Association of ultra-rare coding variants with genetic generalized epilepsy: A case\u2013control 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\u2013control 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 \u3b3-aminobutyric acid type A [GABAA] receptors, 113 genes representing the GABAergic pathway). Results: GABRG2 was associated with GGE (p = 1.8  7 10 125), approaching study-wide significance in familial GGE (p = 3.0  7 10 126), 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\u20137.8, false discovery rate [FDR]-adjusted p =.0024), whereas their association with sporadic GGE had marginally lower odds (OR = 3.1, 95% CI = 1.3\u20136.7, FDR-adjusted p =.022). URVs in GABAergic pathway genes were associated with familial GGE (OR = 1.8, 95% CI = 1.3\u20132.5, FDR-adjusted p =.0024) but not with sporadic GGE (OR = 1.3, 95% CI =.9\u20131.9, 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

Application of rare variant transmission disequilibrium tests to epileptic encephalopathy trio sequence data

The classic epileptic encephalopathies, including infantile spasms (IS) and Lennox–Gastaut syndrome (LGS), are severe seizure disorders that usually arise sporadically. De novo variants in genes mainly encoding ion channel and synaptic proteins have been found to account for over 15% of patients with IS or LGS. The contribution of autosomal recessive genetic variation, however, is less well understood. We implemented a rare variant transmission disequilibrium test (TDT) to search for autosomal recessive epileptic encephalopathy genes in a cohort of 320 outbred patient–parent trios that were generally prescreened for rare metabolic disorders. In the current sample, our rare variant transmission disequilibrium test did not identify individual genes with significantly distorted transmission over expectation after correcting for the multiple tests. While the rare variant transmission disequilibrium test did not find evidence of a role for individual autosomal recessive genes, our current sample is insufficiently powered to assess the overall role of autosomal recessive genotypes in an outbred epileptic encephalopathy population

Ultra-rare genetic variation in common epilepsies: a case-control sequencing study

BACKGROUND:Despite progress in understanding the genetics of rare epilepsies, the more common epilepsies have proven less amenable to traditional gene-discovery analyses. We aimed to assess the contribution of ultra-rare genetic variation to common epilepsies. METHODS:We did a case-control sequencing study with exome sequence data from unrelated individuals clinically evaluated for one of the two most common epilepsy syndromes: familial genetic generalised epilepsy, or familial or sporadic non-acquired focal epilepsy. Individuals of any age were recruited between Nov 26, 2007, and Aug 2, 2013, through the multicentre Epilepsy Phenome/Genome Project and Epi4K collaborations, and samples were sequenced at the Institute for Genomic Medicine (New York, USA) between Feb 6, 2013, and Aug 18, 2015. To identify epilepsy risk signals, we tested all protein-coding genes for an excess of ultra-rare genetic variation among the cases, compared with control samples with no known epilepsy or epilepsy comorbidity sequenced through unrelated studies. FINDINGS:We separately compared the sequence data from 640 individuals with familial genetic generalised epilepsy and 525 individuals with familial non-acquired focal epilepsy to the same group of 3877 controls, and found significantly higher rates of ultra-rare deleterious variation in genes established as causative for dominant epilepsy disorders (familial genetic generalised epilepsy: odd ratio [OR] 2·3, 95% CI 1·7-3·2, p=9·1 × 10-8; familial non-acquired focal epilepsy 3·6, 2·7-4·9, p=1·1 × 10-17). Comparison of an additional cohort of 662 individuals with sporadic non-acquired focal epilepsy to controls did not identify study-wide significant signals. For the individuals with familial non-acquired focal epilepsy, we found that five known epilepsy genes ranked as the top five genes enriched for ultra-rare deleterious variation. After accounting for the control carrier rate, we estimate that these five genes contribute to the risk of epilepsy in approximately 8% of individuals with familial non-acquired focal epilepsy. Our analyses showed that no individual gene was significantly associated with familial genetic generalised epilepsy; however, known epilepsy genes had lower p values relative to the rest of the protein-coding genes (p=5·8 × 10-8) that were lower than expected from a random sampling of genes. INTERPRETATION:We identified excess ultra-rare variation in known epilepsy genes, which establishes a clear connection between the genetics of common and rare, severe epilepsies, and shows that the variants responsible for epilepsy risk are exceptionally rare in the general population. Our results suggest that the emerging paradigm of targeting of treatments to the genetic cause in rare devastating epilepsies might also extend to a proportion of common epilepsies. These findings might allow clinicians to broadly explain the cause of these syndromes to patients, and lay the foundation for possible precision treatments in the future. FUNDING:National Institute of Neurological Disorders and Stroke (NINDS), and Epilepsy Research UK

Early Onset Epileptic Encephalopathy: Genetic Analysis and Further Delineation of Genotype-phenotype Correlation

Objective: Early onset epileptic encephalopathy (EOEE)remains an important diagnostic and therapeutic challenge.The objective was to perform genetic analysis in patientswith EOEE and to further delineate the genotype-phenotype correlation in patients with EOEE. Methods: We recruited 15 refractory epileptic patientswith epileptic onset before age 12 months. All patients had metabolic screening, electroencephalogram, magnetic reso-nance imaging and molecular analysis (comparative genomic hybridization, gene sequencing, next generation sequencing and or whole exome sequencing. Results: Dravet syndrome (DS) with SCN1A mutations was found in six patients with refractory epilepsy (RE) andmoderate to severe developmental delay (DD). Two patients diagnosed (KCNT1, SCN) with malignant migrating partialseizure (MMPS) had RE, severe DD, autistic behavior. The latter had movement disorders (video) (choreoathetosis, ballis-mus) with a worse outcome than the patients with DS phe-notype with SCN1A mutations. Severe DD and RE wasfound in patients with SCN8A, SLC13A5, SMC1A, orHCFC1 and ATRX mutations. Patient with SCN2A mutation had severe DD. A better outcome was observed in the patient with CDKL5 mutations in the catalytic domain in compari-son with the patient with a deletion in Xp22.13 including CDKL5. The patient with SMC1A mutations disclosed the Cornelia de Lange syndrome phenotype (Table 1). TRXmutations and deletions in 2q24.3 and Xp22.13. In SLC13A5 and SCN2A mutations, epileptic onset occurred atthe earliest age

A clinical diagnostic algorithm for early onset cerebellar ataxia

Early onset cerebellar Ataxia (EOAc) comprises a large group of rare heterogeneous disorders. Determination of the underlying etiology can be difficult given the broad differential diagnosis and the complexity of the genotype-phenotype relationships. This may change the diagnostic work-up into a time-consuming, costly and not always rewarding task. In this overview, the Childhood Ataxia and Cerebellar Group of the European Pediatric Neurology Society (CACG-EPNS) presents a diagnostic algorithm for EOAc patients. In seven consecutive steps, the algorithm leads the clinician through the diagnostic process, including EOA identification, application of the Inventory of Non-Ataxic Signs (INAS), consideration of the family history, neuro-imaging, laboratory investigations, genetic testing by array CGH and Next Generation Sequencing (NGS). In children with EOAc, this algorithm is intended to contribute to the diagnostic process and to allow uniform data entry in EOAc databases. (C) 2019 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.</p