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Intellectual disability (ID) is a severe neurodevelopmental disorder with genetically heterogeneous causes. Large-scale sequencing has led to the identification of many gene-disrupting mutations; however, a substantial proportion of cases lack a molecular diagnosis. As such, there remains much to uncover for a complete understanding of the genetic underpinnings of ID. Genetic variants present in non-coding regions of the genome have been highlighted as potential contributors to neurodevelopmental disorders given their role in regulating gene expression. Nevertheless the functional characterization of non-coding variants remains challenging. We describe the identification and characterization of de novo non-coding variation in 3′UTR regulatory regions within an ID cohort of 50 patients. This cohort was previously screened for structural and coding pathogenic variants via CNV, whole exome and whole genome analysis. We identified 44 high-confidence single nucleotide non-coding variants within the 3′UTR regions of these 50 genomes. Four of these variants were located within predicted miRNA binding sites and were thus hypothesised to have regulatory consequences. Functional testing showed that two of the variants interfered with miRNA-mediated regulation of their target genes, AMD1 and FAIM. Both these variants were found in the same individual and their functional consequences may point to a potential role for such variants in intellectual disability.

Upon the discovery of numerous genes involved in the pathogenesis of neurodevelopmental disorders, several studies showed that a significant proportion of these genes converge on common pathways and protein networks. Here, we used a reversed approach, by screening the AnkyrinG protein-protein interaction network for genetic variation in a large cohort of 1009 cases with neurodevelopmental disorders. We identified a significant enrichment of de novo potentially disease-causing variants in this network, confirming that this protein network plays an important role in the emergence of several neurodevelopmental disorders.

Background The interleukin (IL)-1 pathway is primarily associated with innate immunological defense and plays a major role in the induction and regulation of inflammation. Both common and rare genetic variation in this pathway underlies various inflammation-mediated diseases, but the role of rare variants relative to common variants in immune response variability in healthy individuals remains unclear. Methods We performed molecular inversion probe sequencing on 48 IL-1 pathway-related genes in 463 healthy individuals from the Human Functional Genomics Project. We functionally grouped common and rare variants, over gene, subpathway, and inflammatory levels and performed the Sequence Kernel Association Test to test for association with in vitro stimulation-induced cytokine responses; specifically, IL-1β and IL-6 cytokine measurements upon stimulations that represent an array of microbial infections: lipopolysaccharide (LPS), phytohaemagglutinin (PHA), Candida albicans ( C. albicans ), and Staphylococcus aureus ( S. aureus ). Results We identified a burden of NCF4 rare variants with PHA-induced IL-6 cytokine and showed that the respective carriers are in the 1% lowest IL-6 producers. Collapsing rare variants in IL-1 subpathway genes produces a bidirectional association with LPS-induced IL-1β cytokine levels, which is reflected by a significant Spearman correlation. On the inflammatory level, we identified a burden of rare variants in genes encoding for proteins with an anti-inflammatory function with S. aureus -induced IL-6 cytokine. In contrast to these rare variant findings which were based on different types of stimuli, common variant associations were exclusively identified with C. albicans -induced cytokine over various levels of grouping, from the gene, to subpathway, to inflammatory level. Conclusions In conclusion, this study shows that functionally grouping common and rare genetic variants enables the elucidation IL-1-mediated biological mechanisms, specifically, for IL-1β and IL-6 cytokine responses induced by various stimuli. The framework used in this study may allow for the analysis of rare and common genetic variants in a wider variety of (non-immune) complex phenotypes and therefore has the potential to contribute to better understanding of unresolved, complex traits and diseases.

Anorectal malformations (ARM) are rare congenital malformations, resulting from disturbed hindgut development. A genetic etiology has been suggested, but evidence for the involvement of specific genes is scarce. We evaluated the contribution of rare and low-frequency coding variants in ARM etiology, assuming a multifactorial model. We analyzed 568 Caucasian ARM patients and 1,860 population-based controls using the Illumina HumanExome Beadchip array, which contains >240,000 rare and low-frequency coding variants. GenomeStudio clustering and calling was followed by re-calling of 'no-calls' using zCall for patients and controls simultaneously. Single variant and gene-based analyses were performed to identify statistically significant associations, applying Bonferroni correction. Following an extra quality control step, candidate variants were selected for validation using Sanger sequencing. When we applied a MAF of ≥1.0%, no variants or genes showed statistically significant associations with ARM. Using a MAF cut-off at 0.4%, 13 variants initially reached statistical significance, but had to be discarded upon further inspection: ten variants represented calling errors of the software, while the minor alleles of the remaining three variants were not confirmed by Sanger sequencing. Our results show that rare and low-frequency coding variants with large effect sizes, present on the exome chip do not contribute to ARM etiology.

Inborn errors of metabolism (IEM) are inherited conditions caused by genetic defects in enzymes or cofactors. These defects result in a specific metabolic fingerprint in patient body fluids, showing accumulation of substrate or lack of an end-product of the defective enzymatic step. Untargeted metabolomics has evolved as a high throughput methodology offering a comprehensive readout of this metabolic fingerprint. This makes it a promising tool for diagnostic screening of IEM patients. However, the size and complexity of metabolomics data have posed a challenge in translating this avalanche of information into knowledge, particularly for clinical application. We have previously established next-generation metabolic screening (NGMS) as a metabolomics-based diagnostic tool for analyzing plasma of individual IEM-suspected patients. To fully exploit the clinical potential of NGMS, we present a computational pipeline to streamline the analysis of untargeted metabolomics data. This pipeline allows for time-efficient and reproducible data analysis, compatible with ISO:15189 accredited clinical diagnostics. The pipeline implements a combination of tools embedded in a workflow environment for large-scale clinical metabolomics data analysis. The accompanying graphical user interface aids end-users from a diagnostic laboratory for efficient data interpretation and reporting. We also demonstrate the application of this pipeline with a case study and discuss future prospects.

Genotype-first combined with reverse phenotyping has shown to be a powerful tool in human genetics, especially in the era of next generation sequencing. This combines the identification of individuals with mutations in the same gene and linking these to consistent (endo)phenotypes to establish disease causality. We have performed a MIP (molecular inversion probe)-based targeted re-sequencing study in 3,275 individuals with intellectual disability (ID) to facilitate a genotype-first approach for 24 genes previously implicated in ID.Combining our data with data from a publicly available database, we confirmed 11 of these 24 genes to be relevant for ID. Amongst these, PHIP was shown to have an enrichment of disruptive mutations in the individuals with ID (5 out of 3,275). Through international collaboration, we identified a total of 23 individuals with PHIP mutations and elucidated the associated phenotype. Remarkably, all 23 individuals had developmental delay/ID and the majority were overweight or obese. Other features comprised behavioral problems (hyperactivity, aggression, features of autism and/or mood disorder) and dysmorphisms (full eyebrows and/or synophrys, upturned nose, large ears and tapering fingers). Interestingly, PHIP encodes two protein-isoforms, PHIP/DCAF14 and NDRP, each involved in neurodevelopmental processes, including E3 ubiquitination and neuronal differentiation. Detailed genotype-phenotype analysis points towards haploinsufficiency of PHIP/DCAF14, and not NDRP, as the underlying cause of the phenotype.Thus, we demonstrated the use of large scale re-sequencing by MIPs, followed by reverse phenotyping, as a constructive approach to verify candidate disease genes and identify novel syndromes, highlighted by PHIP haploinsufficiency causing an ID-overweight syndrome.

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 add to the growing body of evidence linking ALS and FTD and suggest a key role for the OPTN/TBK1 pathway in these diseases.

Whole-genome sequencing is used to identify genetic alterations in patients with severe intellectual disability for whom all other tests, including array and exome sequencing, returned negative results; de novo single-nucleotide and copy number variations affecting the coding region seem to be a major cause of this disorder. Gene variation in intellectual disability Intellectual disability has been shown to be linked to genetic variation but the majority of cases remain undiagnosed. This paper demonstrates the use of whole-genome sequencing to identify genetic alterations in patients with severe intellectual disability for whom all other tests, including array and exome sequencing, had returned negative results. Whole-genome sequencing of 50 patients with severe intellectual disability — and with no family history of the condition — resulted in a conclusive genetic diagnosis in 21 patients. The results suggest that de novo copy number variations and single-nucleotide variations affecting the coding region are a major cause of severe intellectual disability. Severe intellectual disability (ID) occurs in 0.5% of newborns and is thought to be largely genetic in origin 1 , 2 . 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 3 , 4 , 5 , 6 . 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.

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.

ObjectiveGout is characterised by severe interleukin (IL)-1-mediated joint inflammation induced by monosodium urate crystals. Since IL-37 is a pivotal anti-inflammatory cytokine suppressing the activity of IL-1, we conducted genetic and functional studies aimed at elucidating the role of IL-37 in the pathogenesis and treatment of gout.MethodsVariant identification was performed by DNA sequencing of all coding bases of IL37 using molecular inversion probe-based resequencing (discovery cohort: gout n=675, controls n=520) and TaqMan genotyping (validation cohort: gout n=2202, controls n=2295). Predictive modelling of the effects of rare variants on protein structure was followed by in vitro experiments evaluating the impact on protein function. Treatment with recombinant IL-37 was evaluated in vitro and in vivo in a mouse model of gout.ResultsWe identified four rare variants in IL37 in six of the discovery gout patients; p.(A144P), p.(G174Dfs*16), p.(C181*) and p.(N182S), whereas none emerged in healthy controls (Fisher’s exact p-value=0.043). All variants clustered in the functional domain of IL-37 in exon 5 (p-value=5.71×10−5). Predictive modelling and functional studies confirmed loss of anti-inflammatory functions and we substantiated the therapeutic potential of recombinant IL-37 in the treatment of gouty inflammation. Furthermore, the carrier status of p.(N182S)(rs752113534) was associated with increased risk (OR=1.81, p-value=0.031) of developing gout in hyperuricaemic individuals of Polynesian ancestry.ConclusionHere, we provide genetic as well as mechanistic evidence for the role of IL-37 in the pathogenesis of gout, and highlight the therapeutic potential of recombinant IL-37 for the treatment of gouty arthritis.