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Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice.

Objective: Determining the pathogenicity of missense variants in clinical genetic tests for individuals with epilepsy is crucial for guiding personalized treatment. However, achieving a definitive pathogenic classification remains challenging, with most missense variants still classified as variants of uncertain significance (VUS) and with the availability of many computational tools which may provide conflicting predictions. Here, we aim to evaluate the performance of state‐of‐the‐art computational tools in pathogenicity prediction of missense variants in epilepsy‐associated genes. This will assist in selecting the most appropriate tool and critically assess their use in clinical setting. Methods: We assessed the performance of nine in silico pathogenicity prediction tools for missense variants in epilepsy‐associated genes on three carefully curated data sets. The first two data sets comprise missense variants in epilepsy associated genes that have been uploaded to ClinVar in the last year and were, therefore, not part of the training set of any of the nine considered tools. These two data sets are based on two different lists of epilepsy‐associated genes and comprise ~700 and ~ 250 missense variants, respectively. The third data set includes ~400 missense variants within epilepsy‐associated genes for which the functional effects have been determined experimentally and are therefore used here to infer pathogenicity. These three data sets represent the best available approximation to blind and independent test sets. Results: Among the nine assessed tools, AlphaMissense (area under the curve [AUC]:.93,.88, and.95) and REVEL (AUC:.93,.88, and.93) showed the best classification performance, also outperforming other tools in the number of classified variants. Significance: We show which recently developed prediction tools achieve higher performance in epilepsy‐associated genes and should be integrated, therefore, into the American College of Medical Genetics and Genomics/Association of Molecular Pathology (AGMC/AMP) variant classification process. Periodic reevaluation of genetic test results with newly developed or updated tools should be incorporated into standard clinical practice to improve diagnostic yield and better inform precision medicine. [ABSTRACT FROM AUTHOR]

Objective: Dravet syndrome (DS) is a developmental and epileptic encephalopathy characterized by high seizure burden, treatment‐resistant epilepsy, and developmental stagnation. Family members rate communication deficits among the most impactful disease manifestations. We evaluated seizure burden and language/communication development in children with DS. Methods: ENVISION was a prospective, observational study evaluating children with DS associated with SCN1A pathogenic variants (SCN1A+ DS) enrolled at age ≤5 years. Seizure burden and antiseizure medications were assessed every 3 months and communication and language every 6 months with the Bayley Scales of Infant and Toddler Development 3rd edition and the parent‐reported Vineland Adaptive Behavior Scales 3rd edition. We report data from the first year of observation, including analyses stratified by age at Baseline: 0:6–2:0 years:months (Y:M; youngest), 2:1–3:6 Y:M (middle), and 3:7–5:0 Y:M (oldest). Results: Between December 2020 and March 2023, 58 children with DS enrolled at 16 sites internationally. Median follow‐up was 17.5 months (range =.0–24.0), with 54 of 58 (93.1%) followed for at least 6 months and 51 of 58 (87.9%) for 12 months. Monthly countable seizure frequency (MCSF) increased with age (median [minimum–maximum] = 1.0 in the youngest [1.0–70.0] and middle [1.0–242.0] age groups and 4.5 [.0–2647.0] in the oldest age group), and remained high, despite use of currently approved antiseizure medications. Language/communication delays were observed early, and developmental stagnation occurred after age 2 years with both instruments. In predictive modeling, chronologic age was the only significant covariate of seizure frequency (effect size =.52, p =.024). MCSF, number of antiseizure medications, age at first seizure, and convulsive status epilepticus were not predictors of language/communication raw scores. Significance: In infants and young children with SCN1A+ DS, language/communication delay and stagnation were independent of seizure burden. Our findings emphasize that the optimal therapeutic window to prevent language/communication delay is before 3 years of age. [ABSTRACT FROM AUTHOR]

Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. As a consequence, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion-channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated. We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion-channel families. We collected and curated 3049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12 546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures. We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5Å distance from the pore axis centre and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and functional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N -methyl-D-aspartate receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1422 neurodevelopmental disorder pathogenic patient variants and 679 electrophysiological experiments, we show that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain versus loss-of-channel function. In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional readouts and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future. [ABSTRACT FROM AUTHOR]

Neurodevelopmental disorders (NDDs), including severe paediatric epilepsy, autism and intellectual disabilities are heterogeneous conditions in which clinical genetic testing can often identify a pathogenic variant. For many of them, genetic therapies will be tested in this or the coming years in clinical trials. In contrast to first-generation symptomatic treatments, the new disease-modifying precision medicines require a genetic test-informed diagnosis before a patient can be enrolled in a clinical trial. However, even in 2022, most identified genetic variants in NDD genes are 'variants of uncertain significance'. To safely enrol patients in precision medicine clinical trials, it is important to increase our knowledge about which regions in NDD-associated proteins can 'tolerate' missense variants and which ones are 'essential' and will cause a NDD when mutated. In addition, knowledge about functionally indispensable regions in the 3D structure context of proteins can also provide insights into the molecular mechanisms of disease variants. We developed a novel consensus approach that overlays evolutionary, and population based genomic scores to identify 3D essential sites (Essential3D) on protein structures. After extensive benchmarking of AlphaFold predicted and experimentally solved protein structures, we generated the currently largest expert curated protein structure set for 242 NDDs and identified 14 377 Essential3D sites across 189 gene disorders associated proteins. We demonstrate that the consensus annotation of Essential3D sites improves prioritization of disease mutations over single annotations. The identified Essential3D sites were enriched for functional features such as intermembrane regions or active sites and discovered key inter-molecule interactions in protein complexes that were otherwise not annotated. Using the currently largest autism, developmental disorders, and epilepsies exome sequencing studies including >360 000 NDD patients and population controls, we found that missense variants at Essential3D sites are 8-fold enriched in patients. In summary, we developed a comprehensive protein structure set for 242 NDDs and identified 14 377 Essential3D sites in these. All data are available at https://es-ndd.broadinstitute.org for interactive visual inspection to enhance variant interpretation and development of mechanistic hypotheses for 242 NDDs genes. The provided resources will enhance clinical variant interpretation and in silico drug target development for NDD-associated genes and encoded proteins. [ABSTRACT FROM AUTHOR]

Pathogenic variants in the voltage-gated sodium channel gene family (SCNs) lead to early onset epilepsies, neurodevelopmental disorders, skeletal muscle channelopathies, peripheral neuropathies and cardiac arrhythmias. Disease-associated variants have diverse functional effects ranging from complete loss-of-function to marked gain-of-function. Therapeutic strategy is likely to depend on functional effect. Experimental studies offer important insights into channel function, but are resource intensive and only performed in a minority of cases. Given the evolutionarily conserved nature of the sodium channel genes we investigated whether similarities in biophysical properties between different voltage-gated sodium channels can predict function and inform precision treatment across sodium channelopathies. We performed a systematic literature search identifying functionally assessed variants in any of the nine voltage-gated sodium channel genes until 28 April 2021. We included missense variants that had been electrophysiologically characterised in mammalian cells in whole-cell patch-clamp recordings. We performed an alignment of linear protein sequences of all sodium channel genes and correlated variants by their overall functional effect on biophysical properties. Of 951 identified records, 437 sodium channel-variants met our inclusion criteria and were reviewed for functional properties. Of these, 141 variants were epilepsy-associated (SCN1/2/3/8A), 79 had a neuromuscular phenotype (SCN4/9/10/11A), 149 were associated with a cardiac phenotype (SCN5/10A) and 68 (16%) were considered benign. We detected 38 missense variant pairs with an identical disease-associated variant in a different sodium channel gene. 35 out of 38 of those pairs resulted in similar functional consequences indicating up to 92% biophysical agreement between corresponding sodium channel variants (odds ratio = 11.3; 95% CI = 2.8 to 66.9; P < 0.001). Pathogenic missense variants were clustered in specific functional domains, whereas population variants were significantly more frequent across non conserved domains (odds ratio = 18.6; 95% CI = 10.9 to 34.4; P < 0.001). Pore-loop regions were frequently associated with loss-of-function (LoF) variants, whereas inactivation sites were associated with gain-of-function (GoF; odds ratio = 42.1, 95% CI = 14.5 to 122.4; P < 0.001), whilst variants occurring in voltage-sensing regions comprised a range of gain- and loss-of-function effects. Our findings suggest that biophysical characterisation of variants in one SCN-gene can predict channel function across different SCN-genes where experimental data are not available. The collected data represent the first GoF versus LoF topological map of SCN proteins indicating shared patterns of biophysical effects aiding variant analysis and guiding precision therapy. We integrated our findings into a free online webtool to facilitate functional sodium channel gene variant interpretation (http://SCN-viewer.broadinstitute.org). [ABSTRACT FROM AUTHOR]

The article is a response to a comment on a previous study about predicting the pathogenicity of variants in ion channels. The authors of the response acknowledge that their cross-channel approach may not be accurate for all families of ion channels due to their structural and functional differences. They suggest that a protein-specific approach, tailored to the structure and activation mechanism of each ion channel, may be more effective. The response highlights the merits of this approach, including the need for clinical-grade accuracy, consideration of protein dynamics, and the refinement of predictive features. The study by Absalom et al. demonstrates the potential of a protein-specific approach to improve variant classification and deepen our understanding of biological functions. [Extracted from the article]

Genetic variants in genes GRIN1 , GRIN2A , GRIN2B , and GRIN2D , which encode subunits of the N-methyl-D-aspartate receptor (NMDAR), have been associated with severe and heterogeneous neurologic diseases. Missense variants in these genes can result in gain or loss of the NMDAR function, requiring opposite therapeutic treatments. Computational methods that predict pathogenicity and molecular functional effects are therefore crucial for accurate diagnosis and therapeutic applications. We assembled missense variants: 201 from patients, 631 from general population, and 159 characterized by electrophysiological readouts showing whether they can enhance or reduce the receptor function. This includes new functional data from 47 variants reported here, for the first time. We found that pathogenic/benign variants and variants that increase/decrease the channel function were distributed unevenly on the protein structure, with spatial proximity to ligands bound to the agonist and antagonist binding sites being key predictive features. Leveraging distances from ligands, we developed two independent machine learning-based predictors for NMDAR missense variants: a pathogenicity predictor which outperforms currently available predictors (AUC=0.945, MCC=0.726), and the first binary predictor of molecular function (increase or decrease) (AUC=0.809, MCC=0.523). Using these, we reclassified variants of uncertain significance in the ClinVar database and refined a previous genome-informed epidemiological model to estimate the birth incidence of molecular mechanism-defined GRIN disorders. Our findings demonstrate that distance from ligands is an important feature in NMDARs that can enhance variant pathogenicity prediction and enable functional prediction. Further studies with larger numbers of phenotypically and functionally characterized variants will enhance the potential clinical utility of this method.

It is challenging to apply traditional mutational scanning to voltage-gated sodium channels (Na V s) and functionally annotate the large number of coding variants in these genes. Using a cytosine base editor and a pooled viability assay, we screen a library of 368 guide RNAs (gRNAs) tiling Na V 1.2 to identify more than 100 gRNAs that change Na V 1.2 function. We sequence base edits made by a subset of these gRNAs to confirm specific variants that drive changes in channel function. Electrophysiological characterization of these channel variants validates the screen results and provides functional mechanisms of channel perturbation. Most of the changes caused by these gRNAs are classifiable as loss of function along with two missense mutations that lead to gain of function in Na V 1.2 channels. This two-tiered strategy to functionally characterize ion channel protein variants at scale identifies a large set of loss-of-function mutations in Na V 1.2., Competing Interests: Declaration of interests A.L.G. consults for and receives sponsored research funding from Praxis Precision Medicines and Neurocrine Biosciences for unrelated work., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

We report detailed functional analyses and genotype-phenotype correlations in 392 individuals carrying disease-causing variants in SCN8A, encoding the voltage-gated Na+ channel Nav1.6, with the aim of describing clinical phenotypes related to functional effects. Six different clinical subgroups were identified: Group 1, benign familial infantile epilepsy (n = 15, normal cognition, treatable seizures); Group 2, intermediate epilepsy (n = 33, mild intellectual disability, partially pharmaco-responsive); Group 3, developmental and epileptic encephalopathy (n = 177, severe intellectual disability, majority pharmaco-resistant); Group 4, generalized epilepsy (n = 20, mild to moderate intellectual disability, frequently with absence seizures); Group 5, unclassifiable epilepsy (n = 127); and Group 6, neurodevelopmental disorder without epilepsy (n = 20, mild to moderate intellectual disability). Those in Groups 1-3 presented with focal or multifocal seizures (median age of onset: 4 months) and focal epileptiform discharges, whereas the onset of seizures in patients with generalized epilepsy was later (median: 42 months) with generalized epileptiform discharges. We performed functional studies expressing missense variants in ND7/23 neuroblastoma cells and primary neuronal cultures using recombinant tetrodotoxin-insensitive human Nav1.6 channels and whole-cell patch-clamping. Two variants causing developmental and epileptic encephalopathy showed a strong gain-of-function (hyperpolarizing shift of steady-state activation, strongly increased neuronal firing rate) and one variant causing benign familial infantile epilepsy or intermediate epilepsy showed a mild gain-of-function (defective fast inactivation, less increased firing). In contrast, all three variants causing generalized epilepsy induced a loss-of-function (reduced current amplitudes, depolarizing shift of steady-state activation, reduced neuronal firing). Functional effects were known for 170 individuals. All 136 individuals carrying a functionally tested gain-of-function variant had either focal (n = 97, Groups 1-3) or unclassifiable (n = 39) epilepsy, whereas 34 individuals with a loss-of-function variant had either generalized (n = 14), no (n = 11) or unclassifiable (n = 6) epilepsy; only three had developmental and epileptic encephalopathy. Computational modelling in the gain-of-function group revealed a significant correlation between the severity of the electrophysiological and clinical phenotypes. Gain-of-function variant carriers responded significantly better to sodium channel blockers than to other anti-seizure medications, and the same applied for all individuals in Groups 1-3. In conclusion, our data reveal clear genotype-phenotype correlations between age at seizure onset, type of epilepsy and gain- or loss-of-function effects of SCN8A variants. Generalized epilepsy with absence seizures is the main epilepsy phenotype of loss-of-function variant carriers and the extent of the electrophysiological dysfunction of the gain-of-function variants is a main determinant of the severity of the clinical phenotype in focal epilepsies. Our pharmacological data indicate that sodium channel blockers present a treatment option in SCN8A-related focal epilepsy with onset in the first year of life., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)