Project description:The ‘Genetic Epidemiology of Asthma in Costa Rica’ is a family-based cross-sectional cohort ascertained between February 2001 and August 2008 on a Hispanic population isolate from the Central Valley of Costa Rica. The study recruited children between 6 to 14 years of age with moderate persistent asthma.
Project description:Asthma bronchiale is an inflammatory disease of the respiratory airways and a major factor of increasing health care costs worldwide. The molecular actors leading to asthma are not fully understood and require further investigation. The aim of this study was to monitor the proteome during asthma development from early inflammatory to late fibrotic stages. A time-course-based ovalbumin (OVA) mouse model was applied to establish an asthma phenotype and the lung proteome was analysed at four time points during asthma development (0 weeks = control, 5 weeks, 8 weeks and 12 weeks of OVA treatment).
Project description:Background: MicroRNAs are potent regulators of biologic systems that are critical to tissue homeostasis. Individual microRNAs have been identified in airway samples. However, a systems analysis of the microRNA-mRNA networks present in the sputum that contribute to airway inflammation in asthma has not been published. Methods: We conducted a genome-wide analysis of microRNA and messenger RNA (mRNA) in the sputum from patients with asthma and correlated expression with clinical phenotypes. Weighted gene correlation network analysis (WGCNA) was implemented to identify microRNA networks (modules) that significantly correlate with clinical features of asthma and mRNA expression networks. MicroRNA expression in peripheral blood neutrophils and lymphocytes, and in situ hybridization of the sputum were used to identify the cellular sources of microRNAs. MicroRNA expression obtained before and after ozone exposure was also used to identify changes associated with neutrophil counts in the airway. Results: Six microRNA modules were associated with clinical features of asthma. A single module (nely) was associated with a history of hospitalizations, lung function impairment, and numbers of neutrophils and lymphocytes in the sputum. Of the 12 microRNAs in the nely module, hsa-miR-223-3p was the highest expressed microRNA in neutrophils and was associated with increased neutrophil counts in the sputum in response to ozone exposure. Multiple microRNAs in the nely module correlated with two mRNA modules enriched for toll-like receptor (TLR) and Th17 signaling, and endoplasmic reticulum stress. Hsa-miR-223-3p was a key regulator of the TLR and Th17 pathways in the sputum of subjects with asthma. Conclusions: This study of sputum microRNA and mRNA expression from patients with asthma demonstrates the existence of microRNA networks and genes that are associated with features of asthma severity. Among these, hsa-miR-223-3p, a neutrophil-derived microRNA, regulates TLR/Th17 signaling and endoplasmic reticulum stress.
Project description:Severe asthma is a clinically and physiologically heterogeneous disease. Benralizumab is a monoclonal antibody which binds the alpha chain of the interleukin-5 receptor and used for severe eosinophilic asthma worldwide. However, not all eosinophilic asthma patients will benefit from benralizumab due to heterogeneity of this disease. Therefore, we performed comprehensive gene expression analysis of whole blood cells that examine severe asthma disease heterogeneity in response to benralizumab. This study is the first to perform comprehensive transcriptome analysis of whole blood cells to identify transcriptomic endotypes of severe asthma clusters that correlate with benralizumab response. The identified transcriptomic endotypes of severe asthma clusters are associated with gene signatures of eosinophils and neutrophilis.
Project description:We leverage a systems-scale network analysis approach to demonstrate repertoires of cellular transcriptional pathways underlying loss of asthma control, and show how these pathways differ in viral associated and non-viral exacerbations.
Project description:We leverage a systems-scale network analysis approach to demonstrate repertoires of cellular transcriptional pathways underlying loss of asthma control, and show how these pathways differ in viral associated and non-viral exacerbations.
Project description:We analyzed the transcriptomes of children with controlled and uncontrolled asthma in Taiwanese Consortium of Childhood Asthma Study (TCCAS). Hierarchical clustering, differentially expressed gene (DEG), weighted gene co-expression network analysis (WGCNA) and pathway enrichment methods were performed, to investigate important genes between two groups.
Project description:Profiling miRNA expression in cells that directly contribute to human disease pathogenesis is likely to aid the discovery of novel drug targets and biomarkers. However, tissue heterogeneity and the limited amount of human diseased tissue available for research purposes present fundamental difficulties that often constrain the scope and potential of such studies. We established a flow cytometry-based method for isolating pure populations of pathogenic T cells from bronchial biopsy samples of asthma patients, and optimized a high-throughput nano-scale qRT-PCR method capable of accurately measuring 96 miRNAs in as little as 100 cells. Comparison of circulating and airway T cells from healthy and asthmatic subjects revealed asthma-associated and tissue-specific miRNA expression patterns. These results establish the feasibility and utility of investigating miRNA expression in small populations of cells involved in asthma pathogenesis, and set a precedent for application of our nano-scale approach in other human diseases. We analyzed the concordance in results obtained by nano-scale qPCR and miRNA microarrays. RNA extracted from human Th2 cells was used for parallel profiling by both nano-scale PCR and microarray method. Fifty nanograms (ng) of RNA was used for the microarray method and cDNA from 1 ng (~1000 cell equivalent) of RNA, pre-amplified by 18 cycle PCR reaction, was used for miRNA detection by the nano-scale qPCR method (G.Seumois et al. in submission). Out of the 92 miRNAs assayed, 51 were detected by nano-scale qPCR. Of these, 45 were detected by microarray analysis, including the 32 miRNAs with the strongest signal intensities on the nano-scale qPCR platform. One sample; one color design. This is a single array from a larger normalized set of data investigating targeting microRNAs for asthma treatment that is to published separately.