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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.

BackgroundCLN2 disease (Neuronal Ceroid Lipofuscinosis Type 2) is an ultra-rare, neurodegenerative lysosomal storage disease, caused by an enzyme deficiency of tripeptidyl peptidase 1 (TPP1). Lack of disease awareness and the non-specificity of presenting symptoms often leads to delayed diagnosis. These guidelines provide robust evidence-based, expert-agreed recommendations on the risks/benefits of disease-modifying treatments and the medical interventions used to manage this condition.MethodsAn expert mapping tool process was developed ranking multidisciplinary professionals, with knowledge of CLN2 disease, diagnostic or management experience of CLN2 disease, or family support professionals. Individuals were sequentially approached to identify two chairs, ensuring that the process was transparent and unbiased. A systematic literature review of published evidence using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance was independently and simultaneously conducted to develop key statements based upon the strength of the publications. Clinical care statements formed the basis of an international modified Delphi consensus determination process using the virtual meeting (Within3) online platform which requested experts to agree or disagree with any changes. Statements reaching the consensus mark became the guiding statements within this manuscript, which were subsequently assessed against the Appraisal of Guidelines for Research and Evaluation (AGREEII) criteria.ResultsTwenty-one international experts from 7 different specialities, including a patient advocate, were identified. Fifty-three guideline statements were developed covering 13 domains: General Description and Statements, Diagnostics, Clinical Recommendations and Management, Assessments, Interventions and Treatment, Additional Care Considerations, Social Care Considerations, Pain Management, Epilepsy / Seizures, Nutritional Care Interventions, Respiratory Health, Sleep and Rest, and End of Life Care. Consensus was reached after a single round of voting, with one exception which was revised, and agreed by 100% of the SC and achieved 80% consensus in the second voting round. The overall AGREE II assessment score obtained for the development of the guidelines was 5.7 (where 1 represents the lowest quality, and 7 represents the highest quality).ConclusionThis program provides robust evidence- and consensus-driven guidelines that can be used by all healthcare professionals involved in the management of patients with CLN2 disease and other neurodegenerative disorders. This addresses the clinical need to complement other information available.

ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations.MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome-wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses.ResultsOur analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations.SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy.

ObjectiveClassification of epilepsy into types and subtypes is important for both clinical care and research into underlying disease mechanisms. A quantitative, data-driven approach may augment traditional electroclinical classification and shed new light on existing classification frameworks.MethodsWe used latent class analysis, a statistical method that assigns subjects into groups called latent classes based on phenotypic elements, to classify individuals with common familial epilepsies from the Epi4K Multiplex Families study. Phenotypic elements included seizure types, seizure symptoms, and other elements of the medical history. We compared class assignments to traditional electroclinical classifications and assessed familial aggregation of latent classes.ResultsA total of 1120 subjects with epilepsy were assigned to five latent classes. Classes 1 and 2 contained subjects with generalized epilepsy, largely reflecting the distinction between absence epilepsies and younger onset (class 1) versus myoclonic epilepsies and older onset (class 2). Classes 3 and 4 contained subjects with focal epilepsies, and in contrast to classes 1 and 2, these did not adhere as closely to clinically defined focal epilepsy subtypes. Class 5 contained nearly all subjects with febrile seizures plus or unknown epilepsy type, as well as a few subjects with generalized epilepsy and a few with focal epilepsy. Family concordance of latent classes was similar to or greater than concordance of clinically defined epilepsy types.SignificanceQuantitative classification of epilepsy has the potential to augment traditional electroclinical classification by (1) combining some syndromes into a single class, (2) splitting some syndromes into different classes, (3) helping to classify subjects who could not be classified clinically, and (4) defining the boundaries of clinically defined classifications. This approach can guide future research, including molecular genetic studies, by identifying homogeneous sets of individuals that may share underlying disease mechanisms.

Objective: To assess the possible effects of genetics on seizure outcome by estimating the familial aggregation of three outcome measures: seizure remission, history of ≥4 tonic–clonic seizures, and seizure control for individuals taking antiseizure medication. Methods: We analyzed families containing multiple persons with epilepsy in four previously collected retrospective cohorts. Seizure remission was defined as being 5 and 10 years seizure‐free at last observation. Total number of tonic–clonic seizures was dichotomized at <4 and ≥4 seizures. Seizure control in patients taking antiseizure medication was defined as no seizures for 1, 2, and 3 years. We used Bayesian generalized linear mixed‐effects model (GLMM) to estimate the intraclass correlation coefficient (ICC) of the family‐specific random effect, controlling for epilepsy type, age at epilepsy onset, and age at last data collection as fixed effects. We analyzed each cohort separately and performed meta‐analysis using GLMMs. Results: The combined cohorts included 3644 individuals with epilepsy from 1463 families. A history of ≥4 tonic–clonic seizures showed strong familial aggregation in three separate cohorts and meta‐analysis (ICC.28, 95% confidence interval [CI].21–.35, Bayes factor 8 × 1016). Meta‐analyses did not reveal significant familial aggregation of seizure remission (ICC.08, 95% CI.01–.17, Bayes factor 1.46) or seizure control for individuals taking antiseizure medication (ICC.13, 95% CI 0–.35, Bayes factor 0.94), with heterogeneity among cohorts. Significance: A history of ≥4 tonic–clonic seizures aggregated strongly in families, suggesting a genetic influence, whereas seizure remission and seizure control for individuals taking antiseizure medications did not aggregate consistently in families. Different seizure outcomes may have different underlying biology and risk factors. These findings should inform the future molecular genetic studies of seizure outcomes. [ABSTRACT FROM AUTHOR]

Exome sequencing has readily enabled the discovery of the genetic mutations responsible for a wide range of diseases. This success has been particularly remarkable in the severe epilepsies and other neurodevelopmental diseases for which rare, often de novo, mutations play a significant role in disease risk. Despite significant progress, the high genetic heterogeneity of these disorders often requires large sample sizes to identify a critical mass of individuals with disease-causing mutations in a single gene. By pooling genetic findings across multiple studies, we have identified six individuals with severe developmental delay (6/6), refractory seizures (5/6), and similar dysmorphic features (3/6), each harboring a de novo mutation in PPP3CA. PPP3CA encodes the alpha isoform of a subunit of calcineurin. Calcineurin encodes a calcium- and calmodulin-dependent serine/threonine protein phosphatase that plays a role in a wide range of biological processes, including being a key regulator of synaptic vesicle recycling at nerve terminals. Five individuals with de novo PPP3CA mutations were identified among 4,760 trio probands with neurodevelopmental diseases; this is highly unlikely to occur by chance (p = 1.2 × 10-8) given the size and mutability of the gene. Additionally, a sixth individual with a de novo mutation in PPP3CA was connected to this study through GeneMatcher. Based on these findings, we securely implicate PPP3CA in early-onset refractory epilepsy and further support the emerging role for synaptic dysregulation in epilepsy.

Gene identification in epilepsy has mainly been limited to large families segregating genes of major effect and de novo mutations in epileptic encephalopathies. Many families that present with common non-acquired focal epilepsies and genetic generalized epilepsies remain unexplained. We assembled a cohort of 'genetically enriched' common epilepsies by collecting and phenotyping families containing multiple individuals with unprovoked seizures. We aimed to determine if specific clinical epilepsy features aggregate within families, and whether this segregation of phenotypes may constitute distinct 'familial syndromes' that could inform genomic analyses. Families with three or more individuals with unprovoked seizures were studied across multiple international centres. Affected individuals were phenotyped and classified according to specific electroclinical syndromes. Families were categorized based on syndromic groupings of affected family members, examined for pedigree structure and phenotypic patterns and, where possible, assigned specific familial epilepsy syndromes. A total of 303 families were assembled and analysed, comprising 1120 affected phenotyped individuals. Of the 303 families, 117 exclusively segregated generalized epilepsy, 62 focal epilepsy, and 22 were classified as genetic epilepsy with febrile seizures plus. Over one-third (102 families) were observed to have mixed epilepsy phenotypes: 78 had both generalized and focal epilepsy features within the same individual (n = 39), or within first or second degree relatives (n = 39). Among the genetic generalized epilepsy families, absence epilepsies were found to cluster within families independently of juvenile myoclonic epilepsy, and significantly more females were affected than males. Of the 62 familial focal epilepsy families, two previously undescribed familial focal syndrome patterns were evident: 15 families had posterior quadrant epilepsies, including seven with occipito-temporal localization and seven with temporo-parietal foci, and four families displayed familial focal epilepsy of childhood with multiple affected siblings that was suggestive of recessive inheritance. The findings suggest (i) specific patterns of syndromic familial aggregation occur, including newly recognized forms of familial focal epilepsy; (ii) although syndrome-specificity usually occurs in multiplex families, the one-third of families with features of both focal and generalized epilepsy is suggestive of shared genetic determinants; and (iii) patterns of features observed across families including pedigree structure, sex, and age of onset may hold clues for future gene identification. Such detailed phenotypic information will be invaluable in the conditioning and interpretation of forthcoming sequencing data to understand the genetic architecture and inter-relationships of the common epilepsy syndromes.

Trio exome sequencing has been successful in identifying genes with de novo mutations (DNMs) causing epileptic encephalopathy (EE) and other neurodevelopmental disorders. Here, we evaluate how well a case-control collapsing analysis recovers genes causing dominant forms of EE originally implicated by DNM analysis. We performed a genome-wide search for an enrichment of "qualifying variants" in protein-coding genes in 488 unrelated cases compared to 12,151 unrelated controls. These "qualifying variants" were selected to be extremely rare variants predicted to functionally impact the protein to enrich for likely pathogenic variants. Despite modest sample size, three known EE genes (KCNT1, SCN2A, and STXBP1) achieved genome-wide significance (p

Epileptic encephalopathies (EEs) are the most clinically important group of severe early-onset epilepsies. Next-generation sequencing has highlighted the crucial contribution of de novo mutations to the genetic architecture of EEs as well as to their underlying genetic heterogeneity. Our previous whole-exome sequencing study of 264 parent-child trios revealed more than 290 candidate genes in which only a single individual had a de novo variant. We sought to identify additional pathogenic variants in a subset (n = 27) of these genes via targeted sequencing in an unsolved cohort of 531 individuals with a diverse range of EEs. We report 17 individuals with pathogenic variants in seven of the 27 genes, defining a genetic etiology in 3.2% of this unsolved cohort. Our results provide definitive evidence that de novo mutations in SLC1A2 and CACNA1A cause specific EEs and expand the compendium of clinically relevant genotypes for GABRB3. We also identified EEs caused by genetic variants in ALG13, DNM1, and GNAO1 and report a mutation in IQSEC2. Notably, recurrent mutations accounted for 7/17 of the pathogenic variants identified. As a result of high-depth coverage, parental mosaicism was identified in two out of 14 cases tested with mutant allelic fractions of 5%-6% in the unaffected parents, carrying significant reproductive counseling implications. These results confirm that dysregulation in diverse cellular neuronal pathways causes EEs, and they will inform the diagnosis and management of individuals with these devastating disorders.

Infantile spasms (IS) and Lennox-Gastaut syndrome (LGS) are epileptic encephalopathies characterized by early onset, intractable seizures, and poor developmental outcomes. De novo sequence mutations and copy number variants (CNVs) are causative in a subset of cases. We used exome sequence data in 349 trios with IS or LGS to identify putative de novo CNVs. We confirm 18 de novo CNVs in 17 patients (4.8%), 10 of which are likely pathogenic, giving a firm genetic diagnosis for 2.9% of patients. Confirmation of exome-predicted CNVs by array-based methods is still required due to false-positive rates of prediction algorithms. Our exome-based results are consistent with recent array-based studies in similar cohorts and highlight novel candidate genes for IS and LGS.

Emerging evidence indicates that epileptic encephalopathies are genetically highly heterogeneous, underscoring the need for large cohorts of well-characterized individuals to further define the genetic landscape. Through a collaboration between two consortia (EuroEPINOMICS and Epi4K/EPGP), we analyzed exome-sequencing data of 356 trios with the "classical" epileptic encephalopathies, infantile spasms and Lennox Gastaut syndrome, including 264 trios previously analyzed by the Epi4K/EPGP consortium. In this expanded cohort, we find 429 de novo mutations, including de novo mutations in DNM1 in five individuals and de novo mutations in GABBR2, FASN, and RYR3 in two individuals each. Unlike previous studies, this cohort is sufficiently large to show a significant excess of de novo mutations in epileptic encephalopathy probands compared to the general population using a likelihood analysis (p = 8.2 × 10(-4)), supporting a prominent role for de novo mutations in epileptic encephalopathies. We bring statistical evidence that mutations in DNM1 cause epileptic encephalopathy, find suggestive evidence for a role of three additional genes, and show that at least 12% of analyzed individuals have an identifiable causal de novo mutation. Strikingly, 75% of mutations in these probands are predicted to disrupt a protein involved in regulating synaptic transmission, and there is a significant enrichment of de novo mutations in genes in this pathway in the entire cohort as well. These findings emphasize an important role for synaptic dysregulation in epileptic encephalopathies, above and beyond that caused by ion channel dysfunction.

BackgroundAlthough there is increasing recognition of the role of somatic mutations in genetic disorders, the prevalence of somatic mutations in neurodevelopmental disease and the optimal techniques to detect somatic mosaicism have not been systematically evaluated.MethodsUsing a customized panel of known and candidate genes associated with brain malformations, we applied targeted high-coverage sequencing (depth, ≥200×) to leukocyte-derived DNA samples from 158 persons with brain malformations, including the double-cortex syndrome (subcortical band heterotopia, 30 persons), polymicrogyria with megalencephaly (20), periventricular nodular heterotopia (61), and pachygyria (47). We validated candidate mutations with the use of Sanger sequencing and, for variants present at unequal read depths, subcloning followed by colony sequencing.ResultsValidated, causal mutations were found in 27 persons (17%; range, 10 to 30% for each phenotype). Mutations were somatic in 8 of the 27 (30%), predominantly in persons with the double-cortex syndrome (in whom we found mutations in DCX and LIS1), persons with periventricular nodular heterotopia (FLNA), and persons with pachygyria (TUBB2B). Of the somatic mutations we detected, 5 (63%) were undetectable with the use of traditional Sanger sequencing but were validated through subcloning and subsequent sequencing of the subcloned DNA. We found potentially causal mutations in the candidate genes DYNC1H1, KIF5C, and other kinesin genes in persons with pachygyria.ConclusionsTargeted sequencing was found to be useful for detecting somatic mutations in patients with brain malformations. High-coverage sequencing panels provide an important complement to whole-exome and whole-genome sequencing in the evaluation of somatic mutations in neuropsychiatric disease. (Funded by the National Institute of Neurological Disorders and Stroke and others.).

Objective: Copy number variants (CNVs) contribute to genetic risk and genetic etiology of both rare and common epilepsies. Whereas many studies have explored the role of CNVs in sporadic or severe cases, fewer have been done in familial generalized and focal epilepsies. Methods: We analyzed exome sequence data from 267 multiplex families and 859 first‐degree relative pairs with a diagnosis of genetic generalized epilepsies or nonacquired focal epilepsies to predict CNVs. Validation and segregation studies were performed using an orthogonal method when possible. Results: We identified CNVs likely to contribute to epilepsy risk or etiology in the probands of 43 of 1116 (3.9%) families, including known recurrent CNVs (16p13.11 deletion, 15q13.3 deletion, 15q11.2 deletion, 16p11.2 duplication, 1q21.1 duplication, and 5‐Mb duplication of 15q11q13). We also identified CNVs affecting monogenic epilepsy genes, including four families with CNVs disrupting the DEPDC5 gene, and a de novo deletion of HNRNPU in one affected individual from a multiplex family. Several large CNVs (>500 kb) of uncertain clinical significance were identified, including a deletion in 18q, a large duplication encompassing the SCN1A gene, and a 15q13.3 duplication (BP4‐BP5). Significance: The overall CNV landscape in common familial epilepsies is similar to that of sporadic epilepsies, with large recurrent deletions at 15q11, 15q13, and 16p13 contributing in 2.5%–3% of families. CNVs that interrupt known epilepsy genes and rare, large CNVs were also identified. Multiple etiologies were found in a subset of families, emphasizing the importance of genetic testing for multiple affected family members. Rare CNVs found in a single proband remain difficult to interpret and require larger cohorts to confirm their potential role in disease. Overall, our work indicates that CNVs contribute to the complex genetic architecture of familial generalized and focal epilepsies, supporting the role for clinical testing in affected individuals. [ABSTRACT FROM AUTHOR]

Objective: People with neuropsychiatric symptoms often experience delay in accurate diagnosis. Although cerebrospinal fluid neurofilament light (CSF NfL) shows promise in distinguishing neurodegenerative disorders (ND) from psychiatric disorders (PSY), its accuracy in a diagnostically challenging cohort longitudinally is unknown. Methods: We collected longitudinal diagnostic information (mean = 36 months) from patients assessed at a neuropsychiatry service, categorising diagnoses as ND/mild cognitive impairment/other neurological disorders (ND/MCI/other) and PSY. We pre-specified NfL > 582 pg/mL as indicative of ND/MCI/other. Results: Diagnostic category changed from initial to final diagnosis for 23% (49/212) of patients. NfL predicted the final diagnostic category for 92% (22/24) of these and predicted final diagnostic category overall (ND/MCI/other vs. PSY) in 88% (187/212), compared to 77% (163/212) with clinical assessment alone. Conclusions: CSF NfL improved diagnostic accuracy, with potential to have led to earlier, accurate diagnosis in a real-world setting using a pre-specified cut-off, adding weight to translation of NfL into clinical practice. [ABSTRACT FROM AUTHOR]