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IMPORTANCE: Mesial temporal lobe epilepsy (MTLE) is the most common focal epilepsy subtype and is often refractory to antiseizure medications. While most patients with MTLE do not have pathogenic germline genetic variants, the contribution of postzygotic (ie, somatic) variants in the brain is unknown. OBJECTIVE: To test the association between pathogenic somatic variants in the hippocampus and MTLE. DESIGN, SETTING, AND PARTICIPANTS: This case-control genetic association study analyzed the DNA derived from hippocampal tissue of neurosurgically treated patients with MTLE and age-matched and sex-matched neurotypical controls. Participants treated at level 4 epilepsy centers were enrolled from 1988 through 2019, and clinical data were collected retrospectively. Whole-exome and gene-panel sequencing (each genomic region sequenced more than 500 times on average) were used to identify candidate pathogenic somatic variants. A subset of novel variants was functionally evaluated using cellular and molecular assays. Patients with nonlesional and lesional (mesial temporal sclerosis, focal cortical dysplasia, and low-grade epilepsy-associated tumors) drug-resistant MTLE who underwent anterior medial temporal lobectomy were eligible. All patients with available frozen tissue and appropriate consents were included. Control brain tissue was obtained from neurotypical donors at brain banks. Data were analyzed from June 2020 to August 2022. EXPOSURES: Drug-resistant MTLE. MAIN OUTCOMES AND MEASURES: Presence and abundance of pathogenic somatic variants in the hippocampus vs the unaffected temporal neocortex. RESULTS: Of 105 included patients with MTLE, 53 (50.5%) were female, and the median (IQR) age was 32 (26-44) years; of 30 neurotypical controls, 11 (36.7%) were female, and the median (IQR) age was 37 (18-53) years. Eleven pathogenic somatic variants enriched in the hippocampus relative to the unaffected temporal neocortex (median [IQR] variant allele frequency, 1.92 [1.5-2.7] v

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 contr ols (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.

Hypothalamic hamartoma with gelastic seizures is a well-established cause of drug-resistant epilepsy in early life. The development of novel surgical techniques has permitted the genomic interrogation of hypothalamic hamartoma tissue. This has revealed causative mosaic variants within GLI3, OFD1 and other key regulators of the sonic-hedgehog pathway in a minority of cases. Sonic-hedgehog signalling proteins localize to the cellular organelle primary cilia. We therefore explored the hypothesis that cilia gene variants may underlie hitherto unsolved cases of sporadic hypothalamic hamartoma. We performed high-depth exome sequencing and chromosomal microarray on surgically resected hypothalamic hamartoma tissue and paired leukocyte-derived DNA from 27 patients. We searched for both germline and somatic variants under both dominant and bi-allelic genetic models. In hamartoma-derived DNA of seven patients we identified bi-allelic (one germline, one somatic) variants within one of four cilia genes-DYNC2I1, DYNC2H1, IFT140 or SMO. In eight patients, we identified single somatic variants in the previously established hypothalamic hamartoma disease genes GLI3 or OFD1. Overall, we established a plausible molecular cause for 15/27 (56%) patients. Here, we expand the genetic architecture beyond single variants within dominant disease genes that cause sporadic hypothalamic hamartoma to bi-allelic (one germline/one somatic) variants, implicate three novel cilia genes and reconceptualize the disorder as a ciliopathy.

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, padj = 5×10-9), sporadic patients (OR 1·11, padj = 0.008), and their own unaffected relatives (OR 1·12, padj = 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 (padj = 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 gene

CSNK2B has recently been implicated as a disease gene for neurodevelopmental disability (NDD) and epilepsy. Information about developmental outcomes has been limited by the young age and short follow-up for many of the previously reported cases, and further delineation of the spectrum of associated phenotypes is needed. We present 25 new patients with variants in CSNK2B and refine the associated NDD and epilepsy phenotypes. CSNK2B variants were identified by research or clinical exome sequencing, and investigators from different centers were connected via GeneMatcher. Most individuals had developmental delay and generalized epilepsy with onset in the first 2 years. However, we found a broad spectrum of phenotypic severity, ranging from early normal development with pharmacoresponsive seizures to profound intellectual disability with intractable epilepsy and recurrent refractory status epilepticus. These findings suggest that CSNK2B should be considered in the diagnostic evaluation of patients with a broad range of NDD with treatable or intractable seizures.

OBJECTIVE: We sought to identify novel genes and to establish the contribution of known genes in a large cohort of patients with nonsyndromic sporadic polymicrogyria and epilepsy. METHODS: We enrolled participants with polymicrogyria and their parents through the Epilepsy Phenome/Genome Project. We performed phenotyping and whole exome sequencing (WES), trio analysis, and gene-level collapsing analysis to identify de novo or inherited variants, including germline or mosaic (postzygotic) single nucleotide variants, small insertion-deletion (indel) variants, and copy number variants present in leukocyte-derived DNA. RESULTS: Across the cohort of 86 individuals with polymicrogyria and epilepsy, we identified seven with pathogenic or likely pathogenic variants in PIK3R2, including four germline and three mosaic variants. PIK3R2 was the only gene harboring more than expected de novo variants across the entire cohort, and likewise the only gene that passed the genome-wide threshold of significance in the gene-level rare variant collapsing analysis. Consistent with previous reports, the PIK3R2 phenotype consisted of bilateral polymicrogyria concentrated in the perisylvian region with macrocephaly. Beyond PIK3R2, we also identified one case each with likely causal de novo variants in CCND2 and DYNC1H1 and biallelic variants in WDR62, all genes previously associated with polymicrogyria. Candidate genetic explanations in this cohort included single nucleotide de novo variants in other epilepsy-associated and neurodevelopmental disease-associated genes (SCN2A in two individuals, GRIA3, CACNA1C) and a 597-kb deletion at 15q25, a neurodevelopmental disease susceptibility locus. SIGNIFICANCE: This study confirms germline and postzygotically acquired de novo variants in PIK3R2 as an important cause of bilateral perisylvian polymicrogyria, notably with macrocephaly. In total, trio-based WES identified a genetic diagnosis in 12% and a candidate diagnosis in 6% of our polymicrogyria

Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.

Cytogenic testing is routinely applied in most neurological centres for severe paediatric epilepsies. However, which characteristics of copy number variants (CNVs) confer most epilepsy risk and which epilepsy subtypes carry the most CNV burden, have not been explored on a genome-wide scale. Here, we present the largest CNV investigation in epilepsy to date with 10 712 European epilepsy cases and 6746 ancestry-matched controls. Patients with genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, and developmental and epileptic encephalopathy were included. All samples were processed with the same technology and analysis pipeline. All investigated epilepsy types, including lesional focal epilepsy patients, showed an increase in CNV burden in at least one tested category compared to controls. However, we observed striking differences in CNV burden across epilepsy types and investigated CNV categories. Genetic generalized epilepsy patients have the highest CNV burden in all categories tested, followed by developmental and epileptic encephalopathy patients. Both epilepsy types also show association for deletions covering genes intolerant for truncating variants. Genome-wide CNV breakpoint association showed not only significant loci for genetic generalized and developmental and epileptic encephalopathy patients but also for lesional focal epilepsy patients. With a 34-fold risk for developing genetic generalized epilepsy, we show for the first time that the established epilepsy-associated 15q13.3 deletion represents the strongest risk CNV for genetic generalized epilepsy across the whole genome. Using the human interactome, we examined the largest connected component of the genes overlapped by CNVs in the four epilepsy types. We observed that genetic generalized epilepsy and non-acquired focal epilepsy formed disease modules. In summary, we show that in all common epilepsy types, 1.5-3% of patients carry epilepsy-associated CNVs. The character

OBJECTIVE: Recent reports have described single individuals with neurodevelopmental disability (NDD) harboring heterozygous KCNQ3 de novo variants (DNVs). We sought to assess whether pathogenic variants in KCNQ3 cause NDD and to elucidate the associated phenotype and molecular mechanisms. METHODS: Patients with NDD and KCNQ3 DNVs were identified through an international collaboration. Phenotypes were characterized by clinical assessment, review of charts, electroencephalographic (EEG) recordings, and parental interview. Functional consequences of variants were analyzed in vitro by patch-clamp recording. RESULTS: Eleven patients were assessed. They had recurrent heterozygous DNVs in KCNQ3 affecting residues R230 (R230C, R230H, R230S) and R227 (R227Q). All patients exhibited global developmental delay within the first 2 years of life. Most (8/11, 73%) were nonverbal or had a few words only. All patients had autistic features, and autism spectrum disorder (ASD) was diagnosed in 5 of 11 (45%). EEGs performed before 10 years of age revealed frequent sleep-activated multifocal epileptiform discharges in 8 of 11 (73%). For 6 of 9 (67%) recorded between 1.5 and 6 years of age, spikes became near-continuous during sleep. Interestingly, most patients (9/11, 82%) did not have seizures, and no patient had seizures in the neonatal period. Voltage-clamp recordings of the mutant KCNQ3 channels revealed gain-of-function (GoF) effects. INTERPRETATION: Specific GoF variants in KCNQ3 cause NDD, ASD, and abundant sleep-activated spikes. This new phenotype contrasts both with self-limited neonatal epilepsy due to KCNQ3 partial loss of function, and with the neonatal or infantile onset epileptic encephalopathies due to KCNQ2 GoF. ANN NEUROL 2019;86:181-192.

OBJECTIVE: Classification 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. METHODS: We 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. RESULTS: A 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. SIGNIFICANCE: Quantitative 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 identifyi

OBJECTIVE: The Epilepsy Genetics Initiative (EGI) was formed in 2014 to create a centrally managed database of clinically generated exome sequence data. EGI performs systematic research-based reanalysis to identify new molecular diagnoses that were not possible at the time of initial sequencing and to aid in novel gene discovery. Herein we report on the efficacy of this approach 3 years after inception. METHODS: One hundred sixty-six individuals with epilepsy who underwent diagnostic whole exome sequencing (WES) were enrolled, including 139 who had not received a genetic diagnosis. Sequence data were transferred to the EGI and periodically reevaluated on a research basis. RESULTS: Eight new diagnoses were made as a result of updated annotations or the discovery of novel epilepsy genes after the initial diagnostic analysis was performed. In five additional cases, we provided new evidence to support or contradict the likelihood of variant pathogenicity reported by the laboratory. One novel epilepsy gene was discovered through dual interrogation of research and clinically generated WES. SIGNIFICANCE: EGI's diagnosis rate of 5.8% represents a considerable increase in diagnostic yield and demonstrates the value of periodic reinterrogation of whole exome data. The initiative's contributions to gene discovery underscore the importance of data sharing and the value of collaborative enterprises.

PurposeAs part of the Epilepsy Genetics Initiative, we re-evaluated clinically generated exome sequence data from 54 epilepsy patients and their unaffected parents to identify molecular diagnoses not provided in the initial diagnostic interpretation.MethodsWe compiled and analyzed exome sequence data from 54 genetically undiagnosed trios using a validated analysis pipeline. We evaluated the significance of the genetic findings by reanalyzing sequence data generated at Ambry Genetics, and from a number of additional case and control cohorts.ResultsIn 54 previously undiagnosed trios, we identified two de novo missense variants in SCN8A in the highly expressed alternative exon 5 A-an exon only recently added to the Consensus Coding Sequence database. One additional undiagnosed epilepsy patient harboring a de novo variant in exon 5 A was found in the Ambry Genetics cohort. Missense variants in SCN8A exon 5 A are extremely rare in the population, further supporting the pathogenicity of the de novo alterations identified.ConclusionThese results expand the range of SCN8A variants in epileptic encephalopathy patients and illustrate the necessity of ongoing reanalysis of negative exome sequences, as advances in the knowledge of disease genes and their annotations will permit new diagnoses to be made.

This is the second of a 2-part primer on the genetics of the epilepsies within the Genetic Literacy Series of the Genetics Commission of the International League Against Epilepsy. In Part 1, we covered types of genetic variation, inheritance patterns, and their relationship to disease. In Part 2, we apply these basic principles to the case of a young boy with epileptic encephalopathy and ask 3 important questions: (1) Is the gene in question an established genetic etiology for epilepsy? (2) Is the variant in this particular gene pathogenic by established variant interpretation criteria? (3) Is the variant considered causative in the clinical context? These questions are considered and then answered for the clinical case in question.

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology.

Periventricular nodular heterotopia (PVNH) is a malformation of cortical development commonly associated with epilepsy. We exome sequenced 202 individuals with sporadic PVNH to identify novel genetic risk loci. We first performed a trio-based analysis and identified 219 de novo variants. Although no novel genes were implicated in this initial analysis, PVNH cases were found overall to have a significant excess of nonsynonymous de novo variants in intolerant genes (p = 3.27x10-7), suggesting a role for rare new alleles in genes yet to be associated with the condition. Using a gene-level collapsing analysis comparing cases and controls, we identified a genome-wide significant signal driven by four ultra-rare loss-of-function heterozygous variants in MAP1B, including one de novo variant. In at least one instance, the MAP1B variant was inherited from a parent with previously undiagnosed PVNH. The PVNH was frontally predominant and associated with perisylvian polymicrogyria. These results implicate MAP1B in PVNH. More broadly, our findings suggest that detrimental mutations likely arising in immediately preceding generations with incomplete penetrance may also be responsible for some apparently sporadic diseases.

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<2.68×10-6). In addition, six of the 10 most significantly associated genes are known EE genes, and the majority of the known EE genes (17 out of 25) originally implicated in trio sequencing are nominally significant (p<0.05), a proportion significantly higher than the expected (Fisher's exact p = 2.33×10-17). Our results indicate that a case-control collapsing analysis can identify several of the EE genes originally implicated in trio sequencing studies, and clearly show that additional genes would be implicated with larger sample sizes. The case-control analysis not only makes discovery easier and more economical in early onset disorders, particularly when large cohorts are available, but also supports the use of this approach to identify genes in diseases that present later in life when parents are not readily available.

Identifying the underlying causes of disease requires accurate interpretation of genetic variants. Current methods ineffectively capture pathogenic non-coding variants in genic regions, resulting in overlooking synonymous and intronic variants when searching for disease risk. Here we present the Transcript-inferred Pathogenicity (TraP) score, which uses sequence context alterations to reliably identify non-coding variation that causes disease. High TraP scores single out extremely rare variants with lower minor allele frequencies than missense variants. TraP accurately distinguishes known pathogenic and benign variants in synonymous (AUC = 0.88) and intronic (AUC = 0.83) public datasets, dismissing benign variants with exceptionally high specificity. TraP analysis of 843 exomes from epilepsy family trios identifies synonymous variants in known epilepsy genes, thus pinpointing risk factors of disease from non-coding sequence data. TraP outperforms leading methods in identifying non-coding variants that are pathogenic and is therefore a valuable tool for use in gene discovery and the interpretation of personal genomes.While non-coding synonymous and intronic variants are often not under strong selective constraint, they can be pathogenic through affecting splicing or transcription. Here, the authors develop a score that uses sequence context alterations to predict pathogenicity of synonymous and non-coding genetic variants, and provide a web server of pre-computed scores.

Technological advances have paved the way for accelerated genomic discovery and are bringing precision medicine clearly into view. Epilepsy research in particular is well suited to serve as a model for the development and deployment of targeted therapeutics in precision medicine because of the rapidly expanding genetic knowledge base in epilepsy, the availability of good in-vitro and in-vivo model systems to efficiently study the biological consequences of genetic mutations, the ability to turn these models into effective drug-screening platforms, and the establishment of collaborative research groups. Moving forward, it is crucial that these collaborations are strengthened, particularly through integrated research platforms, to provide robust analyses both for accurate personal genome analysis and gene and drug discovery. Similarly, the implementation of clinical trial networks will allow the expansion of patient sample populations with genetically defined epilepsy so that drug discovery can be translated into clinical practice.

This is the first of a two-part primer on the genetics of the epilepsies within the Genetic Literacy Series of the Genetics Commission of the International League Against Epilepsy. In Part 1, we cover the foundations of epilepsy genetics including genetic epidemiology and the range of genetic variants that can affect the risk for developing epilepsy. We discuss various epidemiologic study designs that have been applied to the genetics of the epilepsies including population studies, which provide compelling evidence for a strong genetic contribution in many epilepsies. We discuss genetic risk factors varying in size, frequency, inheritance pattern, effect size, and phenotypic specificity, and provide examples of how genetic risk factors within the various categories increase the risk for epilepsy. We end by highlighting trends in epilepsy genetics including the increasing use of massive parallel sequencing technologies.

BACKGROUND: Mutations in the gene ATP1A3 have recently been identified to be prevalent in patients with alternating hemiplegia of childhood (AHC2). Based on a large series of patients with AHC, we set out to identify the spectrum of different mutations within the ATP1A3 gene and further establish any correlation with phenotype. METHODS: Clinical data from an international cohort of 155 AHC patients (84 females, 71 males; between 3 months and 52 years) were gathered using a specifically formulated questionnaire and analysed relative to the mutational ATP1A3 gene data for each patient. RESULTS: In total, 34 different ATP1A3 mutations were detected in 85 % (132/155) patients, seven of which were novel. In general, mutations were found to cluster into five different regions. The most frequent mutations included: p.Asp801Asn (43 %; 57/132), p.Glu815Lys (16 %; 22/132), and p.Gly947Arg (11 %; 15/132). Of these, p.Glu815Lys was associated with a severe phenotype, with more severe intellectual and motor disability. p.Asp801Asn appeared to confer a milder phenotypic expression, and p.Gly947Arg appeared to correlate with the most favourable prognosis, compared to the other two frequent mutations. Overall, the comparison of the clinical profiles suggested a gradient of severity between the three major mutations with differences in intellectual (p = 0.029) and motor (p = 0.039) disabilities being statistically significant. For patients with epilepsy, age at onset of seizures was earlier for patients with either p.Glu815Lys or p.Gly947Arg mutation, compared to those with p.Asp801Asn mutation (p < 0.001). With regards to the five mutation clusters, some clusters appeared to correlate with certain clinical phenotypes. No statistically significant clinical correlations were found between patients with and without ATP1A3 mutations. CONCLUSIONS: Our results, demonstrate a highly variable clinical phenotype in patients with AHC2 that correlates with certain mutations and possibly clust

OBJECTIVE: To elucidate the functional consequences of epileptic encephalopathy-causing de novo mutations in DNM1 (A177P, K206N, G359A), which encodes a large mechanochemical GTPase essential for neuronal synaptic vesicle endocytosis. METHODS: HeLa and COS-7 cells transfected with wild-type and mutant DNM1 constructs were used for transferrin assays, high-content imaging, colocalization studies, Western blotting, and electron microscopy (EM). EM was also conducted on the brain sections of mice harboring a middle-domain Dnm1 mutation (Dnm1 (Ftfl)). RESULTS: We demonstrate that the expression of each mutant protein decreased endocytosis activity in a dominant-negative manner. One of the G-domain mutations, K206N, decreased protein levels. The G359A mutation, which occurs in the middle domain, disrupted higher-order DNM1 oligomerization. EM of mutant DNM1-transfected HeLa cells and of the Dnm1 (Ftfl) mouse brain revealed vesicle defects, indicating that the mutations likely interfere with DNM1's vesicle scission activity. CONCLUSION: Together, these data suggest that the dysfunction of vesicle scission during synaptic vesicle endocytosis can lead to serious early-onset epilepsies.

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.

BACKGROUND: Mutations in the gene ATP1A3 have recently been identified to be prevalent in patients with alternating hemiplegia of childhood (AHC2). Based on a large series of patients with AHC, we set out to identify the spectrum of different mutations within the ATP1A3 gene and further establish any correlation with phenotype. METHODS: Clinical data from an international cohort of 155 AHC patients (84 females, 71 males; between 3 months and 52 years) were gathered using a specifically formulated questionnaire and analysed relative to the mutational ATP1A3 gene data for each patient. RESULTS: In total, 34 different ATP1A3 mutations were detected in 85 % (132/155) patients, seven of which were novel. In general, mutations were found to cluster into five different regions. The most frequent mutations included: p.Asp801Asn (43 %; 57/132), p.Glu815Lys (16 %; 22/132), and p.Gly947Arg (11 %; 15/132). Of these, p.Glu815Lys was associated with a severe phenotype, with more severe intellectual and motor disability. p.Asp801Asn appeared to confer a milder phenotypic expression, and p.Gly947Arg appeared to correlate with the most favourable prognosis, compared to the other two frequent mutations. Overall, the comparison of the clinical profiles suggested a gradient of severity between the three major mutations with differences in intellectual (p = 0.029) and motor (p = 0.039) disabilities being statistically significant. For patients with epilepsy, age at onset of seizures was earlier for patients with either p.Glu815Lys or p.Gly947Arg mutation, compared to those with p.Asp801Asn mutation (p < 0.001). With regards to the five mutation clusters, some clusters appeared to correlate with certain clinical phenotypes. No statistically significant clinical correlations were found between patients with and without ATP1A3 mutations. CONCLUSIONS: Our results, demonstrate a highly variable clinical phenotype in patients with AHC2 that correlates with certain mutations and possibly clust

A central challenge in interpreting personal genomes is determining which mutations most likely influence disease. Although progress has been made in scoring the functional impact of individual mutations, the characteristics of the genes in which those mutations are found remain largely unexplored. For example, genes known to carry few common functional variants in healthy individuals may be judged more likely to cause certain kinds of disease than genes known to carry many such variants. Until now, however, it has not been possible to develop a quantitative assessment of how well genes tolerate functional genetic variation on a genome-wide scale. Here we describe an effort that uses sequence data from 6503 whole exome sequences made available by the NHLBI Exome Sequencing Project (ESP). Specifically, we develop an intolerance scoring system that assesses whether genes have relatively more or less functional genetic variation than expected based on the apparently neutral variation found in the gene. To illustrate the utility of this intolerance score, we show that genes responsible for Mendelian diseases are significantly more intolerant to functional genetic variation than genes that do not cause any known disease, but with striking variation in intolerance among genes causing different classes of genetic disease. We conclude by showing that use of an intolerance ranking system can aid in interpreting personal genomes and identifying pathogenic mutations.

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox-Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10(-3)). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10(-10) and P = 7.8 × 10(-12), respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10(-8)), as has been reported previously for autism spectrum disorders.

We identified a small family with autosomal recessive, infantile onset epilepsy and intellectual disability. Exome sequencing identified a homozygous missense variant in the gene TNK2, encoding a brain-expressed tyrosine kinase. Sequencing of the coding region of TNK2 in 110 patients with a similar phenotype failed to detect further homozygote or compound heterozygote mutations. Pathogenicity of the variant is supported by the results of our functional studies, which demonstrated that the variant abolishes NEDD4 binding to TNK2, preventing its degradation after epidermal growth factor stimulation. Definitive proof of pathogenicity will require confirmation in unrelated patients.

Alternating hemiplegia of childhood (AHC) is a rare, severe neurodevelopmental syndrome characterized by recurrent hemiplegic episodes and distinct neurological manifestations. AHC is usually a sporadic disorder and has unknown etiology. We used exome sequencing of seven patients with AHC and their unaffected parents to identify de novo nonsynonymous mutations in ATP1A3 in all seven individuals. In a subsequent sequence analysis of ATP1A3 in 98 other patients with AHC, we found that ATP1A3 mutations were likely to be responsible for at least 74% of the cases; we also identified one inherited mutation in a case of familial AHC. Notably, most AHC cases are caused by one of seven recurrent ATP1A3 mutations, one of which was observed in 36 patients. Unlike ATP1A3 mutations that cause rapid-onset dystonia-parkinsonism, AHC-causing mutations in this gene caused consistent reductions in ATPase activity without affecting the level of protein expression. This work identifies de novo ATP1A3 mutations as the primary cause of AHC and offers insight into disease pathophysiology by expanding the spectrum of phenotypes associated with mutations in ATP1A3.