Publications by authors named "Jos van Nijnatten"

Introduction: Asthma is an inflammatory airways disease encompassing multiple phenotypes and endotypes. Several studies suggested gene expression in nasal epithelium to serve as a proxy for bronchial epithelium, being a non-invasive approach to investigate lung diseases. We hypothesised that molecular differences in upper airway epithelium reflect asthma-associated differences in the lower airways and are associated with clinical expression of asthma.

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Introduction: A subset of COPD patients develops advanced disease with severe airflow obstruction, hyperinflation and extensive emphysema. We propose that the pathogenesis in these patients differs from mild-moderate COPD and is reflected by bronchial gene expression. The aim of the present study was to identify a unique bronchial epithelial gene signature for severe COPD patients.

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Background And Objective: Smoking disturbs the bronchial-mucus-barrier. This study assesses the cellular composition and gene expression shifts of the bronchial-mucus-barrier with smoking to understand the mechanism of mucosal damage by cigarette smoke exposure. We explore whether single-cell-RNA-sequencing (scRNA-seq) based cellular deconvolution (CD) can predict cell-type composition in RNA-seq data.

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Smoking is a leading cause of chronic obstructive pulmonary disease (COPD). It is known to have a significant impact on gene expression and (inflammatory) cell populations in the airways involved in COPD pathogenesis. In this study, we investigated the impact of smoking on the expression of miRNAs in healthy and COPD individuals.

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Background: Changes in microRNA (miRNA) expression can contribute to the pathogenesis of many diseases, including asthma. We aimed to identify miRNAs that are differentially expressed between asthma patients and healthy controls, and explore their association with clinical and inflammatory parameters of asthma.

Methods: Differentially expressed miRNAs were determined by small RNA sequencing on bronchial biopsies of 79 asthma patients and 82 healthy controls using linear regression models.

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Unlabelled: We present iFUSE (integrated fusion gene explorer), an online visualization tool that provides a fast and informative view of structural variation data and prioritizes those breaks likely representing fusion genes. This application uses calculated break points to determine fusion genes based on the latest annotation for genomic sequence information, and where relevant the structural variation (SV) events are annotated with predicted RNA and protein sequences. iFUSE takes as input a Complete Genomics (CG) junction file, a FusionMap fusion detection report file or a file already analysed and annotated by the iFUSE application on a previous occasion.

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