Developmental and epileptic encephalopathy (DEE) is a group of conditions characterized by the co-occurrence of epilepsy and intellectual disability (ID), typically with developmental plateauing or regression associated with frequent epileptiform activity. The cause of DEE remains unknown in the majority of cases. We performed whole-genome sequencing (WGS) in 197 individuals with unexplained DEE and pharmaco-resistant seizures and in their unaffected parents. We focused our attention on de novo mutations (DNMs) and identified candidate genes containing such variants. We sought to identify additional subjects with DNMs in these genes by performing targeted sequencing in another series of individuals with DEE and by mining various sequencing datasets. We also performed meta-analyses to document enrichment of DNMs in candidate genes by leveraging our WGS dataset with those of several DEE and ID series. By combining these strategies, we were able to provide a causal link between DEE and the following genes: NTRK2, GABRB2, CLTC, DHDDS, NUS1, RAB11A, GABBR2, and SNAP25. Overall, we established a molecular diagnosis in 63/197 (32%) individuals in our WGS series. The main cause of DEE in these individuals was de novo point mutations (53/63 solved cases), followed by inherited mutations (6/63 solved cases) and de novo CNVs (4/63 solved cases). De novo missense variants explained a larger proportion of individuals in our series than in other series that were primarily ascertained because of ID. Moreover, these DNMs were more frequently recurrent than those identified in ID series. These observations indicate that the genetic landscape of DEE might be different from that of ID without epilepsy.

The standard of care for first-tier clinical investigation of the aetiology of congenital malformations and neurodevelopmental disorders is chromosome microarray analysis (CMA) for copy-number variations (CNVs), often followed by gene(s)-specific sequencing searching for smaller insertion–deletions (indels) and single-nucleotide variant (SNV) mutations. Whole-genome sequencing (WGS) has the potential to capture all classes of genetic variation in one experiment; however, the diagnostic yield for mutation detection of WGS compared to CMA, and other tests, needs to be established. In a prospective study we utilised WGS and comprehensive medical annotation to assess 100 patients referred to a paediatric genetics service and compared the diagnostic yield versus standard genetic testing. WGS identified genetic variants meeting clinical diagnostic criteria in 34% of cases, representing a fourfold increase in diagnostic rate over CMA (8%; P value=1.42E−05) alone and more than twofold increase in CMA plus targeted gene sequencing (13%; P value=0.0009). WGS identified all rare clinically significant CNVs that were detected by CMA. In 26 patients, WGS revealed indel and missense mutations presenting in a dominant (63%) or a recessive (37%) manner. We found four subjects with mutations in at least two genes associated with distinct genetic disorders, including two cases harbouring a pathogenic CNV and SNV. When considering medically actionable secondary findings in addition to primary WGS findings, 38% of patients would benefit from genetic counselling. Clinical implementation of WGS as a primary test will provide a higher diagnostic yield than conventional genetic testing and potentially reduce the time required to reach a genetic diagnosis.

Summary Objective Epilepsy is a common neurologic disorder of childhood. To determine the genetic diagnostic yield in epileptic encephalopathy, we performed a retrospective cohort study in a single epilepsy genetics clinic. Methods We included all patients with intractable epilepsy, global developmental delay, and cognitive dysfunction seen between January 2012 and June 2014 in the Epilepsy Genetics Clinic. Electronic patient charts were reviewed for clinical features, neuroimaging, biochemical investigations, and molecular genetic investigations including targeted next‐generation sequencing of epileptic encephalopathy genes. Results Genetic causes were identified in 28% of the 110 patients: 7% had inherited metabolic disorders including pyridoxine dependent epilepsy caused by ALDH7A1 mutation, Menkes disease, pyridox(am)ine‐5‐phosphate oxidase deficiency, cobalamin G deficiency, methylenetetrahydrofolate reductase deficiency, glucose transporter 1 deficiency, glycine encephalopathy, and pyruvate dehydrogenase complex deficiency; 21% had other genetic causes including genetic syndromes, pathogenic copy number variants on array comparative genomic hybridization, and epileptic encephalopathy related to mutations in the SCN1A, SCN2A, SCN8A, KCNQ2, STXBP1, PCDH19, and SLC9A6 genes. Forty‐five percent of patients obtained a genetic diagnosis by targeted next‐generation sequencing epileptic encephalopathy panels. It is notable that 4.5% of patients had a treatable inherited metabolic disease. Significance To the best of our knowledge, this is the first study to combine inherited metabolic disorders and other genetic causes of epileptic encephalopathy. Targeted next‐generation sequencing panels increased the genetic diagnostic yield from <10% to >25% in patients with epileptic encephalopathy.

The system of assigning locus symbols to specify chromosomal regions that are associated with a familial disorder has a number of problems when used as a reference list of genetically determined disorders,including (I) erroneously assigned loci, (II) duplicated loci, (III) missing symbols or loci, (IV) unconfirmed loci and genes, (V) a combination of causative genes and risk factor genes in the same list, and (VI) discordance between phenotype and list assignment. In this article, we report on the recommendations of the International Parkinson and Movement Disorder Society Task Force for Nomenclature of Genetic Movement Disorders and present a system for naming genetically determined movement disorders that addresses these problems. We demonstrate how the system would be applied to currently known genetically determined parkinsonism, dystonia, dominantly inherited ataxia, spastic paraparesis, chorea, paroxysmal movement disorders, neurodegeneration with brain iron accumulation, and primary familial brain calcifications. This system provides a resource for clinicians and researchers that, unlike the previous system, can be considered an accurate and criterion-based list of confirmed genetically determined movement disorders at the time it was last updated.

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Guanidinoactetate methyltransferase deficiency should be considered in patients with unexplained intellectual disability, and urinary guanidinoacetate should be determined as an initial diagnostic approach.

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