Data-driven historical characterization of epilepsy-associated genes

Unusual Voltage-Gated Sodium and Potassium Channelopathies Related to Epilepsy

BACKGROUND AND PURPOSE

There is extensive literature on monogenic epilepsies caused by mutations in familiar channelopathy genes such as SCN1A. However, information on other less-common channelopathy genes is scarce. This study aimed to explore the genetic and clinical characteristics of patients diagnosed with unusual voltage-gated sodium and potassium channelopathies related to epilepsy.

METHODS

This observational, retrospective study analyzed pediatric patients with epilepsy who carried pathogenic variants of unusual voltage-gated sodium and potassium channelopathy genes responsible for seizure-associated phenotypes. Targeted next-generation sequencing (NGS) panel tests were performed between November 2016 and June 2022 at Severance Children's Hospital, Seoul, South Korea. Clinical characteristics and the treatment responses to different types of antiseizure medications were further analyzed according to different types of gene mutation.

RESULTS

This study included 15 patients with the following unusual voltage-gated sodium and potassium channelopathy genes: SCN3A (n=1), SCN4A (n=1), KCNA1 (n=1), KCNA2 (n=4), KCNB1 (n=6), KCNC1 (n=1), and KCNMA1 (n=1). NGS-based genetic testing identified 13 missense mutations (87%), 1 splice-site variant (7%), and 1 copy-number variant (7%). Developmental and epileptic encephalopathy was diagnosed in nine (60%) patients. Seizure freedom was eventually achieved in eight (53%) patients, whereas seizures persisted in seven (47%) patients.

CONCLUSIONS

Our findings broaden the genotypic and phenotypic spectra of less-common voltage-gated sodium and potassium channelopathies associated with epilepsy.

Genetic and phenotypic landscape of pediatric-onset epilepsy in 142 Indian families: Counseling and therapeutic implications

The application of genomic technologies has led to unraveling of the complex genetic landscape of disorders of epilepsy, gaining insights into their underlying disease mechanisms, aiding precision medicine, and providing informed genetic counseling. We herein present the phenotypic and genotypic insights from 142 Indian families with epilepsy with or without comorbidities. Based on the electroclinical findings, epilepsy syndrome diagnosis could be made in 44% (63/142) of the families adopting the latest proposal for the classification by the ILAE task force (2022). Of these, 95% (60/63) of the families exhibited syndromes with developmental epileptic encephalopathy or progressive neurological deterioration. A definitive molecular diagnosis was achieved in 74 of 142 (52%) families. Infantile-onset epilepsy was noted in 81% of these families (61/74). Fifty-five monogenic, four chromosomal, and one imprinting disorder were identified in 74 families. The genetic variants included 65 (96%) single-nucleotide variants/small insertion-deletions, 1 (2%) copy-number variant, and 1 (2%) triplet-repeat expansion in 53 epilepsy-associated genes causing monogenic disorders. Of these, 35 (52%) variants were novel. Therapeutic implications were noted in 51% of families (38/74) with definitive diagnosis. Forty-one out of 66 families with monogenic disorders exhibited autosomal recessive and inherited autosomal dominant disorders with high risk of recurrence.

Providing quality care for people with CDKL5 deficiency disorder: A European expert panel opinion on the patient journey

Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is a developmental and epileptic encephalopathy caused by variants in the CDKL5 gene. The disorder is characterized by intractable early-onset seizures, severe neurodevelopmental delay, hypotonia, motor disabilities, cerebral (cortical) visual impairment and microcephaly. With no disease-modifying therapies available for CDD, treatment is symptomatic with an initial focus on seizure control. Another unmet need in the management of people with CDD is the lack of evidence to aid standardized care and guideline development. To address this gap, experts in CDD and representatives from patient advocacy groups from Denmark, Finland, France, Germany, Italy, Poland, Spain, and the United Kingdom convened to form an Expert Working Group. The aim was to provide an expert opinion consensus on how to ensure quality care in routine clinical practice within the European setting, including in settings with limited experience or resources for multidisciplinary care of CDD and other developmental and epileptic encephalopathies. By means of one-to-one interviews around the current treatment landscape in CDD, insights from the Expert Working Group were collated and developed into a Europe-specific patient journey for individuals with CDD, which was later validated by the group. Further discussions followed to gain consensus of opinions on challenges and potential solutions for achieving quality care in this setting. The panel recognized the benefit of early genetic testing, a holistic personalized approach to seizure control (taking into consideration various factors such as concomitant medications and comorbidities), and age- and comorbidity-dependent multidisciplinary care for optimizing patient outcomes and quality of life. However, their insights and experiences also highlighted much disparity in management approaches and resources across different European countries. Development of standardized European recommendations is required to align realistic diagnostic criteria, treatment goals, and management approaches that can be adapted for different settings. PLAIN LANGUAGE SUMMARY: Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is a rare condition caused by a genetic mutation with a broad range of symptoms apparent from early childhood, including epileptic seizures that do not respond to medication and severe delays in development. Due to the lack of guidance on managing CDD, international experts and patient advocates discussed best practices in the care of people with CDD in Europe. The panel agreed that early testing, a personalized approach to managing seizures, and access to care from different disciplines are beneficial. Development of guidelines to ensure that care is standardized would also be valuable.

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.

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.

Two epilepsy-associated variants in KCNA2 (KV 1.2) at position H310 oppositely affect channel functional expression

Two KCNA2 variants (p.H310Y and p.H310R) were discovered in paediatric patients with epilepsy and developmental delay. KCNA2 encodes KV 1.2-channel subunits, which regulate neuronal excitability. Both gain and loss of KV 1.2 function cause epilepsy, precluding the prediction of variant effects; and while H310 is conserved throughout the KV -channel superfamily, it is largely understudied. We investigated both variants in heterologously expressed, human KV 1.2 channels by immunocytochemistry, electrophysiology and voltage-clamp fluorometry. Despite affecting the same channel, at the same position, and being associated with severe neurological disease, the two variants had diametrically opposite effects on KV 1.2 functional expression. The p.H310Y variant produced 'dual gain of function', increasing both cell-surface trafficking and activity, delaying channel closure. We found that the latter is due to the formation of a hydrogen bond that stabilizes the active state of the voltage-sensor domain. Additionally, H310Y abolished 'ball and chain' inactivation of KV 1.2 by KV β1 subunits, enhancing gain of function. In contrast, p.H310R caused 'dual loss of function', diminishing surface levels by multiple impediments to trafficking and inhibiting voltage-dependent channel opening. We discuss the implications for KV -channel biogenesis and function, an emergent hotspot for disease-associated variants, and mechanisms of epileptogenesis. KEY POINTS: KCNA2 encodes the subunits of KV 1.2 voltage-activated, K+ -selective ion channels, which regulate electrical signalling in neurons. We characterize two KCNA2 variants from patients with developmental delay and epilepsy. Both variants affect position H310, highly conserved in KV channels. The p.H310Y variant caused 'dual gain of function', increasing both KV 1.2-channel activity and the number of KV 1.2 subunits on the cell surface. H310Y abolished 'ball and chain' (N-type) inactivation of KV 1.2 by KV β1 subunits, enhancing the gain-of-function phenotype. The p.H310R variant caused 'dual loss of function', diminishing the presence of KV 1.2 subunits on the cell surface and inhibiting voltage-dependent channel opening. As H310Y stabilizes the voltage-sensor active conformation and abolishes N-type inactivation, it can serve as an investigative tool for functional and pharmacological studies.

Classification of missense variants in the N-methyl-d-aspartate receptor GRIN gene family as gain- or loss-of-function

Advances in sequencing technology have generated a large amount of genetic data from patients with neurological conditions. These data have provided diagnosis of many rare diseases, including a number of pathogenic de novo missense variants in GRIN genes encoding N-methyl-d-aspartate receptors (NMDARs). To understand the ramifications for neurons and brain circuits affected by rare patient variants, functional analysis of the variant receptor is necessary in model systems. For NMDARs, this functional analysis needs to assess multiple properties in order to understand how variants could impact receptor function in neurons. One can then use these data to determine whether the overall actions will increase or decrease NMDAR-mediated charge transfer. Here, we describe an analytical and comprehensive framework by which to categorize GRIN variants as either gain-of-function (GoF) or loss-of-function (LoF) and apply this approach to GRIN2B variants identified in patients and the general population. This framework draws on results from six different assays that assess the impact of the variant on NMDAR sensitivity to agonists and endogenous modulators, trafficking to the plasma membrane, response time course and channel open probability. We propose to integrate data from multiple in vitro assays to arrive at a variant classification, and suggest threshold levels that guide confidence. The data supporting GoF and LoF determination are essential to assessing pathogenicity and patient stratification for clinical trials as personalized pharmacological and genetic agents that can enhance or reduce receptor function are advanced. This approach to functional variant classification can generalize to other disorders associated with missense variants.

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.