104 research outputs found

    Genetically predicted complement component 4A expression: effects on memory function and middle temporal lobe activation

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    Background The longstanding association between the major histocompatibility complex (MHC) locus and schizophrenia (SZ) risk has recently been accounted for, partially, by structural variation at the complement component 4 (C4) gene. This structural variation generates varying levels of C4 RNA expression, and genetic information from the MHC region can now be used to predict C4 RNA expression in the brain. Increased predicted C4A RNA expression is associated with the risk of SZ, and C4 is reported to influence synaptic pruning in animal models. Methods Based on our previous studies associating MHC SZ risk variants with poorer memory performance, we tested whether increased predicted C4A RNA expression was associated with reduced memory function in a large (n = 1238) dataset of psychosis cases and healthy participants, and with altered task-dependent cortical activation in a subset of these samples. Results We observed that increased predicted C4A RNA expression predicted poorer performance on measures of memory recall (p = 0.016, corrected). Furthermore, in healthy participants, we found that increased predicted C4A RNA expression was associated with a pattern of reduced cortical activity in middle temporal cortex during a measure of visual processing (p < 0.05, corrected). Conclusions These data suggest that the effects of C4 on cognition were observable at both a cortical and behavioural level, and may represent one mechanism by which illness risk is mediated. As such, deficits in learning and memory may represent a therapeutic target for new molecular developments aimed at altering C4’s developmental role

    Quantifying single nucleotide variant detection sensitivity in exome sequencing

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    BACKGROUND: The targeted capture and sequencing of genomic regions has rapidly demonstrated its utility in genetic studies. Inherent in this technology is considerable heterogeneity of target coverage and this is expected to systematically impact our sensitivity to detect genuine polymorphisms. To fully interpret the polymorphisms identified in a genetic study it is often essential to both detect polymorphisms and to understand where and with what probability real polymorphisms may have been missed. RESULTS: Using down-sampling of 30 deeply sequenced exomes and a set of gold-standard single nucleotide variant (SNV) genotype calls for each sample, we developed an empirical model relating the read depth at a polymorphic site to the probability of calling the correct genotype at that site. We find that measured sensitivity in SNV detection is substantially worse than that predicted from the naive expectation of sampling from a binomial. This calibrated model allows us to produce single nucleotide resolution SNV sensitivity estimates which can be merged to give summary sensitivity measures for any arbitrary partition of the target sequences (nucleotide, exon, gene, pathway, exome). These metrics are directly comparable between platforms and can be combined between samples to give “power estimates” for an entire study. We estimate a local read depth of 13X is required to detect the alleles and genotype of a heterozygous SNV 95% of the time, but only 3X for a homozygous SNV. At a mean on-target read depth of 20X, commonly used for rare disease exome sequencing studies, we predict 5–15% of heterozygous and 1–4% of homozygous SNVs in the targeted regions will be missed. CONCLUSIONS: Non-reference alleles in the heterozygote state have a high chance of being missed when commonly applied read coverage thresholds are used despite the widely held assumption that there is good polymorphism detection at these coverage levels. Such alleles are likely to be of functional importance in population based studies of rare diseases, somatic mutations in cancer and explaining the “missing heritability” of quantitative traits

    Bank insolvencies, priority claims and systemic risk

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    We review an extensive literature debating the merits of alternative priority structures for banking liabilities put forward by financial economists, legal scholars and policymakers. Up to now, this work has focused exclusively on the relative advantages of each group of creditors to monitor the activities of bankers. We argue that systemic risk is another dimension that this discussion must include. The main message of our work is that when bank failures are contagious then when regulators assign priority rights need also to take into account how the bankruptcy resolution of one institution might affect the survival of other institutions that have acted as its creditors. When the network structure is fixed the solution is straightforward. Other banks should have priority to minimize the risk of their downfall. However, if the choice of policy can affect the structure of the network, policy design becomes more complex.This is a fruitful avenue for future research

    Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia

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    The antipsychotic clozapine is uniquely effective in the management of schizophrenia; however, its use is limited by its potential to induce agranulocytosis. The causes of this, and of its precursor neutropenia, are largely unknown, although genetic factors have an important role. We sought risk alleles for clozapine-associated neutropenia in a sample of 66 cases and 5583 clozapine-treated controls, through a genome-wide association study (GWAS), imputed human leukocyte antigen (HLA) alleles, exome array and copy-number variation (CNV) analyses. We then combined associated variants in a meta-analysis with data from the Clozapine-Induced Agranulocytosis Consortium (up to 163 cases and 7970 controls). In the largest combined sample to date, we identified a novel association with rs149104283 (odds ratio (OR)=4.32, P=1.79 × 10−8), intronic to transcripts of SLCO1B3 and SLCO1B7, members of a family of hepatic transporter genes previously implicated in adverse drug reactions including simvastatin-induced myopathy and docetaxel-induced neutropenia. Exome array analysis identified gene-wide associations of uncommon non-synonymous variants within UBAP2 and STARD9. We additionally provide independent replication of a previously identified variant in HLA-DQB1 (OR=15.6, P=0.015, positive predictive value=35.1%). These results implicate biological pathways through which clozapine may act to cause this serious adverse effec

    Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia

    Get PDF
    Abstract The antipsychotic clozapine is uniquely effective in the management of schizophrenia; however, its use is limited by its potential to induce agranulocytosis. The causes of this, and of its precursor neutropenia, are largely unknown, although genetic factors have an important role. We sought risk alleles for clozapine-associated neutropenia in a sample of 66 cases and 5583 clozapine-treated controls, through a genome-wide association study (GWAS), imputed human leukocyte antigen (HLA) alleles, exome array and copy-number variation (CNV) analyses. We then combined associated variants in a meta-analysis with data from the Clozapine-Induced Agranulocytosis Consortium (up to 163 cases and 7970 controls). In the largest combined sample to date, we identified a novel association with rs149104283 (odds ratio (OR)=4.32, P=1.79 × 10−8), intronic to transcripts of SLCO1B3 and SLCO1B7, members of a family of hepatic transporter genes previously implicated in adverse drug reactions including simvastatin-induced myopathy and docetaxel-induced neutropenia. Exome array analysis identified gene-wide associations of uncommon non-synonymous variants within UBAP2 and STARD9. We additionally provide independent replication of a previously identified variant in HLA-DQB1 (OR=15.6, P=0.015, positive predictive value=35.1%). These results implicate biological pathways through which clozapine may act to cause this serious adverse effect.</jats:p

    Pathogenic copy number variants and SCN1A mutations in patients with intellectual disability and childhood-onset epilepsy

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    Background Copy number variants (CNVs) have been linked to neurodevelopmental disorders such as intellectual disability (ID), autism, epilepsy and psychiatric disease. There are few studies of CNVs in patients with both ID and epilepsy. Methods We evaluated the range of rare CNVs found in 80 Welsh patients with ID or developmental delay (DD), and childhood-onset epilepsy. We performed molecular cytogenetic testing by single nucleotide polymorphism array or microarray-based comparative genome hybridisation. Results 8.8 % (7/80) of the patients had at least one rare CNVs that was considered to be pathogenic or likely pathogenic. The CNVs involved known disease genes (EHMT1, MBD5 and SCN1A) and imbalances in genomic regions associated with neurodevelopmental disorders (16p11.2, 16p13.11 and 2q13). Prompted by the observation of two deletions disrupting SCN1A we undertook further testing of this gene in selected patients. This led to the identification of four pathogenic SCN1A mutations in our cohort. Conclusions We identified five rare de novo deletions and confirmed the clinical utility of array analysis in patients with ID/DD and childhood-onset epilepsy. This report adds to our clinical understanding of these rare genomic disorders and highlights SCN1A mutations as a cause of ID and epilepsy, which can easily be overlooked in adults

    Polymorphous adenocarcinoma of the salivary glands : reappraisal and update

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    Although relatively rare, polymorphous adenocarcinoma (PAC) is likely the second most common malignancy of the minor salivary glands (MiSG). The diagnosis is mainly based on an incisional biopsy. The optimal treatment comprises wide surgical excision, often with adjuvant radiotherapy. In general, PAC has a good prognosis. Previously, PAC was referred to as polymorphous low-grade adenocarcinoma (PLGA), but the new WHO classification of salivary gland tumours has also included under the PAC subheading, the so-called cribriform adenocarcinoma of minor salivary glands (CAMSG). This approach raised controversy, predominantly because of possible differences in clinical behaviour. For example, PLGA (PAC, classical variant) only rarely metastasizes, whereas CAMSG often shows metastases to the neck lymph nodes. Given the controversy, this review reappraises the definition, epidemiology, clinical presentation, diagnostic work-up, genetics, treatment modalities, and prognosis of PAC of the salivary glands with a particular focus on contrasting differences with CAMSG.Peer reviewe

    Array-CGH and breast cancer

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    The introduction of comparative genomic hybridization (CGH) in 1992 opened new avenues in genomic investigation; in particular, it advanced analysis of solid tumours, including breast cancer, because it obviated the need to culture cells before their chromosomes could be analyzed. The current generation of CGH analysis uses ordered arrays of genomic DNA sequences and is therefore referred to as array-CGH or matrix-CGH. It was introduced in 1998, and further increased the potential of CGH to provide insight into the fundamental processes of chromosomal instability and cancer. This review provides a critical evaluation of the data published on array-CGH and breast cancer, and discusses some of its expected future value and developments

    Parsimonious Higher-Order Hidden Markov Models for Improved Array-CGH Analysis with Applications to Arabidopsis thaliana

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    Array-based comparative genomic hybridization (Array-CGH) is an important technology in molecular biology for the detection of DNA copy number polymorphisms between closely related genomes. Hidden Markov Models (HMMs) are popular tools for the analysis of Array-CGH data, but current methods are only based on first-order HMMs having constrained abilities to model spatial dependencies between measurements of closely adjacent chromosomal regions. Here, we develop parsimonious higher-order HMMs enabling the interpolation between a mixture model ignoring spatial dependencies and a higher-order HMM exhaustively modeling spatial dependencies. We apply parsimonious higher-order HMMs to the analysis of Array-CGH data of the accessions C24 and Col-0 of the model plant Arabidopsis thaliana. We compare these models against first-order HMMs and other existing methods using a reference of known deletions and sequence deviations. We find that parsimonious higher-order HMMs clearly improve the identification of these polymorphisms. Moreover, we perform a functional analysis of identified polymorphisms revealing novel details of genomic differences between C24 and Col-0. Additional model evaluations are done on widely considered Array-CGH data of human cell lines indicating that parsimonious HMMs are also well-suited for the analysis of non-plant specific data. All these results indicate that parsimonious higher-order HMMs are useful for Array-CGH analyses. An implementation of parsimonious higher-order HMMs is available as part of the open source Java library Jstacs (www.jstacs.de/index.php/PHHMM)
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