188 research outputs found
Whole genome sequencing identifies putative associations between genomic polymorphisms and clinical response to the antiepileptic drug levetiracetam
In the context of pharmacogenomics, whole genome sequencing provides a powerful approach for identifying correlations between response variability to specific drugs and genomic polymorphisms in a population, in an unbiased manner. In this study, we employed whole genome sequencing of DNA samples from patients showing extreme response (n=72) and non-response (n=27) to the antiepileptic drug levetiracetam, in order to identify genomic variants that underlie response to the drug. Although no common SNP (MAF>5%) crossed the conventional genome-wide significance threshold of 5e-8, we found common polymorphisms in genes SPNS3, HDC, MDGA2, NSG1 and RASGEF1C, which collectively predict clinical response to levetiracetam in our cohort with ~91% predictive accuracy. Among these genes, HDC, NSG1, MDGA2 and RASGEF1C are potentially implicated in synaptic neurotransmission, while SPNS3 is an atypical solute carrier transporter homologous to SV2A, the known molecular target of levetiracetam. Furthermore, we performed gene- and pathway-based statistical analysis on sets of rare and low-frequency variants (MAF<5%) and we identified associations between the following genes or pathways and response to levetiracetam: a) genes PRKCB and DLG2, which are involved in glutamatergic neurotransmission, a known target of anticonvulsants, including levetiracetam; b) genes FILIP1 and SEMA6D, which are involved in axon guidance and modelling of neural connections; and c) pathways with a role in synaptic neurotransmission, such as WNT5A-dependent internalization of FZD4 and disinhibition of SNARE formation. In summary, our approach to utilise whole genome sequencing on subjects with extreme response phenotypes is a feasible route to generate plausible hypotheses for investigating the genetic factors underlying drug response variability in cases of pharmaco-resistant epilepsy
Homozygous microdeletion of exon 5 in ZNF277 in a girl with specific language impairment
Peer reviewedPublisher PD
A family with autism and rare copy number variants disrupting the Duchenne/Becker muscular dystrophy gene DMD and TRPM3
Autism spectrum disorder is a genetically complex and clinically heterogeneous neurodevelopmental disorder. A recent study by the Autism Genome Project (AGP) used 1M single-nucleotide polymorphism arrays to show that rare genic copy number variants (CNVs), possibly acting in tandem, play a significant role in the genetic aetiology of this condition. In this study, we describe the phenotypic and genomic characterisation of a multiplex autism family from the AGP study that was found to harbour a duplication of exons 31–44 of the Duchenne/Becker muscular dystrophy gene DMD and also a rare deletion involving exons 1–9 of TRPM3. Further characterisation of these extremely rare CNVs was carried out using quantitative PCR, fluorescent in situ hybridisation, long-range PCR amplification and sequencing of junction fragments. The maternal chrX:32,097,213-32,321,945 tandem duplication and paternal chr9:72,480,413-73,064,196 deletion (NCBI build 36 coordinates) were transmitted to both affected boys, potentially signifying a multi-hit mechanism. The DMD reading frame rule predicts a Becker phenotype, characterised by later onset and milder symptoms. When last evaluated, neither child had developed signs of muscular dystrophy. These data are consistent with a degree of comorbidity between autism and muscular dystrophy and suggest that genomic background as well as the position of the mutation within the DMD gene may impact on the neurological correlates of Duchenne/Becker muscular dystrophy. Finally, communicating unexpected findings such as these back to families raises a number of ethical questions, which are discussed
Cheek swabs, SNP chips, and CNVs: Assessing the quality of copy number variant calls generated with subject-collected mail-in buccal brush DNA samples on a high-density genotyping microarray
Delineation of dominant and recessive forms of LZTR1-associated Noonan syndrome.
Noonan syndrome (NS) is characterised by distinctive facial features, heart defects, variable degrees of intellectual disability and other phenotypic manifestations. Although the mode of inheritance is typically dominant, recent studies indicate LZTR1 may be associated with both dominant and recessive forms. Seeking to describe the phenotypic characteristics of LZTR1-associated NS, we searched for likely pathogenic variants using two approaches. First, scrutiny of exomes from 9624 patients recruited by the Deciphering Developmental Disorders (DDDs) study uncovered six dominantly-acting mutations (p.R97L; p.Y136C; p.Y136H, p.N145I, p.S244C; p.G248R) of which five arose de novo, and three patients with compound-heterozygous variants (p.R210*/p.V579M; p.R210*/p.D531N; c.1149+1G>T/p.R688C). One patient also had biallelic loss-of-function mutations in NEB, consistent with a composite phenotype. After removing this complex case, analysis of human phenotype ontology terms indicated significant phenotypic similarities (P = 0.0005), supporting a causal role for LZTR1. Second, targeted sequencing of eight unsolved NS-like cases identified biallelic LZTR1 variants in three further subjects (p.W469*/p.Y749C, p.W437*/c.-38T>A and p.A461D/p.I462T). Our study strengthens the association of LZTR1 with NS, with de novo mutations clustering around the KT1-4 domains. Although LZTR1 variants explain ~0.1% of cases across the DDD cohort, the gene is a relatively common cause of unsolved NS cases where recessive inheritance is suspected
KELVIN: A Software Package for Rigorous Measurement of Statistical Evidence in Human Genetics
This paper describes the software package KELVIN, which supports the PPL (posterior probability of linkage) framework for the measurement of statistical evidence in human (or more generally, diploid) genetic studies. In terms of scope, KELVIN supports two-point (trait-marker or marker-marker) and multipoint linkage analysis, based on either sex-averaged or sex-specific genetic maps, with an option to allow for imprinting; trait-marker linkage disequilibrium (LD), or association analysis, in case-control data, trio data, and/or multiplex family data, with options for joint linkage and trait-marker LD or conditional LD given linkage; dichotomous trait, quantitative trait and quantitative trait threshold models; and certain types of gene-gene interactions and covariate effects. Features and data (pedigree) structures can be freely mixed and matched within analyses. The statistical framework is specifically tailored to accumulate evidence in a mathematically rigorous way across multiple data sets or data subsets while allowing for multiple sources of heterogeneity, and KELVIN itself utilizes sophisticated software engineering to provide a powerful and robust platform for studying the genetics of complex disorders
FOXN1 forms higher-order nuclear condensates displaced by mutations causing immunodeficiency
The transcription factor FOXN1 is a master regulator of thymic epithelial cell (TEC) development and function. Here, we demonstrate that FOXN1 expression is differentially regulated during organogenesis and participates in multimolecular nuclear condensates essential for the factor’s transcriptional activity. FOXN1’s C-terminal sequence regulates the diffusion velocity within these aggregates and modulates the binding to proximal gene regulatory regions. These dynamics are altered in a patient with a mutant FOXN1 that is modified in its C-terminal sequence. This mutant is transcriptionally inactive and acts as a dominant negative factor displacing wild-type FOXN1 from condensates and causing athymia and severe lymphopenia in heterozygotes. Expression of the mutated mouse ortholog selectively impairs mouse TEC differentiation, revealing a gene dose dependency for individual TEC subtypes. We have therefore identified the cause for a primary immunodeficiency disease and determined the mechanism by which this FOXN1 gain-of-function mutant mediates its dominant negative effect
Analysis of exome data for 4293 trios suggests GPI-anchor biogenesis defects are a rare cause of developmental disorders.
Over 150 different proteins attach to the plasma membrane using glycosylphosphatidylinositol (GPI) anchors. Mutations in 18 genes that encode components of GPI-anchor biogenesis result in a phenotypic spectrum that includes learning disability, epilepsy, microcephaly, congenital malformations and mild dysmorphic features. To determine the incidence of GPI-anchor defects, we analysed the exome data from 4293 parent-child trios recruited to the Deciphering Developmental Disorders (DDD) study. All probands recruited had a neurodevelopmental disorder. We searched for variants in 31 genes linked to GPI-anchor biogenesis and detected rare biallelic variants in PGAP3, PIGN, PIGT (n=2), PIGO and PIGL, providing a likely diagnosis for six families. In five families, the variants were in a compound heterozygous configuration while in a consanguineous Afghani kindred, a homozygous c.709G>C; p.(E237Q) variant in PIGT was identified within 10-12 Mb of autozygosity. Validation and segregation analysis was performed using Sanger sequencing. Across the six families, five siblings were available for testing and in all cases variants co-segregated consistent with them being causative. In four families, abnormal alkaline phosphatase results were observed in the direction expected. FACS analysis of knockout HEK293 cells that had been transfected with wild-type or mutant cDNA constructs demonstrated that the variants in PIGN, PIGT and PIGO all led to reduced activity. Splicing assays, performed using leucocyte RNA, showed that a c.336-2A>G variant in PIGL resulted in exon skipping and p.D113fs*2. Our results strengthen recently reported disease associations, suggest that defective GPI-anchor biogenesis may explain ~0.15% of individuals with developmental disorders and highlight the benefits of data sharing
Variable skeletal phenotypes associated with biallelic variants in PRKG2.
CC BY 4.0Published Online First: 15 November 2021Brief communicationThe Genomics England Research ConsortiumCorrespondence to Dr Deborah Shears; [email protected] Dr Jenny C Taylor; [email protected]</p
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