Polygenic burden in focal and generalized epilepsies

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.

Unraveling the genetic basis of epilepsy: Recent advances and implications for diagnosis and treatment

Epilepsy, affecting approximately 1% of the global population, manifests as recurring seizures and is heavily influenced by genetic factors. Recent advancements in genetic technologies have revolutionized our understanding of epilepsy's genetic landscape. Key studies, such as the discovery of mutations in ion channels (e.g., SCN1A and SCN2A), neurotransmitter receptors (e.g., GABRA1), and synaptic proteins (e.g., SYNGAP1, KCNQ2), have illuminated critical pathways underlying epilepsy susceptibility and pathogenesis. Genome-wide association studies (GWAS) have identified specific genetic variations linked to epilepsy risk, such as variants near SCN1A and PCDH7, enhancing diagnostic accuracy and enabling personalized treatment strategies. Moreover, epigenetic mechanisms, including DNA methylation (e.g., MBD5), histone modifications (e.g., HDACs), and non-coding RNAs (e.g., miR-134), play pivotal roles in altering gene expression and synaptic plasticity, contributing to epileptogenesis. These discoveries offer promising avenues for therapeutic interventions aimed at improving outcomes for epilepsy patients. Genetic testing has become essential in clinical practice, facilitating precise diagnosis and tailored management approaches based on individual genetic profiles. Furthermore, insights into epigenetic regulation suggest novel therapeutic targets for developing more effective epilepsy treatments. In summary, this review highlights significant progress in understanding the genetic and epigenetic foundations of epilepsy. By integrating findings from key studies and specifying genes involved in epigenetic modifications, we underscore the potential for advanced therapeutic strategies in this complex neurological disorder, emphasizing the importance of personalized medicine approaches in epilepsy management.

Clinical features and underlying etiology of children with Lennox-Gastaut syndrome

OBJECTIVE

Lennox-Gastaut Syndrome (LGS) is characterized by the presence of multiple seizure types and encompasses a heterogenous group of etiologies. The aim of our study was to evaluate the etiological profile of LGS and investigate seizure outcomes based on different clinical variables.

METHODS

The clinical features, neuroimaging findings, genetic testing and other testing results of LGS patients were systematically reviewed. The identifiable etiology was categorized as either acquired or nonacquired. Univariate and multivariate regression analyses were performed to explore the association between clinical variables and seizure outcome at the last follow-up.

RESULTS

We enrolled 156 patients diagnosed with LGS, of whom 66% were male. The mean age of patients was 34.2 months and the median follow-up duration was 29.5 months (interquartile range = 14-56.25 months). The initial seizure type was epileptic spasm in 61 patients, among which 33 of them met the criteria for infantile epileptic spasm syndrome. All patients underwent neuroimaging test, with 25% falling into the acquired structural category. Etiology could be identified in 84 individuals, including pathogenetic variants found in 34 out of 117 patients with nonacquired etiology. CHD2 mutations were most frequently observed among these pathogenetic variants. At the last follow-up, favorable outcomes were observed in 27 patients. The identification of etiology emerged as a significant determinant influencing LGS outcome; specifically, patients with unknown etiology had a higher likelihood of experiencing favorable outcomes compared to those with known cause (p = 0.041). Early onset age and longer epilepsy duration significantly increased the odds of an unfavorable outcome (p = 0.006 and 0.024).

SIGNIFICANCE

We present novel data on the clinical and etiological spectrum of LGS, with determined etiology observed in over half of the patients. Epileptic spasms were found to be more prevalent than tonic seizures as seizure onset types in LGS. The presence of a known etiology, earlier age at onset, and longer duration of epilepsy were associated with a poorer long-term epileptological outcome.

Gene-gene interaction network analysis indicates CNTN2 is a candidate gene for idiopathic generalized epilepsy

Twin and family studies have established the genetic contribution to idiopathic generalized epilepsy (IGE). The genetic architecture of IGE is generally complex and heterogeneous, and the majority of the genetic burden in IGE remains unsolved. We hypothesize that gene-gene interactions contribute to the complex inheritance of IGE. CNTN2 (OMIM* 615,400) variants have been identified in cases with familial adult myoclonic epilepsy and other epilepsies. To explore the gene-gene interaction network in IGE, we took the CNTN2 gene as an example and investigated its co-occurrent genetic variants in IGE cases. We performed whole-exome sequencing in 114 unrelated IGE cases and 296 healthy controls. Variants were qualified with sequencing quality, minor allele frequency, in silico prediction, genetic phenotype, and recurrent case numbers. The STRING_TOP25 gene interaction network analysis was introduced with the bait gene CNTN2 (denoted as A). The gene-gene interaction pair mode was presumed to be A + c, A + d, A + e, with a leading gene A, or A + B + f, A + B + g, A + B + h, with a double-gene A + B, or other combinations. We compared the number of gene interaction pairs between the case and control groups. We identified three pairs in the case group, CNTN2 + PTPN18, CNTN2 + CNTN1 + ANK2 + ANK3 + SNTG2, and CNTN2 + PTPRZ1, while we did not discover any pairs in the control group. The number of gene interaction pairs in the case group was much more than in the control group (p = 0.021). Taking together the genetic bioinformatics, reported epilepsy cases, and statistical evidence in the study, we supposed CNTN2 as a candidate pathogenic gene for IGE. The gene interaction network analysis might help screen candidate genes for IGE or other complex genetic disorders.

Polygenic burden and its association with baseline cognitive function and postoperative cognitive outcome in temporal lobe epilepsy

OBJECTIVE

Demographic and disease factors are associated with cognitive deficits and postoperative cognitive declines in adults with pharmacoresistant temporal lobe epilepsy (TLE), but the role of genetic factors in cognition in TLE is not well understood. Polygenic scores (PGS) for neurological and neuropsychiatric disorders and IQ have been associated with cognition in patient and healthy populations. In this exploratory study, we examined the relationship between PGS for Alzheimer's disease (AD), depression, and IQ and cognitive outcomes in adults with TLE.

METHODS

202 adults with pharmacoresistant TLE had genotyping and completed neuropsychological evaluations as part of a presurgical work-up. A subset (n = 116) underwent temporal lobe resection and returned for postoperative cognitive testing. Logistic regression was used to determine if PGS for AD, depression, and IQ predicted baseline domain-specific cognitive function and cognitive phenotypes as well as postoperative language and memory decline.

RESULTS

No significant findings survived correction for multiple comparisons. Prior to correction, higher PGS for AD and depression (i.e., increased genetic risk for the disorder), but lower PGS for IQ (i.e., decreased genetic likelihood of high IQ) appeared possibly associated with baseline cognitive impairment in TLE. In comparison, higher PGS for AD and IQ appeared as possible risk factors for cognitive decline following temporal lobectomy, while the possible relationship between PGS for depression and post-operative cognitive outcome was mixed.

SIGNIFICANCE

We did not observe any relationships of large effect between PGS and cognitive function or postsurgical outcome; however, results highlight several promising trends in the data that warrant future investigation in larger samples better powered to detect small genetic effects.

Healthcare utilization and clinical characteristics of genetic epilepsy in electronic health records

Understanding the clinical characteristics and medical treatment of individuals affected by genetic epilepsies is instrumental in guiding selection for genetic testing, defining the phenotype range of these rare disorders, optimizing patient care pathways and pinpointing unaddressed medical need by quantifying healthcare resource utilization. To date, a matched longitudinal cohort study encompassing the entire spectrum of clinical characteristics and medical treatment from childhood through adolescence has not been performed. We identified individuals with genetic and non-genetic epilepsies and onset at ages 0-5 years by linkage across the Cleveland Clinic Health System. We used natural language processing to extract medical terms and procedures from longitudinal electronic health records and tested for cross-sectional and temporal associations with genetic epilepsy. We implemented a two-stage design: in the discovery cohort, individuals were stratified as being 'likely genetic' or 'non-genetic' by a natural language processing algorithm, and controls did not receive genetic testing. The validation cohort consisted of cases with genetic epilepsy confirmed by manual chart review and an independent set of controls who received negative genetic testing. The discovery and validation cohorts consisted of 503 and 344 individuals with genetic epilepsy and matched controls, respectively. The median age at the first encounter was 0.1 years and 7.9 years at the last encounter, and the mean duration of follow-up was 8.2 years. We extracted 188,295 Unified Medical Language System annotations for statistical analysis across 9659 encounters. Individuals with genetic epilepsy received an earlier epilepsy diagnosis and had more frequent and complex encounters with the healthcare system. Notably, the highest enrichment of encounters compared with the non-genetic groups was found during the transition from paediatric to adult care. Our computational approach could validate established comorbidities of genetic epilepsies, such as behavioural abnormality and intellectual disability. We also revealed novel associations for genitourinary abnormalities (odds ratio 1.91, 95% confidence interval: 1.66-2.20, P = 6.16 × 10-19) linked to a spectrum of underrecognized epilepsy-associated genetic disorders. This case-control study leveraged real-world data to identify novel features associated with the likelihood of a genetic aetiology and quantified the healthcare utilization of genetic epilepsies compared with matched controls. Our results strongly recommend early genetic testing to stratify individuals into specialized care paths, thus improving the clinical management of people with genetic epilepsies.

CRISPR/Cas9 system and its applications in nervous system diseases

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system is an acquired immune system of many bacteria and archaea, comprising CRISPR loci, Cas genes, and its associated proteins. This system can recognize exogenous DNA and utilize the Cas9 protein's nuclease activity to break DNA double-strand and to achieve base insertion or deletion by subsequent DNA repair. In recent years, multiple laboratory and clinical studies have revealed the therapeutic role of the CRISPR/Cas9 system in neurological diseases. This article reviews the CRISPR/Cas9-mediated gene editing technology and its potential for clinical application against neurological diseases.

Epilepsy with generalized tonic-clonic seizures alone: Electroclinical features and prognostic patterns

OBJECTIVE

Epilepsy with generalized tonic-clonic seizures alone (GTCA) is a common but poorly characterized idiopathic generalized epilepsy (IGE) syndrome. Hence, we investigated electroclinical features, seizure outcome, and antiseizure medication (ASM) withdrawal in a large cohort of GTCA patients.

METHODS

In this multicenter retrospective study, GTCA patients defined according to the diagnostic criteria of the International League Against Epilepsy (2022) were included. We investigated prognostic patterns, drug resistance at the last visit, and ASM withdrawal, along with their prognostic factors.

RESULTS

We included 247 patients with a median (interquartile range [IQR]) age at onset of 17 years (13-22) and a median follow-up duration of 10 years (IQR = 5-20). Drug resistance at the last visit was observed in 40 (16.3%) patients, whereas the median latency to achieve 2-year remission was 24 months (IQR = 24-46.5) with a median number of 1 (IQR = 1-2) ASM. During the long-term follow-up (i.e., 202 patients followed ≥5-years after the first ASM trial), 69 (34.3%) patients displayed an early remission pattern and 36 (17.9%) patients displayed a late remission pattern, whereas 16 (8%) and 73 (36.3%) individuals had no-remission and relapsing-remitting patterns, respectively. Catamenial seizures and morning predominance of generalized tonic-clonic seizures (GTCS) independently predicted drug resistance at the last visit according to multivariable logistic regression. Treatment withdrawal was attempted in 63 (25.5%) patients, with 59 (93.7%) of them having at least a 12-month follow-up after ASM discontinuation. At the last visit, 49 (83%) of those patients had experienced GTCS recurrence. A longer duration of seizure freedom was the only factor predicting a higher chance of successful ASM withdrawal according to multivariable Cox regression.

SIGNIFICANCE

GTCA could be considered a relatively easily manageable IGE syndrome, with a low rate of drug resistance and a high prevalence of early response to treatment. Nevertheless, a considerable proportion of patients experience relapsing patterns of seizure control, highlighting the need for appropriate counseling and lifestyle recommendations.

Solving the unsolved genetic epilepsies: Current and future perspectives

Many patients with epilepsy undergo exome or genome sequencing as part of a diagnostic workup; however, many remain genetically unsolved. There are various factors that account for negative results in exome/genome sequencing for patients with epilepsy: (1) the underlying cause is not genetic; (2) there is a complex polygenic explanation; (3) the illness is monogenic but the causative gene remains to be linked to a human disorder; (4) family segregation with reduced penetrance; (5) somatic mosaicism or the complexity of, for example, a structural rearrangement; or (6) limited knowledge or diagnostic tools that hinder the proper classification of a variant, resulting in its designation as a variant of unknown significance. The objective of this review is to outline some of the diagnostic options that lie beyond the exome/genome, and that might become clinically relevant within the foreseeable future. These options include: (1) re-analysis of older exome/genome data as knowledge increases or symptoms change; (2) looking for somatic mosaicism or long-read sequencing to detect low-complexity repeat variants or specific structural variants missed by traditional exome/genome sequencing; (3) exploration of the non-coding genome including disruption of topologically associated domains, long range non-coding RNA, or other regulatory elements; and finally (4) transcriptomics, DNA methylation signatures, and metabolomics as complementary diagnostic methods that may be used in the assessment of variants of unknown significance. Some of these tools are currently not integrated into standard diagnostic workup. However, it is reasonable to expect that they will become increasingly available and improve current diagnostic capabilities, thereby enabling precision diagnosis in patients who are currently undiagnosed.

SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis

Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).

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.

Familial Mesial Temporal Lobe Epilepsy: Clinical Spectrum and Genetic Evidence for a Polygenic Architecture

OBJECTIVE

Familial mesial temporal lobe epilepsy (FMTLE) is an important focal epilepsy syndrome; its molecular genetic basis is unknown. Clinical descriptions of FMTLE vary between a mild syndrome with prominent déjà vu to a more severe phenotype with febrile seizures and hippocampal sclerosis. We aimed to refine the phenotype of FMTLE by analyzing a large cohort of patients and asked whether common risk variants for focal epilepsy and/or febrile seizures, measured by polygenic risk scores (PRS), are enriched in individuals with FMTLE.

METHODS

We studied 134 families with ≥ 2 first or second-degree relatives with temporal lobe epilepsy, with clear mesial ictal semiology required in at least one individual. PRS were calculated for 227 FMTLE cases, 124 unaffected relatives, and 16,077 population controls.

RESULTS

The age of patients with FMTLE onset ranged from 2.5 to 70 years (median = 18, interquartile range = 13-28 years). The most common focal seizure symptom was déjà vu (62% of cases), followed by epigastric rising sensation (34%), and fear or anxiety (22%). The clinical spectrum included rare cases with drug-resistance and/or hippocampal sclerosis. FMTLE cases had a higher mean focal epilepsy PRS than population controls (odds ratio = 1.24, 95% confidence interval = 1.06, 1.46, p = 0.007); in contrast, no enrichment for the febrile seizure PRS was observed.

INTERPRETATION

FMTLE is a generally mild drug-responsive syndrome with déjà vu being the commonest symptom. In contrast to dominant monogenic focal epilepsy syndromes, our molecular data support a polygenic basis for FMTLE. Furthermore, the PRS data suggest that sub-genome-wide significant focal epilepsy genome-wide association study single nucleotide polymorphisms are important risk variants for FMTLE. ANN NEUROL 2023;94:825-835.

Population genetics of marmosets in Asian primate research centers and loci associated with epileptic risk revealed by whole-genome sequencing

The common marmoset ( Callithrix jacchus) has emerged as a valuable nonhuman primate model in biomedical research with the recent release of high-quality reference genome assemblies. Epileptic marmosets have been independently reported in two Asian primate research centers. Nevertheless, the population genetics within these primate centers and the specific genetic variants associated with epilepsy in marmosets have not yet been elucidated. Here, we characterized the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmoset pedigrees using whole-genome sequencing. We identified 14 558 184 single nucleotide polymorphisms (SNPs) from the 41 samples and found higher chimerism levels in blood samples than in fingernail samples. Genetic analysis showed fourth-degree of relatedness among marmosets at the primate centers. In addition, SNP and copy number variation (CNV) analyses suggested that the WW domain-containing oxidoreductase ( WWOX) and Tyrosine-protein phosphatase nonreceptor type 21 ( PTPN21) genes may be associated with epilepsy in marmosets. Notably, KCTD18-like gene deletion was more common in epileptic marmosets than control marmosets. This study provides valuable population genomic resources for marmosets in two Asian primate centers. Genetic analyses identified a reasonable breeding strategy for genetic diversity maintenance in the two centers, while the case-control study revealed potential risk genes/variants associated with epilepsy in marmosets.

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.

Identifying Novel Drug Targets for Epilepsy Through a Brain Transcriptome-Wide Association Study and Protein-Wide Association Study with Chemical-Gene-Interaction Analysis

Epilepsy is a severe neurological condition affecting 50-65 million individuals worldwide that can lead to brain damage. Nevertheless, the etiology of epilepsy remains poorly understood. Meta-analyses of genome-wide association studies involving 15,212 epilepsy cases and 29,677 controls of the ILAE Consortium cohort were used to conduct transcriptome-wide association studies (TWAS) and protein-wide association studies (PWAS). Furthermore, a protein-protein interaction (PPI) network was generated using the STRING database, and significant epilepsy-susceptible genes were verified using chip data. Chemical-related gene set enrichment analysis (CGSEA) was performed to determine novel drug targets for epilepsy. TWAS analysis identified 21,170 genes, of which 58 were significant (TWASfdr < 0.05) in ten brain regions, and 16 differentially expressed genes were verified based on mRNA expression profiles. The PWAS identified 2249 genes, of which 2 were significant (PWASfdr < 0.05). Through chemical-gene set enrichment analysis, 287 environmental chemicals associated with epilepsy were identified. We identified five significant genes (WIPF1, IQSEC1, JAM2, ICAM3, and ZNF143) that had causal relationships with epilepsy. CGSEA identified 159 chemicals that were significantly correlated with epilepsy (Pcgsea < 0.05), such as pentobarbital, ketone bodies, and polychlorinated biphenyl. In summary, we performed TWAS, PWAS (for genetic factors), and CGSEA (for environmental factors) analyses and identified several epilepsy-associated genes and chemicals. The results of this study will contribute to our understanding of genetic and environmental factors for epilepsy and may predict novel drug targets.

Epilepsies of presumed genetic etiology show enrichment of rare variants that occur in the general population

Previous studies suggested that severe epilepsies, e.g., developmental and epileptic encephalopathies (DEEs), are mainly caused by ultra-rare de novo genetic variants. For milder disease, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 control individuals. Here, we separately analyzed three different groups of epilepsies: severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in control individuals with an allele count ≥ 1 and a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD ≥ 20), and to have an odds ratio in individuals with epilepsy ≥ 2. We identified genes enriched with QRVs primarily in NAFE (n = 72), followed by GGE (n = 32) and DEE (n = 21). This suggests that rare variants may play a more important role for causality of NAFE than for DEE. Moreover, we found that genes harboring QRVs, e.g., HSGP2, FLNA, or TNC, encode proteins that are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE that occur also in the general population, while in DEE and GGE, the contribution of such variants appears more limited.

Genetics and SUDEP: Challenges and Future Directions

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related deaths in children and adults with epilepsy. The incidence of SUDEP in children and adults is equal, approximately 1.2 per 1000-person years. Although inroads have been made in our understanding of SUDEP, its pathophysiology remains unknown. The most important risk factor for SUDEP is the presence of tonic-clonic seizures. Recently there has been growing interest in the contribution of genetic risk factors to SUDEP deaths. Pathogenic variants in epilepsy-related and cardiac genes have been found in some cases of SUDEP post-mortem. Pleiotropy may occur in which a single gene when altered may cause multiple phenotypes (i.e., epilepsy and cardiac arrhythmia). Recently it has been shown that some developmental and epileptic encephalopathies (DEEs) may also be at heightened risk of SUDEP. In addition, polygenic risk has been postulated to effect SUDEP risk with current models evaluating the additive effect of variants in multiple genes. However, the mechanisms underpinning polygenic risk in SUDEP are likely more complex than this. Some preliminary studies also highlight the feasibility of detecting genetic variants in brain tissue post-mortem. Despite the advances in the field of SUDEP genetics, the use of molecular autopsy remains underutilized in SUDEP cases. Several challenges exist concerning genetic testing post-mortem in SUDEP cases, such as interpretation, cost of testing, and availability. In this focused review, we highlight the current landscape of genetic testing in SUDEP cases, its challenges, and future directions.

Individualised human phenotype ontology gene panels improve clinical whole exome and genome sequencing analytical efficacy in a cohort of developmental and epileptic encephalopathies

BACKGROUND

The majority of genetic epilepsies remain unsolved in terms of specific genotype. Phenotype-based genomic analyses have shown potential to strengthen genomic analysis in various ways, including improving analytical efficacy.

METHODS

We have tested a standardised phenotyping method termed 'Phenomodels' for integrating deep-phenotyping information with our in-house developed clinical whole exome/genome sequencing analytical pipeline. Phenomodels includes a user-friendly epilepsy phenotyping template and an objective measure for selecting which template terms to include in individualised Human Phenotype Ontology (HPO) gene panels. In a pilot study of 38 previously solved cases of developmental and epileptic encephalopathies, we compared the sensitivity and specificity of the individualised HPO gene panels with the clinical epilepsy gene panel.

RESULTS

The Phenomodels template showed high sensitivity for capturing relevant phenotypic information, where 37/38 individuals' HPO gene panels included the causative gene. The HPO gene panels also had far fewer variants to assess than the epilepsy gene panel.

CONCLUSION

We have demonstrated a viable approach for incorporating standardised phenotype information into clinical genomic analyses, which may enable more efficient analysis.

Variation in prognosis and treatment outcome in juvenile myoclonic epilepsy: a Biology of Juvenile Myoclonic Epilepsy Consortium proposal for a practical definition and stratified medicine classifications

Reliable definitions, classifications and prognostic models are the cornerstones of stratified medicine, but none of the current classifications systems in epilepsy address prognostic or outcome issues. Although heterogeneity is widely acknowledged within epilepsy syndromes, the significance of variation in electroclinical features, comorbidities and treatment response, as they relate to diagnostic and prognostic purposes, has not been explored. In this paper, we aim to provide an evidence-based definition of juvenile myoclonic epilepsy showing that with a predefined and limited set of mandatory features, variation in juvenile myoclonic epilepsy phenotype can be exploited for prognostic purposes. Our study is based on clinical data collected by the Biology of Juvenile Myoclonic Epilepsy Consortium augmented by literature data. We review prognosis research on mortality and seizure remission, predictors of antiseizure medication resistance and selected adverse drug events to valproate, levetiracetam and lamotrigine. Based on our analysis, a simplified set of diagnostic criteria for juvenile myoclonic epilepsy includes the following: (i) myoclonic jerks as mandatory seizure type; (ii) a circadian timing for myoclonia not mandatory for the diagnosis of juvenile myoclonic epilepsy; (iii) age of onset ranging from 6 to 40 years; (iv) generalized EEG abnormalities; and (v) intelligence conforming to population distribution. We find sufficient evidence to propose a predictive model of antiseizure medication resistance that emphasises (i) absence seizures as the strongest stratifying factor with regard to antiseizure medication resistance or seizure freedom for both sexes and (ii) sex as a major stratifying factor, revealing elevated odds of antiseizure medication resistance that correlates to self-report of catamenial and stress-related factors including sleep deprivation. In women, there are reduced odds of antiseizure medication resistance associated with EEG-measured or self-reported photosensitivity. In conclusion, by applying a simplified set of criteria to define phenotypic variations of juvenile myoclonic epilepsy, our paper proposes an evidence-based definition and prognostic stratification of juvenile myoclonic epilepsy. Further studies in existing data sets of individual patient data would be helpful to replicate our findings, and prospective studies in inception cohorts will contribute to validate them in real-world practice for juvenile myoclonic epilepsy management.

The importance of discriminative power rather than significance when evaluating potential clinical biomarkers in epilepsy research

OBJECTIVE

The quest for epilepsy biomarkers is on the rise. Variables with statistically significant group-level differences are often misinterpreted as biomarkers with sufficient discriminative power. This study aimed to demonstrate the relationship between significant group-level differences and a variable's power to discriminate between individuals.

METHODS

We simulated normal-distributed datasets from hypothetical populations with varying sample sizes (25-800), effect sizes (Cohen's d: .25-2.50), and variability (standard deviation: 10-35) to assess the impact of these parameters on significance and discriminative power. The simulation data were illustrated by assessing the discriminative power of a potential real-case biomarker-the EEG beta band power-to diagnose generalized epilepsy, using data from 66 children with generalized epilepsy and 385 controls. Additionally, we evaluated recently reported epilepsy biomarkers by comparing their effect sizes to our simulation-derived effect size criterion.

RESULTS

Group size affects significance but not discriminative power. Discriminative power is much more related to variability and effect size. Our real data example supported these simulation results by demonstrating that group-level significance does not translate, one to one, into discriminative power. Although we found a significant difference in the beta band power between children with and without epilepsy, the discriminative power was poor due to a small effect size. A Cohen's d of at least 1.25 is required to reach good discriminative power in univariable prediction modeling. Slightly over 60% of the biomarkers in our literature search met this criterion.

SIGNIFICANCE

Rather than statistical significance of group-level differences, effect size should be used as an indicator of a variable's biomarker potential. The minimal required effects size for individual biomarkers-a Cohen's d of 1.25-is large. This calls for multivariable approaches, in which combining multiple variables with smaller effect sizes could increase the overall effect size and discriminative power.

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.

The role of rare genetic variants enrichment in epilepsies of presumed genetic etiology

Previous studies suggested that severe epilepsies e.g., developmental and epileptic encephalopathies (DEE) are mainly caused by ultra-rare de novo genetic variants. For milder phenotypes, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 controls. Here, we separately analyzed three different groups of epilepsies : severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in controls at a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD≥20), and to have an odds ratio in epilepsy cases ≥2. We identified genes enriched with QRVs in DEE (n=21), NAFE (n=72), and GGE (n=32) - the number of enriched genes are found greatest in NAFE and least in DEE. This suggests that rare variants may play a more important role for causality of NAFE than in DEE. Moreover, we found that QRV-carrying genes e.g., HSGP2, FLNA or TNC are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE, while in DEE and GGE, the contribution of such variants appears more limited.

The emergence of genotypic divergence and future precision medicine applications

Genotypic divergence is a term adapted from population genetics and intimately linked to evolution. We use divergence here to emphasize the differences that set individuals apart in any cohort. The history of genetics is filled with descriptions of genotypic differences, but causal inference of interindividual biological variation has been scarce. We suggest that the practice of precision medicine requires a divergent approach, an approach dependent on the causal interpretation of previous convergent (and preliminary) knowledge in the field. This knowledge has relied on convergent descriptive syndromology (lumping), which has overemphasized a reductionistic gene determinism on the quest of seeking associations without causal understanding. Regulatory variants with small effect and somatic mutations are some of the modifying factors that lead to incomplete penetrance and intrafamilial variable expressivity often observed in apparently monogenic clinical disorders. A truly divergent approach to precision medicine requires splitting, that is, the consideration of different layers of genetic phenomena that interact causally in a nonlinear fashion. This chapter reviews convergences and divergences in genetics and genomics, aiming to discuss what can be causally understood to approximate the as-yet utopian lands of Precision Medicine for patients with neurodegenerative disorders.

Channeling the Future of Pathogenicity Prediction for Genetic Variants in Epilepsy

[Box: see text]

A Brief Focus on Joubert Syndrome and Related Acute Complications

Joubert syndrome (JS) and related disorders are a group of congenital anomalies syndromes in which the obligatory hallmark is the molar tooth sign, a complex midbrain–hindbrain malformation. Moreover, JS may be associated with multiorgan involvement, mainly nephronophthisis, hepatic fibrosis, retinal dystrophy, and other abnormalities with both inter- and intra-familial variability. Therefore, these patients should be followed by both diagnostic protocol and multidisciplinary approach to assess multiorgan involvement. Here, we briefly summarize the possible complications in patients with JS.

An Overview of Genes Involved in the Pure Joubert Syndrome and in Joubert Syndrome-Related Disorders (JSRD)

Joubert syndrome (JS) is a rare autosomal recessive disease characterized by a peculiar brain malformation, hypotonia, ataxia, developmental delay, abnormal eye movements, and neonatal breathing abnormalities. This picture is often associated with variable multiorgan involvement, mainly of the retina, kidneys and liver, defining a group of conditions termed syndrome and Joubert syndrome-related disorders (JSRD). Currently, more than 30 causative genes have been identified, involved in the development and stability of the primary cilium. Correlations genotype–phenotype are emerging between clinical presentations and mutations in JSRD genes, with implications in terms of molecular diagnosis, prenatal diagnosis, follow-up, and management of mutated patients.

Epilepsy in Joubert Syndrome: A Still Few Explored Matter

Epilepsy is rarely associated with Joubert's syndrome and related disorders (JSRD), being reported only in 3% of cases. Few patients have been described, moreover, with poor evidences of specific seizures' semiology or standard of practice for pharmacological treatment. Epilepsy is likely to be related to brain malformations in ciliopathies. Beyond the typical hindbrain malformation, the molar tooth sign, other cerebral anomalies variably reported in JSRD, such as generalized polymicrogyria, hamartomas, periventricular nodular heterotopia, and hippocampal defects, have been described. Herein, we aimed to revise the main clinical and etiopathogenetic characteristics of epilepsy associated with JSRD.

Radiological Features of Joubert's Syndrome

Joubert syndrome (JS) is a rare autosomal recessive disorder. All patients affected by this syndrome presented a characteristic picture of cranial fossa malformations, called “molar tooth sign.” This sign is defined by the presence in axial section at the level of a deck/midbrain, of hypo/dysplasia of the cerebellar vermis, abnormally deep interpeduncular fossa and horizontalized thickened and elongated superior cerebellar peduncles. Although “molar tooth sign” is peculiar of JS, other radiological findings have been also reported in these patients. Here, the authors briefly assumed the principal magnetic resonance imaging findings of JS.

Genetic Mechanisms Behind Severe Psychotic Reactions to Levetiracetam

A Pharmacogenomic Assessment of Psychiatric Adverse Drug Reactions to Levetiracetam

Campbell C, McCormack M, Patel S, Stapleton C, Bobbili D, Krause R, Depondt C, Sills GJ, Koeleman BP, Striano P, Zara F, Sander JW, Lerche H, Kunz WS, Stefansson K, Stefansson H, Doherty CP, Heinzen EL, Scheffer IE, Goldstein DB, O’Brien T, Cotter D, Berkovic SF, EpiPGX Consortium; Sisodiya SM, Delanty N, Cavalleri GL. Epilepsia. 2022;63(6):1563-1570. doi:10.1111/epi.17228

Objective:

Levetiracetam (LEV) is an effective antiseizure medicine, but 10%-20% of people treated with LEV report psychiatric side-effects, and up to 1% may have psychotic episodes. Pharmacogenomic predictors of these adverse drug reactions (ADRs) have yet to be identified. We sought to determine the contribution of both common and rare genetic variation to psychiatric and behavioral ADRs associated with LEV.

Methods:

This case-control study compared cases of LEV-associated behavioral disorder (n = 149) or psychotic reaction (n = 37) to LEV-exposed people with no history of psychiatric ADRs (n = 920). All samples were of European ancestry. We performed genome-wide association study (GWAS) analysis comparing those with LEV ADRs to controls. We estimated the polygenic risk scores (PRS) for schizophrenia and compared cases with LEV-associated psychotic reaction to controls. Rare variant burden analysis was performed using exome sequence data of cases with psychotic reactions (n = 18) and controls (n = 122).

Results:

Univariate GWAS found no significant associations with either LEV-associated behavioural disorder or LEV-psychotic reaction. PRS analysis showed that cases of LEV-associated psychotic reaction had an increased PRS for schizophrenia relative to controls (p = .0097, estimate = .4886). The rare-variant analysis found no evidence of an increased burden of rare genetic variants in people who had experienced LEV-associated psychotic reaction relative to controls.

Significance:

The polygenic burden for schizophrenia is a risk factor for LEV-associated psychotic reaction. To assess the clinical utility of PRS as a predictor, it should be tested in an independent and ideally prospective cohort. Larger sample sizes are required for the identification of significant univariate common genetic signals or rare genetic signals associated with psychiatric LEV ADRs.

Joubert Syndrome: Diagnostic Evaluation and Follow-up

The follow-up of a child with genetic syndrome is necessarily multidisciplinary because of the multiplicity of problems and calls for close collaboration between different specialists. The primary objective is the total care of the child and his family, regardless of the rarity and complexity of the disease, to obtain the highest possible degree of mental and physical health and autonomy.

Age-Related Neurodevelopmental Features in Children with Joubert Syndrome

Joubert syndrome (JS) is a rare inherited disorder of central nervous system with neonatal/infantile onset, mainly affecting cerebellum and brainstem, and clinically characterized by agenesis or dysgenesis of the cerebellar vermis with accompanying brainstem malformations. More than 20 disease-causing genes have been associated with JS but a clear genotype–phenotype correlation has not been assessed yet. Diagnosis is usually confirmed by detection of the JS neuroradiological hallmark, the molar tooth sign. Patients with JS typically present with neurological manifestations, moreover, a heterogeneous spectrum of multisystemic anomalies may be observed. Signs and symptoms onset varies according to the age range and clinical diagnosis might become complicated. Moreover, specific neurodevelopmental disorders can be associated with JS such as autism spectrum disorders, attention deficit with hyperactivity, and a wide range of behavioral disturbances. Here, we examined the main neurological and neurodevelopmental features of JS according to an age-dependent mode of presentation. Furthermore, differential diagnosis with other neurological syndromes was closely reviewed.

Alström Syndrome: A Systematic Review

Alström syndrome (AS) is a rare multisystem disorder characterized by cone-rod retinal dystrophy leading to vision loss, hearing deficiency, obesity, type 2 diabetes mellitus, and insulin resistance with hyperinsulinemia. The conditions include dilated cardiomyopathy, recurrent fibrotic pulmonary infections, and progressive renal, hepatic, and endocrinological dysfunction. Other clinical findings consist of thyroid problems, short height, and growth hormone insufficiency. In addition, patients present with normal IQ, but in some cases delay in psychomotor and cognitive development is described. There is no treatment for AS, and life expectancy is around 40 years. However, an early identification of the disease can help in reducing the progression to severe conditions and in ameliorating the patient's quality of life. Our intent was to analyze the clinical data in literature on AS and provide an up-to-date review.

Ophthalmological Findings in Joubert Syndrome and Related Disorders

Joubert syndrome (JS) is a rare genetic condition characterized by congenital malformation of the mid-hindbrain, cerebellar ataxia, hypotonia, oculomotor apraxia, hypoplasia of the cerebellar vermis resulting in breathing defects, ataxia, and delayed development. Ophthalmological examination reveals eye involvement with nystagmus and retinal defects. Genetic counseling is important for the prevention of new cases. Great advances have been made in recent years. Management is symptomatic and multidisciplinary. In the present review, we discussed the most frequent ophthalmological anomalies associated with JS and speculated on the role of ciliary physiology in eye development.

Paediatric epilepsy and cognition

Cognitive comorbidities are more frequent in children with epilepsy than in the general population. The cognitive function of children with epilepsy should be appropriately screened, and when there is an impairment, it must be diagnosed and managed. Several factors contribute to the occurrence of this comorbidity. The underlying aetiology and epilepsy syndrome are the major risk factors. Other factors also play a role, such as seizure recurrence, antiseizure medication, and interictal abnormalities. Recent evidence also suggested that cognitive involvement is an ongoing process that interacts with the normal maturation of cognitive function in children with epilepsy. Furthermore, some patients experience rapid cognitive deterioration related to epileptic activity, resulting in epileptic encephalopathy. Further research is needed to better understand how to prevent or modify factors that affect cognitive function in children with epilepsy. WHAT THIS PAPER ADDS: Cognitive comorbidities are more frequent in children with epilepsy than in the general population. The risk factors for cognitive impairment are the underlying aetiology/syndrome, seizure recurrence, antiseizure medication, and interictal abnormalities. Advanced genetic and neuroimaging studies are useful tools to better understand cognitive impairment in children with epilepsy.

Joubert Syndrome and Renal Implication

Twenty-five to 30% of patients with Joubert syndrome (JS) have renal involvement. Two forms of renal disease (RD) have traditionally been described. The less common form is the Dekaban–Arima syndrome, a JS RD that includes congenital blindness and occasional encephalocele. The other, more common RD is juvenile nephronophthisis (NPHP), that presents a progressive interstitial fibrosis, associated with small cysts at the corticomedullary junction. NPHP is the most frequent genetic cause for end-stage RD in the first three decades of life. Symptoms start at approximately 6 years of age with urine concentrating defects, polydipsia, polyuria, and secondary enuresis.

Polygenic risk scores in epilepsy

An epilepsy diagnosis has large consequences for an individual but is often difficult to make in clinical practice. Novel biomarkers are thus greatly needed. Here, we give an overview of how thousands of common genetic factors that increase the risk for epilepsy can be summarized as epilepsy polygenic risk scores (PRS). We discuss the current state of research on how epilepsy PRS can serve as a biomarker for the risk for epilepsy. The high heritability of common forms of epilepsy, particularly genetic generalized epilepsy, indicates a promising potential for epilepsy PRS in diagnosis and risk prediction. Small sample sizes and low ancestral diversity of current epilepsy genome-wide association studies show, however, a need for larger and more diverse studies before epilepsy PRS could be properly implemented in the clinic.

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.

Whole exome sequencing and co-expression analysis identify an SCN1A variant that modifies pathogenicity in a family with genetic epilepsy and febrile seizures plus

OBJECTIVE

Family members carrying the same SCN1A variant often exhibit differences in the clinical severity of epilepsy. This variable expressivity suggests that other factors aside from the primary sodium channel variant influence the clinical manifestation. However, identifying such factors has proven challenging in humans.

METHODS

We perform whole exome sequencing (WES) in a large family in which an SCN1A variant (p.K1372E) is segregating that is associated with a broad spectrum of phenotypes ranging from lack of epilepsy, to febrile seizures and absence seizures, to Dravet syndrome. We assessed the hypothesis that the severity of the SCN1A-related phenotype was affected by alternate alleles at a modifier locus (or loci).

RESULTS

One of our top candidates identified by WES was a second variant in the SCN1A gene (p.L375S) that was shared exclusively by unaffected carriers of the K1372E allele. To test the hypothesized that L375S variant nullifies the loss-of-function effect of K1372E, we transiently expressed Nav1.1 carrying the two variants in HEK293T cells and compared their biophysical properties with the wild-type (WT) variant, and then co-expressed WT with K1372E or L375S with K1372E in equal quantity and tested the functional consequence. The data demonstrated that co-expression of the L375S and K1372E alleles reversed the loss-of-function property brought by the K1372E variant, whereas WT-K1372E co-expression remained partial loss-of-function.

SIGNIFICANCE

These results support the hypothesis that L375S counteracts the loss-of-function effect of K1372E such that individuals carrying both alleles in trans do not present epilepsy-related symptoms. We demonstrate that monogenic epilepsies with wide expressivity can be modified by additional variants in the disease gene, providing a novel framework for the gene-phenotype relationship in genetic epilepsies.

Epigenetic genes and epilepsy - emerging mechanisms and clinical applications

An increasing number of epilepsies are being attributed to variants in genes with epigenetic functions. The products of these genes include factors that regulate the structure and function of chromatin and the placing, reading and removal of epigenetic marks, as well as other epigenetic processes. In this Review, we provide an overview of the various epigenetic processes, structuring our discussion around five function-based categories: DNA methylation, histone modifications, histone-DNA crosstalk, non-coding RNAs and chromatin remodelling. We provide background information on each category, describing the general mechanism by which each process leads to altered gene expression. We also highlight key clinical and mechanistic aspects, providing examples of genes that strongly associate with epilepsy within each class. We consider the practical applications of these findings, including tissue-based and biofluid-based diagnostics and precision medicine-based treatments. We conclude that variants in epigenetic genes are increasingly found to be causally involved in the epilepsies, with implications for disease mechanisms, treatments and diagnostics.

Genetic causes of rare and common epilepsies: What should the epileptologist know?

In past decades, the identification of genes involved in epileptic disorders has grown exponentially. The pace of gene identification in epileptic disorders began to accelerate in the late 2000s, driven by new technologies such as molecular cytogenetics and next-generation sequencing (NGS). These technologies have also been applied to genetic diagnostics, with different configurations, such as gene panels, whole-exome sequencing and whole-genome sequencing. The clinician must be aware that any technology has its limitations and complementary techniques must still be used to establish a diagnosis for specific diseases. In addition, increasing the amount of genetic information available in a larger patient sample also increases the need for rigorous interpretation steps, when taking into account the clinical, electroclinical, and when available, functional data. Local, multidisciplinary discussions have proven valuable in difficult diagnostic situations, especially in cases where precision medicine is being considered. They also serve to improve genetic counseling in complex situations. In this article, we will briefly review the genetic basis of rare and common epilepsies, the current strategies used for molecular diagnosis, including their limitations, and some pitfalls for data interpretation, in the context of etiological diagnosis and genetic counseling.

The role of common genetic variation in presumed monogenic epilepsies

BACKGROUND

The developmental and epileptic encephalopathies (DEEs) are the most severe group of epilepsies which co-present with developmental delay and intellectual disability (ID). DEEs usually occur in people without a family history of epilepsy and have emerged as primarily monogenic, with damaging rare mutations found in 50% of patients. Little is known about the genetic architecture of patients with DEEs in whom no pathogenic variant is identified. Polygenic risk scoring (PRS) is a method that measures a person's common genetic burden for a trait or condition. Here, we used PRS to test whether genetic burden for epilepsy is relevant in individuals with DEEs, and other forms of epilepsy with ID.

METHODS

Genetic data on 2,759 cases with DEEs, or epilepsy with ID presumed to have a monogenic basis, and 447,760 population-matched controls were analysed. We compared PRS for 'all epilepsy', 'focal epilepsy', and 'genetic generalised epilepsy' (GGE) between cases and controls. We performed pairwise comparisons between cases stratified for identifiable rare deleterious genetic variants and controls.

FINDINGS

Cases of presumed monogenic severe epilepsy had an increased PRS for 'all epilepsy' (p<0.0001), 'focal epilepsy' (p<0.0001), and 'GGE' (p=0.0002) relative to controls, which explain between 0.08% and 3.3% of phenotypic variance. PRS was increased in cases both with and without an identified deleterious variant of major effect, and there was no significant difference in PRS between the two groups.

INTERPRETATION

We provide evidence that common genetic variation contributes to the aetiology of DEEs and other forms of epilepsy with ID, even when there is a known pathogenic variant of major effect. These results provide insight into the genetic underpinnings of the severe epilepsies and warrant a shift in our understanding of the aetiology of the DEEs as complex, rather than monogenic, disorders.

FUNDING

Science foundation Ireland, Human Genome Research Institute; National Heart, Lung, and Blood Institute; German Research Foundation.

Atrial fibrillation is associated with a subsequent epilepsy diagnosis independent of stroke: A retrospective matched administrative cohort study on 149,632 patients

Recently there has been a rising interest in the identification and possible prevention of risk factors for epilepsies. In the present study, we investigated the potential association between atrial fibrillation (AF) and epilepsy in a German cohort of ambulatory patients aged ≥18 with an initial diagnosis of atrial fibrillation documented in 1274 general practices in Germany between January 2005 and December 2018. Using the IQVIA Disease Analyzer database, we identified 74,681 ambulatory patients with AF. These were matched 1:1 to patients without AF based on sex, age, index year, yearly consultation frequency, and defined co-diagnoses like stroke. Cox regression models were used to evaluate the association between AF and epilepsy. Within 10 years of the index date, 1.9% of individuals with AF and 1.5% of individuals without AF were diagnosed with epilepsy (log-rank p < 0.001). Atrial fibrillation was significantly associated with an increase in the incidence of epilepsy (Hazard Ratio (HR): 1.51, p < 0.001). The association was significant in all age groups, except in patients >80 years of age (HR: 1.29, p = 0.031). Our study demonstrates that AF is associated with an increased incidence of epilepsy. This finding could help understand the mechanisms of epilepsy in heart disease and to better protect affected individuals in the future.

Impact of Genetic Testing on Therapeutic Decision-Making in Childhood-Onset Epilepsies-a Study in a Tertiary Epilepsy Center

We assessed the frequency of pediatric monogenic epilepsies and precision therapies at a tertiary epilepsy center. We analyzed medical records of children, born in 2006-2011 and followed at the Danish Epilepsy Center from January to December 2015; 357 patients were identified, of whom 27 without epilepsy and 35 with acquired brain damage were excluded. Of the remaining 295 children, 188 were consented for study inclusion and genetic testing. At inclusion, 86/188 had a preexisting genetic diagnosis and did not undergo further genetic testing. The 102 genetically unsolved patients underwent WES, which identified a (likely) pathogenic variant in eight patients and a highly relevant variant of unknown significance (VUS) in seven additional patients. Single nucleotide polymorphism array was performed in the remaining 87 patients and revealed no (likely) pathogenic copy number variants (CNVs). Patients with a genetic diagnosis had a significantly lower median age at seizure onset and more often had febrile seizures, status epilepticus, or neurodevelopmental impairment compared to those who remained genetically unsolved. Most common epilepsies were focal or multifocal epilepsies and developmental and epileptic encephalopathies (DDEs). Fifty-three patients, with a putative genetic diagnosis, were potentially eligible for precision therapy approaches. Indeed, genetic diagnosis enabled treatment adjustment in 32/53 (60%); 30/32 (93%) patients experienced at least a 50% reduction in seizure burden while only 4/32 (12.5%) became seizure-free. In summary, a genetic diagnosis was achieved in approximately 50% of patients with non-acquired epilepsy enabling precision therapy approaches in half of the patients, a strategy that results in > 50% reduction in seizure burden, in the majority of the treated patients.

Common risk variants for epilepsy are enriched in families previously targeted for rare monogenic variant discovery

BACKGROUND

The epilepsies are highly heritable conditions that commonly follow complex inheritance. While monogenic causes have been identified in rare familial epilepsies, most familial epilepsies remain unsolved. We aimed to determine (1) whether common genetic variation contributes to familial epilepsy risk, and (2) whether that genetic risk is enriched in familial compared with non-familial (sporadic) epilepsies.

METHODS

Using common variants derived from the largest epilepsy genome-wide association study, we calculated polygenic risk scores (PRS) for patients with familial epilepsy (n = 1,818 from 1,181 families), their unaffected relatives (n = 771), sporadic patients (n = 1,182), and population controls (n = 15,929). We also calculated separate PRS for genetic generalised epilepsy (GGE) and focal epilepsy. Statistical analyses used mixed-effects regression models to account for familial relatedness, sex, and ancestry.

FINDINGS

Patients with familial epilepsies had higher epilepsy PRS compared to population controls (OR 1·20, p_adj = 5×10^-9), sporadic patients (OR 1·11, p_adj = 0.008), and their own unaffected relatives (OR 1·12, p_adj = 0.01). The top 1% of the PRS distribution was enriched 3.8-fold for individuals with familial epilepsy when compared to the lowest decile (p_adj = 5×10^-11). Familial PRS enrichment was consistent across epilepsy type; overall, polygenic risk was greatest for the GGE clinical group. There was no significant PRS difference in familial cases with established rare variant genetic etiologies compared to unsolved familial cases.

INTERPRETATION

The aggregate effects of common genetic variants, measured as polygenic risk scores, play an important role in explaining why some families develop epilepsy, why specific family members are affected while their relatives are not, and why families manifest specific epilepsy types. Polygenic risk contributes to the complex inheritance of the epilepsies, including in individuals with a known genetic etiology.

FUNDING

National Health and Medical Research Council of Australia, National Institutes of Health, American Academy of Neurology, Thomas B and Jeannette E Laws McCabe Fund, Mirowski Family Foundation.

SCN1A overexpression, associated with a genomic region marked by a risk variant for a common epilepsy, raises seizure susceptibility

Mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures is associated with common variation at rs7587026, located in the promoter region of SCN1A. We sought to explore possible underlying mechanisms. SCN1A expression was analysed in hippocampal biopsy specimens of individuals with mesial temporal lobe epilepsy with hippocampal sclerosis who underwent surgical treatment, and hippocampal neuronal cell loss was quantitatively assessed using immunohistochemistry. In healthy individuals, hippocampal volume was measured using MRI. Analyses were performed stratified by rs7587026 type. To study the functional consequences of increased SCN1A expression, we generated, using transposon-mediated bacterial artificial chromosome transgenesis, a zebrafish line expressing exogenous scn1a, and performed EEG analysis on larval optic tecta at 4 day post-fertilization. Finally, we used an in vitro promoter analysis to study whether the genetic motif containing rs7587026 influences promoter activity. Hippocampal SCN1A expression differed by rs7587026 genotype (Kruskal-Wallis test P = 0.004). Individuals homozygous for the minor allele showed significantly increased expression compared to those homozygous for the major allele (Dunn's test P = 0.003), and to heterozygotes (Dunn's test P = 0.035). No statistically significant differences in hippocampal neuronal cell loss were observed between the three genotypes. Among 597 healthy participants, individuals homozygous for the minor allele at rs7587026 displayed significantly reduced mean hippocampal volume compared to major allele homozygotes (Cohen's D = - 0.28, P = 0.02), and to heterozygotes (Cohen's D = - 0.36, P = 0.009). Compared to wild type, scn1lab-overexpressing zebrafish larvae exhibited more frequent spontaneous seizures [one-way ANOVA F(4,54) = 6.95 (P < 0.001)]. The number of EEG discharges correlated with the level of scn1lab overexpression [one-way ANOVA F(4,15) = 10.75 (P < 0.001]. Finally, we showed that a 50 bp promoter motif containing rs7587026 exerts a strong regulatory role on SCN1A expression, though we could not directly link this to rs7587026 itself. Our results develop the mechanistic link between rs7587026 and mesial temporal lobe epilepsy with hippocampal sclerosis and a history of febrile seizures. Furthermore, we propose that quantitative precision may be important when increasing SCN1A expression in current strategies aiming to treat seizures in conditions involving SCN1A haploinsufficiency, such as Dravet syndrome.

Phenotypic Spectrum in a Family Sharing a Heterozygous KCNQ3 Variant

BACKGROUND AND PURPOSE

Mutations in KCNQ3 have classically been associated with benign familial neonatal and infantile seizures and more recently identified in patients with neurodevelopmental disorders and abnormal electroencephalogram (EEG) findings. We present 4 affected patients from a family with a pathogenic mutation in KCNQ3 with a unique constellation of clinical findings.

METHODS

A family of 3 affected siblings and mother sharing a KCNQ3 pathogenic variant are described, including clinical history, genetic results, and EEG and magnetic resonance imaging (MRI) findings.

RESULTS

This family shows a variety of clinical manifestations, including neonatal seizures, developmental delays, autism spectrum disorder, and anxiety. One child developed absence epilepsy, 2 children have infrequent convulsive seizures that have persisted into childhood, and their parent developed adult-onset epilepsy. An underlying c.1091G>A (R364H) variant in KCNQ3 was found in all affected individuals.

CONCLUSIONS

The phenotypic variability of KCNQ3 channelopathies continues to expand as more individuals and families are described, and the variant identified in this family adds to the understanding of the manifestations of KCNQ3-related disorders.

Association of ultra-rare coding variants with genetic generalized epilepsy: A case-control whole exome sequencing study

OBJECTIVE

We aimed to identify genes associated with genetic generalized epilepsy (GGE) by combining large cohorts enriched with individuals with a positive family history. Secondarily, we set out to compare the association of genes independently with familial and sporadic GGE.

METHODS

We performed a case-control whole exome sequencing study in unrelated individuals of European descent diagnosed with GGE (previously recruited and sequenced through multiple international collaborations) and ancestry-matched controls. The association of ultra-rare variants (URVs; in 18 834 protein-coding genes) with epilepsy was examined in 1928 individuals with GGE (vs. 8578 controls), then separately in 945 individuals with familial GGE (vs. 8626 controls), and finally in 1005 individuals with sporadic GGE (vs. 8621 controls). We additionally examined the association of URVs with familial and sporadic GGE in two gene sets important for inhibitory signaling (19 genes encoding γ-aminobutyric acid type A [GABAA ] receptors, 113 genes representing the GABAergic pathway).

RESULTS

GABRG2 was associated with GGE (p = 1.8 × 10-5 ), approaching study-wide significance in familial GGE (p = 3.0 × 10-6 ), whereas no gene approached a significant association with sporadic GGE. Deleterious URVs in the most intolerant subgenic regions in genes encoding GABAA receptors were associated with familial GGE (odds ratio [OR] = 3.9, 95% confidence interval [CI] = 1.9-7.8, false discovery rate [FDR]-adjusted p = .0024), whereas their association with sporadic GGE had marginally lower odds (OR = 3.1, 95% CI = 1.3-6.7, FDR-adjusted p = .022). URVs in GABAergic pathway genes were associated with familial GGE (OR = 1.8, 95% CI = 1.3-2.5, FDR-adjusted p = .0024) but not with sporadic GGE (OR = 1.3, 95% CI = .9-1.9, FDR-adjusted p = .19).

SIGNIFICANCE

URVs in GABRG2 are likely an important risk factor for familial GGE. The association of gene sets of GABAergic signaling with familial GGE is more prominent than with sporadic GGE.

Functional seizures are associated with cerebrovascular disease and functional stroke is more common in patients with functional seizures than epileptic seizures

PURPOSE

To characterize the relationship between functional seizures (FSe), cerebrovascular disease (CVD), and functional stroke.

METHOD

A retrospective case-control study of 189 patients at a single large tertiary medical center. We performed a manual chart review of medical records of patients with FSe or epileptic seizures (ES), who also had ICD code evidence of CVD. The clinical characteristics of FSe, ES, CVD, and functional stroke were recorded. Logistic regression and Welch's t-tests were used to evaluate the differences between the FSe and ES groups.

RESULTS

Cerebrovascular disease was confirmed in 58.7% and 87.6% of patients with FSe or ES through manual chart review. Stroke was significantly more common in patients with ES (76.29%) than FSe (43.48%) (p = 4.07 × 10^-6). However, compared to nonepileptic controls FSe was associated with both CVD (p < 0.0019) and stroke (p < 6.62 × 10^-10). Functional stroke was significantly more common in patients with FSe (39.13%) than patients with ES (4.12%) (p = 4.47 × 10^-9). Compared to patients with ES, patients with FSe were younger (p = 0.00022), more likely to be female (p = 0.00040), and more likely to have comorbid mental health needs including anxiety (p = 1.06 × 10^-6), PTSD or history of trauma (e.g., sexual abuse) (p = 1.06 × 10^-13), and bipolar disorder (p = 0.0011).

CONCLUSION

Our results confirm the initial observation of increased CVD in patients with FSe and further suggest that patients with FSe may be predisposed to developing another functional neurological disorder (FND) (i.e., functional stroke). We speculate that this may be due to shared risk factors and pathophysiological processes that are common to various manifestations of FND.

NCOR2 is a novel candidate gene for migraine-epilepsy phenotype

HYPOTHESIS

To identify genetic factors predisposing to migraine-epilepsy phenotype utilizing a multi-generational family with known linkage to chr12q24.2-q24.3.

METHODS

We used single nucleotide polymorphism (SNP) genotyping and next-generation sequencing technologies to perform linkage, haplotype, and variant analyses in an extended Finnish migraine-epilepsy family (n = 120). In addition, we used a large genome-wide association study (GWAS) dataset of migraine and two biobank studies, UK Biobank and FinnGen, to test whether variants within the susceptibility region associate with migraine or epilepsy related phenotypes in a population setting.

RESULTS

The family showed the highest evidence of linkage (LOD 3.42) between rs7966411 and epilepsy. The haplotype shared among 12 out of 13 epilepsy patients in the family covers almost the entire NCOR2 and co-localizes with one of the risk loci of the recent GWAS on migraine. The haplotype harbors nine low-frequency variants with potential regulatory functions. Three of them, in addition to two common variants, show nominal associations with neurological disorders in either UK Biobank or FinnGen.

CONCLUSION

We provide several independent lines of evidence supporting association between migraine-epilepsy phenotype and NCOR2. Our study suggests that NCOR2 may have a role in both migraine and epilepsy and thus would provide evidence for shared pathophysiology underlying these two diseases.

Genetic generalized epilepsies in adults - challenging assumptions and dogmas

Genetic generalized epilepsy (GGE) syndromes start during childhood or adolescence, and four commonly persist into adulthood, making up 15-20% of all cases of epilepsy in adults. These four GGE syndromes are childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy and epilepsy with generalized tonic-clonic seizures alone. However, in ~20% of patients with GGE, characteristics of more than one syndrome are present. Novel insights into the genetic aetiology, comorbidities and prognosis of the GGE syndromes have emerged and challenge traditional concepts about these conditions. Evidence has shown that the mode of inheritance in GGE is mostly polygenic. Neuropsychological and imaging studies indicate similar abnormalities in unaffected relatives of patients with GGE, supporting the concept that underlying alterations in bilateral frontothalamocortical networks are genetically determined. Contrary to popular belief, first-line anti-seizure medication often fails to provide seizure freedom in combination with good tolerability. Nevertheless, long-term follow-up studies have shown that with advancing age, many patients can discontinue their anti-seizure medication without seizure relapses. Several outcome predictors have been identified, but prognosis across the syndromes is more homogeneous than previously assumed. Overall, overlap in pathophysiology, seizure types, treatment responses and outcomes support the idea that GGEs are not separate nosological entities but represent a neurobiological continuum.