8A alternative splicing on variant function by comparing the functional attributes of 15 variants expressed in 2 developmentally regulated splice isoforms (NaV1.6N, NaV1.6A). We employed automated patch clamp recording to enhance throughput, and developed a neuronal cell line (ND7/LoNav) with low levels of endogenous NaV current to obviate the need for TTX-resistance mutations. Expression of NaV1.6N or NaV1.6A in ND7/LoNav cells generated NaV currents with small, but significant, differences in voltage dependence of activation and inactivation. TTX-resistant versions of both isoforms exhibited significant functional differences compared with the corresponding WT channels. We demonstrated that many of the 15 disease-associated variants studied exhibited isoform-dependent functional effects, and that many of the studied SCN8A variants exhibited functional properties that were not easily classified as either gain- or loss-of-function. Our work illustrates the value of considering molecular and cellular context when investigating SCN8A variants.

An iPSC line (FINi003-A) from a male with late-onset developmental and epileptic encephalopathy caused by a heterozygous p.E1211K variant in the SCN2A gene encoding the voltage-gated sodium channel Nav1.2

Many developmental and epileptic encephalopathies (DEEs) result from variants in cation channel genes. Using mRNA transfection, we generated and characterised an induced pluripotent stem cell (iPSC) line from the fibroblasts of a male late-onset DEE patient carrying a heterozygous missense variant (E1211K) in Nav1.2(SCN2A) protein. The iPSC line displays features characteristic of the human iPSCs, colony morphology and expression of pluripotency-associated marker genes, ability to produce derivatives of all three embryonic germ layers, and normal karyotype without SNP array-detectable abnormalities. We anticipate that this iPSC line will aid in the modelling and development of precision therapies for this debilitating condition.

Clinical characteristics and genetic analysis of pediatric patients with sodium channel gene mutation-related childhood epilepsy: a review of 94 patients

Objective

This study aimed to examine the clinical and gene-mutation characteristics of pediatric patients with sodium channel gene mutation-related childhood epilepsy and to provide a basis for precision treatment and genetic counseling.

Methods

The clinical data from 94 patients with sodium channel gene mutation-related childhood epilepsy who were treated at Hunan Children's Hospital from August 2012 to December 2022 were retrospectively evaluated, and the clinical characteristics, gene variants, treatment, and follow-up status were analyzed and summarized.

Results

Our 94 pediatric patients with sodium channel gene variant-related childhood epilepsy comprised 37 girls and 57 boys. The age of disease onset ranged from 1 day to 3 years. We observed seven different sodium channel gene variants, and 55, 14, 9, 6, 6, 2, and 2 patients had SCNlA, SCN2A, SCN8A, SCN9A, SCN1B, SCN11A, and SCN3A variants, respectively. We noted that 52 were reported variants and 42 were novel variants. Among all gene types, SCN1A, SCN2A, and SCN8A variants were associated with an earlier disease onset age. With the exception of the SCN1B, the other six genes were associated with clustering seizures. Except for variants SCN3A and SCN11A, some patients with other variants had status epilepticus (SE). The main diagnosis of children with SCN1A variants was Dravet syndrome (DS) (72.7%), whereas patients with SCN2A and SCN8A variants were mainly diagnosed with various types of epileptic encephalopathy, accounting for 85.7% (12 of 14) and 88.9% (8 of 9) respectively. A total of five cases of sudden unexpected death in epilepsy (SUDEP) occurred in patients with SCN1A, SCN2A, and SCN8A variants. The proportion of benign epilepsy in patients with SCN9A, SCN11A, and SCN1B variants was relatively high, and the epilepsy control rate was higher than the rate of other variant types.

Conclusion

Sodium channel gene variants involve different epileptic syndromes, and the treatment responses also vary. We herein reported 42 novel variants, and we are also the first ever to report two patients with SCN11A variants, thereby increasing the gene spectrum and phenotypic profile of sodium channel dysfunction. We provide a basis for precision treatment and prognostic assessment.

Opto-electronic feedback control of membrane potential for real-time control of action potentials

To unlock new research possibilities by acquiring control of action potential (AP) morphologies in excitable cells, we developed an opto-electronic feedback loop-based system integrating cellular electrophysiology, real-time computing, and optogenetic approaches and applied it to monolayers of heart muscle cells. This allowed accurate restoration and preservation of cardiac AP morphologies in the presence of electrical perturbations of different origin in an unsupervised, self-regulatory manner, without any prior knowledge of the disturbance. Moreover, arbitrary AP waveforms could be enforced onto these cells. Collectively, these results set the stage for the refinement and application of opto-electronic control systems to enable in-depth investigation into the regulatory role of membrane potential in health and disease.

Evaluating the interplay between estrous cyclicity and flurothyl-induced seizure susceptibility in Scn2a K1422E mice

Recently, we demonstrated that Scn2a K1422E female mice showed a distinct distribution of flurothyl-induced seizure thresholds. To evaluate whether the estrous cycle contributes to this effect, estrous cycle monitoring was performed in mice that had undergone ovariectomy, sham surgery, or no treatment prior to seizure induction. Ovariectomy did not affect the non-unimodal distribution of flurothyl seizure thresholds observed in Scn2a K1422E females. Additionally, seizure thresholds were not associated with estrous cycle stage in mice that underwent sham surgery or in non-surgerized (intact) mice. Interestingly, intact Scn2a K1422E females showed evidence of disrupted estrous cyclicity, an effect not previously described in a genetic epilepsy model.

Scn2a insufficiency alters spontaneous neuronal Ca2+ activity in somatosensory cortex during wakefulness

SCN2A protein-truncating variants (PTV) can result in neurological disorders such as autism spectrum disorder and intellectual disability, but they are less likely to cause epilepsy in comparison to missense variants. While in vitro studies showed PTV reduce action potential firing, consequences at in vivo network level remain elusive. Here, we generated a mouse model of Scn2a insufficiency using antisense oligonucleotides (Scn2a ASO mice), which recapitulated key clinical feature of SCN2A PTV disorders. Simultaneous two-photon Ca2+ imaging and electrocorticography (ECoG) in awake mice showed that spontaneous Ca2+ transients in somatosensory cortical neurons, as well as their pairwise co-activities were generally decreased in Scn2a ASO mice during spontaneous awake state and induced seizure state. The reduction of neuronal activities and paired co-activity are mechanisms associated with motor, social and cognitive deficits observed in our mouse model of severe Scn2a insufficiency, indicating these are likely mechanisms driving SCN2A PTV pathology.

Molecular and Cellular Context Influences SCN8A Variant Function

Pathogenic variants in SCN8A , which encodes the voltage-gated sodium (Na V ) channel Na V 1.6, are associated with neurodevelopmental disorders including epileptic encephalopathy. Previous approaches to determine SCN8A variant function may be confounded by the use of a neonatal-expressed alternatively spliced isoform of Na V 1.6 (Na V 1.6N), and engineered mutations to render the channel tetrodotoxin (TTX) resistant. In this study, we investigated the impact of SCN8A alternative splicing on variant function by comparing the functional attributes of 15 variants expressed in two developmentally regulated splice isoforms (Na V 1.6N, Na V 1.6A). We employed automated patch clamp recording to enhance throughput, and developed a novel neuronal cell line (ND7/LoNav) with low levels of endogenous Na V current to obviate the need for TTX-resistance mutations. Expression of Na V 1.6N or Na V 1.6A in ND7/LoNav cells generated Na V currents that differed significantly in voltage-dependence of activation and inactivation. TTX-resistant versions of both isoforms exhibited significant functional differences compared to the corresponding wild-type (WT) channels. We demonstrated that many of the 15 disease-associated variants studied exhibited isoform-dependent functional effects, and that many of the studied SCN8A variants exhibited functional properties that were not easily classified as either gain- or loss-of-function. Our work illustrates the value of considering molecular and cellular context when investigating SCN8A variants.

Distinguishing Loss-of-Function and Gain-of-Function SCN8A Variants Using a Random Forest Classification Model Trained on Clinical Features

Background and Objectives

Pathogenic variants at the voltage-gated sodium channel gene, SCN8A, are associated with a wide spectrum of clinical disease outcomes. A critical challenge for neurologists is to determine whether patients carry gain-of-function (GOF) or loss-of-function (LOF) variants to guide treatment decisions, yet in vitro studies to infer channel function are often not feasible in the clinic. In this study, we develop a predictive modeling approach to classify variants based on clinical features present at initial diagnosis.

Methods

We performed an exhaustive search for individuals deemed to carry SCN8A GOF and LOF variants by means of in vitro studies in heterologous cell systems, or because the variant was classified as truncating, and recorded clinical features. This resulted in a total of 69 LOF variants: 34 missense and 35 truncating variants, including 9 nonsense, 13 frameshift, 6 splice site, 6 indels, and 1 large deletion. We then assembled a truth set of variants with known functional effects, excluding individuals carrying variants at other loci associated with epilepsy. We then trained a predictive model based on random forest using this truth set of 45 LOF variants and 45 GOF variants randomly selected from a set of variants tested by in vitro methods.

Results

Phenotypic categories assigned to individuals correlated strongly with GOF or LOF variants. All patients with GOF variants experienced early-onset seizures (mean age at onset = 4.5 ± 3.1 months) while only 64.4% patients with LOF variants had seizures, most of which were late-onset absence seizures (mean age at onset = 40.0 ± 38.1 months). With high accuracy (95.4%), our model including 5 key clinical features classified individuals with GOF and LOF variants into 2 distinct cohorts differing in age at seizure onset, development of seizures, seizure type, intellectual disability, and developmental and epileptic encephalopathy.

Discussion

The results support the hypothesis that patients with SCN8A GOF and LOF variants represent distinct clinical phenotypes. The clinical model developed in this study has great utility because it provides a rapid and highly accurate platform for predicting the functional class of patient variants during SCN8A diagnosis, which can aid in initial treatment decisions and improve prognosis.

Cation leak: a common functional defect causing HCN1 developmental and epileptic encephalopathy

Pathogenic variants in HCN1 are an established cause of developmental and epileptic encephalopathy (DEE). To date, the stratification of patients with HCN1-DEE based on the biophysical consequence on channel function of a given variant has not been possible. Here, we analysed data from eleven patients carrying seven different de novo HCN1 pathogenic variants located in the transmembrane domains of the protein. All patients were diagnosed with severe disease including epilepsy and intellectual disability. The functional properties of the seven HCN1 pathogenic variants were assessed using two-electrode voltage-clamp recordings in Xenopus oocytes. All seven variants showed a significantly larger instantaneous current consistent with cation leak. The impact of each variant on other biophysical properties was variable, including changes in the half activation voltage and activation and deactivation kinetics. These data suggest that cation leak is an important pathogenic mechanism in HCN1-DEE. Furthermore, published mouse model and clinical case reports suggest that seizures are exacerbated by sodium channel blockers in patients with HCN1 variants that cause cation leak. Stratification of patients based on their 'cation leak' biophysical phenotype may therefore provide key information to guide clinical management of individuals with HCN1-DEE.

Evaluating the interplay between estrous cyclicity and induced seizure susceptibility in Scn2aK1422E mice

Pathogenic variants in SCN2A are associated with a range of neurodevelopmental disorders (NDD). SCN2A-related NDD show wide phenotypic heterogeneity, suggesting that modifying factors must be considered in order to properly elucidate the mechanisms of pathogenic variants. Recently, we characterized neurological phenotypes in a mouse model of the variant SCN2A-p.K1422E. We demonstrated that heterozygous Scn2aK1422E female mice showed a distinct, reproducible distribution of flurothyl-induced seizure thresholds. Women with epilepsy often show a cyclical pattern of altered seizure susceptibility during specific phases of the menstrual cycle which can be attributed to fluctuations in hormones and corresponding changes in neurosteroid levels. Rodent models have been used extensively to examine the relationship between the estrous (menstrual) cycle, steroid hormones, and seizure susceptibility. However, the effects of the estrous cycle on seizure susceptibility have not been evaluated in the context of an epilepsy-associated genetic variant. To determine whether the estrous cycle affects susceptibility to flurothyl-induced seizures in Scn2aK1422E female mice, estrous cycle monitoring was performed in mice that had undergone ovariectomy (OVX), sham surgery, or no treatment prior to seizure induction. Removing the influence of circulating sex hormones via OVX did not affect the non-unimodal distribution of flurothyl seizure thresholds observed in Scn2aK1422E females. Additionally, flurothyl seizure thresholds were not associated with estrous cycle stage in mice that underwent sham surgery or were untreated. These data suggest that variation in Scn2aK1422E flurothyl seizure threshold is not significantly influenced by the estrous cycle and, by extension, fluctuations in ovarian hormones. Interestingly, untreated Scn2aK1422E females showed evidence of disrupted estrous cyclicity, an effect not previously described in a genetic epilepsy model. This unexpected result highlights the importance of considering sex specific effects and the estrous cycle in support of more inclusive biomedical research.

Predicting functional effects of ion channel variants using new phenotypic machine learning methods

Missense variants in genes encoding ion channels are associated with a spectrum of severe diseases. Variant effects on biophysical function correlate with clinical features and can be categorized as gain- or loss-of-function. This information enables a timely diagnosis, facilitates precision therapy, and guides prognosis. Functional characterization presents a bottleneck in translational medicine. Machine learning models may be able to rapidly generate supporting evidence by predicting variant functional effects. Here, we describe a multi-task multi-kernel learning framework capable of harmonizing functional results and structural information with clinical phenotypes. This novel approach extends the human phenotype ontology towards kernel-based supervised machine learning. Our gain- or loss-of-function classifier achieves high performance (mean accuracy 0.853 SD 0.016, mean AU-ROC 0.912 SD 0.025), outperforming both conventional baseline and state-of-the-art methods. Performance is robust across different phenotypic similarity measures and largely insensitive to phenotypic noise or sparsity. Localized multi-kernel learning offered biological insight and interpretability by highlighting channels with implicit genotype-phenotype correlations or latent task similarity for downstream analysis.