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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.

Monogenic disorders can present clinically heterogeneous symptoms. We hypothesized that in patients with a monogenic disorder caused by a large deletion, frequently additional loss-of-function (LOF)-intolerant genes are affected, potentially contributing to the phenotype.We investigated the LOF-intolerant gene distribution across the genome and its association with benign population and pathogenic classified deletions from individuals with presumably monogenic disorders. For people with presumably monogenic epilepsy, we compared Human Phenotype Ontology terms in people with large and small deletions.We identified LOF-intolerant gene dense regions that were enriched for ClinVar and depleted for population copy number variants. Analysis of data from143,000 individuals with a suspected monogenic disorder showed that 2.5% of haploinsufficiency disorder-associated deletions can affect at least 1 other LOF-intolerant gene. Focusing on epilepsy, we observed that 13.1% of pathogenic and likely pathogenic ClinVar deletions3 megabase pair, covering the diagnostically most relevant genes, affected at least 1 additional LOF-intolerant gene. Those patients have potentially more complex phenotypes with increasing deletion size.We could systematically show that large deletions frequently affected admditional LOF-intolerant genes in addition to the established disease gene. Further research is needed to understand how additional potential disease-relevant genes influence monogenic disorders to improve clinical care and the efficacy of targeted therapies.

Many epilepsy-associated genes have been identified over the last three decades, revealing a remarkable molecular heterogeneity with the shared outcome of recurrent seizures. Information about the genetic landscape of epilepsies is scattered throughout the literature and answering the simple question of how many genes are associated with epilepsy is not straightforward. Here, we present a computationally driven analytical review of epilepsy-associated genes using the complete scientific literature in PubMed. Based on our search criteria, we identified a total of 738 epilepsy-associated genes. We further classified these genes into two Tiers. A broad gene list of 738 epilepsy-associated genes (Tier 2) and a narrow gene list composed of 143 epilepsy-associated genes (Tier 1). Our search criteria do not reflect the degree of association. The average yearly number of identified epilepsy-associated genes between 1992 and 2021 was 4.8. However, most of these genes were only identified in the last decade (2010-2019). Ion channels represent the largest class of epilepsy-associated genes. For many of these, both gain- and loss-of-function effects have been associated with epilepsy in recent years. We identify 28 genes frequently reported with heterogenous variant effects which should be considered for variant interpretation. Overall, our study provides an updated and manually curated list of epilepsy-related genes together with additional annotations and classifications reflecting the current genetic landscape of epilepsy.

Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. Consequently, 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 3,049 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 novel 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 center 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 fucntional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate (NMDA) receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1,422 neurodevelopmental disorder pathogenic patient variants, and 679 electrophysiological experiments that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain vs. 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 read-outs 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.

Background and ObjectivesPathogenic variants in the neuronal sodium channel α1 subunit gene (SCN1A) are the most frequent monogenic cause of epilepsy. Phenotypes comprise a wide clinical spectrum, including severe childhood epilepsy; Dravet syndrome, characterized by drug-resistant seizures, intellectual disability, and high mortality; and the milder genetic epilepsy with febrile seizures plus (GEFS+), characterized by normal cognition. Early recognition of a child's risk for developing Dravet syndrome vs GEFS+ is key for implementing disease-modifying therapies when available before cognitive impairment emerges. Our objective was to develop and validate a prediction model using clinical and genetic biomarkers for early diagnosis of SCN1A-related epilepsies.MethodsWe performed a retrospective multicenter cohort study comprising data from patients with SCN1A-positive Dravet syndrome and patients with GEFS+ consecutively referred for genetic testing (March 2001–June 2020) including age at seizure onset and a newly developed SCN1A genetic score. A training cohort was used to develop multiple prediction models that were validated using 2 independent blinded cohorts. Primary outcome was the discriminative accuracy of the model predicting Dravet syndrome vs other GEFS+ phenotypes.ResultsA total of 1,018 participants were included. The frequency of Dravet syndrome was 616/743 (83%) in the training cohort, 147/203 (72%) in validation cohort 1, and 60/72 (83%) in validation cohort 2. A high SCN1A genetic score (133.4 [SD 78.5] vs 52.0 [SD 57.5]; p < 0.001) and young age at onset (6.0 [SD 3.0] vs 14.8 [SD 11.8] months; p < 0.001) were each associated with Dravet syndrome vs GEFS+. A combined SCN1A genetic score and seizure onset model separated Dravet syndrome from GEFS+ more effectively (area under the curve [AUC] 0.89 [95% CI 0.86–0.92]) and outperformed all other models (AUC 0.79–0.85; p < 0.001). Model performance was replicated in both validation cohorts 1 (AUC 0.94 [95% CI 0.91–0.97]) and 2 (AUC 0.92 [95% CI 0.82–1.00]).DiscussionThe prediction model allows objective estimation at disease onset whether a child will develop Dravet syndrome vs GEFS+, assisting clinicians with prognostic counseling and decisions on early institution of precision therapies (http://scn1a-prediction-model.broadinstitute.org/).Classification of EvidenceThis study provides Class II evidence that a combined SCN1A genetic score and seizure onset model distinguishes Dravet syndrome from other GEFS+ phenotypes.

Understanding the exact molecular mechanisms involved in the aetiology of epileptogenic pathologies with or without tumour activity is essential for improving treatment of drug-resistant focal epilepsy. Here, we characterize the landscape of somatic genetic variants in resected brain specimens from 474 individuals with drug-resistant focal epilepsy using deep whole-exome sequencing (>350×) and whole-genome genotyping. Across the exome, we observe a greater number of somatic single-nucleotide variants in low-grade epilepsy-associated tumours (7.92 ± 5.65 single-nucleotide variants) than in brain tissue from malformations of cortical development (6.11 ± 4 single-nucleotide variants) or hippocampal sclerosis (5.1 ± 3.04 single-nucleotide variants). Tumour tissues also had the largest number of likely pathogenic variant carrying cells. low-grade epilepsy-associated tumours had the highest proportion of samples with one or more somatic copy-number variants (24.7%), followed by malformations of cortical development (5.4%) and hippocampal sclerosis (4.1%). Recurring somatic whole chromosome duplications affecting Chromosome 7 (16.8%), chromosome 5 (10.9%), and chromosome 20 (9.9%) were observed among low-grade epilepsy-associated tumours. For germline variant-associated malformations of cortical development genes such as TSC2, DEPDC5 and PTEN, germline single-nucleotide variants were frequently identified within large loss of heterozygosity regions, supporting the recently proposed ‘second hit’ disease mechanism in these genes. We detect somatic variants in 12 established lesional epilepsy genes and demonstrate exome-wide statistical support for three of these in the aetiology of low-grade epilepsy-associated tumours (e.g. BRAF) and malformations of cortical development (e.g. SLC35A2 and MTOR). We also identify novel significant associations for PTPN11 with low-grade epilepsy-associated tumours and NRAS Q61 mutated protein with a complex malformation of cortical development characterized by polymicrogyria and nodular heterotopia. The variants identified in NRAS are known from cancer studies to lead to hyperactivation of NRAS, which can be targeted pharmacologically. We identify large recurrent 1q21–q44 duplication including AKT3 in association with focal cortical dysplasia type 2a with hyaline astrocytic inclusions, another rare and possibly under-recognized brain lesion. The clinical-genetic analyses showed that the numbers of somatic single-nucleotide variant across the exome and the fraction of affected cells were positively correlated with the age at seizure onset and surgery in individuals with low-grade epilepsy-associated tumours. In summary, our comprehensive genetic screen sheds light on the genome-scale landscape of genetic variants in epileptic brain lesions, informs the design of gene panels for clinical diagnostic screening and guides future directions for clinical implementation of epilepsy surgery genetics.

By accumulating ever greater amounts of genomic data, scientists have identified >100 genes associated with Mendelian forms of epilepsy and neurodevelopmental disorders with seizures. For most of the identified genes a wide range of genetic variants have been identified and affected patients are clinically heterogeneous. It is not clear to which degree the clinical heterogeneity can be attributed to the disease causing variant alone. We need to improve our current understanding of biophysical effects of variants on protein function and the role of polygenic background in modifying the clinical representation. In addition, longitudinal clinical data need to be recorded using standardized methods and shared across research centers to build large virtual cohorts for each single gene disorder. Without large, comprehensive, longitudinal datasets, studying the interplay of environmental factors and genetic factors will be challenging. As a community, we must work together to set the foundation for biorepositories and the collection and sharing of ‘big data’ in order to allow genetic-phenotypic characterization of the epilepsies and to fully utilize the potential for drug discovery, and patient-specific tailored management.

Gallstones Disease (GSD) is one of the most common digestive diseases requiring hospitalization and surgical procedures in the world. GSD has a high prevalence in populations with European or Amerindian ancestry (10–20%) and the influence of genetic factors is broadly acknowledged. However, known genetic variants do not entirely explain the disease heritability suggesting that additional genetic variants remain to be identified. Here, we examined the association of copy number variants (CNVs) with GSD in a sample of 4778 individuals (1929 GSD cases and 2849 controls) including two European cohorts from Germany (n = 3702) and one admixed Latin American cohort from Chile (n = 1076). We detected 2936 large and rare CNVs events (size > 100 kb, frequency

It is challenging to estimate genetic variant burden across different subtypes of epilepsy. Herein, we used a comparative approach to assess the genetic variant burden and genotype–phenotype correlations in four most common brain lesions in patients with drug-resistant focal epilepsy. Targeted sequencing analysis was performed for a panel of 161 genes with a mean coverage of >400×. Lesional tissue was histopathologically reviewed and dissected from hippocampal sclerosis (n = 15), ganglioglioma (n = 16), dysembryoplastic neuroepithelial tumors (n = 8), and focal cortical dysplasia type II (n = 15). Peripheral blood (n = 12) or surgical tissue samples histopathologically classified as lesion-free (n = 42) were available for comparison. Variants were classified as pathogenic or likely pathogenic according to American College of Medical Genetics and Genomics guidelines. Overall, we identified pathogenic and likely pathogenic variants in 25.9% of patients with a mean coverage of 383×. The highest number of pathogenic/likely pathogenic variants was observed in patients with ganglioglioma (43.75%; all somatic) and dysembryoplastic neuroepithelial tumors (37.5%; all somatic), and in 20% of cases with focal cortical dysplasia type II (13.33% somatic, 6.67% germline). Pathogenic/likely pathogenic positive genes were disorder specific and BRAF V600E the only recurrent pathogenic variant. This study represents a reference for the genetic variant burden across the four most common lesion entities in patients with drug-resistant focal epilepsy. The observed large variability in variant burden by epileptic lesion type calls for whole exome sequencing of histopathologically well-characterized tissue in a diagnostic setting and in research to discover novel disease-associated genes.

Whole human genome sequencing initiatives help us understand population history and the basis of genetic diseases. Current data mostly focuses on Old World populations, and the information of the genomic structure of Native Americans, especially those from the Southern Cone is scant. Here we present annotation and variant discovery from high-quality complete genome sequences of a cohort of 11 Mapuche-Huilliche individuals (HUI) from Southern Chile. We found approximately 3.1 × 106 single nucleotide variants (SNVs) per individual and identified 403,383 (6.9%) of novel SNVs events. Analyses of large-scale genomic events detected 680 copy number variants (CNVs) and 4,514 structural variants (SVs), including 398 and 1,910 novel events, respectively. Global ancestry composition of HUI genomes revealed that the cohort represents a sample from a marginally admixed population from the Southern Cone, whose main genetic component derives from Native American ancestors. Additionally, we found that HUI genomes contain variants in genes associated with 5 of the 6 leading causes of noncommunicable diseases in Chile, which may have an impact on the risk of prevalent diseases in Chilean and Amerindian populations. Our data represents a useful resource that can contribute to population-based studies and for the design of early diagnostics or prevention tools for Native and admixed Latin American populations.

CACNA1I is implicated in the susceptibility to schizophrenia by large-scale genetic association studies of single nucleotide polymorphisms. However, the channelopathy of CACNA1I in schizophrenia is unknown. CACNA1I encodes CaV3.3, a neuronal voltage-gated calcium channel that underlies a subtype of T-type current that is important for neuronal excitability in the thalamic reticular nucleus and other regions of the brain. Here, we present an extensive functional characterization of 57 naturally occurring rare and common missense variants of CACNA1I derived from a Swedish schizophrenia cohort of more than 10 000 individuals. Our analysis of this allelic series of coding CACNA1I variants revealed that reduced CaV3.3 channel current density was the dominant phenotype associated with rare CACNA1I coding alleles derived from control subjects, whereas rare CACNA1I alleles from schizophrenia patients encoded CaV3.3 channels with altered responses to voltages. CACNA1I variants associated with altered current density primarily impact the ionic channel pore and those associated with altered responses to voltage impact the voltage-sensing domain. CaV3.3 variants associated with altered voltage dependence of the CaV3.3 channel and those associated with peak current density deficits were significantly segregated across affected and unaffected groups (Fisher’s exact test, P = 0.034). Our results, together with recent data from the SCHEMA (Schizophrenia Exome Sequencing Meta-Analysis) cohort, suggest that reduced CaV3.3 function may protect against schizophrenia risk in rare cases. We subsequently modelled the effect of the biophysical properties of CaV3.3 channel variants on thalamic reticular nucleus excitability and found that compared with common variants, ultrarare CaV3.3-coding variants derived from control subjects significantly decreased thalamic reticular nucleus excitability (P = 0.011). When all rare variants were analysed, there was a non-significant trend between variants that reduced thalamic reticular nucleus excitability and variants that either had no effect or increased thalamic reticular nucleus excitability across disease status. Taken together, the results of our functional analysis of an allelic series of >50 CACNA1I variants in a schizophrenia cohort reveal that loss of function of CaV3.3 is a molecular phenotype associated with reduced disease risk burden, and our approach may serve as a template strategy for channelopathies in polygenic disorders.

Significance Recent large-scale sequencing efforts have enabled the detection of millions of missense variants. Elucidating their functional effect is of crucial importance but challenging. We approach this problem by performing a wide-scale characterization of missense variants from 1,330 disease-associated genes using >14,000 protein structures. We identify 3D features associated with pathogenic and benign variants that unveiled the mutations’ effect at the molecular level. We further extend our analysis to account for the different essential structural regions in proteins performing different functions. By analyzing variants from 24 gene groups encoding for different protein functional families, we capture function-specific characteristics of missense variants, which match the experimental readouts. We show that our results derived using structural data will effectively inform variant interpretation., Interpretation of the colossal number of genetic variants identified from sequencing applications is one of the major bottlenecks in clinical genetics, with the inference of the effect of amino acid-substituting missense variations on protein structure and function being especially challenging. Here we characterize the three-dimensional (3D) amino acid positions affected in pathogenic and population variants from 1,330 disease-associated genes using over 14,000 experimentally solved human protein structures. By measuring the statistical burden of variations (i.e., point mutations) from all genes on 40 3D protein features, accounting for the structural, chemical, and functional context of the variations’ positions, we identify features that are generally associated with pathogenic and population missense variants. We then perform the same amino acid-level analysis individually for 24 protein functional classes, which reveals unique characteristics of the positions of the altered amino acids: We observe up to 46% divergence of the class-specific features from the general characteristics obtained by the analysis on all genes, which is consistent with the structural diversity of essential regions across different protein classes. We demonstrate that the function-specific 3D features of the variants match the readouts of mutagenesis experiments for BRCA1 and PTEN, and positively correlate with an independent set of clinically interpreted pathogenic and benign missense variants. Finally, we make our results available through a web server to foster accessibility and downstream research. Our findings represent a crucial step toward translational genetics, from highlighting the impact of mutations on protein structure to rationalizing the variants’ pathogenicity in terms of the perturbed molecular mechanisms.

Focal epilepsy (FE) is clinically highly heterogeneous. It has been shown recently that not only rare but also a subset of common genetic variants confer risk for FE. The relatively modest power of genetic studies in FE suggests a high genetic heterogeneity of FE when grouped as one disorder. We hypothesize that the clinical heterogeneity of FE is correlated with genetic heterogeneity on a common risk variant level. To test the hypothesis, we used an FE polygenic risk score "FE-PRS" that combines small effect sizes of thousands of common variants from the largest FE-GWAS (genome-wide association study) into a single measure. We grouped 414 individuals with FE according to common clinical features into subgroups, either by one feature at a time or by all features combined in a cluster analysis. We examined their association with FE-PRS compared to 20 435 matched population controls and observed heterogeneous FE-PRS burden among the subgroups. The highest phenotypic variance explained by FE-PRS was identified in a cluster analysis-defined FE subgroup where all individuals had unknown etiologies and psychiatric comorbidities, and the majority had early onset seizures. Our results indicate that genetic factors associated with FE have differential burden among FE subtypes. Future studies using better-powered FE-PRS might have clinical utility.

Advances in gene discovery have identified genetic variants in the solute carrier family 6 member 1 gene as a monogenic cause of neurodevelopmental disorders, including epilepsy with myoclonic atonic seizures, autism spectrum disorder and intellectual disability. The solute carrier family 6 member 1 gene encodes for the GABA transporter protein type 1, which is responsible for the reuptake of the neurotransmitter GABA, the primary inhibitory neurotransmitter in the central nervous system, from the extracellular space. GABAergic inhibition is essential to counterbalance neuronal excitation, and when significantly disrupted, it negatively impacts brain development leading to developmental differences and seizures. Aggregation of patient variants and observed clinical manifestations expand understanding of the genotypic and phenotypic spectrum of this disorder. Here, we assess genetic and phenotypic features in 116 individuals with solute carrier family 6 member 1 variants, the vast majority of which are likely to lead to GABA transporter protein type 1 loss-of-function. The knowledge acquired will guide therapeutic decisions and the development of targeted therapies that selectively enhance transporter function and may improve symptoms. We analysed the longitudinal and cell type-specific expression of solute carrier family 6 member 1 in humans and localization of patient and control missense variants in a novel GABA transporter protein type 1 protein structure model. In this update, we discuss the progress made in understanding and treating solute carrier family 6 member 1-related disorders thus far, through the concerted efforts of clinicians, scientists and family support groups., Genetic variants in the SLC6A1 gene have been identified as a monogenic cause of neurodevelopmental disorders, including epilepsy with myoclonic atonic seizures, autism spectrum disorder and intellectual disability. Here, we assess the genetic and phenotypic features observed in 116 patients with SLC6A1 variants., Graphical Abstract Graphical Abstract

Background: Parkinson's disease is the second most common neurodegenerative disorder and affects people from all ethnic backgrounds, yet little is known about the genetics of Parkinson's disease in non-European populations. In addition, the overall identification of copy number variants at a genome-wide level has been understudied in Parkinson's disease patients. Objectives: To understand the genome-wide burden of copy number variants in Latinos and its association with Parkinson's disease. Methods: We used genome-wide genotyping data from 747 Parkinson's disease patients and 632 ancestry matched controls from the Latin American Research Consortium on the Genetics of Parkinson's disease. Results: Genome-wide copy number burden analysis showed no difference between patients vs. controls, whereas patients were significantly enriched for copy number variants overlapping known Parkinson's disease genes compared to controls (Odds Ratio: 3.97 [1.69 - 10.5], P = 0.018). PARK2 showed the strongest copy number burden, with 20 copy number variant carriers. These patients presented an earlier age of disease onset compared to patients with other copy number variants (median age at onset: 31 years vs. 57 years, P = 7.46 x 10-7). Conclusions: We found that Parkinson's disease patients are significantly enriched with copy number variants affecting known Parkinson's disease genes. We also identified that out of 250 patients with early-onset disease, 5.6% carried a copy number variant on PARK2 in our cohort. Our study is the first to analyze genome-wide copy number variants association in Latino Parkinson's disease patients and provides insights about this complex disease in this understudied population.

Background Sudden Unexpected Death in Pediatrics (SUDP) is a tragic event, likely caused by the complex interaction of multiple factors. The presence of hippocampal abnormalities in many children with SUDP suggests that epilepsy‐related mechanisms may contribute to death, similar to Sudden Unexplained Death in Epilepsy. Because of known associations between the genes SCN1A and SCN5A and sudden death, and shared mechanisms and patterns of expression in genes encoding many voltage‐gated sodium channels (VGSCs), we hypothesized that individuals dying from SUDP have pathogenic variants across the entire family of cardiac arrhythmia‐ and epilepsy‐associated VGSC genes. Methods To address this hypothesis, we evaluated whole‐exome sequencing data from infants and children with SUDP for variants in VGSC genes, reviewed the literature for all SUDP‐associated variants in VGSCs, applied a novel paralog analysis to all variants, and evaluated all variants according to American College of Medical Genetics and Genomics (ACMG) guidelines. Results In our cohort of 73 cases of SUDP, we assessed 11 variants as pathogenic in SCN1A, SCN1B, and SCN10A, genes with long‐standing disease associations, and in SCN3A, SCN4A, and SCN9A, VGSC gene paralogs with more recent disease associations. From the literature, we identified 82 VGSC variants in SUDP cases. Pathogenic variants clustered at conserved amino acid sites intolerant to variation across the VGSC genes, which is unlikely to occur in the general population (p, Sudden Unexpected Death in Pediatrics (SUDP) is a tragic event. We evaluated WES data from 73 cases and reviewed the literature for sodium channel variants in SUDP. We report variants in several sodium channel genes, involved in central nervous system and/or cardiac rhythm dysfunction.

Importance: Clinical genetic sequencing is frequently utilized to diagnose individuals with neurodevelopmental disorders (NDDs). Several reviews have been published regarding clinical genetic testing in various NDD subtypes. However, there is no systematic review and meta-analysis – in accordance with the PRISMA guidelines – which compares the genetic testing yield across neurodevelopmental disorder subtypes and sequencing technology. Objective: To perform a meta-analysis and systematic review of the success rate (diagnostic yield) of clinical sequencing through NGS across NDDs. Data Sources: Systematic review of the literature from PubMed until July 2019 for clinical sequencing studies that utilized NGS in individuals with epilepsy, autism spectrum disorder (ASD), or intellectual disability (ID). Study Selection: Data were taken from clinical sequencing studies that screened more than five genes and performed variant classification in at least 20 individuals with epilepsy, ASD, or ID. 5.6% of identified studies met the selection criteria. Data Extraction and Synthesis: Data were extracted, reviewed, and categorized according to PRISMA guidelines. Clinical evaluation and grouping were performed by two investigators following the ILAE guidelines. Pooled rates of the diagnostic yield and 95% confidence intervals were estimated with a random-effects model and adjusted for publication bias by the Duval and Tweedie procedure. Main Outcomes and Measures: Diagnostic yield, defined as the proportion of individuals in a cohort who received a diagnosis based on a positive genetic test with variants identified as pathogenic or likely pathogenic. Results: We identified 79 studies (epilepsy, n = 54; ASD, n = 13; ID, n = 17) across 29,301 individuals. Targeted gene panel sequencing was used in 53 cohorts and exome sequencing (ES) in 27 cohorts. The diagnostic yield was 16.7% for epilepsy, 20.2% for ASD, 24.8% for ID, and 16.6% overall. The diagnostic yield was significantly higher for exome sequencing compared to panels (33.9% vs. 16.2%, P = 1.38×10−5). We observed that the number of clinical sequencing studies increased annually, particularly studies from Asia (0-2 per year between 2012 and 2017, up to 10 in 2018). No studies from Africa, India, or Latin America were identified. We also found that recent studies are more likely to report variants of uncertain significance and few studies reported benign variants. Conclusions and Relevance: This meta-analysis and systematic review provides a comprehensive overview of clinical sequencing studies of NDDs, which will help guide policymaking and steer decision-making in patient management. Key Points Question What is the diagnostic yield of next-generation sequencing (NGS) in neurodevelopmental disorders and their subtypes? Findings In this systematic review and meta-analysis of 79 studies that include 29,301 individuals, the overall diagnostic yield was 16.6% (16.7% for epilepsy, 20.2% for ASD, and 24.8% for ID). Across all studies, downstream analyses showed a significant difference in yield between exome sequencing (33.9%) and targeted gene panels (16.2%). Meaning Around one in five NDD patients will receive a diagnosis using NGS, especially when investigating the whole exome.

A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-scale genomic screens. Yet, knowledge of disease incidence is important for clinicians and researchers to guide health policy planning. Here, we adjusted a statistical method based on genetic data to predict, for the first time, the incidences of 101 known de novo variant-associated neurodevelopmental disorders as well as 3106 putative monogenic disorders. Two corroboration analyses supported the validity of the calculated estimates. First, greater predicted gene-disorder incidences positively correlated with larger numbers of pathogenic variants collected from patient variant databases (Kendall’s τ = 0.093, P-value = 6.9 × 10−6). Second, for six of seven (86%) de novo variant associated monogenic disorders for which epidemiological estimates were available (SCN1A, SLC2A1, SALL1, TBX5, KCNQ2, and CDKL5), the predicted incidence estimates matched the reported estimates. We conclude that in the absence of epidemiological data, our catalogue of 3207 incidence estimates for disorders caused by de novo variants can guide patient advocacy groups, clinicians, researchers, and policymakers in strategic decision-making.

Interpretation of the colossal number of genetic variants identified from sequencing applications is one of the major bottlenecks in clinical genetics, with the inference of the effect of amino acid-substituting missense variants on protein structure and function being especially challenging. Here we evaluated the burden of amino acids affected in pathogenic variants (n=32,923) compared to the variants (n=164,915) from the general population in 1,330 disease-associated genes on forty protein features using over 14,000 experimentally-solved 3D structures. By analyzing the whole gene/variant set jointly, we identified 18 features associated with 3D mutational hotspots that are generally important for protein fitness and stability. Individual analyses performed for twenty-four protein functional classes further revealed 240 characteristics of mutational hotspots in total, including new associations recapitulating the sheer diversity across proteins essential structural regions. We demonstrated that the function-specific features of variants correspond to the readouts of mutagenesis experiments and positively correlate with clinically-interpreted pathogenic and benign missense variants. Finally, we made our results available through a web server to foster accessibility and downstream research. Our findings represent a crucial step towards translational genetics, from highlighting the impact of mutations on protein structure to rationalizing the pathogenicity of variants in terms of the perturbed molecular mechanisms.

Rare and large copy number variants (CNVs) around known genomic ‘hotspots’ are strongly implicated in epilepsy etiology. But it remains unclear whether the observed associations are specific to an epilepsy phenotype, and if additional risk signal can be found outside hotspots. Here, we present the largest CNV burden and first CNV breakpoint level association analysis in epilepsy to date with 11,246 European epilepsy cases and 7,318 ancestry-matched controls. We studied five epilepsy phenotypes: genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, epileptic encephalopathy, and unclassified epilepsy. We discovered novel epilepsy-associated CNV loci and further characterized the CNV burden enrichment among phenotype-specific epilepsies. Finally, we provide evidence for deletion burden outside of known hotspot regions and show that CNVs play a significant role in the genetic architecture of lesional focal epilepsies.

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2,871 gene family protein sequence alignments involving 9,990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 65,034 missense variants from patients. With this gene family approach, we identified 398 regions enriched for patient variants spanning 33,887 amino acids in 1,058 genes. As a comparison, testing the same genes individually we identified less patient variant enriched regions involving only 2,167 amino acids and 180 genes. Next, we selected de novo variants from 6,753 patients with neurodevelopmental disorders and 1,911 unaffected siblings, and observed a 5.56-fold enrichment of patient variants in our identified regions (95% C.I. =2.76-Inf, p-value = 6.66×10−8). Using an independent ClinVar variant set, we found missense variants inside the identified regions are 111-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 111.48, 95% C.I = 68.09-195.58, p-value < 2.2e−16). All patient variant enriched regions identified (PERs) are available online through a user-friendly platform for interactive data mining, visualization and download at http://per.broadinstitute.org. In summary, our gene family burden analysis approach identified novel patient variant enriched regions in protein sequences. This annotation can empower variant interpretation.

Variants in the SCN1A gene are associated with a wide range of disorders including genetic epilepsy with febrile seizures plus (GEFS+), familial hemiplegic migraine (FHM), and the severe childhood epilepsy Dravet syndrome (DS). Predicting disease outcomes based on variant type remains challenging. Despite thousands of SCN1A variants being reported, only a minority has been functionally assessed. We review the functional SCN1A work performed to date, critically appraise electrophysiological measurements, compare this to in silico predictions, and relate our findings to the clinical phenotype. Our results show, regardless of the underlying phenotype, that conventional in silico software correctly predicted benign from pathogenic variants in nearly 90%, however was unable to differentiate within the disease spectrum (DS vs. GEFS+ vs. FHM). In contrast, patch-clamp data from mammalian expression systems revealed functional differences among missense variants allowing discrimination between disease severities. Those presenting with milder phenotypes retained a degree of channel function measured as residual whole-cell current, whereas those without any whole-cell current were often associated with DS (p = .024). These findings demonstrate that electrophysiological data from mammalian expression systems can serve as useful disease biomarker when evaluating SCN1A variants, particularly in view of new and emerging treatment options in DS.

PURPOSE OF REVIEW: Recent publications point to an increasingly important role of variants in genes encoding GABAA receptor subunits associated with both common and rare forms of epilepsies. The aim of this review is to give an overview of the current clinical phenotypes, genetic findings and pathophysiological mechanisms related to GABAA receptor variants.RECENT FINDINGS: Early work showed that inherited variants in GABRG2 and GABRA1 cause relatively mild forms of monogenic epilepsies in large families. More recent studies have revealed that de novo variants in several GABAA receptor genes cause severe developmental and epileptic encephalopathies, inherited variants cause remarkably variable phenotypes within the same pedigrees ranging from asymptomatic carriers to developmental and epileptic encephalopathies, and variants in all GABAA receptor genes are enriched in common forms of epilepsy, namely rolandic epilepsy and genetic generalized epilepsy. Analyses from cellular expression systems and mouse models suggest that all variants cause a loss of GABAA receptor function resulting in GABAergic disinhibition.SUMMARY: Genetic studies have revealed a crucial role of the GABAergic system in the underlying pathogenesis of various forms of common and rare epilepsies. Our understanding of functional consequences of GABAA receptor variants provide an opportunity to develop precision-based therapeutic strategies that are hopefully free from the side-effect burden seen with currently available GABAergic drugs.

Motivation The correct classification of missense variants as benign or pathogenic remains challenging. Pathogenic variants are expected to have higher deleterious prediction scores than benign variants in the same gene. However, most of the existing variant annotation tools do not reference the score range of benign population variants on gene level. Results We present a web-application, Variant Score Ranker, which enables users to rapidly annotate variants and perform gene-specific variant score ranking on the population level. We also provide an intuitive example of how gene- and population-calibrated variant ranking scores can improve epilepsy variant prioritization. Availability and implementation http://vsranker.broadinstitute.org Supplementary information Supplementary data are available at Bioinformatics online.

Sudden Unexpected Death in Pediatrics (SUDP) is a tragic condition with hypothesized multifactorial etiology. While there is recent evidence implicating genes related to cardiac arrhythmia and epilepsy as genetic risk factors contributing to some cases of SUDP, the underlying mechanisms of SUDP remain under active investigation. SUDP encompasses Sudden Infant Death Syndrome (SIDS) and Sudden Unexplained Death in Childhood (SUDC), affecting children under and over 1 year of age, respectively. The presence of developmental hippocampal malformations in many children with SIDS and SUDC suggests that a subset of patients may share epilepsy-related mechanisms with Sudden Unexplained Death in Epilepsy Patients (SUDEP). Pathogenic variants in both epilepsy- and arrhythmia-related sodium channel genes have recently been identified in patients with SIDS, SUDC, and SUDEP.We performed a candidate gene analysis for genes encoding sodium channel subunits in whole exome sequencing (WES) data from 73 SUDP patients. After a thorough literature review, we mapped all reported SUDP-associated sodium channel variants alongside variants from the population on a structural protein model to evaluate whether patient variants clustered in important protein domains compared to controls.In our cohort, 13 variants met criteria for pathogenicity or potential pathogenicity. While SCN1A, SCN1B, and SCN5A have established disease associations, we also considered variants in the paralogs SCN3A, SCN4A and SCN9A. Overall, the patient-associated variants clustered at conserved amino acid sites across the sodium channel gene family that do not tolerate variation in these genes.This study provides a molecular overview of sodium channel variants present in cases with SUDP and reveals key amino acid sites that do not tolerate variation across the SCN paralog family. Further research will lead to an improved understanding of the contribution of sodium channels to SUDP, with a goal of one day implementing prevention strategies to avoid untimely deaths in at-risk children.Author SummaryThe sudden unexplained death of an infant or a child is a tragic event, which is likely caused by the complex interaction of multiple factors. Besides environmental factors, genes related to epilepsy and cardiac arrhythmia have been identified as risk factors. The sodium channel family encompasses genes, related to both cardiac arrhythmia as well as epilepsy, whose proteins share structural homology. We evaluated sodium channel gene variants in our cohort, examined all known variants in sodium genes in SUDP patients from the literature, and mapped patient variants alongside variants from the population on a 3D protein model. The patient variants clustered at conserved amino acid sites with low rates of variation in the general population, not only in the particular gene involved but also in the gene family. This study illustrates that sodium channel variants contribute to the complex phenotype of sudden death in pediatrics, suggesting complex mechanisms of neurologic and/or cardiac dysfunction contributing to death.

Latin Americans and Chilean Amerindians have the highest prevalence of gallstone disease (GSD) and gallbladder cancer (GBC) in the world. A handful of loci have been associated with GSD in populations of predominantly European ancestry, however, they only explain a small portion of the genetic component of the disease. Here, we performed a genome-wide association study (GWAS) for GSD in 1,095 admixed Chilean Latinos with Mapuche Native American ancestry. Disease status was assessed by cholecystectomy or abdominal ultrasonography. Top-10 candidate variants surpassing the suggestive cutoff of P −5 in the discovery cohort were genotyped in an independent replication sample composed of 1,643 individuals. Variants with positive replication were further examined in two European GSD populations and a Chilean GBC cohort. We consistently replicated the association of ABCG8 gene with GSD (rs11887534, P = 3.24 × 10−8, OR = 1.74) and identified TRAF3 (rs12882491, P = 1.11 × 10−7, OR = 1.40) as a novel candidate gene for the disease in admixed Chilean Latinos. ABCG8 and TRAF3 variants also conferred risk to GBC. Gene expression analyses indicated that TRAF3 was significantly decreased in gallbladder (P = 0.015) and duodenal mucosa (P = 0.001) of GSD individuals compared to healthy controls, where according to GTEx data in the small intestine, the presence of the risk allele contributes to the observed effect. We conclude that ABCG8 and TRAF3 genes are associated with GSD and GBC in admixed Latinos and that decreased TRAF3 levels could enhance gallbladder inflammation as is observed in GSD and GSD-associated GBC.

BackgroundLatin Americans and Chilean Amerindians have the highest prevalence of cholesterol gallstone disease (GSD) and gallbladder cancer (GBC) in the world. A handful of loci have been associated with GSD in populations of predominantly European ancestry, however they only explain a small portion of the population-attributable risk of the disease.MethodsWe performed a genome-wide association study (GWAS) for GSD in 1,095 admixed Latinos with Mapuche Native American Ancestry, followed by a replication analysis of 10 candidate single nucleotide polymorphisms (SNPs) with suggestive genome-wide significance (P−5) in 1,643 individuals. Disease status was assessed by cholecystectomy or abdominal ultrasonography. Logistic regression analyses were adjusted for age, sex, BMI, Type 2 Diabetes and Amerindian ancestry. Associated variants were further examined in two large GSD European populations and in a Chilean gallbladder cancer (GBC) cohort. We determined the expression levels of a novel GSD-candidate gene in normal and GSD-tissue samples.ResultsWe consistently replicated theABCG8gene (rs11887534; P=3.24×10−8, OR=1.74) associated with GSD in admixed Latinos and identified a novel candidate signal within theTRAF3gene on chromosome 14 (rs12882491; P=1.11×10−7, OR=1.40).ABCG8andTRAF3variants also conferred risk to GBC. Gene expression analyses indicated thatTRAF3levels were significantly decreased in the gallbladder (P=0.015) and the duodenal mucosa (P=0.001) of affected GSD individuals compared to healthy controls.ConclusionsWe confirmedABCG8and identifiedTRAF3both associated with GSD and GBC in admixed Latinos. Decreased TRAF3 expression levels could enhance gallbladder inflammation as is observed in GSD and GSD-associated GBC.

Objective: After the recent publication of the first patients with disease-associated missense variants in the GRIN2D gene, we evaluate the effect of copy number variants (CNVs) overlapping this gene toward the presentation of neurodevelopmental disorders (NDDs). Methods: We explored ClinVar (numberofCNVs= 50,794) and DECIPHER (numberofCNVs=28,085) clinical databases of genomic variations for patients with copy number changes overlapping the GRIN2D gene at the 19q13.33 locus and evaluated their respective phenotype alongside their frequency, gene content, and expression, with publicly available reference databases. Results: We identified 11 patients with microduplications at the 19q13.33 locus. The majority of CNVs arose de novo, and comparable CNVs are not present in control databases. All patients were reported to have NDDs and dysmorphic features as the most common clinical phenotype (N = 8/11), followed by seizures (N = 6/11) and intellectual disability (N = 5/11). All duplications shared a consensus region of 405 kb overlapping 13 genes. After screening for duplication tolerance in control populations, positive gene brain expression, and gene dosage sensitivity analysis, we highlight 4 genes for future evaluation: CARD8, C19orf68, KDELR1, and GRIN2D, which are promising candidates for disease causality. Furthermore, investigation of the literature especially supports GRIN2D as the best candidate gene. Conclusions: Our study presents dup19q13.33 as a novel duplication syndrome locus associated with NDDs. CARD8, C19orf68, KDELR1, and GRIN2D are promising candidates for functional follow-up., SCOPUS: ar.j, info:eu-repo/semantics/published

BackgroundWhole human genome sequencing initiatives provide a compendium of genetic variants that help us understand population history and the basis of genetic diseases. Current data mostly focuses on Old World populations and information on the genomic structure of Native Americans, especially those from the Southern Cone is scant.ResultsHere we present a high-quality complete genome sequence of 11 Mapuche-Huilliche individuals (HUI) from Southern Chile (85% genomic and 98% exonic coverage at > 30X), with 96–97% high confidence calls. We found approximately 3.1×106 single nucleotide variants (SNVs) per individual and identified 403,383 (6.9%) of novel SNVs that are not included in current sequencing databases. Analyses of large-scale genomic events detected 680 copy number variants (CNVs) and 4,514 structural variants (SVs), including 398 and 1,910 novel events, respectively. Global ancestry composition of HUI genomes revealed that the cohort represents a marginally admixed population from the Southern Cone, whose genetic component is derived from early Native American ancestors. In addition, we found that HUI genomes display highly divergent and novel variants with potential functional impact that converge in ontological categories essential in cell metabolic processes.ConclusionsMapuche-Huilliche genomes contain a unique set of small– and large-scale genomic variants in functionally linked genes, which may contribute to susceptibility for the development of common complex diseases or traits in admixed Latinos and Native American populations. Our data represents an ancestral reference panel for population-based studies in Native and admixed Latin American populations.

The functional interpretation of genetic variation in disease-associated genes is far outpaced by data generation. Existing algorithms for prediction of variant consequences do not adequately distinguish pathogenic variants from benign rare variants. This lack of statistical and bioinformatics analyses, accompanied by an ever-increasing number of identified variants in biomedical research and clinical applications, has become a major challenge. Established methods to predict the functional effect of genetic variation use the degree of amino acid conservation across species in linear protein sequence alignment. More recent methods include the spatial distribution pattern of known patient and control variants. Here, we propose to combine the linear conservation and spatial constrained based scores to devise a novel score that incorporates 3-dimensional structural properties of amino acid residues, such as the solvent-accessible surface area, degree of flexibility, secondary structure propensity and binding tendency, to quantify the effect of amino acid substitutions. For this study, we develop a framework for large-scale mapping of established linear sequence-based paralog and ortholog conservation scores onto the tertiary structures of human proteins. This framework can be utilized to map the spatial distribution of mutations on solved protein structures as well as homology models. As a proof of concept, using a homology model of the human Nav1.2 voltage-gated sodium channel structure, we observe spatial clustering in distinct domains of mutations, associated with Autism Spectrum Disorder (>20 variants) and Epilepsy (>100 variants), that exert opposing effects on channel function. We are currently characterizing all variants (>300k individuals) found in ClinVar, the largest disease variant database, as well as variants identified in >140k individuals from general population. The variant mapping framework and our score, informed with structural information, will be useful in identifying structural motifs of proteins associated with disease risk.

Differentiating risk-conferring from benign missense variants, and therefore optimal calculation of gene-variant burden, represent a major challenge in particular for rare and genetic heterogeneous disorders. While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes are paralogs and belong to gene families. It has not been thoroughly investigated how gene family information can be utilized for disease gene discovery and variant interpretation. We developed a paralog conservation score to empirically evaluate whether paralog conserved or nonconserved sites of in-human paralogs are important for protein function. Using this score, we demonstrate that disease-associated missense variants are significantly enriched at paralog conserved sites across all disease groups and disease inheritance models tested. Next, we assessed whether gene family information could assist in discovering novel disease-associated genes. We subsequently developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in more than 10k neurodevelopmental disorder patients. 33 gene family enriched genes represent novel candidate genes which are brain expressed and variant constrained in neurodevelopmental disorders.

OBJECTIVEAfter recent publication of the first patients with disease associated missense variants in GRIN2D, we evaluate the effect of copy number variation (CNV) overlapping this gene towards the presentation of neurodevelopmental disorders.METHODSWe explored ClinVar (N°CNV = 41,398) and DECIPHER (N°CNV = 30,222) clinical databases of genomic variations for patients with copy number changes overlapping the GRIN2D gene at the 19q13.33 locus and evaluated their respective phenotype alongside their frequency, gene content and expression with publicly available reference databases.RESULTSWe identified 13 patients with microduplications at the 19q13.33 locus. The majority of CNVs arose de novo and comparable CNVs are not present in control databases. All patients were reported to have neurodevelopmental disorders and dysmorphic features as the most common clinical phenotype (N= 10/13), followed by seizures (N= 6/13) and intellectual disability (N= 5/13). All duplications shared a consensus region of 405 kb overlapping 13 genes. After screening for duplication tolerance in control populations, positive gene brain expression and gene dosage sensitivity analysis, we highlight four genes for future evaluation: CARD8, C19orf68, KDELR1 and GRIN2D, which are promising candidates for disease causality. Further, investigation of the literature especially supports GRIN2D as the best candidate gene.CONCLUSIONSOur study presents dup19q13.33 as novel duplication syndrome locus associated with neurodevelopmental disorders. CARD8, C19orf68, KDELR1 and GRIN2D are promising candidates for functional follow up.

Alzheimer's disease is a neurodegenerative disorder that causes a progressive decline of mental and cognitive processes such as memory, judgment and reasoning. We proposed earlier that a sustained loss of function of Wnt/β- catenin signaling components underlies the onset and progression of the disease. Here, we discuss recent data on the involvement of Wnt/b-catenin signaling on amyloid precursor protein (APP) processing, Aβ peptide neurotoxicity, τ phosphorylation, and modulation of Apolipoprotein E function in the brain. We conclude that several components of the cascade are actively engaged in the events leading to AD neuropathology and propose that compounds that mimic activation of this signaling cascade, such as lithium, should be considered for therapeutic intervention in Alzheimer's patients. In summary, data accumulated during the past decade confirm some important predictions of our hypothesis where components of this signaling cascade are actively engaged in the events leading to AD neuropathology and that compounds that mimic activation of this signaling cascade, such as lithium, should be considered for therapeutic intervention in Alzheimer's patients.

BackgroundMicrodeletions are known to confer risk to epilepsy, particularly at genomic rearrangement “hotspot” loci. However, deciphering their role outside hotspots and risk assessment by epilepsy sub-type has not been conducted.MethodsWe assessed the burden, frequency and genomic content of rare, large microdeletions found in a previously published cohort of 1,366 patients with Genetic Generalized Epilepsy (GGE) plus two sets of additional unpublished genome-wide microdeletions found in 281 Rolandic Epilepsy (RE) and 807 Adult Focal Epilepsy (AFE) patients, totaling 2,454 cases. These microdeletion sets were assessed in a combined analysis and in sub-type specific approaches against 6,746 ethnically matched controls.ResultsWhen hotspots are considered, we detected an enrichment of microdeletions in the combined epilepsy analysis (adjusted-P= 2.00×10-7; OR = 1.89; 95%-CI: 1.51-2.35), where the implicated microdeletions overlapped with rarely deleted genes and those involved in neurodevelopmental processes. Sub-type specific analyses showed that hotspot deletions in the GGE subgroup contribute most of the signal (adjusted-P = 1.22×10-12; OR = 7.45; 95%-CI = 4.20-11.97). Outside hotspot loci, microdeletions were enriched in the GGE cohort for neurodevelopmental genes (adjusted-P = 4.78×10-3; OR = 2.30; 95%-CI = 1.42-3.70), whereas no additional signal was observed for RE and AFE. Still, gene content analysis was able to identify known (NRXN1, RBFOX1 and PCDH7) and novel (LOC102723362) candidate genes affected in more than one epilepsy sub-type but not in controls.ConclusionsOur results show a heterogeneous effect of recurrent and non-recurrent microdeletions as part of the genetic architecture of GGE and a minor to negligible contribution in the etiology of RE and AFE.