Purpose Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene–disease associations. Methods We analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects, and characterized the patterns of genotypes enriched across this collection of patients. Results We obtained a genetic diagnosis for 29 (24%) of our patients. We showed that patients carried an excess of damaging de novo mutations in intolerant genes, particularly those shown to be essential in mice (P = 3.4 × 10−8). This enrichment is only partially explained by mutations found in known disease-causing genes. Conclusion This work indicates that the application of appropriate bioinformatics analyses to clinical sequence data can also help implicate novel disease genes and suggest expanded phenotypes for known disease genes. These analyses further suggest that some cases resolved by whole-exome sequencing will have direct therapeutic implications.

This multicenter investigation into the phenotypic correlates of MECP2 mutations in Rett syndrome has provided a greater depth of understanding than hitherto available about the specific phenotypic characteristics associated with commonly occurring mutations. Although the modifying influence of X inactivation on clinical severity could not be included in the analysis, the findings confirm clear genotype-phenotype relationships in Rett syndrome and show the benefits of collaboration crucial to effective research in rare disorders.

Progressive myoclonus epilepsies (PMEs) are a group of rare, inherited disorders manifesting with action myoclonus, tonic-clonic seizures, and ataxia. We exome-sequenced 84 unrelated PME patients of unknown cause and molecularly solved 26 cases (31%). Remarkably, a recurrent de novo mutation c.959G>A (p.Arg320His) in KCNC1 was identified as a novel major cause for PME. Eleven unrelated exome-sequenced (13%) and two patients in a secondary cohort (7%) had this mutation. KCNC1 encodes K V 3.1, a subunit of the K V 3 voltage-gated K + channels, major determinants of high-frequency neuronal firing. Functional analysis of the p.Arg320His mutant channel revealed a dominant-negative loss-of-function effect. Ten patients had pathogenic mutations in known PME-associated genes (NEU1, NHLRC1, AFG3L2, EPM2A, CLN6, SERPINI1). Identification of mutations in PRNP, SACS, and TBC1D24 expand their phenotypic spectrum to PME. These findings provide important insights into the molecular genetic basis of PME and reveal the role of de novo mutations in this disease entity.Correspondence should be addressed to Anna-Elina Lehesjoki (anna-elina.lehesjoki@helsinki.fi). Author Contributions Accession codesMutation nomenclatures correspond to the following canonical Ensembl transcripts: KCNC1, ENST00000265969.6; NEU1, ENST00000375631.4; NHLRC1, ENST00000340650.3; EPM2A, ENST00000367519.3; CLN6, ENST00000249806.5; AFG3L2, ENST00000269143.3; TBC1D24, ENST00000293970.5; SACS, ENST00000382298.3; SERPINI1, ENST00000295777.5; PRNP, ENST00000379440.4; SCN1A, ENST00000303395.4. The raw aligned sequence reads were submitted to the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home) by Wellcome Trust Sanger Institute under study accession numbers EGAS00001000048 and EGAS00001000386. Competing Financial InterestsAuthors declare no potential competing financial interests. Europe PMC Funders GroupAuthor Manuscript Nat Genet. Author manuscript; available in PMC 2015 July 01. Published in final edited form as:Nat Genet. 5,6 and GOSR2 7 also contribute to cases of PME with preserved cognition. Other PMEs may have additional features, particularly dementia. PME-associated genes encode a variety of proteins, many of them being associated with endosomal and lysosomal function 8,9 , but the associated disease mechanisms are generally poorly understood.The precise clinical diagnosis of specific forms of PME is challenging due to their genetic heterogeneity, phenotypic similarities and overlap of symptoms with other epileptic and neurodegenerative diseases. In many cases, there are no distinguishing clinical features or biomarkers. Consequently, a substantial proportion of PME cases remain without a molecular diagnosis 3 .Here, we aimed to identify the causative genes for unsolved PME cases by employing exome sequencing in unrelated patients assembled from multiple centers in Europe, North America, Asia, and Australia over a 25-year period. The extent of previous molecular studies varied, but all cases were negative for mutations in the ...