The Epilepsy Genetics Initiative: Systematic reanalysis of diagnostic exomes increases yield

Phenotyping of FGF12AV52H mutation in mouse implies a complex FGF12 network

Pathogenic missense mutation of the FGF12 gene is responsible for a variable disease phenotypic spectrum. Disease-specific therapies require precise dissection of the relationship between different mutations and phenotypes. The lack of a proper animal model hinders the investigation of related diseases, such as early-onset epileptic encephalopathy. Here, an FGF12AV52H mouse model was generated using CRISPR/Cas9 technology, which altered the A isoform without affecting the B isoform. The FGF12AV52H mice exhibited seizure susceptibility, while no spontaneous seizures were observed. The increased excitability in dorsal hippocampal CA3 neurons was confirmed by patch-clamp recordings. Furthermore, immunostaining showed that the balance of excitatory/inhibitory neurons in the hippocampus of the FGF12AV52H mice was perturbed. The increases in inhibitory SOM+ neurons and excitatory CaMKII+ neurons were heterogeneous. Moreover, the locomotion, anxiety levels, risk assessment behavior, social behavior, and cognition of the FGF12AV52H mice were investigated by elevated plus maze, open field, three-chamber sociability, and novel object tests, respectively. Cognition deficit, impaired risk assessment, and social behavior with normal social indexes were observed, implying complex consequences of V52H FGF12A in mice. Together, these data suggest that the function of FGF12A in neurons can be immediate or long-term and involves modulation of ion channels and the differentiation and maturation of neurons. The FGF12AV52H mouse model increases the understanding of the function of FGF12A, and it is of great importance for revealing the complex network of the FGF12 gene in physiological and pathological processes.

Characterization of 13 Novel Genetic Variants in Genes Associated with Epilepsy: Implications for Targeted Therapeutic Strategies

BACKGROUND

Childhood epilepsies are caused by heterogeneous underlying disorders where approximately 40% of the origins of epilepsy can be attributed to genetic factors. The application of next-generation sequencing (NGS) has revolutionized molecular diagnostics and has enabled the identification of disease-causing genes and variants in childhood epilepsies. The objective of this study was to use NGS to identify variants in patients with childhood epilepsy, to expand the variant spectrum and discover potential therapeutic targets.

METHODS

In our study, 55 children with epilepsy of unknown etiology were analyzed by combining clinical-exome and whole-exome sequencing. Novel variants were characterized using various in silico algorithms for pathogenicity and structure prediction.

RESULTS

The molecular genetic cause of epilepsy was identified in 28 patients and the overall diagnostic success rate was 50.9%. We identified variants in 22 different genes associated with epilepsy that correlate well with the described phenotype. SCN1A gene variants were found in five unrelated patients, while ALDH7A1 and KCNQ2 gene variants were found twice. In the other 19 genes, variants were found only in a single patient. This includes genes such as ASH1L, CSNK2B, RHOBTB2, and SLC13A5, which have only recently been associated with epilepsy. Almost half of diagnosed patients (46.4%) carried novel variants. Interestingly, we identified variants in ALDH7A1, KCNQ2, PNPO, SCN1A, and SCN2A resulting in gene-directed therapy decisions for 11 children from our study, including four children who all carried novel SCN1A genetic variants.

CONCLUSIONS

Described novel variants will contribute to a better understanding of the European genetic landscape, while insights into the genotype-phenotype correlation will contribute to a better understanding of childhood epilepsies worldwide. Given the expansion of molecular-based approaches, each newly identified genetic variant could become a potential therapeutic target.

Variants in mitochondrial disease genes are common causes of inherited peripheral neuropathies

BACKGROUND

Peripheral neuropathies in mitochondrial disease are caused by mutations in nuclear genes encoding mitochondrial proteins, or in the mitochondrial genome. Whole exome or genome sequencing enable parallel testing of nuclear and mtDNA genes, and it has significantly advanced the genetic diagnosis of inherited diseases. Despite this, approximately 40% of all Charcot-Marie-Tooth (CMT) cases remain undiagnosed.

METHODS

The genome-phenome analysis platform (GPAP) in RD-Connect was utilised to create a cohort of 2087 patients with at least one Human Phenotype Ontology (HPO) term suggestive of a peripheral neuropathy, from a total of 10,935 patients. These patients' genetic data were then analysed and searched for variants in known mitochondrial disease genes.

RESULTS

A total of 1,379 rare variants were identified, 44 of which were included in this study as either reported pathogenic or likely causative in 42 patients from 36 families. The most common genes found to be likely causative for an autosomal dominant neuropathy were GDAP1 and GARS1. We also detected heterozygous likely pathogenic variants in DNA2, MFN2, DNM2, PDHA1, SDHA, and UCHL1. Biallelic variants in SACS, SPG7, GDAP1, C12orf65, UCHL1, NDUFS6, ETFDH and DARS2 and variants in the mitochondrial DNA (mtDNA)-encoded MT-ATP6 and MT-TK were also causative for mitochondrial CMT. Only 50% of these variants were already reported as solved in GPAP.

CONCLUSION

Variants in mitochondrial disease genes are frequent in patients with inherited peripheral neuropathies. Due to the clinical overlap between mitochondrial disease and CMT, agnostic exome or genome sequencing have better diagnostic yields than targeted gene panels.

Systematic reanalysis of genomic data by diagnostic laboratories: a scoping review of ethical, economic, legal and (psycho)social implications

With the introduction of Next Generation Sequencing (NGS) techniques increasing numbers of disease-associated variants are being identified. This ongoing progress might lead to diagnoses in formerly undiagnosed patients and novel insights in already solved cases. Therefore, many studies suggest introducing systematic reanalysis of NGS data in routine diagnostics. Introduction will, however, also have ethical, economic, legal and (psycho)social (ELSI) implications that Genetic Health Professionals (GHPs) from laboratories should consider before possible implementation of systematic reanalysis. To get a first impression we performed a scoping literature review. Our findings show that for the vast majority of included articles ELSI aspects were not mentioned as such. However, often these issues were raised implicitly. In total, we identified nine ELSI aspects, such as (perceived) professional responsibilities, implications for consent and cost-effectiveness. The identified ELSI aspects brought forward necessary trade-offs for GHPs to consciously take into account when considering responsible implementation of systematic reanalysis of NGS data in routine diagnostics, balancing the various strains on their laboratories and personnel while creating optimal results for new and former patients. Some important aspects are not well explored yet. For example, our study shows GHPs see the values of systematic reanalysis but also experience barriers, often mentioned as being practical or financial only, but in fact also being ethical or psychosocial. Engagement of these GHPs in further research on ELSI aspects is important for sustainable implementation.

Semiautomated approach focused on new genomic information results in time and effort-efficient reannotation of negative exome data

Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting. We developed RENEW, (REannotation of NEgative WES/WGS) an automated reannotation procedure that uses relevant new information in on-line genomic databases to enable rapid review of genomic findings. We tested RENEW in an unselected cohort of 1066 undiagnosed cases with a broad spectrum of phenotypes from the Mayo Clinic Center for Individualized Medicine using new information in ClinVar, HGMD and OMIM between the date of previous analysis/testing and April of 2022. 5741 variants prioritized by RENEW were rapidly reviewed by variant interpretation specialists. Mean analysis time was approximately 20 s per variant (32 h total time). Reviewed cases were classified as: 879 (93.0%) undiagnosed, 63 (6.6%) putatively diagnosed, and 4 (0.4%) definitively diagnosed. New strategies are needed to enable efficient review of genomic findings in unsolved cases. We report on a fast and practical approach to address this need and improve overall diagnostic success in patient testing through a recurrent reannotation process.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.

Next-generation sequencing and comprehensive data reassessment in 263 adult patients with neuromuscular disorders: insights into the gray zone of molecular diagnoses

BACKGROUND

Neuromuscular disorders (NMDs) are heterogeneous conditions with a considerable fraction attributed to monogenic defects. Despite the advancements in genomic medicine, many patients remain without a diagnosis. Here, we investigate whether a comprehensive reassessment strategy improves the diagnostic outcomes.

METHODS

We analyzed 263 patients with NMD phenotypes that underwent diagnostic exome or genome sequencing at our tertiary referral center between 2015 and 2023. We applied a comprehensive reassessment encompassing variant reclassification, re-phenotyping and NGS data reanalysis. Multivariable logistic regression was performed to identify predictive factors associated with a molecular diagnosis.

RESULTS

Initially, a molecular diagnosis was identified in 53 cases (20%), while an additional 23 (9%) had findings of uncertain significance. Following comprehensive reassessment, the diagnostic yield increased to 23%, revealing 44 distinct monogenic etiologies. Reasons for newly obtained molecular diagnoses were variant reclassifications in 7 and NGS data reanalysis in 3 cases including one recently described disease-gene association (DNAJB4). Male sex reduced the odds of receiving a molecular diagnosis (OR 0.42; 95%CI 0.21-0.82), while a positive family history (OR 5.46; 95%CI 2.60-11.76) and a myopathy phenotype (OR 2.72; 95%CI 1.11-7.14) increased the likelihood. 7% were resolved through targeted genetic testing or classified as acquired etiologies.

CONCLUSION

Our findings reinforce the use of NGS in NMDs of suspected monogenic origin. We show that a comprehensive reassessment enhances diagnostic accuracy. However, one needs to be aware that genetic diagnoses are often made with uncertainty and can even be downgraded based on new evidence.

Reanalysis of whole-exome sequencing (WES) data of children with neurodevelopmental disorders in a standard patient care context

This study aims to inform future genetic reanalysis management by evaluating the yield of whole-exome sequencing (WES) reanalysis in standard patient care in the Netherlands. Single-center data of 159 patients with a neurodevelopmental disorder (NDD), in which WES analysis and reanalysis were performed between January 1, 2014, and December 31, 2021, was retrospectively collected. Patients were included if they were under the age of 18 years at initial analysis and if this initial analysis did not result in a diagnosis. Demographic, phenotypic, and genotypic characteristics of patients were collected and analyzed. The primary outcomes of our study were (i) diagnostic yield at reanalysis, (ii) reasons for detecting a new possibly causal variant at reanalysis, (iii) unsolicited findings, and (iv) factors associated with positive result of reanalysis. In addition, we conducted a questionnaire study amongst the 7 genetic department in the Netherlands creating an overview of used techniques, yield, and organization of WES reanalysis. The single-center data show that in most cases, WES reanalysis was initiated by the clinical geneticist (65%) or treating physician (30%). The mean time between initial WES analysis and reanalysis was 3.7 years. A new (likely) pathogenic variant or VUS with a clear link to the phenotype was found in 20 initially negative cases, resulting in a diagnostic yield of 12.6%. In 75% of these patients, the diagnosis had clinical consequences, as for example, a screening plan for associated signs and symptoms could be devised. Most (32%) of the (likely) causal variants identified at WES reanalysis were discovered due to a newly described gene-disease association. In addition to the 12.6% diagnostic yield based on new diagnoses, reclassification of a variant of uncertain significance found at initial analysis led to a definite diagnosis in three patients. Diagnostic yield was higher in patients with dysmorphic features compared to patients without clear dysmorphic features (yield 27% vs. 6%; p = 0.001).

CONCLUSIONS

Our results show that WES reanalysis in patients with NDD in standard patient care leads to a substantial increase in genetic diagnoses. In the majority of newly diagnosed patients, the diagnosis had clinical consequences. Knowledge about the clinical impact of WES reanalysis, clinical characteristics associated with higher yield, and the yield per year after a negative WES in larger clinical cohorts is warranted to inform guidelines for genetic reanalysis. These guidelines will be of great value for pediatricians, pediatric rehabilitation specialists, and pediatric neurologists in daily care of patients with NDD.

WHAT IS KNOWN

• Whole exome sequencing can cost-effectively identify a genetic cause of intellectual disability in about 30-40% of patients. • WES reanalysis in a research setting can lead to a definitive diagnosis in 10-20% of previously exome negative cases.

WHAT IS NEW

• WES reanalysis in standard patient care resulted in a diagnostic yield of 13% in previously exome negative children with NDD. • The presence of dysmorphic features is associated with an increased diagnostic yield of WES reanalysis.

Relevance of next generation sequencing (NGS) data re-analysis in the diagnosis of monogenic diseases leading to organ failure

BACKGROUND

In 2018, our center started a program to offer genetic diagnosis to patients with kidney and liver monogenic rare conditions, potentially eligible for organ transplantation. We exploited a clinical exome sequencing approach, followed by analyses of in silico gene panels tailored to clinical suspicions, obtaining detection rates in line with what reported in literature. However, a percentage of patients remains without a definitive genetic diagnosis. This work aims to evaluate the utility of NGS data re-analysis for those patients with an inconclusive or negative genetic test at the time of first analysis considering that (i) the advance of alignment and variant calling processes progressively improve the detection rate, limiting false positives and false negatives; (ii) gene panels are periodically updated and (iii) variant annotation may change over time.

METHODS

114 patients, recruited between 2018 and 2020, with an inconclusive or negative NGS report at the time of first analysis, were included in the study. Re-alignment and variant calling of previously generated sequencing raw data were performed using the GenomSys Variant Analyzer software.

RESULTS

21 previously not reported potentially causative variants were identified in 20 patients. In most cases (n = 19), causal variants were retrieved out of the re-classification from likely benign to variants of unknown significance (VUS). In one case, the variant was included because of inclusion in the analysis of a newly disease-associated gene, not present in the original gene panel, and in another one due to the improved data alignment process. Whenever possible, variants were validated with Sanger sequencing and family segregation studies. As of now, 16 out of 20 patients have been analyzed and variants confirmed in 8 patients. Specifically, in two pediatric patients, causative variants were de novo mutations while in the others, the variant was present also in other affected relatives. In the remaining patients, variants were present also in non-affected parents, raising questions on their re-classification.

CONCLUSIONS

Overall, these data indicate that periodic and systematic re-analysis of negative or inconclusive NGS data reports can lead to new variant identification or reclassification in a small but significant proportion of cases, with benefits for patients' management.

An updated catalog of CTCF variants associated with neurodevelopmental disorder phenotypes

Introduction

CTCF-related disorder (CRD) is a neurodevelopmental disorder (NDD) caused by monoallelic pathogenic variants in CTCF. The first CTCF variants in CRD cases were documented in 2013. To date, 76 CTCF variants have been further described in the literature. In recent years, due to the increased application of next-generation sequencing (NGS), growing numbers of CTCF variants are being identified, and multiple genotype-phenotype databases cataloging such variants are emerging.

Methods

In this study, we aimed to expand the genotypic spectrum of CRD, by cataloging NDD phenotypes associated with reported CTCF variants. Here, we systematically reviewed all known CTCF variants reported in case studies and large-scale exome sequencing cohorts. We also conducted a meta-analysis using public variant data from genotype-phenotype databases to identify additional CTCF variants, which we then curated and annotated.

Results

From this combined approach, we report an additional 86 CTCF variants associated with NDD phenotypes that have not yet been described in the literature. Furthermore, we describe and explain inconsistencies in the quality of reported variants, which impairs the reuse of data for research of NDDs and other pathologies.

Discussion

From this integrated analysis, we provide a comprehensive and annotated catalog of all currently known CTCF mutations associated with NDD phenotypes, to aid diagnostic applications, as well as translational and basic research.

Genes4Epilepsy: An epilepsy gene resource

OBJECTIVE

"How many epilepsy genes are there?" is a frequently asked question. We sought to (1) provide a curated list of genes that cause monogenic epilepsies, and (2) compare and contrast epilepsy gene panels from multiple sources.

METHODS

We compared genes included on the epilepsy panels (as of July 29, 2022) of four clinical diagnostic providers: Invitae, GeneDx, Fulgent Genetics, and Blueprint Genetics; and two research resources: PanelApp Australia and ClinGen. A master list of all unique genes was supplemented by additional genes identified via PubMed searches up until August 15, 2022, using the search terms "genetics" AND/OR "epilepsy" AND/OR "seizures". Evidence supporting a monogenic role for all genes was manually reviewed; those with limited or disputed evidence were excluded. All genes were annotated according to inheritance pattern and broad epilepsy phenotype.

RESULTS

The comparison of genes included on epilepsy clinical panels revealed high heterogeneity in both number of genes (range: 144-511) and content. Just 111 genes (15.5%) were included on all four clinical panels. Subsequent manual curation of all "epilepsy genes" identified >900 monogenic etiologies. Almost 90% of genes were associated with developmental and epileptic encephalopathies. By comparison only 5% of genes were associated with monogenic causes of "common epilepsies" (i.e., generalized and focal epilepsy syndromes). Autosomal recessive genes were most frequent (56% of genes); however, this varied according to the associated epilepsy phenotype(s). Genes associated with common epilepsy syndromes were more likely to be dominantly inherited and associated with multiple epilepsy types.

SIGNIFICANCE

Our curated list of monogenic epilepsy genes is publicly available: github.com/bahlolab/genes4epilepsy and will be regularly updated. This gene resource can be utilized to target genes beyond those included on clinical gene panels, for gene enrichment methods and candidate gene prioritization. We invite ongoing feedback and contributions from the scientific community via genes4-epilepsy@unimelb.edu.au.

A concurrent dual analysis of genomic data augments diagnoses: Experiences of 2 clinical sites in the Undiagnosed Diseases Network

PURPOSE

Next-generation sequencing (NGS) has revolutionized the diagnostic process for rare/ultrarare conditions. However, diagnosis rates differ between analytical pipelines. In the National Institutes of Health-Undiagnosed Diseases Network (UDN) study, each individual's NGS data are concurrently analyzed by the UDN sequencing core laboratory and the clinical sites. We examined the outcomes of this practice.

METHODS

A retrospective review was performed at 2 UDN clinical sites to compare the variants and diagnoses/candidate genes identified with the dual analyses of the NGS data.

RESULTS

In total, 95 individuals had 100 diagnoses/candidate genes. There was 59% concordance between the UDN sequencing core laboratories and the clinical sites in identifying diagnoses/candidate genes. The core laboratory provided more diagnoses, whereas the clinical sites prioritized more research variants/candidate genes (P < .001). The clinical sites solely identified 15% of the diagnoses/candidate genes. The differences between the 2 pipelines were more often because of variant prioritization disparities than variant detection.

CONCLUSION

The unique dual analysis of NGS data in the UDN synergistically enhances outcomes. The core laboratory provided a clinical analysis with more diagnoses and the clinical sites prioritized more research variants/candidate genes. Implementing such concurrent dual analyses in other genomic research studies and clinical settings can improve both variant detection and prioritization.

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

PURPOSE

Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the "ClinVar low-hanging fruit" reanalysis, reasons for the failure of previous analyses, and lessons learned.

METHODS

Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted.

RESULTS

We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency).

CONCLUSION

The "ClinVar low-hanging fruit" analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock.

Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures

Epilepsy is a neurological disorder characterized by hypersynchronous recurrent neuronal activities and seizures, as well as loss of muscular control and sometimes awareness. Clinically, seizures have been reported to display daily variations. Conversely, circadian misalignment and circadian clock gene variants contribute to epileptic pathogenesis. Elucidation of the genetic bases of epilepsy is of great importance because the genetic variability of the patients affects the efficacies of antiepileptic drugs (AEDs). For this narrative review, we compiled 661 epilepsy-related genes from the PHGKB and OMIM databases and classified them into 3 groups: driver genes, passenger genes, and undetermined genes. We discuss the potential roles of some epilepsy driver genes based on GO and KEGG analyses, the circadian rhythmicity of human and animal epilepsies, and the mutual effects between epilepsy and sleep. We review the advantages and challenges of rodents and zebrafish as animal models for epileptic studies. Finally, we posit chronomodulated strategy-based chronotherapy for rhythmic epilepsies, integrating several lines of investigation for unraveling circadian mechanisms underpinning epileptogenesis, chronopharmacokinetic and chronopharmacodynamic examinations of AEDs, as well as mathematical/computational modeling to help develop time-of-day-specific AED dosing schedules for rhythmic epilepsy patients.

Genetic testing and counseling for the unexplained epilepsies: An evidence‐based practice guideline of the National Society of Genetic Counselors

Epilepsy, defined by the occurrence of two or more unprovoked seizures or one unprovoked seizure with a propensity for others, affects 0.64% of the population and can lead to significant morbidity and mortality. A majority of unexplained epilepsy (seizures not attributed to an acquired etiology, such as trauma or infection) is estimated to have an underlying genetic etiology. Despite rapid progress in understanding of the genetic underpinnings of the epilepsies, there are no recent evidence-based guidelines for genetic testing and counseling for this population. This practice guideline provides evidence-based recommendations for approaching genetic testing in the epilepsies using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision framework. We used evidence from a recent systematic evidence review and meta-analysis of diagnostic yield of genetic tests in patients with epilepsy. We also compiled data from other sources, including recently submitted conference abstracts and peer-reviewed journal articles. We identified and prioritized outcomes of genetic testing as critical, important or not important and based our recommendations on outcomes deemed critical and important. We considered the desirable and undesirable effects, value and acceptability to relevant stakeholders, impact on health equity, cost-effectiveness, certainty of evidence, and feasibility of the interventions in individuals with epilepsy. Taken together, we generated two clinical recommendations: (1) Genetic testing is strongly recommended for all individuals with unexplained epilepsy, without limitation of age, with exome/genome sequencing and/or a multi-gene panel (>25 genes) as first-tier testing followed by chromosomal microarray, with exome/genome sequencing conditionally recommended over multi-gene panel. (2) It is strongly recommended that genetic tests be selected, ordered, and interpreted by a qualified healthcare provider in the setting of appropriate pre-test and post-test genetic counseling. Incorporation of genetic counselors into neurology practices and/or referral to genetics specialists are both useful models for supporting providers without genetics expertise to implement these recommendations.

Case report: PLPHP deficiency, a rare but important cause of B6-responsive disorders: A report of three novel individuals and review of 51 cases

PLPHP (pyridoxal-phosphate homeostasis protein) deficiency is caused by biallelic pathogenic variants in PLPBP and is a rare cause of pyridoxine-responsive disorders. We describe three French-Canadian individuals with PLPHP deficiency, including one with unusual paroxysmal episodes lacking EEG correlation with a suspicious movement disorder, rarely reported in B6RDs. In addition, we review the clinical features and treatment responses of all 51 previously published individuals with PLPHP deficiency. Our case series underlines the importance of considering PLPBP mutations in individuals with partially B6-responsive seizures and highlights the presence of a founder effect in the French-Canadian population.

Precision medicine for genetic epilepsy on the horizon: Recent advances, present challenges, and suggestions for continued progress

The genetic basis of many epilepsies is increasingly understood, giving rise to the possibility of precision treatments tailored to specific genetic etiologies. Despite this, current medical therapy for most epilepsies remains imprecise, aimed primarily at empirical seizure reduction rather than targeting specific disease processes. Intellectual and technological leaps in diagnosis over the past 10 years have not yet translated to routine changes in clinical practice. However, the epilepsy community is poised to make impressive gains in precision therapy, with continued innovation in gene discovery, diagnostic ability, and bioinformatics; increased access to genetic testing and counseling; fuller understanding of natural histories; agility and rigor in preclinical research, including strategic use of emerging model systems; and engagement of an evolving group of stakeholders (including patient advocates, governmental resources, and clinicians and scientists in academia and industry). In each of these areas, we highlight notable examples of recent progress, new or persistent challenges, and future directions. The future of precision medicine for genetic epilepsy looks bright if key opportunities on the horizon can be pursued with strategic and coordinated effort.

Exploring the genetic etiology of drug-resistant epilepsy: incorporation of exome sequencing into practice

BACKGROUND

By affecting about 50 million people worldwide, epilepsy is considered a global concern in neurology. Intolerable enough, up to ¼ of all patients do not respond to antiepileptic drugs and have recurring seizures. Therefore, revealing the underlying etiology is quite demanding in a clinical context to improve diagnosis and disease management.

METHODS

Initially, 85 patients suspected of epilepsy underwent thorough clinical and paraclinical evaluation and 24 individuals with drug-resistant epilepsy entered the study. Using whole-exome sequencing, the genetic etiology of drug-resistant epilepsy was investigated and discerned whether this method could facilitate the management of drug-resistant epilepsy through personalized medicine. Eventually, functional annotation was performed and drug-gene interaction networks were constructed to find potential therapeutic targets.

RESULTS

We found eleven novel variants in various genes including IRF2BPL, ST3GAL3, and GPAA1, for which a few epilepsy-related variants are available in public databases. The overall diagnostic yield for likely pathogenic and pathogenic variants and the detection rate of novel variants were 25% and 84.6%, respectively. Based on the results, two patients were considered potential candidates for personalized medicine. The highest number of interaction with drugs was demonstrated for SCN1A, SCN2A, and GRIN2A genes.

CONCLUSIONS

This study highlighted the importance of consanguineous marriage in drug-resistant epilepsy and suggested the possibility of reduced penetrance and variable expressivity in some of the autosomal dominant cases. We also suggest that whole-exome sequencing could facilitate personalized management of drug-resistant epilepsy. Regarding drug-gene interactions, some genes such as SCN1A and SCN2A might serve as therapeutic targets in drug-resistant epilepsy.

Systematic analysis of inheritance pattern determination in genes that cause rare neurodevelopmental diseases

Despite recent advancements in our understanding of genetic etiology and its molecular and physiological consequences, it is not yet clear what genetic features determine the inheritance pattern of a disease. To address this issue, we conducted whole exome sequencing analysis to characterize genetic variants in 1,180 Korean patients with neurological symptoms. The diagnostic yield for definitive pathogenic variant findings was 50.8%, after including 33 cases (5.9%) additionally diagnosed by reanalysis. Of diagnosed patients, 33.4% carried inherited variants. At the genetic level, autosomal recessive-inherited genes were characterized by enrichments in metabolic process, muscle organization and metal ion homeostasis pathways. Transcriptome and interactome profiling analyses revealed less brain-centered expression and fewer protein-protein interactions for recessive genes. The majority of autosomal recessive genes were more tolerant of variation, and functional prediction scores of recessively-inherited variants tended to be lower than those of dominantly-inherited variants. Additionally, we were able to predict the rates of carriers for recessive variants. Our results showed that genes responsible for neurodevelopmental disorders harbor different molecular mechanisms and expression patterns according to their inheritance patterns. Also, calculated frequency rates for recessive variants could be utilized to pre-screen rare neurodevelopmental disorder carriers.

Recommendations for next generation sequencing data reanalysis of unsolved cases with suspected Mendelian disorders: A systematic review and meta-analysis

PURPOSE

The study aimed to determine the diagnostic yield, optimal timing, and methodology of next generation sequencing data reanalysis in suspected Mendelian disorders.

METHODS

We conducted a systematic review and meta-analysis of studies that conducted data reanalysis in patients with suspected Mendelian disorders. Random effects model was used to pool the estimated outcome with subgroup analysis stratified by timing, sequencing methodology, sample size, segregation, use of research validation, and artificial intelligence (AI) variant curation tools.

RESULTS

A search of PubMed, Embase, Scopus, and Web of Science between 2007 and 2021 yielded 9327 articles, of which 29 were selected. Significant heterogeneity was noted between studies. Reanalysis had an overall diagnostic yield of 0.10 (95% CI = 0.06-0.13). Literature updates accounted for most new diagnoses. Diagnostic yield was higher after 24 months, although this was not statistically significant. Increased diagnoses were obtained with research validation and data sharing. AI-based tools did not adversely affect reanalysis diagnostic rate.

CONCLUSION

Next generation sequencing data reanalysis can improve diagnostic yield. Owing to the heterogeneity of the studies, the optimal time to reanalysis and the impact of AI-based tools could not be determined with confidence. We propose standardized guidelines for future studies to reduce heterogeneity and improve the quality of the conclusions.

Re-analysis of genomic data: An overview of the mechanisms and complexities of clinical adoption

Re-analyzing genomic information from a patient suspected of having an underlying genetic condition can improve the diagnostic yield of sequencing tests, potentially providing significant benefits to the patient and to the health care system. Although a significant number of studies have shown the clinical potential of re-analysis, less work has been performed to characterize the mechanisms responsible for driving the increases in diagnostic yield. Complexities surrounding re-analysis have also emerged. The terminology itself represents a challenge because "re-analysis" can refer to a range of different concepts. Other challenges include the increased workload that re-analysis demands of curators, adequate reimbursement pathways for clinical and diagnostic services, and the development of systems to handle large volumes of data. Re-analysis also raises ethical implications for patients and families, most notably when re-classification of a variant alters diagnosis, treatment, and prognosis. This review highlights the possibilities and complexities associated with the re-analysis of existing clinical genomic data. We propose a terminology that builds on the foundation presented in a recent statement from the American College of Medical Genetics and Genomics and describes each re-analysis process. We identify mechanisms for increasing diagnostic yield and provide perspectives on the range of challenges that must be addressed by health care systems and individual patients.

Implications of Dosage Deficiencies in CTCF and Cohesin on Genome Organization, Gene Expression, and Human Neurodevelopment

Properly organizing DNA within the nucleus is critical to ensure normal downstream nuclear functions. CTCF and cohesin act as major architectural proteins, working in concert to generate thousands of high-intensity chromatin loops. Due to their central role in loop formation, a massive research effort has been dedicated to investigating the mechanism by which CTCF and cohesin create these loops. Recent results lead to questioning the direct impact of CTCF loops on gene expression. Additionally, results of controlled depletion experiments in cell lines has indicated that genome architecture may be somewhat resistant to incomplete deficiencies in CTCF or cohesin. However, heterozygous human genetic deficiencies in CTCF and cohesin have illustrated the importance of their dosage in genome architecture, cellular processes, animal behavior, and disease phenotypes. Thus, the importance of considering CTCF or cohesin levels is especially made clear by these heterozygous germline variants that characterize genetic syndromes, which are increasingly recognized in clinical practice. Defined primarily by developmental delay and intellectual disability, the phenotypes of CTCF and cohesin deficiency illustrate the importance of architectural proteins particularly in neurodevelopment. We discuss the distinct roles of CTCF and cohesin in forming chromatin loops, highlight the major role that dosage of each protein plays in the amplitude of observed effects on gene expression, and contrast these results to heterozygous mutation phenotypes in murine models and clinical patients. Insights highlighted by this comparison have implications for future research into these newly emerging genetic syndromes.

A Framework of Critical Considerations in Clinical Exome Reanalyses by Clinical and Laboratory Standards Institute

Exome reanalysis is useful for providing molecular diagnoses for previously uninformative samples. However, challenges exist in implementing a practical solution for clinicians and laboratories. This study complements the current literature by providing practical considerations for patient-level and cohort-level reanalyses. The Clinical and Laboratory Standards Institute assembled the Document Development Committee and an interpretation working group that developed the framework for reevaluation of exome-based data. We describe two distinct but complementary approaches toward exome reanalyses: clinician-initiated patient-level reanalysis, and laboratory-initiated cohort-level reanalysis. We highlight the advantages and constraints for both approaches, and provide a high-level conceptual guide for ordering clinicians and laboratories through the critical decision pathways. Because clinical exome sequencing continues to be the standard of care in genetics, exome reanalysis would be critical in increasing the overall diagnostic yield. A systematic guide will facilitate the efficient adoption of reevaluation of exome data for laboratories, health care professionals, genetic counselors, and clinicians.

Expanding the known phenotype of Mullegama-Klein-Martinez syndrome in male patients

Here, we report a novel case of a male patient with a hemizygous missense variant in STAG2 (p.Tyr159His) resulting in Mullegama–Klein–Martinez syndrome (MKMS), a rare X-linked cohesinopathy. He shares distinct clinical features with a previously reported male patient carrying the STAG2 variant p.Tyr159Cys, suggesting that this phenotype is determined by the position of the mutation. Additionally, our patient exhibits symptoms not previously associated with MKMS, expanding the known clinical phenotype of this rare disease.

Effective treatments for FGF12-related early-onset epileptic encephalopathies patients

BACKGROUND

FGF12 (FHF1) gene encodes voltage-gated sodium channel (Nav)-binding protein fibroblast growth factor homologous factor 1, which could cause seizures by regulating voltage dependence of Nav fast inactivation and neuron excitability. The most common pathogenic variant FGF12 c.341G > A related early-onset epileptic encephalopathies (EOEE) was characterized by intractable seizures and developmental disabilities.

RESULTS

Using whole exome sequencing, a de novo hotspot variant c.341G > A (NM_021032.4) of FGF12 was identified in three unrelated EOEE probands. All probands were seizure free after a combination treatment of valproic acid (VPA) and topiramate (TPM). The motor and cognitive skills in two probands were improved due to the early and effective treatment. In order to compare the effectiveness of different treatment strategies for the disease, a review of treatments for FGF12-related epilepsy was made.

CONCLUSION

We reported three FGF12 c.341G > A related EOEE patients responded well to a combination antiepileptic therapy of VPA and TPM. The current study is the first to describe the combination therapy of VPA and TPM in FGF12 c.341G > A related EOEE patients. This study may contribute to future medication consultation for intractable epilepsy with FGF12 hotspot variants.

Clinical Exome Reanalysis: Current Practice and Beyond

Novel gene-disease discoveries, rapid advancements in technology, and improved bioinformatics tools all have the potential to yield additional molecular diagnoses through the reanalysis of exome sequencing data. Collaborations between clinical laboratories, ordering physicians, and researchers are also driving factors that can contribute to these new insights. Automation in ongoing natural history collection, evolving phenotype updates, advancements in processing next-generation sequencing data, and up-to-date variant-gene-disease databases are increasingly needed for systematic exome reanalysis. Here, we review some of the advantages and challenges for clinician-initiated and laboratory-initiated exome reanalysis, and we propose a model for the future that could potentially maximize the clinical utility of exome reanalysis by integrating information from electronic medical records and knowledge databases into routine clinical workflows.

Paroxysmal Movement Disorders

Paroxysmal movement disorders (PxMDs) are a clinical and genetically heterogeneous group of movement disorders characterized by episodic involuntary movements (dystonia, dyskinesia, chorea and/or ataxia). Historically, PxMDs were classified clinically (triggers and characteristics of the movements) and this directed single-gene testing. With the advent of next-generation sequencing (NGS), how we classify and investigate PxMDs has been transformed. Next-generation sequencing has enabled new gene discovery (RHOBTB2, TBC1D24), expansion of phenotypes in known PxMDs genes and a better understanding of disease mechanisms. However, PxMDs exhibit phenotypic pleiotropy and genetic heterogeneity, making it challenging to predict genotype based on the clinical phenotype. For example, paroxysmal kinesigenic dyskinesia is most commonly associated with variants in PRRT2 but also variants identified in PNKD, SCN8A, and SCL2A1. There are no radiological or biochemical biomarkers to differentiate genetic causes. Even with NGS, diagnosis rates are variable, ranging from 11 to 51% depending on the cohort studied and technology employed. Thus, a large proportion of patients remain undiagnosed compared to other neurological disorders such as epilepsy, highlighting the need for further genomic research in PxMDs. Whole-genome sequencing, deep-sequencing, copy number variant analysis, detection of deep-intronic variants, mosaicism and repeat expansions, will improve diagnostic rates. Identifying the underlying genetic cause has a significant impact on patient care, modification of treatment, long-term prognostication and genetic counseling. This paper provides an update on the genetics of PxMDs, description of PxMDs classified according to causative gene rather than clinical phenotype, highlighting key clinical features and providing an algorithm for genetic testing of PxMDs.

Phenotypic analysis of catastrophic childhood epilepsy genes

Genetic engineering techniques have contributed to the now widespread use of zebrafish to investigate gene function, but zebrafish-based human disease studies, and particularly for neurological disorders, are limited. Here we used CRISPR-Cas9 to generate 40 single-gene mutant zebrafish lines representing catastrophic childhood epilepsies. We evaluated larval phenotypes using electrophysiological, behavioral, neuro-anatomical, survival and pharmacological assays. Local field potential recordings (LFP) were used to screen ∼3300 larvae. Phenotypes with unprovoked electrographic seizure activity (i.e., epilepsy) were identified in zebrafish lines for 8 genes; ARX, EEF1A, GABRB3, GRIN1, PNPO, SCN1A, STRADA and STXBP1. We also created an open-source database containing sequencing information, survival curves, behavioral profiles and representative electrophysiology data. We offer all zebrafish lines as a resource to the neuroscience community and envision them as a starting point for further functional analysis and/or identification of new therapies.

Griffin et al used CRISPR-Cas9 to generate 40 single-gene mutant zebrafish lines representing childhood epilepsies for which they evaluated larval phenotypes using electrophysiological, behavioral, neuro-anatomical, survival and pharmacological assays. Their study provides a useful resource for the future functional analysis and/or identification of potential anti-epileptic therapies.

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.

Challenges in Clinicogenetic Correlations: One Phenotype - Many Genes

Background

In the field of movement disorders, what you see (phenotype) is seldom what you get (genotype). Whereas 1 phenotype was previously associated to 1 gene, the advent of next‐generation sequencing (NGS) has facilitated an exponential increase in disease‐causing genes and genotype–phenotype correlations, and the “one‐phenotype‐many‐genes” paradigm has become prominent.

Objectives

To highlight the “one‐phenotype‐many‐genes” paradigm by discussing the main challenges, perspectives on how to address them, and future directions.

Methods

We performed a scoping review of the various aspects involved in identifying the underlying molecular cause of a movement disorder phenotype.

Results

The notable challenges are (1) the lack of gold standards, overlap in clinical spectrum of different movement disorders, and variability in the interpretation of classification systems; (2) selecting which patients benefit from genetic tests and the choice of genetic testing; (3) problems in the variant interpretation guidelines; (4) the filtering of variants associated with disease; and (5) the lack of standardized, complete, and up‐to‐date gene lists. Perspectives to address these include (1) deep phenotyping and genotype–phenotype integration, (2) adherence to phenotype‐specific diagnostic algorithms, (3) implementation of current and complementary bioinformatic tools, (4) a clinical‐molecular diagnosis through close collaboration between clinicians and genetic laboratories, and (5) ongoing curation of gene lists and periodic reanalysis of genetic sequencing data.

Conclusions

Despite the rapidly emerging possibilities of NGS, there are still many steps to take to improve the genetic diagnostic yield. Future directions, including post‐NGS phenotyping and cohort analyses enriched by genotype–phenotype integration and gene networks, ought to be pursued to accelerate identification of disease‐causing genes and further improve our understanding of disease biology.

Diagnostic Yield of Whole Genome Sequencing After Nondiagnostic Exome Sequencing or Gene Panel in Developmental and Epileptic Encephalopathies

OBJECTIVE

To assess the benefits and limitations of whole genome sequencing (WGS) compared to exome sequencing (ES) or multigene panel (MGP) in the molecular diagnosis of developmental and epileptic encephalopathies (DEE).

METHODS

We performed WGS of 30 comprehensively phenotyped DEE patient trios that were undiagnosed after first-tier testing, including chromosomal microarray and either research ES (n = 15) or diagnostic MGP (n = 15).

RESULTS

Eight diagnoses were made in the 15 individuals who received prior ES (53%): 3 individuals had complex structural variants; 5 had ES-detectable variants, which now had additional evidence for pathogenicity. Eleven diagnoses were made in the 15 MGP-negative individuals (68%); the majority (n = 10) involved genes not included in the panel, particularly in individuals with postneonatal onset of seizures and those with more complex presentations including movement disorders, dysmorphic features, or multiorgan involvement. A total of 42% of diagnoses were autosomal recessive or X-chromosome linked.

CONCLUSION

WGS was able to improve diagnostic yield over ES primarily through the detection of complex structural variants (n = 3). The higher diagnostic yield was otherwise better attributed to the power of re-analysis rather than inherent advantages of the WGS platform. Additional research is required to assist in the assessment of pathogenicity of novel noncoding and complex structural variants and further improve diagnostic yield for patients with DEE and other neurogenetic disorders.

Clinical Utility of Exome Sequencing and Reinterpreting Genetic Test Results in Children and Adults With Epilepsy

The clinical utility of genetic testing for epilepsy has been enhanced with the advancement of next-generation sequencing (NGS) technology along with the rapid updating of publicly available databases. The aim of this study was to evaluate the diagnostic yield of NGS and assess the value of reinterpreting genetic test results in children and adults with epilepsy. We performed genetic testing on 200 patients, including 82 children and 118 adults. The results were classified into three categories: positive, inconclusive, or negative. The reinterpretation of inconclusive results was conducted in April 2020. Overall, we identified disease-causing variants in 12% of the patients in the original analysis, and 14.5% at reinterpretation. The diagnostic yield for adults with epilepsy was similar to that for children (11 vs. 19.5%, p = 0.145). After reinterpretation, 9 of the 86 patients who initially had inconclusive results obtained a clinically significant change in diagnosis. Among these nine revised cases, five obtained positive diagnoses, representing a diagnosis rate of 5.8% (5/86). Manual searches for additional evidence of pathogenicity for candidate variants and updated patient clinical information were the main reasons for diagnostic reclassification. This study emphasizes the diagnostic potential of combining NGS and reinterpretation of inconclusive genetic test reports in children and adults with epilepsy.

Clinical sequencing yield in epilepsy, autism spectrum disorder, and intellectual disability: A systematic review and meta-analysis

Objective

Clinical genetic sequencing is frequently utilized to diagnose individuals with neurodevelopmental disorders (NDDs). Here we perform a meta‐analysis and systematic review of the success rate (diagnostic yield) of clinical sequencing through next‐generation sequencing (NGS) across NDDs. We compare the genetic testing yield across NDD subtypes and sequencing technology.

Methods

We performed a systematic review of the PubMed literature until May 2020. We included clinical sequencing studies that utilized NGS in individuals with epilepsy, autism spectrum disorder (ASD), or intellectual disability (ID). Data were extracted, reviewed, and categorized according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. Two investigators performed clinical evaluation and grouping following the International League Against Epilepsy (ILAE) guidelines. Pooled rates of the diagnostic yield and 95% confidence intervals were estimated with a random‐effects model.

Results

We identified 103 studies (epilepsy, N = 72; ASD, N = 14; ID, N = 21) across 32,331 individuals. Targeted gene panel sequencing was used in 73, and exome sequencing in 36 cohorts. Given highly selected patient cohorts, the diagnostic yield was 17.1% for ASD, 24% for epilepsy, and 28.2% for ID (23.7% overall). The highest diagnostic yield for epilepsy subtypes was observed in individuals with ID (27.9%) and early onset seizures (36.8%). The diagnostic yield for exome sequencing was higher than for panel sequencing, even though not statistically significant (27.2% vs 22.6%, P = .071). We observed that clinical sequencing studies are performed predominantly in countries with a high Inequality‐adjusted Human Development Index (IHDI) (countries with sequencing studies: IHDI median = 0.84, interquartile range [IQR] = 0.09 vs countries without sequencing studies: IHDI median = 0.56, IQR = 0.3). No studies from Africa, India, or Latin America were identified, indicating potential barriers to genetic testing.

Significance

This meta‐analysis and systematic review provides a comprehensive overview of clinical sequencing studies of NDDs and will help guide policymaking and steer decision‐making in patient management.

Evaluating systematic reanalysis of clinical genomic data in rare disease from single center experience and literature review

Background

Our primary aim was to evaluate the systematic reanalysis of singleton exome sequencing (ES) data for unsolved cases referred for any indication. A secondary objective was to undertake a literature review of studies examining the reanalysis of genomic data from unsolved cases.

Methods

We examined data from 58 unsolved cases referred between June 2016 and March 2017. First reanalysis at 4–13 months after the initial report considered genes newly associated with disease since the original analysis; second reanalysis at 9–18 months considered all disease‐associated genes. At 25–34 months we reviewed all cases and the strategies which solved them.

Results

Reanalysis of existing ES data alone at two timepoints did not yield new diagnoses. Over the same timeframe, 10 new diagnoses were obtained (17%) from additional strategies, such as microarray detection of copy number variation, repeat sequencing to improve coverage, and trio sequencing. Twenty‐seven peer‐reviewed articles were identified on the literature review, with a median new diagnosis rate via reanalysis of 15% and median reanalysis timeframe of 22 months.

Conclusion

Our findings suggest that an interval of greater than 18 months from the original report may be optimal for reanalysis. We also recommend a multi‐faceted strategy for cases remaining unsolved after singleton ES.

Nonsense variants of STAG2 result in distinct congenital anomalies

Herein, we report two female cases with novel nonsense mutations of STAG2 at Xq25, encoding stromal antigen 2, a component of the cohesion complex. Exome analysis identified c.3097 C>T, p.(Arg1033*) in Case 1 (a fetus with multiple congenital anomalies) and c.2229 G>A, p.(Trp743*) in Case 2 (a 7-year-old girl with white matter hypoplasia and cleft palate). X inactivation was highly skewed in both cases.

A three-year follow-up study evaluating clinical utility of exome sequencing and diagnostic potential of reanalysis

Exome sequencing (ES) has become one of the important diagnostic tools in clinical genetics with a reported diagnostic rate of 25–58%. Many studies have illustrated the diagnostic and immediate clinical impact of ES. However, up to 75% of individuals remain undiagnosed and there is scarce evidence supporting clinical utility beyond a follow-up period of >1 year. This is a 3-year follow-up analysis to our previous publication by Mak et al. (NPJ Genom. Med. 3:19, 2018), to evaluate the long-term clinical utility of ES and the diagnostic potential of exome reanalysis. The diagnostic yield of the initial study was 41% (43/104). Exome reanalysis in 46 undiagnosed individuals has achieved 12 new diagnoses. The additional yield compared with the initial analysis was at least 12% (increased from 41% to at least 53%). After a median follow-up period of 3.4 years, change in clinical management was observed in 72.2% of the individuals (26/36), leading to positive change in clinical outcome in four individuals (11%). There was a minimum healthcare cost saving of HKD$152,078 (USD$19,497; €17,282) annually for these four individuals. There were a total of six pregnancies from five families within the period. Prenatal diagnosis was performed in four pregnancies; one fetus was affected and resulted in termination. None of the parents underwent preimplantation genetic diagnosis. This 3-year follow-up study demonstrated the long-term clinical utility of ES at individual, familial and health system level, and the promising diagnostic potential of subsequent reanalysis. This highlights the benefits of implementing ES and regular reanalysis in the clinical setting.

Defining the phenotype of FHF1 developmental and epileptic encephalopathy

Fibroblast growth-factor homologous factor (FHF1) gene variants have recently been associated with developmental and epileptic encephalopathy (DEE). FHF1 encodes a cytosolic protein that modulates neuronal sodium channel gating. We aim to refine the electroclinical phenotypic spectrum of patients with pathogenic FHF1 variants. We retrospectively collected clinical, genetic, neurophysiologic, and neuroimaging data of 17 patients with FHF1-DEE. Sixteen patients had recurrent heterozygous FHF1 missense variants: 14 had the recurrent p.Arg114His variant and two had a novel likely pathogenic variant p.Gly112Ser. The p.Arg114His variant is associated with an earlier onset and more severe phenotype. One patient carried a chromosomal microduplication involving FHF1. Twelve patients carried a de novo variant, five (29.5%) inherited from parents with gonadic or somatic mosaicism. Seizure onset was between 1 day and 41 months; in 76.5% it was within 30 days. Tonic seizures were the most frequent seizure type. Twelve patients (70.6%) had drug-resistant epilepsy, 14 (82.3%) intellectual disability, and 11 (64.7%) behavioral disturbances. Brain magnetic resonance imaging (MRI) showed mild cerebral and/or cerebellar atrophy in nine patients (52.9%). Overall, our findings expand and refine the clinical, EEG, and imaging phenotype of patients with FHF1-DEE, which is characterized by early onset epilepsy with tonic seizures, associated with moderate to severe ID and psychiatric features.

Children's rare disease cohorts: an integrative research and clinical genomics initiative

While genomic data is frequently collected under distinct research protocols and disparate clinical and research regimes, there is a benefit in streamlining sequencing strategies to create harmonized databases, particularly in the area of pediatric rare disease. Research hospitals seeking to implement unified genomics workflows for research and clinical practice face numerous challenges, as they need to address the unique requirements and goals of the distinct environments and many stakeholders, including clinicians, researchers and sequencing providers. Here, we present outcomes of the first phase of the Children’s Rare Disease Cohorts initiative (CRDC) that was completed at Boston Children’s Hospital (BCH). We have developed a broadly sharable database of 2441 exomes from 15 pediatric rare disease cohorts, with major contributions from early onset epilepsy and early onset inflammatory bowel disease. All sequencing data is integrated and combined with phenotypic and research data in a genomics learning system (GLS). Phenotypes were both manually annotated and pulled automatically from patient medical records. Deployment of a genomically-ordered relational database allowed us to provide a modular and robust platform for centralized storage and analysis of research and clinical data, currently totaling 8516 exomes and 112 genomes. The GLS integrates analytical systems, including machine learning algorithms for automated variant classification and prioritization, as well as phenotype extraction via natural language processing (NLP) of clinical notes. This GLS is extensible to additional analytic systems and growing research and clinical collections of genomic and other types of data.

Clinical and Genetic Study on a Chinese Patient with Infantile Onset Epileptic Encephalopathy carrying a PPP3CA Null Variant: a case report

Background

PPP3CA gene encodes the catalytic subunit A of a calcium-dependent protein phosphatase called calcineurin. However, two distinct mechanisms in PPP3CA deficiency would cause two clinically different diseases. Gain-of-function mutations in the autoinhibitory domain at the C-terminus would cause ACCIID that stands for arthrogryposis, cleft palate, craniosynostosis and impaired intellectual development. While loss-of-function mutations in PPP3CA would cause infantile or early childhood onset epileptic encephalopathy1, named as IECEE1. IECEE1 is a severe epileptic neurodevelopmental disorder and mainly characterized by psychomotor delay. Here, we report a Chinese patient who was clinically and genetically diagnosed as IECEE1. We also extensively analyzed electroencephalogram (EEG) features of the patient in this study.

Case presentation

A 2-year-old Chinese patient who had recurrent polymorphic seizures was clinically and genetically diagnosed as IECEE1. A frameshift variant c.1283insC (p.T429NfsX22) was identified in this case. Multiple types of abnormal features were observed in the EEG, comparing with the previous reports.

Conclusions

These findings could expand the spectrum of PPP3CA mutations and might also support the diagnosis and further study of IECEE1.

Diagnostic exome sequencing in non-acquired focal epilepsies highlights a major role of GATOR1 complex genes

BACKGROUND

The genetic architecture of non-acquired focal epilepsies (NAFEs) becomes increasingly unravelled using genome-wide sequencing datasets. However, it remains to be determined how this emerging knowledge can be translated into a diagnostic setting. To bridge this gap, we assessed the diagnostic outcomes of exome sequencing (ES) in NAFE.

METHODS

112 deeply phenotyped patients with NAFE were included in the study. Diagnostic ES was performed, followed by a screen to detect variants of uncertain significance (VUSs) in 15 well-established focal epilepsy genes. Explorative gene prioritisation was used to identify possible novel candidate aetiologies with so far limited evidence for NAFE.

RESULTS

ES identified pathogenic or likely pathogenic (ie, diagnostic) variants in 13/112 patients (12%) in the genes DEPDC5, NPRL3, GABRG2, SCN1A, PCDH19 and STX1B. Two pathogenic variants were microdeletions involving NPRL3 and PCDH19. Nine of the 13 diagnostic variants (69%) were found in genes of the GATOR1 complex, a potentially druggable target involved in the mammalian target of rapamycin (mTOR) signalling pathway. In addition, 17 VUSs in focal epilepsy genes and 6 rare variants in candidate genes (MTOR, KCNA2, RBFOX1 and SCN3A) were detected. Five patients with reported variants had double hits in different genes, suggesting a possible (oligogenic) role of multiple rare variants.

CONCLUSION

This study underscores the molecular heterogeneity of NAFE with GATOR1 complex genes representing the by far most relevant genetic aetiology known to date. Although the diagnostic yield is lower compared with severe early-onset epilepsies, the high rate of VUSs and candidate variants suggests a further increase in future years.

Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort

OBJECTIVE

We evaluated the yield of systematic analysis and/or reanalysis of whole exome sequencing (WES) data from a cohort of well-phenotyped pediatric patients with epilepsy and suspected but previously undetermined genetic etiology.

METHODS

We identified and phenotyped 125 participants with pediatric epilepsy. Etiology was unexplained at the time of enrollment despite clinical testing, which included chromosomal microarray (57 patients), epilepsy gene panel (n = 48), both (n = 28), or WES (n = 8). Clinical epilepsy diagnoses included developmental and epileptic encephalopathy (DEE), febrile infection-related epilepsy syndrome, Rasmussen encephalitis, and other focal and generalized epilepsies. We analyzed WES data and compared the yield in participants with and without prior clinical genetic testing.

RESULTS

Overall, we identified pathogenic or likely pathogenic variants in 40% (50/125) of our study participants. Nine patients with DEE had genetic variants in recently published genes that had not been recognized as epilepsy-related at the time of clinical testing (FGF12, GABBR1, GABBR2, ITPA, KAT6A, PTPN23, RHOBTB2, SATB2), and eight patients had genetic variants in candidate epilepsy genes (CAMTA1, FAT3, GABRA6, HUWE1, PTCHD1). Ninety participants had concomitant or subsequent clinical genetic testing, which was ultimately explanatory for 26% (23/90). Of the 67 participants whose molecular diagnoses were "unsolved" through clinical genetic testing, we identified pathogenic or likely pathogenic variants in 17 (25%).

SIGNIFICANCE

Our data argue for early consideration of WES with iterative reanalysis for patients with epilepsy, particularly those with DEE or epilepsy with intellectual disability. Rigorous analysis of WES data of well-phenotyped patients with epilepsy leads to a broader understanding of gene-specific phenotypic spectra as well as candidate disease gene identification. We illustrate the dynamic nature of genetic diagnosis over time, with analysis and in some cases reanalysis of exome data leading to the identification of disease-associated variants among participants with previously nondiagnostic results from a variety of clinical testing strategies.

Epidemiology and etiology of infantile developmental and epileptic encephalopathies in Tasmania

We sought to determine incidence, etiologies, and yield of genetic testing in infantile onset developmental and epileptic encephalopathies (DEEs) in a population isolate, with an intensive multistage approach. Infants born in Tasmania between 2011 and 2016, with seizure onset <2 years of age, epileptiform EEG, frequent seizures, and developmental impairment, were included. Following review of EEG databases, medical records, brain MRIs, and other investigations, clinical genetic testing was undertaken with subsequent research interrogation of whole exome sequencing (WES) in unsolved cases. The incidence of infantile DEEs was 0.44/1000 per year (95% confidence interval 0.25 to 0.71), with 16 cases ascertained. The etiology was structural in 5/16 cases. A genetic basis was identified in 6 of the remaining 11 cases (3 gene panel, 3 WES). In two further cases, WES identified novel variants with strong in silico data; however, paternal DNA was not available to support pathogenicity. The etiology was not determined in 3/16 (19%) cases, with a candidate gene identified in one of these. Pursuing clinical imaging and genetic testing followed by WES at an intensive research level can give a high diagnostic yield in the infantile DEEs, providing a solid base for prognostic and genetic counseling.

The Epilepsy Genetics Initiative: Systematic reanalysis of diagnostic exomes increases yield

OBJECTIVE

The Epilepsy Genetics Initiative (EGI) was formed in 2014 to create a centrally managed database of clinically generated exome sequence data. EGI performs systematic research-based reanalysis to identify new molecular diagnoses that were not possible at the time of initial sequencing and to aid in novel gene discovery. Herein we report on the efficacy of this approach 3 years after inception.

METHODS

One hundred sixty-six individuals with epilepsy who underwent diagnostic whole exome sequencing (WES) were enrolled, including 139 who had not received a genetic diagnosis. Sequence data were transferred to the EGI and periodically reevaluated on a research basis.

RESULTS

Eight new diagnoses were made as a result of updated annotations or the discovery of novel epilepsy genes after the initial diagnostic analysis was performed. In five additional cases, we provided new evidence to support or contradict the likelihood of variant pathogenicity reported by the laboratory. One novel epilepsy gene was discovered through dual interrogation of research and clinically generated WES.

SIGNIFICANCE

EGI's diagnosis rate of 5.8% represents a considerable increase in diagnostic yield and demonstrates the value of periodic reinterrogation of whole exome data. The initiative's contributions to gene discovery underscore the importance of data sharing and the value of collaborative enterprises.