Severe intellectual disability (ID) occurs in 0.5% of newborns and is thought to be largely genetic in origin. The extensive genetic heterogeneity of this disorder requires a genome-wide detection of all types of genetic variation. Microarray studies and, more recently, exome sequencing have demonstrated the importance of de novo copy number variations (CNVs) and single-nucleotide variations (SNVs) in ID, but the majority of cases remain undiagnosed. Here we applied whole-genome sequencing to 50 patients with severe ID and their unaffected parents. All patients included had not received a molecular diagnosis after extensive genetic prescreening, including microarray-based CNV studies and exome sequencing. Notwithstanding this prescreening, 84 de novo SNVs affecting the coding region were identified, which showed a statistically significant enrichment of loss-of-function mutations as well as an enrichment for genes previously implicated in ID-related disorders. In addition, we identified eight de novo CNVs, including single-exon and intra-exonic deletions, as well as interchromosomal duplications. These CNVs affected known ID genes more frequently than expected. On the basis of diagnostic interpretation of all de novo variants, a conclusive genetic diagnosis was reached in 20 patients. Together with one compound heterozygous CNV causing disease in a recessive mode, this results in a diagnostic yield of 42% in this extensively studied cohort, and 62% as a cumulative estimate in an unselected cohort. These results suggest that de novo SNVs and CNVs affecting the coding region are a major cause of severe ID. Genome sequencing can be applied as a single genetic test to reliably identify and characterize the comprehensive spectrum of genetic variation, providing a genetic diagnosis in the majority of patients with severe ID.
Frontotemporal lobar degeneration with TAR DNA binding protein 43 inclusions (FTLD-TDP) is the most common pathology associated with frontotemporal dementia (FTD). Repeat expansions in chromosome 9 open reading frame 72 (C9ORF72) and mutations in progranulin (GRN) are the major known genetic causes of FTLD-TDP; however, the genetic etiology in the majority of FTLD-TDP remains unexplained. In this study, we performed whole-genome sequencing in 104 pathologically confirmed FTLD-TDP patients from the Mayo Clinic brain bank negative for C9ORF72 and GRN mutations and report on the contribution of rare single nucleotide and copy-number variants in 21 known neurodegenerative disease genes. Interestingly, we identified 5 patients (4.8%) with variants in optineurin (OPTN) and TANK-binding kinase 1 (TBK1) that are predicted to be highly pathogenic, including two double mutants. Case A was a compound heterozygote for mutations in OPTN, carrying the p.Q235* nonsense and p.A481V missense mutation in trans, while case B carried a deletion of OPTN exons 13–15 (p.Gly538Glufs*27) and a loss-of-function mutation (p.Arg117*) in TBK1. Cases C–E carried heterozygous missense mutations in TBK1, including the p.Glu696Lys mutation which was previously reported in two amyotrophic lateral sclerosis (ALS) patients and is located in the OPTN binding domain. Quantitative mRNA expression and protein analysis in cerebellar tissue showed a striking reduction of OPTN and/or TBK1 expression in 4 out of 5 patients supporting pathogenicity in these specific patients and suggesting a loss-of-function disease mechanism. Importantly, neuropathologic examination showed FTLD-TDP type A in the absence of motor neuron disease in 3 pathogenic mutation carriers. In conclusion, we highlight TBK1 as an important cause of pure FTLD-TDP, identify the first OPTN mutations in FTLD-TDP, and suggest a potential oligogenic basis for at least a subset of FTLD-TDP patients. Our data further adds to the growing body of evidence linking ALS and FTD and suggests a key role for the OPTN/TBK1 pathway in these diseases.
The implementation of whole-exome sequencing in clinical diagnostics has generated a need for functional evaluation of genetic variants. In the field of inborn errors of metabolism (IEM), a diverse spectrum of targeted biochemical assays is employed to analyze a limited amount of metabolites. We now present a single-platform, high-resolution liquid chromatography quadrupole time of flight (LC-QTOF) method that can be applied for holistic metabolic profiling in plasma of individual IEM-suspected patients. This method, which we termed “next-generation metabolic screening” (NGMS), can detect >10,000 features in each sample. In the NGMS workflow, features identified in patient and control samples are aligned using the “various forms of chromatography mass spectrometry (XCMS)” software package. Subsequently, all features are annotated using the Human Metabolome Database, and statistical testing is performed to identify significantly perturbed metabolite concentrations in a patient sample compared with controls. We propose three main modalities to analyze complex, untargeted metabolomics data. First, a targeted evaluation can be done based on identified genetic variants of uncertain significance in metabolic pathways. Second, we developed a panel of IEM-related metabolites to filter untargeted metabolomics data. Based on this IEM-panel approach, we provided the correct diagnosis for 42 of 46 IEMs. As a last modality, metabolomics data can be analyzed in an untargeted setting, which we term “open the metabolome” analysis. This approach identifies potential novel biomarkers in known IEMs and leads to identification of biomarkers for as yet unknown IEMs. We are convinced that NGMS is the way forward in laboratory diagnostics of IEMs.Electronic supplementary materialThe online version of this article (10.1007/s10545-017-0131-6) contains supplementary material, which is available to authorized users.
De novo mutations are recognized both as an important source of genetic variation and as a prominent cause of sporadic disease in humans. Mutations identified as de novo are generally assumed to have occurred during gametogenesis and, consequently, to be present as germline events in an individual. Because Sanger sequencing does not provide the sensitivity to reliably distinguish somatic from germline mutations, the proportion of de novo mutations that occur somatically rather than in the germline remains largely unknown. To determine the contribution of post-zygotic events to de novo mutations, we analyzed a set of 107 de novo mutations in 50 parent-offspring trios. Using four different sequencing techniques, we found that 7 (6.5%) of these presumed germline de novo mutations were in fact present as mosaic mutations in the blood of the offspring and were therefore likely to have occurred post-zygotically. Furthermore, genome-wide analysis of "de novo" variants in the proband led to the identification of 4/4,081 variants that were also detectable in the blood of one of the parents, implying parental mosaicism as the origin of these variants. Thus, our results show that an important fraction of de novo mutations presumed to be germline in fact occurred either post-zygotically in the offspring or were inherited as a consequence of low-level mosaicism in one of the parents.
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