Genes4Epilepsy: An epilepsy gene resource

Developmental and epileptic encephalopathies

Developmental and epileptic encephalopathies, the most severe group of epilepsies, are characterized by seizures and frequent epileptiform activity associated with developmental slowing or regression. Onset typically occurs in infancy or childhood and includes many well-defined epilepsy syndromes. Patients have wide-ranging comorbidities including intellectual disability, psychiatric features, such as autism spectrum disorder and behavioural problems, movement and musculoskeletal disorders, gastrointestinal and sleep problems, together with an increased mortality rate. Problems change with age and patients require substantial support throughout life, placing a high psychosocial burden on parents, carers and the community. In many patients, the aetiology can be identified, and a genetic cause is found in >50% of patients using next-generation sequencing technologies. More than 900 genes have been identified as monogenic causes of developmental and epileptic encephalopathies and many cell components and processes have been implicated in their pathophysiology, including ion channels and transporters, synaptic proteins, cell signalling and metabolism and epigenetic regulation. Polygenic risk score analyses have shown that common variants also contribute to phenotypic variability. Holistic management, which encompasses antiseizure therapies and care for multimorbidities, is determined both by epilepsy syndrome and aetiology. Identification of the underlying aetiology enables the development of precision medicines to improve the long-term outcome of patients with these devastating diseases.

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.

Utility of Genome Sequencing After Nondiagnostic Exome Sequencing in Unexplained Pediatric Epilepsy

Importance

Epilepsy is the most common neurological disorder of childhood. Identifying genetic diagnoses underlying epilepsy is critical to developing effective therapies and improving outcomes. Most children with non-acquired (unexplained) epilepsy remain genetically unsolved, and the utility of genome sequencing after nondiagnostic exome sequencing is unknown.

Objective

To determine the diagnostic (primary) and clinical (secondary) utility of genome sequencing after nondiagnostic exome sequencing in individuals with unexplained pediatric epilepsy.

Design

This cohort study performed genome sequencing and comprehensive analyses for 125 participants and available biological parents enrolled from August 2018 to May 2023, with data analysis through April 2024 and clinical return of diagnostic and likely diagnostic genetic findings. Clinical utility was evaluated.

Setting

Pediatric referral center.

Participants

Participants with unexplained pediatric epilepsy and previous nondiagnostic exome sequencing; biological parents when available.

Exposures

Short-read genome sequencing and analysis.

Main Outcomes and Measures

Primary outcome measures were the diagnostic yield of genome sequencing, defined as the percentage of participants receiving a diagnostic or likely diagnostic genetic finding, and the unique diagnostic yield of genome sequencing, defined as the percentage of participants receiving a diagnostic or likely diagnostic genetic finding that required genome sequencing. The secondary outcome measure was clinical utility of genome sequencing, defined as impact on evaluation, treatment, or prognosis for the participant or their family.

Results

125 participants (58 [46%] female) were enrolled with median age at seizure onset 3 [IQR 1.25, 8] years, including 44 (35%) with developmental and epileptic encephalopathies. The diagnostic yield of genome sequencing was 7.2% (9/125), with diagnostic genetic findings in five cases and likely diagnostic genetic findings in four cases. Among the solved cases, 7/9 (78%) required genome sequencing for variant detection (small copy number variant, three noncoding variants, and three difficult to sequence small coding variants), for a unique diagnostic yield of genome sequencing of 5.6% (7/125). Clinical utility was documented for 4/9 solved cases (44%).

Conclusions and Relevance

These findings suggest that genome sequencing can have diagnostic and clinical utility after nondiagnostic exome sequencing and should be considered for patients with unexplained pediatric epilepsy.

Diagnostic utility of DNA methylation analysis in genetically unsolved pediatric epilepsies and CHD2 episignature refinement

Sequence-based genetic testing identifies causative variants in ~ 50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. We interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 582 individuals with genetically unsolved DEEs. We identify rare differentially methylated regions (DMRs) and explanatory episignatures to uncover causative and candidate genetic etiologies in 12 individuals. Using long-read sequencing, we identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and four copy number variants. We also identify pathogenic variants associated with episignatures. Finally, we refine the CHD2 episignature using an 850 K methylation array and bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate variants as 2% (12/582) for unsolved DEE cases.

Solving the Etiology of Developmental and Epileptic Encephalopathy with Spike-Wave Activation in Sleep (D/EE-SWAS)

OBJECTIVE

To understand the etiological landscape and phenotypic differences between 2 developmental and epileptic encephalopathy (DEE) syndromes: DEE with spike-wave activation in sleep (DEE-SWAS) and epileptic encephalopathy with spike-wave activation in sleep (EE-SWAS).

METHODS

All patients fulfilled International League Against Epilepsy (ILAE) DEE-SWAS or EE-SWAS criteria with a Core cohort (n = 91) drawn from our Epilepsy Genetics research program, together with 10 etiologically solved patients referred by collaborators in the Expanded cohort (n = 101). Detailed phenotyping and analysis of molecular genetic results were performed. We compared the phenotypic features of individuals with DEE-SWAS and EE-SWAS. Brain-specific gene co-expression analysis was performed for D/EE-SWAS genes.

RESULTS

We identified the etiology in 42/91 (46%) patients in our Core cohort, including 29/44 (66%) with DEE-SWAS and 13/47 (28%) with EE-SWAS. A genetic etiology was identified in 31/91 (34%). D/EE-SWAS genes were highly co-expressed in brain, highlighting the importance of channelopathies and transcriptional regulators. Structural etiologies were found in 12/91 (13%) individuals. We identified 10 novel D/EE-SWAS genes with a range of functions: ATP1A2, CACNA1A, FOXP1, GRIN1, KCNMA1, KCNQ3, PPFIA3, PUF60, SETD1B, and ZBTB18, and 2 novel copy number variants, 17p11.2 duplication and 5q22 deletion. Although developmental regression patterns were similar in both syndromes, DEE-SWAS was associated with a longer duration of epilepsy and poorer intellectual outcome than EE-SWAS.

INTERPRETATION

DEE-SWAS and EE-SWAS have highly heterogeneous genetic and structural etiologies. Phenotypic analysis highlights valuable clinical differences between DEE-SWAS and EE-SWAS which inform clinical care and prognostic counseling. Our etiological findings pave the way for the development of precision therapies. ANN NEUROL 2024.

Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events

A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 700k Finns and Estonians. We found that a high genetic generalized epilepsy PRS (PRSGGE) increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.73 per PRSGGE standard deviation [SD]) across lifetime and within 10 years after an unspecified seizure event. The effect of PRSGGE was significantly larger on idiopathic generalized epilepsies, in females and for earlier epilepsy onset. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). Here, we outline the potential of epilepsy specific PRSs to serve as biomarkers after a first seizure event.

Knockdown of NeuroD2 leads to seizure-like behavior, brain neuronal hyperactivity and a leaky blood-brain barrier in a Xenopus laevis tadpole model of DEE75

Developmental and Epileptic Encephalopathies (DEE) are a genetically diverse group of severe, early onset seizure disorders. DEE are normally identified clinically in the first six months of life by the presence of frequent, difficult to control seizures and accompanying stalling or regression of development. DEE75 results from de novo mutations of the NEUROD2 gene that result in loss of activity of the encoded transcription factor, and the seizure phenotype was shown to be recapitulated in Xenopus tropicalis tadpoles. We used CRISPR/Cas9 to make a DEE75 model in Xenopus laevis, to further investigate the developmental etiology. NeuroD2.S CRISPR/Cas9 edited tadpoles were more active, swam faster on average, and had more seizures (C-shaped contractions resembling unprovoked C-start escape responses) than their sibling controls. Live imaging of Ca2+ signaling revealed prolongued, strong signals sweeping through the brain, indicative of neuronal hyperactivity. While the resulting tadpole brain appeared grossly normal, the blood-brain barrier (BBB) was found to be leakier than that of controls. Additionally, the TGFβ antagonist Losartan was shown to have a short-term protective effect, reducing neuronal hyperactivity and reducing permeability of the BBB. Treatment of NeuroD2 CRISPant tadpoles with 5 mM Losartan decreased seizure events by more than 4-fold compared to the baseline. Our results support a model of DEE75 resulting from reduced NeuroD2 activity during vertebrate brain development, and indicate that a leaky BBB contributes to epileptogenesis.

Burden re-analysis of neurodevelopmental disorder cohorts for prioritization of candidate genes

This study aimed to uncover novel genes associated with neurodevelopmental disorders (NDD) by leveraging recent large-scale de novo burden analysis studies to enhance a virtual gene panel used in a diagnostic setting. We re-analyzed historical trio-exome sequencing data from 745 individuals with NDD according to the most recent diagnostic standards, resulting in a cohort of 567 unsolved individuals. Next, we designed a virtual gene panel containing candidate genes from three large de novo burden analysis studies in NDD and prioritized candidate genes by stringent filtering for ultra-rare de novo variants with high pathogenicity scores. Our analysis revealed an increased burden of de novo variants in our selected candidate genes within the unsolved NDD cohort and identified qualifying de novo variants in seven candidate genes: RIF1, CAMK2D, RAB11FIP4, AGO3, PCBP2, LEO1, and VCP. Clinical data were collected from six new individuals with de novo or inherited LEO1 variants and three new individuals with de novo PCBP2 variants. Our findings add additional evidence for LEO1 as a risk gene for autism and intellectual disability. Furthermore, we prioritize PCBP2 as a candidate gene for NDD associated with motor and language delay. In summary, by leveraging de novo burden analysis studies, employing a stringent variant filtering pipeline, and engaging in targeted patient recruitment, our study contributes to the identification of novel genes implicated in NDDs.

Current challenges in focal epilepsy treatment: An Italian Delphi consensus

BACKGROUND

Epilepsy, a globally prevalent neurological condition, presents distinct challenges in management, particularly for focal-onset types. This study aimed at addressing the current challenges and perspectives in focal epilepsy management, with focus on the Italian reality.

METHODS

Using the Delphi methodology, this research collected and analyzed the level of consensus of a panel of Italian epilepsy experts on key aspects of focal epilepsy care. Areas of focus included patient flow, treatment pathways, controlled versus uncontrolled epilepsy, follow-up protocols, and the relevance of patient-reported outcomes (PROs). This method allowed for a comprehensive assessment of consensus and divergences in clinical opinions and practices.

RESULTS

The study achieved consensus on 23 out of 26 statements, with three items failing to reach a consensus. There was strong agreement on the importance of timely intervention, individualized treatment plans, regular follow-ups at Epilepsy Centers, and the role of PROs in clinical practice. In cases of uncontrolled focal epilepsy, there was a clear inclination to pursue alternative treatment options following the failure of two previous therapies. Divergent views were evident on the inclusion of epilepsy surgery in treatment for uncontrolled epilepsy and the routine necessity of EEG evaluations in follow-ups. Other key findings included concerns about the lack of pediatric-specific research limiting current therapeutic options in this patient population, insufficient attention to the transition from pediatric to adult care, and need for improved communication. The results highlighted the complexities in managing epilepsy, with broad consensus on patient care aspects, yet notable divergences in specific treatment and management approaches.

CONCLUSION

The study offered valuable insights into the current state and complexities of managing focal-onset epilepsy. It highlighted many deficiencies in the therapeutic pathway of focal-onset epilepsy in the Italian reality, while it also underscored the importance of patient-centric care, the necessity of early and appropriate intervention, and individualized treatment approaches. The findings also called for continued research, policy development, and healthcare system improvements to enhance epilepsy management, highlighting the ongoing need for tailored healthcare solutions in this evolving field.

Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology

Background and Objectives

Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences.

Methods

We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples.

Results

The epilepsies (2.4 k-2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples.

Discussion

Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies.

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.

Leveraging multiple approaches for the detection of pathogenic deep intronic variants in developmental and epileptic encephalopathies: A case report

About 50% of individuals with developmental and epileptic encephalopathies (DEEs) are unsolved following genetic testing. Deep intronic variants, defined as >100 bp from exon-intron junctions, contribute to disease by affecting the splicing of mRNAs in clinically relevant genes. Identifying deep intronic pathogenic variants is challenging and resource intensive, and interpretation is difficult due to limited functional annotations. We aimed to identify deep intronic variants in individuals suspected to have unsolved single gene DEEs. In a research cohort of unsolved cases of DEEs, we searched for children with a DEE syndrome predominantly caused by variants in specific genes in >80% of described cases. We identified two children with Dravet syndrome and one individual with classic lissencephaly. Multiple sequencing and bioinformatics strategies were employed to interrogate intronic regions in SCN1A and PAFAH1B1. A novel de novo deep intronic 12 kb deletion in PAFAH1B1 was identified in the individual with lissencephaly. We showed experimentally that the deletion disrupts mRNA splicing, which results in partial intron retention after exon 2 and disruption of the highly conserved LisH motif. We demonstrate that targeted interrogation of deep intronic regions using multiple genomics technologies, coupled with functional analysis, can reveal hidden causes of unsolved monogenic DEE syndromes. PLAIN LANGUAGE SUMMARY: Deep intronic variants can cause disease by affecting the splicing of mRNAs in clinically relevant genes. A deep intronic deletion that caused abnormal splicing of the PAFAH1B1 gene was identified in a patient with classic lissencephaly. Our findings reinforce that targeted interrogation of deep intronic regions and functional analysis can reveal hidden causes of unsolved epilepsy syndromes.

Unraveling the shared genetics of common epilepsies and general cognitive ability

Objective

Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG).

Methods

We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), and as well as specific subtypes. We functionally annotated the identified loci using a variety of biological resources and validated the results in independent samples.

Results

Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 1.0 × 10-14; 'all epilepsy': p = 5.6 × 10-3).

Significance

Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

The impact of microbiota and ketogenic diet interventions in the management of drug-resistant epilepsy

AIM

Drug-resistant epilepsy (DRE) is a neurological disorder characterized by uncontrolled seizures. It affects between 10%-40% of the patients with epilepsy worldwide. Drug-resistant patients have been reported to have a different microbiota composition compared to drug-sensitive patients and healthy controls. Importantly, fecal microbiota transplantations (FMTs), probiotic and dietary interventions have been shown to be able to reduce seizure frequency and improve the quality of life in drug-resistant patients. The classic ketogenic diet (KD) and its modifications may reduce seizures in DRE in some patients, whereas in others they do not. The mechanisms mediating the dietary effects remain elusive, although it is known that gut microbes play an important role in transmitting dietary effects to the host. Indeed, specific commensal microbes differ even between responders and non-responders to KD treatment.

METHODS

In this narrative mini-review, we summarize what is known about the gut microbiota changes and ketogenic diets with special focus on patients with DRE.

RESULTS AND CONCLUSIONS

By highlighting unanswered questions and by suggesting future research directions, we map the route towards future improvement of successful DRE therapy.

Epilepsy-associated genes: an update

PURPOSE

To provide an updated list of epilepsy-associated genes based on clinical-genetic evidence.

METHODS

Epilepsy-associated genes were systematically searched and cross-checked from the OMIM, HGMD, and PubMed databases up to July 2023. To facilitate the reference for the epilepsy-associated genes that are potentially common in clinical practice, the epilepsy-associated genes were ranked by the mutation number in the HGMD database and by case number in the China Epilepsy Gene 1.0 project, which targeted common epilepsy.

RESULTS

Based on the OMIM database, 1506 genes were identified to be associated with epilepsy and were classified into three categories according to their potential association with epilepsy or other abnormal phenotypes, including 168 epilepsy genes that were associated with epilepsies as pure or core symptoms, 364 genes that were associated with neurodevelopmental disorders as the main symptom and epilepsy, and 974 epilepsy-related genes that were associated with gross physical/systemic abnormalities accompanied by epilepsy/seizures. Among the epilepsy genes, 115 genes (68.5%) were associated with epileptic encephalopathy. After cross-checking with the HGMD and PubMed databases, an additional 1440 genes were listed as potential epilepsy-associated genes, of which 278 genes have been repeatedly identified variants in patients with epilepsy. The top 100 frequently reported/identified epilepsy-associated genes from the HGMD database and the China Epilepsy Gene 1.0 project were listed, among which 40 genes were identical in both sources.

SIGNIFICANCE

Recognition of epilepsy-associated genes will facilitate genetic screening strategies and be helpful for precise molecular diagnosis and treatment of epilepsy in clinical practice.

Genetic Advancements in Infantile Epileptic Spasms Syndrome and Opportunities for Precision Medicine

Infantile epileptic spasms syndrome (IESS) is a devastating developmental epileptic encephalopathy (DEE) consisting of epileptic spasms, as well as one or both of developmental regression or stagnation and hypsarrhythmia on EEG. A myriad of aetiologies are associated with the development of IESS; broadly, 60% of cases are thought to be structural, metabolic or infectious in nature, with the remainder genetic or of unknown cause. Epilepsy genetics is a growing field, and over 28 copy number variants and 70 single gene pathogenic variants related to IESS have been discovered to date. While not exhaustive, some of the most commonly reported genetic aetiologies include trisomy 21 and pathogenic variants in genes such as TSC1, TSC2, CDKL5, ARX, KCNQ2, STXBP1 and SCN2A. Understanding the genetic mechanisms of IESS may provide the opportunity to better discern IESS pathophysiology and improve treatments for this condition. This narrative review presents an overview of our current understanding of IESS genetics, with an emphasis on animal models of IESS pathogenesis, the spectrum of genetic aetiologies of IESS (i.e., chromosomal disorders, single-gene disorders, trinucleotide repeat disorders and mitochondrial disorders), as well as available genetic testing methods and their respective diagnostic yields. Future opportunities as they relate to precision medicine and epilepsy genetics in the treatment of IESS are also explored.

Integrative analysis of epilepsy-associated genes reveals expression-phenotype correlations

Epilepsy is a highly prevalent neurological disorder characterized by recurrent seizures. Patients exhibit broad genetic, molecular, and clinical diversity involving mild to severe comorbidities. The factors that contribute to this phenotypic diversity remain unclear. Here we used publicly available datasets to systematically interrogate the expression pattern of 230 epilepsy-associated genes across human tissues, developmental stages, and central nervous system (CNS) cellular subtypes. We grouped genes based on their curated phenotypes into 3 broad classes: core epilepsy genes (CEG), where seizures are the dominant phenotype, developmental and epileptic encephalopathy genes (DEEG) that are associated with developmental and epileptic encephalopathy, and seizure-related genes (SRG), which are characterized by the presence of seizures and gross brain malformations. We find that compared to the other two groups of genes, DEEGs are highly expressed within the adult CNS, exhibit the highest and most dynamic expression in various brain regions across development, and are significantly enriched in GABAergic neurons. Our analysis provides an overview of the expression pattern of epilepsy-associated genes with spatiotemporal resolution and establishes a broad expression-phenotype correlation in epilepsy.

Identification of potential disease-associated variants in idiopathic generalized epilepsy using targeted sequencing

Many questions remain regarding the genetics of idiopathic generalized epilepsy (IGE), a subset of genetic generalized epilepsy (GGE). We aimed to identify the candidate coding variants of epilepsy panel genes in a cohort of affected individuals, using variant frequency information from a control cohort of the same region. We performed whole-exome sequencing analysis of 121 individuals and 10 affected relatives, focusing on variants of 950 candidate genes associated with epilepsy according to the Genes4Epilepsy curated panel. We identified 168 candidate variants (CVs) in 137 of 950 candidate genes in 88 of 121 affected individuals with IGE, of which 61 were novel variants. Notably, we identified five CVs in known GGE-associated genes (CHD2, GABRA1, RORB, SCN1A, and SCN1B) in five individuals and CVs shared by affected individuals in each of four family cases for other epilepsy candidate genes. The results of this study demonstrate that IGE is a disease with high heterogeneity and provide IGE-associated CVs whose pathogenicity should be proven by future studies, including advanced functional analysis. The low detection rate of CVs in the GGE-associated genes (4.1%) in this study suggests the current incompleteness of the Genes4Epilepsy panel for the diagnosis of IGE in clinical practice.

Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events

A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 360k Finns spanning up to 50 years of individuals' lifetimes. Individuals with a high genetic generalized epilepsy PRS (PRSGGE) in FinnGen had an increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.55 per PRSGGE standard deviation [SD]) across their lifetime and after unspecified seizure events. Effect sizes of epilepsy PRSs were comparable to effect sizes in clinically curated data supporting our EHR-derived epilepsy diagnoses. Within 10 years after an unspecified seizure, the GGE rate was 37% when PRSGGE > 2 SD compared to 5.6% when PRSGGE < -2 SD. The effect of PRSGGE was even larger on GGE subtypes of idiopathic generalized epilepsy (IGE) (HR 2.1 per SD PRSGGE). We further report significantly larger effects of PRSGGE on epilepsy in females and in younger age groups. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). We found PRSGGE specifically associated with GGE in comparison with >2000 independent diseases while PRSNAFE was also associated with other diseases than NAFE such as back pain. Here, we show that epilepsy specific PRSs have good discriminative ability after a first seizure event i.e. in circumstances where the prior probability of epilepsy is high outlining a potential to serve as biomarkers for an epilepsy diagnosis.

Movement Disorders in Patients With Genetic Developmental and Epileptic Encephalopathies

BACKGROUND AND OBJECTIVES

Movement disorders (MDs) are underrecognized in the developmental and epileptic encephalopathies (DEEs). There are now more than 800 genes implicated in causing the DEEs; relatively few of these rare genetic diseases are known to be associated with MDs. We identified patients with genetic DEEs who had MDs, classified the nature of their MDs, and asked whether specific patterns correlated with the underlying mechanism.

METHODS

We classified the type of MDs associated with specific genetic DEEs in a large international cohort of patients and analyzed whether specific patterns of MDs reflected the underlying biological dysfunction.

RESULTS

Our cohort comprised 77 patients with a genetic DEE with a median age of 9 (range 1-38) years. Stereotypies (37/77, 48%) and dystonia (34/77, 44%) were the most frequent MDs, followed by chorea (18/77, 23%), myoclonus (14/77, 18%), ataxia (9/77, 12%), tremor (7/77, 9%), and hypokinesia (6/77, 8%). In 47% of patients, a combination of MDs was seen. The MDs were first observed at a median age of 18 months (range day 2-35 years). Dystonia was more likely to be observed in nonambulatory patients, while ataxia was less likely. In 46% of patients, therapy was initiated with medication (34/77, 44%), deep brain stimulation (1/77, 1%), or intrathecal baclofen (1/77, 1%). We found that patients with channelopathies or synaptic vesicle trafficking defects were more likely to experience dystonia; whereas, stereotypies were most frequent in individuals with transcriptional defects.

DISCUSSION

MDs are often underrecognized in patients with genetic DEEs, but recognition is critical for the management of these complex neurologic diseases. Distinguishing MDs from epileptic seizures is important in tailoring patient treatment. Understanding which MDs occur with different biological mechanisms will inform early diagnosis and management.

Diagnostic Utility of Genome-wide DNA Methylation Analysis in Genetically Unsolved Developmental and Epileptic Encephalopathies and Refinement of a CHD2 Episignature

Sequence-based genetic testing currently identifies causative genetic variants in ∼50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. Rare epigenetic variations ("epivariants") can drive disease by modulating gene expression at single loci, whereas genome-wide DNA methylation changes can result in distinct "episignature" biomarkers for monogenic disorders in a growing number of rare diseases. Here, we interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 516 individuals with genetically unsolved DEEs who had previously undergone extensive genetic testing. We identified rare differentially methylated regions (DMRs) and explanatory episignatures to discover causative and candidate genetic etiologies in 10 individuals. We then used long-read sequencing to identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and two copy number variants. We also identify pathogenic sequence variants associated with episignatures; some had been missed by previous exome sequencing. Although most DEE genes lack known episignatures, the increase in diagnostic yield for DNA methylation analysis in DEEs is comparable to the added yield of genome sequencing. Finally, we refine an episignature for CHD2 using an 850K methylation array which was further refined at higher CpG resolution using bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate genetic causes as ∼2% (10/516) for unsolved DEE cases.

Experiences of adults living with refractory epilepsy and their views and expectations on receiving results from whole genome sequencing

INTRODUCTION

Researchers, clinicians and patients are turning to new innovations in research and clinical practice to further their knowledge in the genetic domain and improve diagnostics or treatment. However, with increased knowledge in genetics, societal issues may arise. Being conscious of these issues is crucial in order to implement standardized and efficient testing on a wider scale that is accessible to a greater number of individuals while simultaneously returning test results, including incidental findings, in a timely manner.

METHODS

Within the framework of a genomics research project, we invited 20 participants who suffer from refractory epilepsy to provide insight on their personal experiences with epilepsy, as well as their thoughts on receiving Whole Genome Sequencing (WGS) results and with whom they would feel comfortable sharing these results with.

RESULTS

All participants had their own unique experience with epilepsy, such as how they handled their diagnosis, their struggles following the diagnosis, the healthcare services they received, how they shared their diagnosis with others, and how they managed stigmatization from others. Most participants would be eager to know their WGS results, whether the results be related to epilepsy (n = 19), response to pharmaceutical drugs including AEDs (n = 16), comorbidities (n = 19) and incidental findings (n = 15).

CONCLUSION

Our findings reinforce the need to improve access to genetic testing for epilepsy patients in clinical settings. Furthermore, while acquiring more genetic knowledge (i.e. WGS) about epilepsy can provide answers for the affected population, it also requires the simultaneous involvement of several medical disciplines, with greater emphasis on genetic and psychological counseling.

ILAE Genetics Literacy series: Progressive myoclonus epilepsies

Progressive Myoclonus Epilepsy (PME) is a rare epilepsy syndrome characterized by the development of progressively worsening myoclonus, ataxia, and seizures. A molecular diagnosis can now be established in approximately 80% of individuals with PME. Almost fifty genetic causes of PME have now been established, although some remain extremely rare. Herein, we provide a review of clinical phenotypes and genotypes of the more commonly encountered PMEs. Using an illustrative case example, we describe appropriate clinical investigation and therapeutic strategies to guide the management of this often relentlessly progressive and devastating epilepsy syndrome. This manuscript in the Genetic Literacy series maps to Learning Objective 1.2 of the ILAE Curriculum for Epileptology (Epileptic Disord. 2019;21:129).

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment.

Redefining cerebral palsies as a diverse group of neurodevelopmental disorders with genetic aetiology

Cerebral palsy is a clinical descriptor covering a diverse group of permanent, non-degenerative disorders of motor function. Around one-third of cases have now been shown to have an underlying genetic aetiology, with the genetic landscape overlapping with those of neurodevelopmental disorders including intellectual disability, epilepsy, speech and language disorders and autism. Here we review the current state of genomic testing in cerebral palsy, highlighting the benefits for personalized medicine and the imperative to consider aetiology during clinical diagnosis. With earlier clinical diagnosis now possible, we emphasize the opportunity for comprehensive and early genomic testing as a crucial component of the routine diagnostic work-up in people with cerebral palsy.

Evaluation of the feasibility, diagnostic yield, and clinical utility of rapid genome sequencing in infantile epilepsy (Gene-STEPS): an international, multicentre, pilot cohort study

BACKGROUND

Most neonatal and infantile-onset epilepsies have presumed genetic aetiologies, and early genetic diagnoses have the potential to inform clinical management and improve outcomes. We therefore aimed to determine the feasibility, diagnostic yield, and clinical utility of rapid genome sequencing in this population.

METHODS

We conducted an international, multicentre, cohort study (Gene-STEPS), which is a pilot study of the International Precision Child Health Partnership (IPCHiP). IPCHiP is a consortium of four paediatric centres with tertiary-level subspecialty services in Australia, Canada, the UK, and the USA. We recruited infants with new-onset epilepsy or complex febrile seizures from IPCHiP centres, who were younger than 12 months at seizure onset. We excluded infants with simple febrile seizures, acute provoked seizures, known acquired cause, or known genetic cause. Blood samples were collected from probands and available biological parents. Clinical data were collected from medical records, treating clinicians, and parents. Trio genome sequencing was done when both parents were available, and duo or singleton genome sequencing was done when one or neither parent was available. Site-specific protocols were used for DNA extraction and library preparation. Rapid genome sequencing and analysis was done at clinically accredited laboratories, and results were returned to families. We analysed summary statistics for cohort demographic and clinical characteristics and the timing, diagnostic yield, and clinical impact of rapid genome sequencing.

FINDINGS

Between Sept 1, 2021, and Aug 31, 2022, we enrolled 100 infants with new-onset epilepsy, of whom 41 (41%) were girls and 59 (59%) were boys. Median age of seizure onset was 128 days (IQR 46-192). For 43 (43% [binomial distribution 95% CI 33-53]) of 100 infants, we identified genetic diagnoses, with a median time from seizure onset to rapid genome sequencing result of 37 days (IQR 25-59). Genetic diagnosis was associated with neonatal seizure onset versus infantile seizure onset (14 [74%] of 19 vs 29 [36%] of 81; p=0·0027), referral setting (12 [71%] of 17 for intensive care, 19 [44%] of 43 non-intensive care inpatient, and 12 [28%] of 40 outpatient; p=0·0178), and epilepsy syndrome (13 [87%] of 15 for self-limited epilepsies, 18 [35%] of 51 for developmental and epileptic encephalopathies, 12 [35%] of 34 for other syndromes; p=0·001). Rapid genome sequencing revealed genetic heterogeneity, with 34 unique genes or genomic regions implicated. Genetic diagnoses had immediate clinical utility, informing treatment (24 [56%] of 43), additional evaluation (28 [65%]), prognosis (37 [86%]), and recurrence risk counselling (all cases).

INTERPRETATION

Our findings support the feasibility of implementation of rapid genome sequencing in the clinical care of infants with new-onset epilepsy. Longitudinal follow-up is needed to further assess the role of rapid genetic diagnosis in improving clinical, quality-of-life, and economic outcomes.

FUNDING

American Academy of Pediatrics, Boston Children's Hospital Children's Rare Disease Cohorts Initiative, Canadian Institutes of Health Research, Epilepsy Canada, Feiga Bresver Academic Foundation, Great Ormond Street Hospital Charity, Medical Research Council, Murdoch Children's Research Institute, National Institute of Child Health and Human Development, National Institute for Health and Care Research Great Ormond Street Hospital Biomedical Research Centre, One8 Foundation, Ontario Brain Institute, Robinson Family Initiative for Transformational Research, The Royal Children's Hospital Foundation, University of Toronto McLaughlin Centre.

Technological and computational approaches to detect somatic mosaicism in epilepsy

Lesional epilepsy is a common and severe disease commonly associated with malformations of cortical development, including focal cortical dysplasia and hemimegalencephaly. Recent advances in sequencing and variant calling technologies have identified several genetic causes, including both short/single nucleotide and structural somatic variation. In this review, we aim to provide a comprehensive overview of the methodological advancements in this field while highlighting the unresolved technological and computational challenges that persist, including ultra-low variant allele fractions in bulk tissue, low availability of paired control samples, spatial variability of mutational burden within the lesion, and the issue of false-positive calls and validation procedures. Information from genetic testing in focal epilepsy may be integrated into clinical care to inform histopathological diagnosis, postoperative prognosis, and candidate precision therapies.

Integrative Analysis of Epilepsy-Associated Genes Reveals Expression-Phenotype Correlations

Epilepsy is a highly prevalent neurological disorder characterized by recurrent seizures. Patients exhibit broad genetic, molecular, and clinical diversity involving mild to severe comorbidities. The factors that contribute to this phenotypic diversity remain unclear. We used publicly available datasets to systematically interrogate the expression pattern of 247 epilepsy-associated genes across human tissues, developmental stages, and central nervous system (CNS) cellular subtypes. We grouped genes based on their curated phenotypes into 3 broad classes: core epilepsy genes (CEG), where seizures are the core syndrome, developmental and epileptic encephalopathy genes (DEEG) that are associated with developmental delay, and seizure-related genes (SRG), which are characterized by developmental delay and gross brain malformations. We find that DEEGs are highly expressed within the CNS, while SRGs are most abundant in non-CNS tissues. DEEGs and CEGs exhibit highly dynamic expression in various brain regions across development, spiking during the prenatal to infancy transition. Lastly, the abundance of CEGs and SRGs is comparable within cellular subtypes in the brain, while the average expression level of DEEGs is significantly higher in GABAergic neurons and non-neuronal cells. Our analysis provides an overview of the expression pattern of epilepsy-associated genes with spatiotemporal resolution and establishes a broad expression-phenotype correlation in epilepsy.

WWOX developmental and epileptic encephalopathy: Understanding the epileptology and the mortality risk

OBJECTIVE

WWOX is an autosomal recessive cause of early infantile developmental and epileptic encephalopathy (WWOX-DEE), also known as WOREE (WWOX-related epileptic encephalopathy). We analyzed the epileptology and imaging features of WWOX-DEE, and investigated genotype-phenotype correlations, particularly with regard to survival.

METHODS

We studied 13 patients from 12 families with WWOX-DEE. Information regarding seizure semiology, comorbidities, facial dysmorphisms, and disease outcome were collected. Electroencephalographic (EEG) and brain magnetic resonance imaging (MRI) data were analyzed. Pathogenic WWOX variants from our cohort and the literature were coded as either null or missense, allowing individuals to be classified into one of three genotype classes: (1) null/null, (2) null/missense, (3) missense/missense. Differences in survival outcome were estimated using the Kaplan-Meier method.

RESULTS

All patients experienced multiple seizure types (median onset = 5 weeks, range = 1 day-10 months), the most frequent being focal (85%), epileptic spasms (77%), and tonic seizures (69%). Ictal EEG recordings in six of 13 patients showed tonic (n = 5), myoclonic (n = 2), epileptic spasms (n = 2), focal (n = 1), and migrating focal (n = 1) seizures. Interictal EEGs demonstrated slow background activity with multifocal discharges, predominantly over frontal or temporo-occipital regions. Eleven of 13 patients had a movement disorder, most frequently dystonia. Brain MRIs revealed severe frontotemporal, hippocampal, and optic atrophy, thin corpus callosum, and white matter signal abnormalities. Pathogenic variants were located throughout WWOX and comprised both missense and null changes including five copy number variants (four deletions, one duplication). Survival analyses showed that patients with two null variants are at higher mortality risk (p-value = .0085, log-rank test).

SIGNIFICANCE

Biallelic WWOX pathogenic variants cause an early infantile developmental and epileptic encephalopathy syndrome. The most common seizure types are focal seizures and epileptic spasms. Mortality risk is associated with mutation type; patients with biallelic null WWOX pathogenic variants have significantly lower survival probability compared to those carrying at least one presumed hypomorphic missense pathogenic variant.