Identification of pathogenic variant enriched regions across genes and gene families

Ligand distances as key predictors of pathogenicity and function in NMDA receptors

Genetic variants in the genes GRIN1, GRIN2A, GRIN2B, and GRIN2D, which encode subunits of the N-methyl-D-aspartate receptor (NMDAR), have been associated with severe and heterogeneous neurologic and neurodevelopmental disorders, including early onset epilepsy, developmental and epileptic encephalopathy, intellectual disability, and autism spectrum disorders. Missense variants in these genes can result in gain or loss of the NMDAR function, requiring opposite therapeutic treatments. Computational methods that predict pathogenicity and molecular functional effects of missense variants are therefore crucial for therapeutic applications. We assembled 223 missense variants from patients, 631 control variants from the general population, and 160 missense variants characterized by electrophysiological readouts that show whether they can enhance or reduce the function of the receptor. This includes new functional data from 33 variants reported here, for the first time. By mapping these variants onto the NMDAR protein structures, we found that pathogenic/benign variants and variants that increase/decrease the channel function were distributed unevenly on the protein structure, with spatial proximity to ligands bound to the agonist and antagonist binding sites being a key predictive feature for both variant pathogenicity and molecular functional consequences. Leveraging distances from ligands, we developed two machine-learning based predictors for NMDA variants: a pathogenicity predictor which outperforms currently available predictors and the first molecular function (increase/decrease) predictor. Our findings can have direct application to patient care by improving diagnostic yield for genetic neurodevelopmental disorders and by guiding personalized treatment informed by the knowledge of the molecular disease mechanism.

Genetic variant profiling of neonatal diabetes mellitus in Iranian patients: Unveiling 58 distinct variants in 14 genes

INTRODUCTION

Neonatal diabetes mellitus (NDM) is a rare non-immunological monogenic disorder characterized by hyperglycemic conditions primarily occurring within the first 6 months of life. The majority of cases are attributed to pathogenic variants in genes affecting beta-cell survival, insulin regulation, and secretion. This study aims to investigate the genetic landscape of NDM in Iran.

METHODS

We recruited a total of 135 patients who were initially diagnosed with diabetes at <12 months of age in Iran and referred to pediatric endocrinology clinics across the country. These patients underwent genetic diagnostic tests conducted by the Exeter Molecular Genetics Laboratory in the UK. The pathogenic variants identified were sorted and described based on type, pathogenicity (according to ACMG/AMP criteria), novelty, and the affected protein domain.

RESULTS

Genetic defects were identified in 93 probands, presenting various pathogenic abnormalities associated with NDM and its associated syndromes. 76% of the patients were born as a result of consanguineous marriage, and a familial history of diabetes was found in 43% of the cases. A total of 58 distinct variants in 14 different genes were discovered, including 20 variants reported for the first time. Causative variants were most frequently identified in EIF2AK3, KCNJ11, and ABCC8, respectively. Notably, EIF2AK3 and ABCC8 exhibited the highest number of novel variants.

DISCUSSION

These findings provide valuable insights into the genetic landscape of NDM in the Iranian population and contribute to the knowledge of novel pathogenic variants within known causative genes.

Voltage-gated sodium channel epilepsies in a tertiary care center: Phenotypic spectrum with correlation to predicted functional effects

BACKGROUND

Variants in sodium channel genes (SCN) are strongly associated with epilepsy phenotypes. Our aim in this study to evaluate the genotype and phenotype correlation of patients with SCN variants in our tertiary care center.

METHODS

In this retrospective study, patients with SCN variants and epilepsy who were followed up at our clinic between 2018 and 2022 were evaluated. Our study discussed the demographics of the patients, the seizure types, the age of seizure onset, the SCN variants, the domains and the functions of the variants, the magnetic resonance imaging findings, the motor, cognitive, and psychiatric comorbidities, and the response to anti-seizure medication. Genetic testing was conducted using a next-generation sequencing gene panel (epilepsy panel) or a whole-exome sequencing. For evaluating variant function, we used a prediction tool (https://funnc.shinyapps.io/shinyappweb/ site). To assess protein domains, we used the PER viewer (http://per.broadinstitute.org/).

RESULTS

Twenty-three patients with SCN variants and epilepsy have been identified. Sixteen patients had variants in the SCN1A, six patients had variants in the SCN2A, and one patient had a variant in the SCN3A. Two novel SCN1A variants and two novel SCN2A variants were identified. The analysis revealed 14/23 missense, 6/23 nonsense, 2/23 frameshift, and 1/23 splice site variants in the SCN. There are seven variants predicted to be gain-of-function and 13 predicted to be loss-of-function. Among 23 patients; 11 had Dravet Syndrome, 6 had early infantile developmental and epileptic encephalopathy, three had genetic epilepsy with febrile seizures plus spectrum disorder, one had self-limited familial neonatal-infantile epilepsy, one had self-limited infantile epilepsy and one had infantile childhood development epileptic encephalopathy.

CONCLUSION

Our cohort consists of mainly SCN1 variants, most of them were predicted to be loss of function. Dravet syndrome was the most common phenotype. The prediction tool used in our study demonstrated overall compatibility with clinical findings. Due to the diverse clinical manifestations of variant functions, it may assist in guiding medication selection and predicting outcomes. We believe that such a tool will help the clinician in both prognosis prediction and solving therapeutic challenges in this group where refractory seizures are common.

Boolean Modeling of Biological Network Applied to Protein-Protein Interaction Network of Autism Patients

Cellular molecules interact with one another in a structured manner, defining a regulatory network topology that describes cellular mechanisms. Genetic mutations alter these networks' pathways, generating complex disorders such as autism spectrum disorder (ASD). Boolean models have assisted in understanding biological system dynamics since Kauffman's 1969 discovery, and various analytical tools for regulatory networks have been developed. This study examined the protein-protein interaction network created in our previous publication of four ASD patients using the SPIDDOR R package, a Boolean model-based method. The aim is to examine how patients' genetic variations in INTS6L, USP9X, RSK4, FGF5, FLNA, SUMF1, and IDS affect mTOR and Wnt cell signaling convergence. The Boolean network analysis revealed abnormal activation levels of essential proteins such as β-catenin, MTORC1, RPS6, eIF4E, Cadherin, and SMAD. These proteins affect gene expression, translation, cell adhesion, shape, and migration. Patients 1 and 2 showed consistent patterns of increased β-catenin activity and decreased MTORC1, RPS6, and eIF4E activity. However, patient 2 had an independent decrease in Cadherin and SMAD activity due to the FLNA mutation. Patients 3 and 4 have an abnormal activation of the mTOR pathway, which includes the MTORC1, RPS6, and eIF4E genes. The shared mTOR pathway behavior in these patients is explained by a shared mutation in two closely related proteins (SUMF1 and IDS). Diverse activities in β-catenin, MTORC1, RPS6, eIF4E, Cadherin, and SMAD contributed to the reported phenotype in these individuals. Furthermore, it unveiled the potential therapeutic options that could be suggested to these individuals.

Genetic constraint at single amino acid resolution in protein domains improves missense variant prioritisation and gene discovery

BACKGROUND

One of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as "genetic constraint". Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes.

METHODS

We aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues.

RESULTS

We identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism.

CONCLUSIONS

Grouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.

Inter-BRCT linker is probably the most intolerant region of the BRCA1 BRCT domain

Pathogenic mutations in BRCA1 are associated with an increased risk of hereditary breast, ovarian, and some other cancers; however, the clinical significance of many mutations in this gene remains unknown (Variants of Unknown Significance/VUS). Since mutations in intolerant regions of a protein lead to dysfunction and pathogenicity, identifying these regions helps to predict the clinical importance of VUSs. This study aimed to identify intolerant regions of BRCA1 and understand the possible root of this susceptibility. Intolerant regions appear to carry more pathogenic mutations than expected due to their lower tolerance to missense variations. Therefore, we hypothesized that among the BRCA1 regions, the higher the mutation density, the greater the intolerance. Thus, pathogenic mutation density and regional intolerance scores were calculated to identify BRCA1-intolerant regions. To investigate the pathogenic mechanisms of missense-intolerant regions in BRCA1, transcription activation (TA) experiments and molecular dynamics (MD) simulations were also performed. The results showed that the RING domain, followed by the BRCT domain, has the highest density of pathogenic mutations. In the BRCT domain, a higher density of pathogenic mutations was observed in the inter-BRCT linker. Additionally, scores generated by Missense Tolerance Ratio-3D (MTR3D) and the Missense Tolerance Ratio consensus (MTRX) showed that the inter-BRCT linker is more intolerant than other regions of the BRCT domain. The MD results showed that mutations in the inter-BRCT linker led to cancer susceptibility, likely due to disruption of the interaction between BRCA1 and phosphopeptides. TA laboratory assays further supported the importance of the inter-BRCT linker.Communicated by Ramaswamy H. Sarma.

Genetic features of patients with MPS type IIIB: Description of five pathogenic gene variations

BACKGROUND

There are four distinct forms of Sanfilippo syndrome (MPS type III), each of which is an autosomal lysosomal storage disorder. These forms are caused by abnormalities in one of four lysosomal enzymes. This study aimed to identify possible genetic variants that contribute to Sanfilippo IIIB in 14 independent families in Southwest Iran.

METHODS

Patients were included if their clinical features and enzyme assay results were suggestive. The patients were subsequently subjected to Sanger Sequencing to screen for Sanfilippo-related genes. Additional investigations have been conducted using various computational analyses to determine the probable functional effects of diagnosed variants.

RESULTS

Five distinct variations were identified in the NAGLU gene. This included two novel variants in two distinct families and three previously reported variants in 12 distinct families. All of these variations were recognized as pathogenic using the MutationTaster web server. In silico analysis showed that all detected variants affected protein structural stability; four destabilized protein structures, and the fifth variation had the opposite effect.

CONCLUSION

In this study, two novel variations in the NAGLU gene were identified. The results of this study positively contribute to the mutation diversity of the NAGLU gene. To identify new disease biomarkers and therapeutic targets, precision medicine must precisely characterize and account for genetic variations. New harmful gene variants are valuable for updating gene databases concerning Sanfilippo disease variations and NGS gene panels. This may also improve genetic counselling for rapid risk examinations and disease surveillance.

Distances from ligands as main predictive features for pathogenicity and functional effect of variants in NMDA receptors

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

A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites

Protein evolution is constrained by structure and function, creating patterns in residue conservation that are routinely exploited to predict structure and other features. Similar constraints should affect variation across individuals, but it is only with the growth of human population sequencing that this has been tested at scale. Now, human population constraint has established applications in pathogenicity prediction, but it has not yet been explored for structural inference. Here, we map 2.4 million population variants to 5885 protein families and quantify residue-level constraint with a new Missense Enrichment Score (MES). Analysis of 61,214 structures from the PDB spanning 3661 families shows that missense depleted sites are enriched in buried residues or those involved in small-molecule or protein binding. MES is complementary to evolutionary conservation and a combined analysis allows a new classification of residues according to a conservation plane. This approach finds functional residues that are evolutionarily diverse, which can be related to specificity, as well as family-wide conserved sites that are critical for folding or function. We also find a possible contrast between lethal and non-lethal pathogenic sites, and a surprising clinical variant hot spot at a subset of missense enriched positions.

Severe communication delays are independent of seizure burden and persist despite contemporary treatments in SCN1A+ Dravet syndrome: Insights from the ENVISION natural history study

OBJECTIVE

Dravet syndrome (DS) is a developmental and epileptic encephalopathy characterized by high seizure burden, treatment-resistant epilepsy, and developmental stagnation. Family members rate communication deficits among the most impactful disease manifestations. We evaluated seizure burden and language/communication development in children with DS.

METHODS

ENVISION was a prospective, observational study evaluating children with DS associated with SCN1A pathogenic variants (SCN1A+ DS) enrolled at age ≤5 years. Seizure burden and antiseizure medications were assessed every 3 months and communication and language every 6 months with the Bayley Scales of Infant and Toddler Development 3rd edition and the parent-reported Vineland Adaptive Behavior Scales 3rd edition. We report data from the first year of observation, including analyses stratified by age at Baseline: 0:6-2:0 years:months (Y:M; youngest), 2:1-3:6 Y:M (middle), and 3:7-5:0 Y:M (oldest).

RESULTS

Between December 2020 and March 2023, 58 children with DS enrolled at 16 sites internationally. Median follow-up was 17.5 months (range = .0-24.0), with 54 of 58 (93.1%) followed for at least 6 months and 51 of 58 (87.9%) for 12 months. Monthly countable seizure frequency (MCSF) increased with age (median [minimum-maximum] = 1.0 in the youngest [1.0-70.0] and middle [1.0-242.0] age groups and 4.5 [.0-2647.0] in the oldest age group), and remained high, despite use of currently approved antiseizure medications. Language/communication delays were observed early, and developmental stagnation occurred after age 2 years with both instruments. In predictive modeling, chronologic age was the only significant covariate of seizure frequency (effect size = .52, p = .024). MCSF, number of antiseizure medications, age at first seizure, and convulsive status epilepticus were not predictors of language/communication raw scores.

SIGNIFICANCE

In infants and young children with SCN1A+ DS, language/communication delay and stagnation were independent of seizure burden. Our findings emphasize that the optimal therapeutic window to prevent language/communication delay is before 3 years of age.

Pathogenic signal peptide variants in the human genome

Secreted and membrane proteins represent a third of all cellular proteins and contain N-terminal signal peptides that are required for protein targeting to endoplasmic reticulum (ER). Mutations in signal peptides affect protein targeting, translocation, processing, and stability, and are associated with human diseases. However, only a few of them have been identified or characterized. In this report, we identified pathogenic signal peptide variants across the human genome using bioinformatic analyses and predicted the molecular mechanisms of their pathology. We recovered more than 65 thousand signal peptide mutations, over 11 thousand we classified as pathogenic, and proposed framework for distinction of their molecular mechanisms. The pathogenic mutations affect over 3.3 thousand genes coding for secreted and membrane proteins. Most pathogenic mutations alter the signal peptide hydrophobic core, a critical recognition region for the signal recognition particle, potentially activating the Regulation of Aberrant Protein Production (RAPP) quality control and specific mRNA degradation. The remaining pathogenic variants (about 25%) alter either the N-terminal region or signal peptidase processing site that can result in translocation deficiencies at the ER membrane or inhibit protein processing. This work provides a conceptual framework for the identification of mutations across the genome and their connection with human disease.

Prophecy or empiricism? Clinical value of predicting versus determining genetic variant functions

The recent explosion of epilepsy genetic testing has created challenges for interpretation of gene variants. Assessments of the functional consequences of genetic variants either by predictive or experimental strategies can contribute to estimating pathogenicity, but there is no consensus on which approach is best. The Special Interest Group on Epilepsy Genetics hosted a session during the Annual American Epilepsy Society Meeting in December 2022 to discuss this topic. The session featured a debate of the relative advantages and limitations of predicting (prophecy) versus experimentally determining (empiricism) variant function using ion channel gene variants as examples. This commentary summarizes these discussions.

TUBB3 and KIF21A in neurodevelopment and disease

Neuronal migration and axon growth and guidance require precise control of microtubule dynamics and microtubule-based cargo transport. TUBB3 encodes the neuronal-specific β-tubulin isotype III, TUBB3, a component of neuronal microtubules expressed throughout the life of central and peripheral neurons. Human pathogenic TUBB3 missense variants result in altered TUBB3 function and cause errors either in the growth and guidance of cranial and, to a lesser extent, central axons, or in cortical neuronal migration and organization, and rarely in both. Moreover, human pathogenic missense variants in KIF21A, which encodes an anterograde kinesin motor protein that interacts directly with microtubules, alter KIF21A function and cause errors in cranial axon growth and guidance that can phenocopy TUBB3 variants. Here, we review reported TUBB3 and KIF21A variants, resulting phenotypes, and corresponding functional studies of both wildtype and mutant proteins. We summarize the evidence that, in vitro and in mouse models, loss-of-function and missense variants can alter microtubule dynamics and microtubule-kinesin interactions. Lastly, we highlight additional studies that might contribute to our understanding of the relationship between specific tubulin isotypes and specific kinesin motor proteins in health and disease.

Current understanding of the genomic abnormities in premature ovarian failure: chance for early diagnosis and management

Premature ovarian failure (POF) is an insidious cause of female infertility and a devastating condition for women. POF also has a strong familial and heterogeneous genetic background. Management of POF is complicated by the variable etiology and presentation, which are generally characterized by abnormal hormone levels, gene instability and ovarian dysgenesis. To date, abnormal regulation associated with POF has been found in a small number of genes, including autosomal and sex chromosomal genes in folliculogenesis, granulosa cells, and oocytes. Due to the complex genomic contributions, ascertaining the exact causative mechanisms has been challenging in POF, and many pathogenic genomic characteristics have yet to be elucidated. However, emerging research has provided new insights into genomic variation in POF as well as novel etiological factors, pathogenic mechanisms and therapeutic intervention approaches. Meanwhile, scattered studies of transcriptional regulation revealed that ovarian cell function also depends on specific biomarker gene expression, which can influence protein activities, thus causing POF. In this review, we summarized the latest research and issues related to the genomic basis for POF and focused on insights gained from their biological effects and pathogenic mechanisms in POF. The present integrated studies of genomic variants, gene expression and related protein abnormalities were structured to establish the role of etiological genes associated with POF. In addition, we describe the design of some ongoing clinical trials that may suggest safe, feasible and effective approaches to improve the diagnosis and therapy of POF, such as Filgrastim, goserelin, resveratrol, natural plant antitoxin, Kuntai capsule et al. Understanding the candidate genomic characteristics in POF is beneficial for the early diagnosis of POF and provides appropriate methods for prevention and drug treatment. Additional efforts to clarify the POF genetic background are necessary and are beneficial for researchers and clinicians regarding genetic counseling and clinical practice. Taken together, recent genomic explorations have shown great potential to elucidate POF management in women and are stepping from the bench to the bedside.

Estimating clinical risk in gene regions from population sequencing cohort data

While pathogenic variants can significantly increase disease risk, it is still challenging to estimate the clinical impact of rare missense variants more generally. Even in genes such as BRCA2 or PALB2, large cohort studies find no significant association between breast cancer and rare missense variants collectively. Here, we introduce REGatta, a method to estimate clinical risk from variants in smaller segments of individual genes. We first define these regions by using the density of pathogenic diagnostic reports and then calculate the relative risk in each region by using over 200,000 exome sequences in the UK Biobank. We apply this method in 13 genes with established roles across several monogenic disorders. In genes with no significant difference at the gene level, this approach significantly separates disease risk for individuals with rare missense variants at higher or lower risk (BRCA2 regional model OR = 1.46 [1.12, 1.79], p = 0.0036 vs. BRCA2 gene model OR = 0.96 [0.85, 1.07] p = 0.4171). We find high concordance between these regional risk estimates and high-throughput functional assays of variant impact. We compare our method with existing methods and the use of protein domains (Pfam) as regions and find REGatta better identifies individuals at elevated or reduced risk. These regions provide useful priors and are potentially useful for improving risk assessment for genes associated with monogenic diseases.

SCN1A gain-of-function mutation causing an early onset epileptic encephalopathy

OBJECTIVE

Loss-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.

METHODS

Individuals carrying the recurrent SCN1A p.R1636Q variant were identified through diagnostic testing. Whole cell voltage-clamp electrophysiological recording in HEK-293 T cells was performed to compare the properties of sodium channels containing wild-type Nav 1.1 or Nav 1.1-R1636Q along with both Nav β1 and Nav β2 subunits, including response to oxcarbazepine. To delineate differences from other SCN1A-related epilepsies, we analyzed electronic medical records.

RESULTS

All 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. The observed functional changes closely paralleled effects of pathogenic variants in SCN3A and SCN8A at corresponding positions. Both wild type 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 at onset.

SIGNIFICANCE

The recurrent SCN1A p.R1636Q variant causes a clinical entity with a wider clinical spectrum than previously reported, characterized by neonatal 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.

Delineation of functionally essential protein regions for 242 neurodevelopmental genes

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.

GRAS-1 is a novel regulator of early meiotic chromosome dynamics in C. elegans

Chromosome movements and licensing of synapsis must be tightly regulated during early meiosis to ensure accurate chromosome segregation and avoid aneuploidy, although how these steps are coordinated is not fully understood. Here we show that GRAS-1, the worm homolog of mammalian GRASP/Tamalin and CYTIP, coordinates early meiotic events with cytoskeletal forces outside the nucleus. GRAS-1 localizes close to the nuclear envelope (NE) in early prophase I and interacts with NE and cytoskeleton proteins. Delayed homologous chromosome pairing, synaptonemal complex (SC) assembly, and DNA double-strand break repair progression are partially rescued by the expression of human CYTIP in gras-1 mutants, supporting functional conservation. However, Tamalin, Cytip double knockout mice do not exhibit obvious fertility or meiotic defects, suggesting evolutionary differences between mammals. gras-1 mutants show accelerated chromosome movement during early prophase I, implicating GRAS-1 in regulating chromosome dynamics. GRAS-1-mediated regulation of chromosome movement is DHC-1-dependent, placing it acting within the LINC-controlled pathway, and depends on GRAS-1 phosphorylation at a C-terminal S/T cluster. We propose that GRAS-1 coordinates the early steps of homology search and licensing of SC assembly by regulating the pace of chromosome movement in early prophase I.

aRgus: Multilevel visualization of non-synonymous single nucleotide variants & advanced pathogenicity score modeling for genetic vulnerability assessment

The widespread use of high-throughput sequencing techniques is leading to a rapidly increasing number of disease-associated variants of unknown significance and candidate genes. Integration of knowledge concerning their genetic, protein as well as functional and conservational aspects is necessary for an exhaustive assessment of their relevance and for prioritization of further clinical and functional studies investigating their role in human disease. To collect the necessary information, a multitude of different databases has to be accessed and data extraction from the original sources commonly is not user-friendly and requires advanced bioinformatics skills. This leads to a decreased data accessibility for a relevant number of potential users such as clinicians, geneticist, and clinical researchers. Here, we present aRgus (https://argus.urz.uni-heidelberg.de/), a standalone webtool for simple extraction and intuitive visualization of multi-layered gene, protein, variant, and variant effect prediction data. aRgus provides interactive exploitation of these data within seconds for any known gene of the human genome. In contrast to existing online platforms for compilation of variant data, aRgus complements visualization of chromosomal exon-intron structure and protein domain annotation with ClinVar and gnomAD variant distributions as well as position-specific variant effect prediction score modeling. aRgus thereby enables timely assessment of protein regions vulnerable to variation with single amino acid resolution and provides numerous applications in variant and protein domain interpretation as well as in the design of in vitro experiments.

Estimating clinical risk in gene regions from population sequencing cohort data

While pathogenic variants significantly increase disease risk in many genes, it is still challenging to estimate the clinical impact of rare missense variants more generally. Even in genes such as BRCA2 or PALB2 , large cohort studies find no significant association between breast cancer and rare germline missense variants collectively. Here we introduce REGatta, a method to improve the estimation of clinical risk in gene segments. We define gene regions using the density of pathogenic diagnostic reports, and then calculate the relative risk in each of these regions using 109,581 exome sequences from women in the UK Biobank. We apply this method in seven established breast cancer genes, and identify regions in each gene with statistically significant differences in breast cancer incidence for rare missense carriers. Even in genes with no significant difference at the gene level, this approach significantly separates rare missense variant carriers at higher or lower risk ( BRCA2 regional model OR=1.46 [1.12, 1.79], p=0.0036 vs. BRCA2 gene model OR=0.96 [0.85,1.07] p=0.4171). We find high concordance between these regional risk estimates and high-throughput functional assays of variant impact. We compare with existing methods and the use of protein domains (Pfam) as regions, and find REGatta better identifies individuals at elevated or reduced risk. These regions provide useful priors which can potentially be used to improve risk assessment and clinical management.

Data-driven historical characterization of epilepsy-associated genes

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.

Gene variant effects across sodium channelopathies predict function and guide precision therapy

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

The gain of function SCN1A disorder spectrum: novel epilepsy phenotypes and therapeutic implications

Brain voltage-gated sodium channel NaV1.1 (SCN1A) loss-of-function variants cause the severe epilepsy Dravet syndrome, as well as milder phenotypes associated with genetic epilepsy with febrile seizures plus. Gain of function SCN1A variants are associated with familial hemiplegic migraine type 3. Novel SCN1A-related phenotypes have been described including early infantile developmental and epileptic encephalopathy with movement disorder, and more recently neonatal presentations with arthrogryposis. Here we describe the clinical, genetic and functional evaluation of affected individuals. Thirty-five patients were ascertained via an international collaborative network using a structured clinical questionnaire and from the literature. We performed whole-cell voltage-clamp electrophysiological recordings comparing sodium channels containing wild-type versus variant NaV1.1 subunits. Findings were related to Dravet syndrome and familial hemiplegic migraine type 3 variants. We identified three distinct clinical presentations differing by age at onset and presence of arthrogryposis and/or movement disorder. The most severely affected infants (n = 13) presented with congenital arthrogryposis, neonatal onset epilepsy in the first 3 days of life, tonic seizures and apnoeas, accompanied by a significant movement disorder and profound intellectual disability. Twenty-one patients presented later, between 2 weeks and 3 months of age, with a severe early infantile developmental and epileptic encephalopathy and a movement disorder. One patient presented after 3 months with developmental and epileptic encephalopathy only. Associated SCN1A variants cluster in regions of channel inactivation associated with gain of function, different to Dravet syndrome variants (odds ratio = 17.8; confidence interval = 5.4-69.3; P = 1.3 × 10-7). Functional studies of both epilepsy and familial hemiplegic migraine type 3 variants reveal alterations of gating properties in keeping with neuronal hyperexcitability. While epilepsy variants result in a moderate increase in action current amplitude consistent with mild gain of function, familial hemiplegic migraine type 3 variants induce a larger effect on gating properties, in particular the increase of persistent current, resulting in a large increase of action current amplitude, consistent with stronger gain of function. Clinically, 13 out of 16 (81%) gain of function variants were associated with a reduction in seizures in response to sodium channel blocker treatment (carbamazepine, oxcarbazepine, phenytoin, lamotrigine or lacosamide) without evidence of symptom exacerbation. Our study expands the spectrum of gain of function SCN1A-related epilepsy phenotypes, defines key clinical features, provides novel insights into the underlying disease mechanisms between SCN1A-related epilepsy and familial hemiplegic migraine type 3, and identifies sodium channel blockers as potentially efficacious therapies. Gain of function disease should be considered in early onset epilepsies with a pathogenic SCN1A variant and non-Dravet syndrome phenotype.

Mendelian gene identification through mouse embryo viability screening

BACKGROUND

The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.

METHODS

Here we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project.

RESULTS

We found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts.

CONCLUSIONS

Information on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

Concise Review: Stem Cell Models of SCN1A-Related Encephalopathies—Current Perspective and Future Therapies

Mutations in the SCN1A gene can cause a variety of phenotypes, ranging from mild forms, such as febrile seizures and generalized epilepsy with febrile seizures plus, to severe, such as Dravet and non-Dravet developmental epileptic encephalopathies. Until now, more than two thousand pathogenic variants of the SCN1A gene have been identified and different pathogenic mechanisms (loss vs. gain of function) described, but the precise molecular mechanisms responsible for the deficits exhibited by patients are not fully elucidated. Additionally, the phenotypic variability proves the involvement of other genetic factors in its final expression. This is the reason why animal models and cell line models used to explore the molecular pathology of SCN1A-related disorders are only of limited use. The results of studies based on such models cannot be directly translated to affected individuals because they do not address each patient’s unique genetic background. The generation of functional neurons and glia for patient-derived iPSCs, together with the generation of isogenic controls using CRISPR/Cas technology, and finally, the 3D brain organoid models, seem to be a good way to solve this problem. Here, we review SCN1A-related encephalopathies, as well as the stem cell models used to explore their molecular basis.

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

BACKGROUND

Variants 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.

METHODS

We 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 several baseline methods.

FINDINGS

MTL-SVM maintains channel family structure during model training, improving overall predictive performance (mean balanced accuracy 0·718 ± 0·041, AU-ROC 0·761 ± 0·063) over baseline (mean balanced accuracy 0·620 ± 0·045, AU-ROC 0·711 ± 0·022). We can obtain meaningful predictions even for channels with few known variants (KCNC1, KCNQ5).

INTERPRETATION

Our 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.

FUNDING

This work was supported by intramural funding of the Medical Faculty, University of Tuebingen (PATE F.1315137.1), the Federal Ministry for Education and Research (Treat-ION, 01GM1907A/B/G/H) and the German Research Foundation (FOR-2715, Le1030/16-2, He8155/1-2).

De novo heterozygous variants in SLC30A7 are a candidate cause for Joubert syndrome

Joubert syndrome (JS), a well-established ciliopathy, is characterized by the distinctive molar tooth sign on brain MRI, ataxia, and neurodevelopmental features. Other manifestations can include polydactyly, accessory frenula, renal, or liver disease. Here, we report individuals meeting criteria for JS with de novo heterozygous variants in SLC30A7 (Chr1p21.2). The first individual is a female with history of unilateral postaxial polydactyly, classic molar tooth sign on MRI, macrocephaly, ataxia, ocular motor apraxia, neurodevelopmental delay, and precocious puberty. Exome sequencing detected a de novo heterozygous missense variant in SLC30A7: NM_133496.5: c.407 T > C, (p.Val136Ala). The second individual had bilateral postaxial polydactyly, molar tooth sign, macrocephaly, developmental delay, and an extra oral frenulum. A de novo deletion-insertion variant in SLC30A7, c.490_491delinsAG (p.His164Ser) was found. Both de novo variants affect highly conserved residues. Variants were not identified in known Joubert genes for either case. SLC30A7 has not yet been associated with a human phenotype. The SLC30 family of zinc transporters, like SLC30A7, permit cellular efflux of zinc, and although it is expressed in the brain its functions remain unknown. Published data from proteomic studies support SLC30A7 interaction with TCTN3, another protein associated with JS. The potential involvement of such genes in primary cilia suggest a role in Sonic Hedgehog signaling. SLC30A7 is a candidate JS-associated gene. Future work could be directed toward further characterization of SLC30A7 variants and understanding its function.

Spectrum of Phenotypic, Genetic, and Functional Characteristics in Patients With Epilepsy With KCNC2 Pathogenic Variants

BACKGROUND AND OBJECTIVES

KCNC2 encodes Kv3.2, a member of the Shaw-related (Kv3) voltage-gated potassium channel subfamily, which is important for sustained high-frequency firing and optimized energy efficiency of action potentials in the brain. The objective of this study was to analyze the clinical phenotype, genetic background, and biophysical function of disease-associated Kv3.2 variants.

METHODS

Individuals with KCNC2 variants detected by exome sequencing were selected for clinical, further genetic, and functional analysis. Cases were referred through clinical and research collaborations. Selected de novo variants were examined electrophysiologically in Xenopus laevis oocytes.

RESULTS

We identified novel KCNC2 variants in 18 patients with various forms of epilepsy, including genetic generalized epilepsy (GGE), developmental and epileptic encephalopathy (DEE) including early-onset absence epilepsy, focal epilepsy, and myoclonic-atonic epilepsy. Of the 18 variants, 10 were de novo and 8 were classified as modifying variants. Eight drug-responsive patients became seizure-free using valproic acid as monotherapy or in combination, including severe DEE cases. Functional analysis of 4 variants demonstrated gain of function in 3 severely affected DEE cases and loss of function in 1 case with a milder phenotype (GGE) as the underlying pathomechanisms.

DISCUSSION

These findings implicate KCNC2 as a novel causative gene for epilepsy and emphasize the critical role of KV3.2 in the regulation of brain excitability.

Impaired Color Recognition in HCN1 Epilepsy: A Single Case Report

Variants in HCN1 are associated with a range of epilepsy syndromes including developmental and epileptic encephalopathies. Here we describe a child harboring a novel de novo HCN1 variant, E246A, in a child with epilepsy and mild developmental delay. By parental report, the child had difficulty in discriminating between colors implicating a visual deficit. This interesting observation may relate to the high expression of HCN1 channels in rod and cone photoreceptors where they play an integral role in shaping the light response. Functional analysis of the HCN1 E246A variant revealed a right shift in the voltage dependence of activation and slowing of the rates of activation and deactivation. The changes in the biophysical properties are consistent with a gain-of-function supporting the role of HCN1 E246A in disease causation. This case suggests that visual function, including color discrimination, should be carefully monitored in patients with diseases due to HCN1 pathogenic variants.

Analysis of missense variants in the human genome reveals widespread gene-specific clustering and improves prediction of pathogenicity

We used a machine learning approach to analyze the within-gene distribution of missense variants observed in hereditary conditions and cancer. When applied to 840 genes from the ClinVar database, this approach detected a significant non-random distribution of pathogenic and benign variants in 387 (46%) and 172 (20%) genes, respectively, revealing that variant clustering is widespread across the human exome. This clustering likely occurs as a consequence of mechanisms shaping pathogenicity at the protein level, as illustrated by the overlap of some clusters with known functional domains. We then took advantage of these findings to develop a pathogenicity predictor, MutScore, that integrates qualitative features of DNA substitutions with the new additional information derived from this positional clustering. Using a random forest approach, MutScore was able to identify pathogenic missense mutations with very high accuracy, outperforming existing predictive tools, especially for variants associated with autosomal-dominant disease and cancer. Thus, the within-gene clustering of pathogenic and benign DNA changes is an important and previously underappreciated feature of the human exome, which can be harnessed to improve the prediction of pathogenicity and disambiguation of DNA variants of uncertain significance.

Amelioration of a neurodevelopmental disorder by carbamazepine in a case having a gain-of-function GRIA3 variant

GRIA3 at Xq25 encodes glutamate ionotropic receptor AMPA type 3 (GluA3), a subunit of postsynaptic glutamate-gated ion channels mediating neurotransmission. Hemizygous loss-of-function (LOF) variants in GRIA3 cause a neurodevelopmental disorder (NDD) in male individuals. Here, we report a gain-of-function (GOF) variant at GRIA3 in a male patient. We identified a hemizygous de novo missense variant in GRIA3 in a boy with an NDD: c.1844C > T (p.Ala615Val) using whole-exome sequencing. His neurological signs, such as hypertonia and hyperreflexia, were opposite to those in previous cases having LOF GRIA3 variants. His seizures and hypertonia were ameliorated by carbamazepine, inhibiting glutamate release from presynapses. Patch-clamp recordings showed that the human GluA3 mutant (p.Ala615Val) had slower desensitization and deactivation kinetics. A fly line expressing a human GluA3 mutant possessing our variant and the Lurcher variant, which makes ion channels leaky, showed developmental defects, while one expressing a mutant possessing either of them did not. Collectively, these results suggest that p.Ala615Val has GOF effects. GRIA3 GOF variants may cause an NDD phenotype distinctive from that of LOF variants, and drugs suppressing glutamatergic neurotransmission may ameliorate this phenotype. This study should help in refining the clinical management of GRIA3-related NDDs.

Three-dimensional missense tolerance ratio analysis

A wealth of genetic information is available describing single-nucleotide variants in the human population that appear to be well-tolerated and in and of themselves do not confer disease. These variant data sets contain signatures about the protein structure-function relationships and provide an unbiased view of various protein functions in the context of human health. This information can be used to determine regional intolerance to variation, defined as the missense tolerance ratio (MTR), which is an indicator of stretches of the polypeptide chain that can tolerate changes without compromising protein function in a manner that impacts human health. This approach circumvents the lack of comprehensive data by averaging the data from adjacent residues on the polypeptide chain. We reasoned that many motifs in proteins consist of nonadjacent residues, but together function as a unit. We therefore developed an approach to analyze nearest neighbors in three-dimensional space as determined by crystallography rather than on the polypeptide chain. We used members of the GRIN gene family that encode subunits of NMDA-type ionotropic glutamate receptors (iGluRs) to exemplify the differences between these methods. Our method, 3DMTR, provides new information about regions of intolerance within iGluRs, allows consideration of protein-protein interfaces in multimeric proteins, and moves this important research tool from one-dimensional analysis to a structurally relevant tool. We validate the improved 3DMTR score by showing that it more accurately classifies the functional consequences of a set of newly measured and published point mutations of Grin family genes than existing methods.

Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes

Rare genetic disorders, while individually rare, are collectively common. They represent some of the most severe disorders affecting patients worldwide with significant morbidity and mortality. Over the last decade, advances in genomic methods have significantly uplifted diagnostic rates for patients and facilitated novel and targeted therapies. However, many patients with rare genetic disorders still remain undiagnosed as the genetic etiology of only a proportion of Mendelian conditions has been discovered to date. This article explores existing strategies to identify novel Mendelian genes and how these discoveries impact clinical care and therapeutics. We discuss the importance of data sharing, phenotype-driven approaches, patient-led approaches, utilization of large-scale genomic sequencing projects, constraint-based methods, integration of multi-omics data, and gene-to-patient methods. We further consider the health economic advantages of novel gene discovery and speculate on potential future methods for improved clinical outcomes.

Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals

Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.

Variants in the degron of AFF3 are associated with intellectual disability, mesomelic dysplasia, horseshoe kidney, and epileptic encephalopathy

The ALF transcription factor paralogs, AFF1, AFF2, AFF3, and AFF4, are components of the transcriptional super elongation complex that regulates expression of genes involved in neurogenesis and development. We describe an autosomal dominant disorder associated with de novo missense variants in the degron of AFF3, a nine amino acid sequence important for its binding to ubiquitin ligase, or with de novo deletions of this region. The sixteen affected individuals we identified, along with two previously reported individuals, present with a recognizable pattern of anomalies, which we named KINSSHIP syndrome (KI for horseshoe kidney, NS for Nievergelt/Savarirayan type of mesomelic dysplasia, S for seizures, H for hypertrichosis, I for intellectual disability, and P for pulmonary involvement), partially overlapping the AFF4-associated CHOPS syndrome. Whereas homozygous Aff3 knockout mice display skeletal anomalies, kidney defects, brain malformations, and neurological anomalies, knockin animals modeling one of the microdeletions and the most common of the missense variants identified in affected individuals presented with lower mesomelic limb deformities like KINSSHIP-affected individuals and early lethality, respectively. Overexpression of AFF3 in zebrafish resulted in body axis anomalies, providing some support for the pathological effect of increased amount of AFF3. The only partial phenotypic overlap of AFF3- and AFF4-associated syndromes and the previously published transcriptome analyses of ALF transcription factors suggest that these factors are not redundant and each contributes uniquely to proper development.

Rare deleterious mutations of HNRNP genes result in shared neurodevelopmental disorders

BACKGROUND

With the increasing number of genomic sequencing studies, hundreds of genes have been implicated in neurodevelopmental disorders (NDDs). The rate of gene discovery far outpaces our understanding of genotype-phenotype correlations, with clinical characterization remaining a bottleneck for understanding NDDs. Most disease-associated Mendelian genes are members of gene families, and we hypothesize that those with related molecular function share clinical presentations.

METHODS

We tested our hypothesis by considering gene families that have multiple members with an enrichment of de novo variants among NDDs, as determined by previous meta-analyses. One of these gene families is the heterogeneous nuclear ribonucleoproteins (hnRNPs), which has 33 members, five of which have been recently identified as NDD genes (HNRNPK, HNRNPU, HNRNPH1, HNRNPH2, and HNRNPR) and two of which have significant enrichment in our previous meta-analysis of probands with NDDs (HNRNPU and SYNCRIP). Utilizing protein homology, mutation analyses, gene expression analyses, and phenotypic characterization, we provide evidence for variation in 12 HNRNP genes as candidates for NDDs. Seven are potentially novel while the remaining genes in the family likely do not significantly contribute to NDD risk.

RESULTS

We report 119 new NDD cases (64 de novo variants) through sequencing and international collaborations and combined with published clinical case reports. We consider 235 cases with gene-disruptive single-nucleotide variants or indels and 15 cases with small copy number variants. Three hnRNP-encoding genes reach nominal or exome-wide significance for de novo variant enrichment, while nine are candidates for pathogenic mutations. Comparison of HNRNP gene expression shows a pattern consistent with a role in cerebral cortical development with enriched expression among radial glial progenitors. Clinical assessment of probands (n = 188-221) expands the phenotypes associated with HNRNP rare variants, and phenotypes associated with variation in the HNRNP genes distinguishes them as a subgroup of NDDs.

CONCLUSIONS

Overall, our novel approach of exploiting gene families in NDDs identifies new HNRNP-related disorders, expands the phenotypes of known HNRNP-related disorders, strongly implicates disruption of the hnRNPs as a whole in NDDs, and supports that NDD subtypes likely have shared molecular pathogenesis. To date, this is the first study to identify novel genetic disorders based on the presence of disorders in related genes. We also perform the first phenotypic analyses focusing on related genes. Finally, we show that radial glial expression of these genes is likely critical during neurodevelopment. This is important for diagnostics, as well as developing strategies to best study these genes for the development of therapeutics.

Current knowledge of SLC6A1-related neurodevelopmental disorders

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.

GJB4 and GJC3 variants in non-syndromic hearing impairment in Ghana

IMPACT STATEMENT

Although connexins are known to be the major genetic factors associated with HI, only a few studies have investigated GJB4 and GJC3 variants among hearing-impaired patients. This study is the first to report GJB4 and GJC3 variants from an African HI cohort. We have demonstrated that GJB4 and GJC3 genes may not contribute significantly to HI in Ghana, hence these genes should not be considered for routine clinical screening in Ghana. However, it is important to study a larger population to determine the association of GJB4 and GJC3 variants with HI.

Unified inference of missense variant effects and gene constraints in the human genome

A challenge in medical genomics is to identify variants and genes associated with severe genetic disorders. Based on the premise that severe, early-onset disorders often result in a reduction of evolutionary fitness, several statistical methods have been developed to predict pathogenic variants or constrained genes based on the signatures of negative selection in human populations. However, we currently lack a statistical framework to jointly predict deleterious variants and constrained genes from both variant-level features and gene-level selective constraints. Here we present such a unified approach, UNEECON, based on deep learning and population genetics. UNEECON treats the contributions of variant-level features and gene-level constraints as a variant-level fixed effect and a gene-level random effect, respectively. The sum of the fixed and random effects is then combined with an evolutionary model to infer the strength of negative selection at both variant and gene levels. Compared with previously published methods, UNEECON shows improved performance in predicting missense variants and protein-coding genes associated with autosomal dominant disorders, and feature importance analysis suggests that both gene-level selective constraints and variant-level predictors are important for accurate variant prioritization. Furthermore, based on UNEECON, we observe a low correlation between gene-level intolerance to missense mutations and that to loss-of-function mutations, which can be partially explained by the prevalence of disordered protein regions that are highly tolerant to missense mutations. Finally, we show that genes intolerant to both missense and loss-of-function mutations play key roles in the central nervous system and the autism spectrum disorders. Overall, UNEECON is a promising framework for both variant and gene prioritization.

Numerous statistical methods have been developed to predict deleterious missense variants or constrained genes in the human genome, but unified prioritization methods that utilize both variant- and gene-level information are underdeveloped. Here we present UNEECON, an evolution-based deep learning framework for unified variant and gene prioritization. By integrating variant-level predictors and gene-level selective constraints, UNEECON outperforms existing methods in predicting missense variants and protein-coding genes associated with dominant disorders. Based on UNEECON, we show that disordered proteins are tolerant to missense mutations but not to loss-of-function mutations. In addition, we find that genes under strong selective constraints at both missense and loss-of-function levels are strongly associated with the central nervous system and the autism spectrum disorders, highlighting the need to investigate the function of these highly constrained genes in future studies.

Clinical Interpretation of Sequence Variants

Clinical interpretation of DNA sequence variants is a critical step in reporting clinical genetic testing results. Application of next-generation sequencing technology in molecular genetic testing has facilitated diagnoses of genetic disorders in clinical practice. However, the large number of DNA sequence variants detected in clinical specimens, many of which have never been seen before, make clinical interpretation challenging. Recommendations by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) have been widely adopted by clinical laboratories around the world to guide clinical interpretation of sequence variants. The ClinGen Sequence Variant Interpretation Working Group and various disease-specific variant curation expert panels have also developed specifications for the ACMG/AMP recommendations. Despite these efforts to standardize variant interpretation in clinical practice, different laboratories may subjectively use professional judgment to determine which criteria are applicable when classifying a variant. In addition, clinicians and researchers who are not familiar with the variant interpretation process may have difficulty understanding clinical genetic reports and communicating the clinical significance of genetic testing results. Here we provide a step-by-step protocol for clinical interpretation of sequence variants, including practical examples. By following this protocol, clinical laboratory geneticists can interpret the clinical significance of sequence variants according to the ACMG/AMP recommendations and ClinGen framework. Furthermore, this article will help clinicians and researchers to understand variant classification in clinical genetic testing reports and evaluate the quality of the reports. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Interpreting the clinical significance of sequence variants Support Protocol: Reevaluating the clinical significance of sequence variants.

Clinical characterization of patients with leucine-rich repeat kinase 2 genetic variants in Japan

Variants of leucine-rich repeat kinase 2 (LRRK2) are the most common genetic cause of familial Parkinson's disease (PD). We aimed to investigate the genetic and clinical features of patients with PD and LRRK2 variants in Japan by screening for LRRK2 variants in three exons (31, 41, and 48), which include the following pathogenic mutations: p.R1441C, p.R1441G, p.R1441H, p.G2019S, and p.I2020T. Herein, we obtained data containing LRRK2 variants derived from 1402 patients with PD (653 with sporadic PD and 749 with familial PD). As a result, we successfully detected pathogenic variants (four with p.R1441G, five with p.R1441H, seven with p.G2019S, and seven with p.I2020T) and other rare variants (two with p.V1447M, one with p.V1450I, one with p.T1491delT, and one with p.H2391Q). Two risk variants, p.P1446L and p.G2385R, were found in 10 and 146 patients, respectively. Most of the patients presented the symptoms resembling a common type of PD, such as middle-aged onset, tremor, akinesia, rigidity, and gait disturbance. Dysautonomia, cognitive decline, and psychosis were rarely observed. Each known pathogenic variant had a different founder in our cohort proven by haplotype analysis. The generation study revealed that the LRRK2 variants p.G2019S and p.I2020T were derived 3500 and 1300 years ago, respectively. Our findings present overviews of the prevalence and distribution of LRRK2 variants in Japanese cohorts.

Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

BACKGROUND

Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs.

METHODS

Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families.

RESULTS

We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint.

CONCLUSION

This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes.

Genomic Landscape and Mutational Spectrum of ADAMTS Family Genes in Mendelian Disorders Based on Gene Evidence Review for Variant Interpretation

ADAMTS (a disintegrin and metalloproteinase with thrombospondin motifs) are a family of multidomain extracellular protease enzymes with 19 members. A growing number of ADAMTS family gene variants have been identified in patients with various hereditary diseases. To understand the genomic landscape and mutational spectrum of ADAMTS family genes, we evaluated all reported variants in the ClinVar database and Human Gene Mutation Database (HGMD), as well as recent literature on Mendelian hereditary disorders associated with ADAMTS family genes. Among 1089 variants in 14 genes reported in public databases, 307 variants previously suggested for pathogenicity in Mendelian diseases were comprehensively re-evaluated using the American College of Medical Genetics and Genomics (ACMG) 2015 guideline. A total of eight autosomal recessive genes were annotated as being strongly associated with specific Mendelian diseases, including two recently discovered genes (ADAMTS9 and ADAMTS19) for their causality in congenital diseases (nephronophthisis-related ciliopathy and nonsyndromic heart valve disease, respectively). Clinical symptoms and affected organs were extremely heterogeneous among hereditary diseases caused by ADAMTS family genes, indicating phenotypic heterogeneity despite their structural and functional similarity. ADAMTS6 was suggested as presenting undiscovered pathogenic mutations responsible for novel Mendelian disorders. Our study is the first to highlight the genomic landscape of ADAMTS family genes, providing an appropriate genetic approach for clinical use.