Functional evaluation of human ion channel variants using automated electrophysiology

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.

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.

Epilepsy-associated SCN2A (NaV1.2) variants exhibit diverse and complex functional properties

Pathogenic variants in voltage-gated sodium (NaV) channel genes including SCN2A, encoding NaV1.2, are discovered frequently in neurodevelopmental disorders with or without epilepsy. SCN2A is also a high-confidence risk gene for autism spectrum disorder (ASD) and nonsyndromic intellectual disability (ID). Previous work to determine the functional consequences of SCN2A variants yielded a paradigm in which predominantly gain-of-function variants cause neonatal-onset epilepsy, whereas loss-of-function variants are associated with ASD and ID. However, this framework was derived from a limited number of studies conducted under heterogeneous experimental conditions, whereas most disease-associated SCN2A variants have not been functionally annotated. We determined the functional properties of SCN2A variants using automated patch-clamp recording to demonstrate the validity of this method and to examine whether a binary classification of variant dysfunction is evident in a larger cohort studied under uniform conditions. We studied 28 disease-associated variants and 4 common variants using two alternatively spliced isoforms of NaV1.2 expressed in HEK293T cells. Automated patch-clamp recording provided a valid high throughput method to ascertain detailed functional properties of NaV1.2 variants with concordant findings for variants that were previously studied using manual patch clamp. Many epilepsy-associated variants in our study exhibited complex patterns of gain- and loss-of-functions that are difficult to classify by a simple binary scheme. The higher throughput achievable with automated patch clamp enables study of variants with greater standardization of recording conditions, freedom from operator bias, and enhanced experimental rigor. This approach offers an enhanced ability to discern relationships between channel dysfunction and neurodevelopmental disorders.

Epilepsy-associated SCN2A (Na V 1.2) Variants Exhibit Diverse and Complex Functional Properties

Pathogenic variants in neuronal voltage-gated sodium (Na V ) channel genes including SCN2A , which encodes Na V 1.2, are frequently discovered in neurodevelopmental disorders with and without epilepsy. SCN2A is also a high confidence risk gene for autism spectrum disorder (ASD) and nonsyndromic intellectual disability (ID). Previous work to determine the functional consequences of SCN2A variants yielded a paradigm in which predominantly gain-of-function (GoF) variants cause epilepsy whereas loss-of-function (LoF) variants are associated with ASD and ID. However, this framework is based on a limited number of functional studies conducted under heterogenous experimental conditions whereas most disease-associated SCN2A variants have not been functionally annotated. We determined the functional properties of more than 30 SCN2A variants using automated patch clamp recording to assess the analytical validity of this approach and to examine whether a binary classification of variant dysfunction is evident in a larger cohort studied under uniform conditions. We studied 28 disease-associated variants and 4 common population variants using two distinct alternatively spliced forms of Na V 1.2 that were heterologously expressed in HEK293T cells. Multiple biophysical parameters were assessed on 5,858 individual cells. We found that automated patch clamp recording provided a valid high throughput method to ascertain detailed functional properties of Na V 1.2 variants with concordant findings for a subset of variants that were previously studied using manual patch clamp. Additionally, many epilepsy-associated variants in our study exhibited complex patterns of gain- and loss-of-function properties that are difficult to classify overall by a simple binary scheme. The higher throughput achievable with automated patch clamp enables study of a larger number of variants, greater standardization of recording conditions, freedom from operator bias, and enhanced experimental rigor valuable for accurate assessment of Na V channel variant dysfunction. Together, this approach will enhance our ability to discern relationships between variant channel dysfunction and neurodevelopmental disorders.

Predicting the functional impact of KCNQ1 variants with artificial neural networks

Recent advances in experimental and computational protein structure determination have provided access to high-quality structures for most human proteins and mutants thereof. However, linking changes in structure in protein mutants to functional impact remains an active area of method development. If successful, such methods can ultimately assist physicians in taking appropriate treatment decisions. This work presents three artificial neural network (ANN)-based predictive models that classify four key functional parameters of KCNQ1 variants as normal or dysfunctional using PSSM-based evolutionary and/or biophysical descriptors. Recent advances in predicting protein structure and variant properties with artificial intelligence (AI) rely heavily on the availability of evolutionary features and thus fail to directly assess the biophysical underpinnings of a change in structure and/or function. The central goal of this work was to develop an ANN model based on structure and physiochemical properties of KCNQ1 potassium channels that performs comparably or better than algorithms using only on PSSM-based evolutionary features. These biophysical features highlight the structure-function relationships that govern protein stability, function, and regulation. The input sensitivity algorithm incorporates the roles of hydrophobicity, polarizability, and functional densities on key functional parameters of the KCNQ1 channel. Inclusion of the biophysical features outperforms exclusive use of PSSM-based evolutionary features in predicting activation voltage dependence and deactivation time. As AI is increasingly applied to problems in biology, biophysical understanding will be critical with respect to 'explainable AI', i.e., understanding the relation of sequence, structure, and function of proteins. Our model is available at www.kcnq1predict.org.

High-throughput evaluation of epilepsy-associated KCNQ2 variants reveals functional and pharmacological heterogeneity

Hundreds of genetic variants in KCNQ2 encoding the voltage-gated potassium channel KV7.2 are associated with early onset epilepsy and/or developmental disability, but the functional consequences of most variants are unknown. Absent functional annotation for KCNQ2 variants hinders identification of individuals who may benefit from emerging precision therapies. We employed automated patch clamp recordings to assess at, to our knowledge, an unprecedented scale the functional and pharmacological properties of 79 missense and 2 inframe deletion KCNQ2 variants. Among the variants we studied were 18 known pathogenic variants, 24 mostly rare population variants, and 39 disease-associated variants with unclear functional effects. We analyzed electrophysiological data recorded from 9,480 cells. The functional properties of 18 known pathogenic variants largely matched previously published results and validated automated patch clamp for this purpose. Unlike rare population variants, most disease-associated KCNQ2 variants exhibited prominent loss-of-function with dominant-negative effects, providing strong evidence in support of pathogenicity. All variants responded to retigabine, although there were substantial differences in maximal responses. Our study demonstrated that dominant-negative loss-of-function is a common mechanism associated with missense KCNQ2 variants. Importantly, we observed genotype-dependent differences in the response of KCNQ2 variants to retigabine, a proposed precision therapy for KCNQ2 developmental and epileptic encephalopathy.

Screening Platforms for Genetic Epilepsies-Zebrafish, iPSC-Derived Neurons, and Organoids

Recent advances in molecular and cellular engineering, such as human cell reprogramming, genome editing, and patient-specific organoids, have provided unprecedented opportunities for investigating human disorders in both animals and human-based models at an improved pace and precision. This progress will inevitably lead to the development of innovative drug-screening platforms and new patient-specific therapeutics. In this review, we discuss recent advances that have been made using zebrafish and human-induced pluripotent stem cell (iPSC)-derived neurons and organoids for modeling genetic epilepsies. We also provide our prospective on how these models can potentially be combined to build new screening platforms for antiseizure and antiepileptogenic drug discovery that harness the robustness and tractability of zebrafish models as well as the patient-specific genetics and biology of iPSC-derived neurons and organoids.