Biology subjects

Helbig, I.

Publications and source records attributed to Helbig, I..

At least 19 recordsLinked to original sources

bioRxiv2026

Identifying Putative Pathogenic Non-Coding Variants in Unresolved Rare Disease Patients Using Topologically Associated Domains

Unresolved rare disease is a major public health challenge affecting ~300 million people worldwide. At least 50% of these individuals remain genetically unresolved after applying exome sequencing and/or whole genome sequencing. One source of these missing diagnoses is the presence of rare variants within the non-coding genome that are detected but not interpreted by whole genome sequencing. In order to systematically evaluate candidate pathogenic non-coding variants, we created the Genomic Analysis of Variants in Unresolved Rare Disease (GAVURD) system. GAVURD leverages trio whole genome sequencing alignment data to produce a short list of putative pathogenic non-coding variants for a given proband. GAVURD uses best practices for de novo and rare inherited variant identification, links variants to human disease genes harnessing topologically associated domain (TAD) data, and rank prioritizes variants based on phenotypic overlap. As a proof-of-concept, we applied GAVURD to ten probands with unresolved rare disease and implicated six potentially causal non-coding variants based on a confluence of evidence supportive of pathogenicity. The GAVURD system serves an important role in prioritizing candidate non-coding causal variants for unresolved rare disease that can serve as the high value and informed focus of additional functional follow-up studies.

genomics↗

bioRxiv2025

Characterization of the functional and clinical impacts of CACNA1A missense variants found in neurodevelopmental disorders

CACNA1A encodes the P/Q-type CaV2.1 calcium channels whose function underlies neuronal excitability, presynaptic neurotransmitter release, and Ca2+ signaling in neurons. Pathogenic variants in CACNA1A have been found in individuals with various neurological conditions, including hemiplegic migraine, epilepsy, developmental delay, and ataxia. Clinical presentations can vary significantly between patients, with limited information known about the underlying neurobiology of these different clinical patterns. Adding further complication, prior work on pathogenic missense variants has demonstrated variable impacts on CaV2.1 channel function, sometimes in opposite directions. As such, the relationships between specific coding variants, electrophysiological properties, and clinical phenotypes remain elusive. In this study, we determined the biophysical properties of an allelic series of 42 de novo missense CACNA1A variants discovered in a neurodevelopmental disorder cohort of more than 31,000 individuals, together with the most common eight coding variants found in the general population. We found that all but one de novo variant altered at least one aspect of the channel properties examined, and the majority (70%) of the variants reduced the channel current density. In addition, for variants that encode human CaV2.1 channels (hCaV2.1) with detectable currents, nearly 50% altered how channels respond to membrane potential, while common variations did not significantly change any channel biophysical properties. Coupled with our functional analyses and AlphaMissense prediction, we showed that CaV2.1 missense variants significantly underlie the risk of developmental epileptic encephalopathy. Subsequently, we examined the physiological impact of variant hCaV2.1 using NEURON simulations as an omnibus output of neuronal function and found that abnormal biophysical channel properties have a profound impact on Purkinje cell excitability. Most interestingly, we correlated the clinical phenotype with molecular consequences of missense variants provided by our comprehensive functional analyses and found that distinct CaV2.1 channel molecular function is significantly associated with different clinical outcomes. By analyzing an entire allelic series of CACNA1A de novo changes in a large cohort of individuals with neurodevelopmental disorders, we provide a powerful approach to dissecting the role of missense variants in CACNA1A channelopathy, which in turn may help pave the way for future precision medicine initiatives.

neuroscience↗

bioRxiv2025

Phenotypic analysis of 11,125 trio exomes in neurodevelopmental disorders

Genomic sequencing is widely used to identify causative genetic changes in neurodevelopmental disorders, such as autism, intellectual disability, and epilepsy. Most neurodevelopmental disorders also present with diverse clinical features, and delineating the interaction between causative genetic changes and phenotypic features is a key prerequisite for developing personalized therapies. However, assessing clinical features at a scale that parallels genomic sequencing remains challenging. Here, we standardize phenotypic information across 11,125 patient-parent trios with exome sequencing data using biomedical ontologies, analyzing 674,767 phenotypic terms. We find that individuals with de novo variants in 69 out of 261 neurodevelopmental genes exhibit statistically significant clinical similarities with distinct phenotypic fingerprints. We also observe that phenotypic relatedness follows a gradient, spanning from highly similar to dissimilar phenotypes, with intra-gene similarities suggesting clinically distinct subgroups for seven neurodevelopmental genes. For most genetic etiologies, only a small subset of highly phenotypically similar individuals carried de novo variants in the same gene, highlighting the heterogeneous and complex clinical landscape of neurodevelopmental disorders. Our study provides a large-scale overview of the dynamic relationship between genotypes and phenotypes in neurodevelopmental disorders, underscoring how the inherent complexity of these conditions can be deciphered through approaches that integrate genomic and phenotypic data.

genetics↗

bioRxiv2025

Comparative molecular landscapes of immature neurons in the mammalian dentate gyrus across species reveal special features in humans

Immature dentate granule cells (imGCs) arising from adult hippocampal neurogenesis contribute to plasticity, learning and memory, but their evolutionary changes across species and specialized features in humans remain poorly understood. Here we performed machine learning-augmented analysis of published single-cell RNA-sequencing datasets and identified macaque imGCs with transcriptome-wide immature neuronal characteristics. Our cross-species comparisons among humans, monkeys, pigs, and mice showed few shared (such as DPYSL5), but mostly species-specific gene expression in imGCs that converged onto common biological processes regulating neuronal development. We further identified human-specific transcriptomic features of imGCs and demonstrated functional roles of human imGC-enriched expression of a family of proton-transporting vacuolar-type ATPase subtypes in development of imGCs derived from human pluripotent stem cells. Our study reveals divergent gene expression patterns but convergent biological processes in the molecular characteristics of imGCs across species, highlighting the importance of conducting independent molecular and functional analyses for adult neurogenesis in different species.

neuroscience↗

bioRxiv2024

Optimizing clinical interpretability of functional evidence in epilepsy-related ion channel variants

Variants in genes encoding the voltage-gated ion channels are among the most common monogenic causes of epilepsy and neurodevelopmental disorders. Functional effects of a variant are increasingly important for diagnosis and therapeutic decisions. To incorporate knowledge regarding functional consequences in formal clinical variant interpretation, we developed an approach for evaluating multiple functional measurements within the Bayesian framework of the modified ACMG/AMP guidelines. We analyzed 216 functional assessments of 191 variants in SCN1A (n=74), SCN2A (n=66), SCN3A (n=18), and SCN8A (n=33). Of 20 commonly measured biophysical parameters, the most frequent drivers of overall functional consequence were persistent current (f=0.54), voltage dependence of activation (f=0.51), and voltage dependence of fast inactivation (f=0.40) for gain-of-function and peak current (f=0.87) for loss-of-function. By comparing measurements of 23 benign variants, we determined thresholds by which published data on these four parameters confer Strong evidence of variant pathogenicity (likelihood ratio > 18.7) under the ACMG/AMP rubric. Similarly, we delineated evidence weights for the most common epilepsy-related potassium channel gene, KCNQ2, through reports of 80 pathogenic and 24 benign variants, accounting for heterozygous and homozygous experimental conditions. We collected the resulting categorization of functional data into FENICS, a biomedical ontology of 152 standardized terms for coherent annotation of electrophysiological results. Across 271 variants in SCN1A/2A/3A/8A and KCNQ2, 1,731 annotations are available in ClinVar, facilitating use of this evidence in variant classification. In summary, we introduce and apply an ACMG/AMP-calibrated framework for electrophysiological studies in epilepsy-related channelopathies to delineate the impact of functional evidence on clinical variant interpretation.

genetics↗

bioRxiv2024

Molecular dynamics simulations reveal molecular mechanisms for the gain and loss of function effects of four SCN2A variants

SCN2A gene disorders cover a wide range of medical conditions, from epileptic encephalopathies to neurodevelopmental disorders. The variants of these disorders, studied through electrophysiology, show complex behaviors that go beyond simple classification as either gain or loss of function. In our study, we simulated the biophysical effects of variants (R937C, V208E, S1336Y, and R853Q) to understand their impact. Our findings reveal that all these variants negatively affect the structural stability of the gene, with R937C being the most unstable. Specifically, R937C disrupts important charged interactions affecting sodium ion flow, while S1336Y introduces a new interaction that impacts the channels inactivation gate. Conversely, the variants V208E and R853Q, which are located in the voltage-sensing domains, have opposite effects: R853Q increases compactness and interaction, whereas V208E shows a decrease. Our computer-based method offers a scalable way to gain crucial insights into how genetic variants influence channel dysfunction and contribute to neurodevelopmental disorders. AUTHOR SUMMARYDespite numerous advancements in computational methods for predicting variant pathogenicity in the SCN2A gene, understanding the precise biophysical molecular mechanisms associated with each variant at the atomic level remains a challenge. Presently, variants are predominantly categorized as either gain or loss of function, often overlooking critical structural details associated with these variants. This study focuses on elucidating the molecular mechanisms linked to the four most common SCN2A variants using all-atom molecular dynamics simulations, employing three replicas for each system. Our findings offer insights into the potential mechanisms underlying these four variants, thereby providing explanations for the observed electrophysiological outcomes. This investigation significantly contributes to enhancing our comprehension of how SCN2A variants manifest in various diseases. It underscores the importance of unraveling the biophysical properties underlying potential disease mechanisms, which could potentially enhance diagnostic and therapeutic strategies for patients afflicted with SCN2A-related disorders.

biophysics↗

bioRxiv2023

Molecular and Cellular Context Influences SCN8A Variant Function

Pathogenic variants in SCN8A, which encodes the voltage-gated sodium (NaV) channel NaV1.6, 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 NaV1.6 (NaV1.6N), 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 (NaV1.6N, NaV1.6A). We employed automated patch clamp recording to enhance throughput, and developed a novel 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 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.

neuroscience↗

bioRxiv2022

Enriching Representation Learning Using 53 Million Patient Notes through Human Phenotype Ontology Embedding

The Human Phenotype Ontology (HPO) is a dictionary of more than 15,000 clinical phenotypic terms with defined semantic relationships, developed to standardize their representation for phenotypic analysis. Over the last decade, the HPO has been used to accelerate the implementation of precision medicine into clinical practice. In addition, recent research in representation learning, specifically in graph embedding, has led to notable progress in automated prediction via learned features. Here, we present a novel approach to phenotype representation by incorporating phenotypic frequencies based on 53 million full-text health care notes from more than 1.5 million individuals. We demonstrate the efficacy of our proposed phenotype embedding technique by comparing our work to existing phenotypic similarity-measuring methods. Using phenotype frequencies in our embedding technique, we are able to identify phenotypic similarities that surpass the current computational models. In addition, we show that our embedding technique aligns with domain experts judgment at a level that exceeds their agreement. We show that our proposed technique efficiently represents complex and multidimensional phenotypes in HPO format, which can then be used as input for various downstream tasks that require deep phenotyping, including patient similarity analyses and disease trajectory prediction.

bioinformatics↗

bioRxiv2022

The SCN1A Philadelphia variant - a gain-of-function mutation causing an early-onset epileptic encephalopathy

ObjectiveLoss-of-function variants in SCN1A cause Dravet Syndrome, the most common genetic developmental and epileptic encephalopathy (DEE). However, emerging evidence suggests separate entities of SCN1A-related disorders due to gain-of-function variants. Here, we aim to refine the clinical, genetic, and functional electrophysiological features of a recurrent p.R1636Q gain-of-function variant, identified in four individuals at a single center. MethodsIndividuals carrying the recurrent SCN1A p.R1636Q variant were identified through diagnostic testing. Whole-cell voltage-clamp electrophysiological recording in HEK-293T cells was performed to compare the properties of sodium channels containing wild-type Nav1.1 or Nav1.1-R1636Q along with both Nav{beta}1 and Nav{beta}2 subunits, including response to oxcarbazepine. To delineate differences to other SCN1A-related epilepsies, we analyzed electronic medical records. ResultsAll four individuals had an early-onset DEE characterized by focal tonic seizures and additional seizure types starting in the first few weeks of life. Electrophysiological analysis showed a mixed gain-of-function effect with normal current density, a leftward (hyperpolarized) shift of steady-state inactivation, and slower inactivation kinetics leading to a prominent late sodium current (INa). The observed functional changes closely paralleled effects of pathogenic variants in SCN3A and SCN8A at corresponding positions. Both wildtype and variant exhibited sensitivity to block by oxcarbazepine, partially correcting electrophysiological abnormalities of the SCN1A p.R1636Q variant. Clinically, a single individual responded to treatment with oxcarbazepine. Across 51 individuals with SCN1A-related epilepsies, those with the recurrent p.R1636Q variants had the earliest ages of onset. InterpretationThe recurrent SCN1A p.R1636Q variant causes a clinical entity with a wider clinical spectrum than previously reported, characterized by ultra early-onset epilepsy and absence of prominent movement disorder. Functional consequences of this variant lead to mixed loss- and gain-of-function that is partially corrected by oxcarbazepine. The recurrent p.R1636Q variant represents one of the most common causes of early-onset SCN1A-related epilepsies with separate treatment and prognosis implications. Key PointsO_LILoss-of-function variants in SCN1A cause Dravet syndrome, but gain-of-function variants have an emerging clinical spectrum. C_LIO_LIThe SCN1A p.R1636Q variant shows similar overall gain-of-function effects to identical missense variants in other voltage-gated sodium channels. C_LIO_LIFeatures of four unreported individuals with SCN1A p.R1636Q from a single center expand the SCN1A gain-of-function phenotype. C_LIO_LIIndividuals with this variant are recognizable by their ultra early-onset seizures in contrast to Dravet syndrome. C_LI

genetics↗

bioRxiv2022

A recurrent de novo splice site variant involving DNM1 alternative exon 10a causes developmental and epileptic encephalopathy through a dominant-negative mechanism

Heterozygous pathogenic variants in DNM1 cause developmental and epileptic encephalopathy (DEE) due to a dominant-negative mechanism impeding vesicular fission. Thus far, pathogenic variants in DNM1 have been studied using a canonical transcript that includes the alternatively spliced exon 10b. However, after performing RNA sequencing in thirty-nine pediatric brain samples, we find the primary transcript expressed in the brain includes the downstream exon 10a instead. Using this information, we evaluated genotype-phenotype correlations of variants affecting exon 10a and identified a cohort of eleven previously unreported individuals. Eight individuals harbor a recurrent de novo splice site variant, NG_029726.1(NM_001288739.1):c.1197-8G>A, which affects exon 10a and leads to DEE consistent with the classical DNM1 phenotype. We find this splice site variant leads to disease through an unexpected dominant-negative mechanism. Functional testing reveals an in-frame upstream splice acceptor causing insertion of two amino acids predicted to impair oligomerization-dependent activity. This is supported by neuropathological samples showing accumulation of synaptic vesicles adherent to the plasma membrane consistent with impaired vesicular fission. Two additional individuals with missense variants affecting exon 10a, p.(Arg399Trp) and p.(Gly401Asp), had a similar DEE phenotype. In contrast, a single individual with a missense variant affecting exon 10b, p.(Pro405Leu), which is less expressed in the brain, had a correspondingly less severe presentation. Thus, we implicate variants affecting exon 10a as causing the severe DEE typically associated with DNM1-related disorders. We highlight the importance of considering relevant isoforms for disease-causing variants, as well as the possibility of splice site variants acting through a dominant-negative mechanism.

genetics↗

bioRxiv2021

Modulating effects of FGF12 variants on NaV1.2 and NaV1.6 associated with Developmental and Epileptic Encephalopathy and Autism Spectrum Disorder

ObjectiveFibroblast growth factor 12 (FGF12) may represent an important modulator of neuronal network activity and has been associated with developmental and epileptic encephalopathy (DEE). We sought to identify the underlying pathomechanism of FGF12-related disorders. MethodsPatients with pathogenic variants in FGF12 were identified through published case reports, GeneMatcher and whole exome sequencing of own case collections. The functional consequences of two missense variants and two copy number variants (CNVs) were studied by co-expression of wild-type and mutant FGF12 in neuronal-like cells (ND7/23) with the sodium channels NaV1.2 or NaV1.6, including their functional active beta-1 and beta-2 sodium channel subunits (SCN1B and SCN2B). ResultsFour variants in FGF12 were identified for functional analysis: one novel FGF12 variant in a patient with autism spectrum disorder and three variants from previously published patients affected by developmental and epileptic encephalopathy (DEE). We demonstrate the differential regulating effects of wildtype and mutant FGF12 on NaV1.2 and NaV1.6 channels. Here, FGF12 variants lead to a complex kinetic influence on Nav1.2 and Nav 1.6, including loss- as well as gain-of function changes in fast inactivation as well as loss-of function changes in slow inactivation. InterpretationFor the first time, we could demonstrate the detailed regulating effect of FGF12 on NaV1.2 and NaV1.6 and confirmed the complex effect of FGF12 on neuronal network activity. Our findings expand the phenotypic spectrum related to FGF12 variants and elucidate the underlying pathomechanism. Specific variants in FGF12-associated disorders may be amenable to precision treatment with sodium channel blockers.

neuroscience↗

bioRxiv2021

Predicting the functional effects of voltage-gated potassium channel missense variants with multi-task learning

PurposeVariants in genes encoding voltage-gated potassium channels are associated with a broad spectrum of neurological diseases including epilepsy, ataxia, and intellectual disability. Knowledge of the resulting functional changes, characterized as overall ion channel gain- or loss-of-function, is essential to guide clinical management including precision medicine therapies. However, for an increasing number of variants, little to no experimental data is available. New tools are needed to evaluate variant functional effects. MethodsWe catalogued a comprehensive dataset of 959 functional experiments across 19 voltage-gated potassium channels, leveraging data from 782 unique disease-associated and synthetic variants. We used these data to train a taxonomy-based multi-task learning support vector machine (MTL-SVM), and compared performance to a baseline of standard SVMs. ResultsMTL-SVM maintains channel family structure during model training, improving overall predictive performance (mean balanced accuracy 0.729 {+/-} 0.029, AU-ROC 0.757 {+/-} 0.039) over baseline (mean balanced accuracy 0.645 {+/-} 0.041, AU-ROC 0.710 {+/-} 0.074). We can obtain meaningful predictions even for channels with few known variants (KCNC1, KCNQ5). ConclusionOur model enables functional variant prediction for voltage-gated potassium channels. It may assist in tailoring current and future precision therapies for the increasing number of patients with ion channel disorders.

bioinformatics↗

bioRxiv2021

High-throughput Evaluation of Epilepsy-associated KCNQ2 Variants Reveals Functional and Pharmacological Heterogeneity

Hundreds of KCNQ2 variants have been identified by genetic testing of children with early onset epilepsy and/or developmental disability. Voltage-clamp recording from heterologous cells has proved useful for establishing deleterious functional effects of KCNQ2 variants, but procedures adapting these assays for standardized, higher throughput data collection and reporting are lacking. In this study, we employed automated patch clamp recording to assess in parallel the functional and pharmacological properties of 79 missense and 2 in-frame deletion variants of KCNQ2. Among the variants we studied were a training set of 18 pathogenic variants previously studied by voltage-clamp recording, 24 mostly rare population variants, and 39 disease-associated variants with unclear functional effects. Variant KCNQ2 subunits were transiently expressed in a cell line stably expressing KCNQ3 to reconstitute the physiologically relevant channel complex. Variants with severe loss-of-function were also co-expressed 1:1 with WT KCNQ2 in the KCNQ3 cell line to mimic the heterozygous genotype and assess dominant-negative behavior. In total, we analyzed electrophysiological data recorded from 9,480 cells. The functional properties of WT KCNQ2/KCNQ3 channels and pharmacological responses to known blockers and activators determined by automated patch clamp recording were highly concordant with previous findings. Similarly, functional properties of 18 known pathogenic variants largely matched previously published results and the validated automated patch clamp assay. Many of the 39 previously unstudied disease-associated KCNQ2 variants exhibited prominent loss-of-function and dominant-negative effects, providing strong evidence in support of pathogenicity. All variants, exhibit response to retigabine (10 {micro}M), although there were differences in maximal responses. Variants within the ion selectivity filter exhibited the weakest responses whereas retigabine had the strongest effect on gain-of-function variants in the voltage-sensor domain. Our study established a high throughput method to detect deleterious functional consequences of KCNQ2 variants. We demonstrated that dominant-negative loss-of-function is a common mechanism associated with missense KCNQ2 variants but this does not occur with rare population variation in this gene. Importantly, we observed genotype-dependent differences in the response of KCNQ2 variants to retigabine.

neuroscience↗

bioRxiv2021

A Gene Replacement Humanization Platform for Rapid Functional Testing of Clinical Variants in Epilepsy-associated STXBP1.

PurposeFunctional evidence is a pillar of variant interpretation according to ACMG guidelines. Functional evidence can be obtained in a variety of models and assay systems, including patient-derived tissues and iPSCs, in vitro cellular assays, and in vivo assays. Here we evaluate the reliability and practicality of variant interpretation in the small animal model, C. elegans, through a series of experiments evaluating the function of syntaxin binding protein, STXBP1, a well-known causative gene for Early infantile epileptic encephalopathy 1 (EIEE1). MethodsUsing CRISPR, we replaced the coding sequence for unc-18 with the coding sequence for the human ortholog STXBP1. Next, we used CRISPR to introduce precise point mutations in the human STXBP1 coding sequence, reflecting three clinical categories (benign, pathogenic, and variants of uncertain significance (VUS)). We quantified 26 features of the resulting worms movement to train Random Forest (RF) and Support Vector Machines (SVM) machine learning classifiers on known pathogenic and benign variants. We characterized the classifiers, and then used the behavioral data from the VUS-expressing animals to predict the categorization of the VUS. ResultsWhereas knock-out worms without unc-18 are severely impaired in motor function, worms expressing STXBP1 in its place have restored motor function. We produced worms with STXBP1 variants previously classified by ACMG criteria, including 25 benign variants, 32 pathogenic, and 24 variants of uncertain significance (VUS). Using either SVM or RF classifiers, we were able to obtain a sensitivity of 0.84-0.97 on known benign and pathogenic strains. By comparing multiple ML classification methods, we were able to classify 9 of the VUS as functionally abnormal, suggesting that these VUS are likely to be pathogenic. ConclusionsWe demonstrate that automated analysis of a small animal system is an effective, scalable, and fast way to understand functional consequences of variants in STXBP1, one of the most common causes of genetic epilepsies and neurodevelopmental disorders.

genetics↗

bioRxiv2019

Targeted gene sequencing in 6994 individuals with neurodevelopmental disorder with epilepsy

PurposeWe aimed to gain insight into frequencies of genetic variants in genes implicated in neurodevelopmental disorder with epilepsy (NDD+E) by investigating large cohorts of patients in a diagnostic setting.\n\nMethodsWe analyzed variants in NDD+E using epilepsy gene panel sequencing performed between 2013 and 2017 by two large diagnostic companies. We compared variant frequencies in 6,994 panels to other 8,588 recently published panels as well as exome-wide de novo variants in 1,942 individuals with NDD+E and 10,937 controls.\n\nResultsGenes with highest frequencies of ultra-rare variants in NDD+E comprised SCN1A, KCNQ2, SCN2A, CDKL5, SCN8A and STXBP1, concordant with the two other epilepsy cohorts we investigated. Only 46% of the analysed 262 dominant and X-linked panel genes contained ultra-rare variants in patients. Among genes with contradictory evidence of association with epilepsy CACNB4, CLCN2, EFHC1, GABRD, MAGI2 and SRPX2 showed equal frequencies in cases and controls.\n\nConclusionWe show that improvement of panel design increased diagnostic yield over time, but panels still display genes with low or no diagnostic yield. With our data, we hope to improve current diagnostic NDD+E panel design and provide a resource of ultra-rare variants in individuals with NDD+E to the community.

genetics↗

bioRxiv2019

Heterozygous variants in KMT2E cause a spectrum of neurodevelopmental disorders and epilepsy

We delineate a KMT2E gene-related neurodevelopmental disorder based on 38 individuals in 36 families. This includes 31 distinct heterozygous variants in the KMT2E gene (28 ascertained from Matchmaker Exchange and 3 previously reported), and 4 individuals with chromosome 7q22.2-22.23 microdeletions encompassing the KMT2E gene (1 previously reported). Almost all variants occurred de novo, and most were truncating. Most affected individuals with protein-truncating variants presented with mild intellectual disability. One-quarter of individuals met criteria for autism. Additional common features include macrocephaly, hypotonia, functional gastrointestinal abnormalities, and a subtle facial gestalt. Epilepsy was present in about one-fifth of individuals with truncating variants, and was responsive to treatment with anti-epileptic medications in almost all. Over 70% of the individuals were male and expressivity was variable by sex, with epilepsy more common in females and autism more common in males. The four individuals with microdeletions encompassing KMT2E generally presented similarly to those with truncating variants, but the degree of developmental delay was greater. The group of four individuals with missense variants in KMT2E presented with the most severe developmental delays. Epilepsy was present in all individuals with missense variants, often manifesting as treatment-resistant infantile epileptic encephalopathy. Microcephaly was also common in this group. Haploinsufficiency versus gain-of-function or dominant negative effects specific to these missense variants in KMT2E may explain this divergence in phenotype, but requires independent validation. Disruptive variants in KMT2E are an under-recognized cause of neurodevelopmental abnormalities.

genetics↗

bioRxiv2019

Ultra-rare genetic variation in the epilepsies: a whole-exome sequencing study of 17,606 individuals

Sequencing-based studies have identified novel risk genes for rare, severe epilepsies and revealed a role of rare deleterious variation in common epilepsies. To identify the shared and distinct ultra-rare genetic risk factors for rare and common epilepsies, we performed a whole-exome sequencing (WES) analysis of 9,170 epilepsy-affected individuals and 8,364 controls of European ancestry. We focused on three phenotypic groups; the rare but severe developmental and epileptic encephalopathies (DEE), and the commoner phenotypes of genetic generalized epilepsy (GGE) and non-acquired focal epilepsy (NAFE). We observed that compared to controls, individuals with any type of epilepsy carried an excess of ultra-rare, deleterious variants in constrained genes and in genes previously associated with epilepsy, with the strongest enrichment seen in DEE and the least in NAFE. Moreover, we found that inhibitory GABAA receptor genes were enriched for missense variants across all three classes of epilepsy, while no enrichment was seen in excitatory receptor genes. The larger gene groups for the GABAergic pathway or cation channels also showed a significant mutational burden in DEE and GGE. Although no single gene surpassed exome-wide significance among individuals with GGE or NAFE, highly constrained genes and genes encoding ion channels were among the top associations, including CACNA1G, EEF1A2, and GABRG2 for GGE and LGI1, TRIM3, and GABRG2 for NAFE. Our study confirms a convergence in the genetics of common and rare epilepsies associated with ultra-rare coding variation and highlights a ubiquitous role for GABAergic inhibition in epilepsy etiology in the largest epilepsy WES study to date.

genetics↗

bioRxiv2017

Characterization of Glycosylphosphatidylinositol Biosynthesis Defects by Clinical Features, Flow Cytometry, and Automated Image Analysis

BackgroundGlycosylphosphatidylinositol Biosynthesis Defects (GPIBDs) cause a group of phenotypically overlapping recessive syndromes with intellectual disability, for which pathogenic mutations have been described in 16 genes of the corresponding molecular pathway. An elevated serum activity of alkaline phosphatase (AP), a GPI-linked enzyme, has been used to assign GPIBDs to the phenotypic series of Hyperphosphatasia with Mental Retardation Syndrome (HPMRS) and to distinguish them from another subset of GPIBDs, termed Multiple Congenital Anomalies Hypotonia Seizures syndrome (MCAHS). However, the increasing number of individuals with a GPIBD shows that hyperphosphatasia is a variable feature that is not ideal for a clinical classification.\n\nMethodsWe studied the discriminatory power of multiple GPI-linked substrates that were assessed by flow cytometry in blood cells and fibroblasts of 39 and 14 individuals with a GPIBD, respectively. On the phenotypic level, we evaluated the frequency of occurrence of clinical symptoms and analyzed the performance of computer-assisted image analysis of the facial gestalt in 91 individuals.\n\nResultsWe found that certain malformations such as Morbus Hirschsprung and Diaphragmatic defects are more likely to be associated with particular gene defects (PIGV, PGAP3, PIGN). However, especially at the severe end of the clinical spectrum of HPMRS, there is a high phenotypic overlap with MCAHS. Elevation of AP has also been documented in some of the individuals with MCAHS, namely those with PIGA mutations. Although the impairment of GPI-linked substrates is supposed to play the key role in the pathophysiology of GPIBDs, we could not observe gene-specific profiles for flow cytometric markers or a correlation between their cell surface levels and the severity of the phenotype. In contrast, it was facial recognition software that achieved the highest accuracy in predicting the disease-causing gene in a GPIBD.\n\nConclusionsDue to the overlapping clinical spectrum of both, HPMRS and MCAHS, in the majority of affected individuals, the elevation of AP and the reduced surface levels of GPI-linked markers in both groups, a common classification as GPIBDs is recommended. The effectiveness of computer-assisted gestalt analysis for the correct gene inference in a GPIBD and probably beyond is remarkable and illustrates how the information contained in human faces is pivotal in the delineation of genetic entities.

genetics↗