138 research outputs found

    Time reversal in thermoacoustic tomography - an error estimate

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    The time reversal method in thermoacoustic tomography is used for approximating the initial pressure inside a biological object using measurements of the pressure wave made on a surface surrounding the object. This article presents error estimates for the time reversal method in the cases of variable, non-trapping sound speeds.Comment: 16 pages, 6 figures, expanded "Remarks and Conclusions" section, added one figure, added reference

    Genome-wide DNA methylation patterns in pancreatic ductal adenocarcinoma reveal epigenetic deregulation of SLIT-ROBO, ITGA2 and MET signaling

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    The importance of epigenetic modifications such as DNA methylation in tumorigenesis is increasingly being appreciated. To define the genome-wide pattern of DNA methylation in pancreatic ductal adenocarcinomas (PDAC), we captured the methylation profiles of 167 untreated resected PDACs and compared them to a panel of 29 adjacent nontransformed pancreata using high-density arrays. A total of 11,634 CpG sites associated with 3,522 genes were significantly differentially methylated (DM) in PDAC and were capable of segregating PDAC from non-malignant pancreas, regardless of tumor cellularity. As expected, PDAC hypermethylation was most prevalent in the 50 region of genes (including the proximal promoter, 50UTR and CpG islands). Approximately 33% DM genes showed significant inverse correlation with mRNA expression levels. Pathway analysis revealed an enrichment of aberrantly methylated genes involved in key molecular mechanisms important to PDAC: TGF-b, WNT, integrin signaling, cell adhesion, stellate cell activation and axon guidance. Given the recent discovery that SLIT-ROBO mutations play a clinically important role in PDAC, the role of epigenetic perturbation of axon guidance was pursued in more detail. Bisulfite amplicon deep sequencing and qRT-PCR expression analyses confirmed recurrent perturbation of axon guidance pathway genes SLIT2, SLIT3, ROBO1, ROBO3, ITGA2 and MET and suggests epigenetic suppression of SLIT-ROBO signaling and upregulation of MET and ITGA2 expression. Hypomethylation of MET and ITGA2 correlated with high gene expression, which was associated with poor survival. These data suggest that aberrant methylation plays an important role in pancreatic carcinogenesis affecting core signaling pathways with potential implications for the disease pathophysiology and therapy. What’s new? Based on a large genome-wide scan of DNA methylation, this study reports that global DNA methylation patterns can robustly segregate tumor and non-malignant pancreata. Cancer methylation also affects key pathways in pancreatic carcinogenesis, including TGF-b, WNT, and axon guidance signaling. This study confirms that methylation plays an important role in the development and progression of pancreatic cancer, with implications for both ongoing research and therapeutic development.Katia Nones ... Karin S. Kassahn ... et. al

    Somatic point mutation calling in low cellularity tumors

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    Somatic mutation calling from next-generation sequencing data remains a challenge due to the difficulties of distinguishing true somatic events from artifacts arising from PCR, sequencing errors or mis-mapping. Tumor cellularity or purity, sub-clonality and copy number changes also confound the identification of true somatic events against a background of germline variants. We have developed a heuristic strategy and software (http://www.qcmg.org/bioinformatics/qsnp/) for somatic mutation calling in samples with low tumor content and we show the superior sensitivity and precision of our approach using a previously sequenced cell line, a series of tumor/normal admixtures, and 3,253 putative somatic SNVs verified on an orthogonal platform.Karin S. Kassahn, Oliver Holmes, Katia Nones, Ann-Marie Patch, David K. Miller, Angelika N. Christ, Ivon Harliwong, Timothy J. Bruxner, Qinying Xu, Matthew Anderson, Scott Wood, Conrad Leonard, Darrin Taylor, Felicity Newell, Sarah Song, Senel Idrisoglu, Craig Nourse, Ehsan Nourbakhsh, Suzanne Manning, Shivangi Wani, Anita Steptoe, Marina Pajic, Mark J. Cowley, Mark Pinese, David K. Chang, Anthony J. Gill, Amber L. Johns, Jianmin Wu, Peter J. Wilson, Lynn Fink, Andrew V. Biankin, Nicola Waddell, Sean M. Grimmond, John V. Pearso

    100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care — Preliminary Report

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    BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection. METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis. RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives. CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.)

    Clinical, genetic, epidemiologic, evolutionary, and functional delineation of TSPEAR-related autosomal recessive ectodermal dysplasia 14

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    TSPEAR variants cause autosomal recessive ectodermal dysplasia (ARED) 14. The function of TSPEAR is unknown. The clinical features, the mutation spectrum, and the underlying mechanisms of ARED14 are poorly understood. Combining data from new and previously published individuals established that ARED14 is primarily characterized by dental anomalies such as conical tooth cusps and hypodontia, like those seen in individuals with WNT10A-related odontoonychodermal dysplasia. AlphaFold-predicted structure-based analysis showed that most of the pathogenic TSPEAR missense variants likely destabilize the β-propeller of the protein. Analysis of 100000 Genomes Project (100KGP) data revealed multiple founder TSPEAR variants across different populations. Mutational and recombination clock analyses demonstrated that non-Finnish European founder variants likely originated around the end of the last ice age, a period of major climatic transition. Analysis of gnomAD data showed that the non-Finnish European population TSPEAR gene-carrier rate is ∼1/140, making it one of the commonest AREDs. Phylogenetic and AlphaFold structural analyses showed that TSPEAR is an ortholog of drosophila Closca, an extracellular matrix-dependent signaling regulator. We, therefore, hypothesized that TSPEAR could have a role in enamel knot, a structure that coordinates patterning of developing tooth cusps. Analysis of mouse single-cell RNA sequencing (scRNA-seq) data revealed highly restricted expression of Tspear in clusters representing enamel knots. A tspeara−/−;tspearb−/− double-knockout zebrafish model recapitulated the clinical features of ARED14 and fin regeneration abnormalities of wnt10a knockout fish, thus suggesting interaction between tspear and wnt10a. In summary, we provide insights into the role of TSPEAR in ectodermal development and the evolutionary history, epidemiology, mechanisms, and consequences of its loss of function variants

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    Neutrinos

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    229 pages229 pages229 pagesThe Proceedings of the 2011 workshop on Fundamental Physics at the Intensity Frontier. Science opportunities at the intensity frontier are identified and described in the areas of heavy quarks, charged leptons, neutrinos, proton decay, new light weakly-coupled particles, and nucleons, nuclei, and atoms

    Genetic mechanisms of critical illness in COVID-19.

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    Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

    Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

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    The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)
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