38 research outputs found

    Frequent detection of high human papillomavirus DNA loads in oral potentially malignant disorders

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    Human papillomavirus (HPV) is estimated to be the cause of 40-80% of the squamous cell carcinoma of the oropharynx but only of a small fraction of the oral cavity cancers. The prevalence of oral HPV infection has significantly increased in the last decade, raising concerns about the HPV role in progression of oral potentially malignant disorders (OPMD) toward squamous cell carcinomas. We sought to study HPV infection in patients with oral lesions, and in control individuals, using non-invasive and site-specific oral brushing and sensitive molecular methods. HPV DNA positivity and viral loads were evaluated in relation to patient data and clinical diagnosis. We enrolled 116 individuals attending Dental Clinics: 62 patients with benign oral lesions (e.g. fibromas, papillomatosis, ulcers) or OPMD (e.g. lichen, leukoplakia) and 54 controls. Oral cells were collected with Cytobrush and HPV-DNA detected with quantitative real-time PCR (qPCR) for the more common high-risk (HR) and low-risk (LR) genotypes. HPV detection rate, percentage of HR HPVs and HPV-DNA loads (namely HPV16 and in particular, HPV18) were significantly higher in patients than in controls. Lichen planus cases had the highest HPV positive rate (75.0%), hairy leukoplakia the lowest (33.3%). This study detected unexpectedly high rates of HPV infection in cells of the oral mucosa. The elevated HR HPV loads found in OPMD suggest the effectiveness of qPCR in testing oral lesions. Prospective studies are needed to establish whether elevated viral loads represent a clinically useful marker of the risk of malignant progression

    Mutations impairing GSK3-mediated MAF phosphorylation cause cataract, deafness, intellectual disability, seizures, and a down syndrome-like facies

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    Transcription factors operate in developmental processes to mediate inductive events and cell competence, and perturbation of their function or regulation can dramatically affect morphogenesis, organogenesis, and growth. We report that a narrow spectrum of amino-acid substitutions within the transactivation domain of the v-maf avian musculoaponeurotic fibrosarcoma oncogene homolog (MAF), a leucine zipper-containing transcription factor of the AP1 superfamily, profoundly affect development. Seven different de novo missense mutations involving conserved residues of the four GSK3 phosphorylation motifs were identified in eight unrelated individuals. The distinctive clinical phenotype, for which we propose the eponym Aymé-Gripp syndrome, is not limited to lens and eye defects as previously reported for MAF/Maf loss of function but includes sensorineural deafness, intellectual disability, seizures, brachycephaly, distinctive flat facial appearance, skeletal anomalies, mammary gland hypoplasia, and reduced growth. Disease-causing mutations were demonstrated to impair proper MAF phosphorylation, ubiquitination and proteasomal degradation, perturbed gene expression in primary skin fibroblasts, and induced neurodevelopmental defects in an in vivo model. Our findings nosologically and clinically delineate a previously poorly understood recognizable multisystem disorder, provide evidence for MAF governing a wider range of developmental programs than previously appreciated, and describe a novel instance of protein dosage effect severely perturbing developmen

    HCI at the boundary of work and life

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    The idea behind this Special Issue originates in a workshop on HCI and CSCW research related to work and non-work-life balance organized in conjunction with the ECSCW 2013 conference by the issue co-editors. Fifteen papers were originally submitted for possible inclusion in this Special Issue, and four papers were finally accepted for publication after two rounds of rigorous peer review. The four accepted papers explore, in different ways, HCI at the boundary of work and life. In this editorial, we offer a description of the overall theme and rationale for the Special Issue, including an introduction on the topic relevance and background, and a reflection on how the four accepted papers further current research and debate on the topic

    Childhood-onset dystonia-causing KMT2B variants result in a distinctive genomic hypermethylation profile

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    Background: Dystonia is a clinically and genetically heterogeneous movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements and/or postures. Heterozygous variants in lysine methyltransferase 2B (KMT2B), encoding a histone H3 methyltransferase, have been associated with a childhood-onset, progressive and complex form of dystonia (dystonia 28, DYT28). Since 2016, more than one hundred rare KMT2B variants have been reported, including frameshift, nonsense, splice site, missense and other in-frame changes, many having an uncertain clinical impact. Results: We characterize the genome-wide peripheral blood DNA methylation profiles of a cohort of 18 patients with pathogenic and unclassified KMT2B variants. We resolve the “episignature” associated with KMT2B haploinsufficiency, proving that this approach is robust in diagnosing clinically unsolved cases, properly classifying them with respect to other partially overlapping dystonic phenotypes, other rare neurodevelopmental disorders and healthy controls. Notably, defective KMT2B function in DYT28 causes a non-random DNA hypermethylation across the genome, selectively involving promoters and other regulatory regions positively controlling gene expression. Conclusions: We demonstrate a distinctive DNA hypermethylation pattern associated with DYT28, provide an epigenetic signature for this disorder enabling accurate diagnosis and reclassification of ambiguous genetic findings and suggest potential therapeutic approaches

    A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

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    Purpose: Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the "ClinVar low-hanging fruit" reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods: Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results: We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion: The "ClinVar low-hanging fruit" analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock.The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement number 779257. Data were analyzed using the RD-Connect Genome-Phenome Analysis Platform, which received funding from the EU projects RD-Connect, Solve-RD, and European Joint Programme on Rare Diseases (grant numbers FP7 305444, H2020 779257, H2020 825575), Instituto de Salud Carlos III (grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática), and ELIXIR Implementation Studies. The collaborations in this study were facilitated by the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies, one of the 24 European Reference Networks approved by the European Reference Network Board of Member States, cofunded by the European Commission. This project was supported by the Czech Ministry of Health (number 00064203) and by the Czech Ministry of Education, Youth and Sports (number - LM2018132) to M.M.S

    A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

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    Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

    Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

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    Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

    Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

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    Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics
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