| 1. |
- Emma, Rosalia, et al.
(författare)
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Enhanced oxidative stress in smoking and ex-smoking severe asthma in the U-BIOPRED cohort
- 2018
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Ingår i: PLOS ONE. - : Public Library Science. - 1932-6203. ; 13:9
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Tidskriftsartikel (refereegranskat)abstract
- Oxidative stress is believed to be a major driver of inflammation in smoking asthmatics. The U-BIOPRED project recruited a cohort of Severe Asthma smokers/ex-smokers (SAs/ex) and non-smokers (SAn) with extensive clinical and biomarker information enabling characterization of these subjects. We investigated oxidative stress in severe asthma subjects by analysing urinary 8-iso-PGF(2 alpha) and the mRNA-expression of the main pro-oxidant (NOX2; NOSs) and anti-oxidant (SODs; CAT; GPX1) enzymes in the airways of SAs/ex and SAn. All the severe asthma U-BIOPRED subjects were further divided into current smokers with severe asthma (CSA), ex-smokers with severe asthma (ESA) and non-smokers with severe asthma (NSA) to deepen the effect of active smoking. Clinical data, urine and sputum were obtained from severe asthma subjects. A bronchoscopy to obtain bronchial biopsy and brushing was performed in a subset of subjects. The main clinical data were analysed for each subset of subjects (urine-8-iso-PGF(2 alpha); IS-transcriptomics; BB-transcriptomics; BBrtranscriptomics). Urinary 8-iso-PGF(2 alpha) was quantified using mass spectrometry. Sputum, bronchial biopsy and bronchial brushing were processed for mRNA expression microarray analysis. Urinary 8-iso-PGF(2 alpha) was increased in SAs/ex, median (IQR) = 31.7 (24.5 +/- 44.7) ng/mmol creatinine, compared to SAn, median (IQR) = 26.6 (19.6 +/- 36.6) ng/mmol creatinine (p< 0.001), and in CSA, median (IQR) = 34.25 (24.4 +/- 47.7), vs. ESA, median (IQR) = 29.4 (22.3 +/- 40.5), and NSA, median (IQR) = 26.5 (19.6 +/- 16.6) ng/mmol creatinine (p = 0.004). Sputum mRNA expression of NOX2 was increased in SAs/ex compared to SAn (probe sets 203922_PM_s_at fold-change = 1.05 p = 0.006; 203923_PM_s_at fold-change = 1.06, p = 0.003; 233538_PM_s_at fold-change = 1.06, p = 0.014). The mRNA expression of antioxidant enzymes were similar between the two severe asthma cohorts in all airway samples. NOS2 mRNA expression was decreased in bronchial brushing of SAs/ex compared to SAn (fold-change = -1.10; p = 0.029). NOS2 mRNA expression in bronchial brushing correlated with FeNO (Kendal's Tau = 0.535; p< 0.001). From clinical and inflammatory analysis, FeNO was lower in CSA than in ESA in all the analysed subject subsets (p< 0.01) indicating an effect of active smoking. Results about FeNO suggest its clinical limitation, as inflammation biomarker, in severe asthma active smokers. These data provide evidence of greater systemic oxidative stress in severe asthma smokers as reflected by a significant changes of NOX2 mRNA expression in the airways, together with elevated urinary 8-iso-PGF(2 alpha) in the smokers/ex-smokers group.
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| 2. |
- Kuo, Chih-Hsi Scott, et al.
(författare)
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A transcriptome-driven analysis of epithelial brushings and bronchial biopsies to define asthma phenotypes in U-BIOPRED
- 2017
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Ingår i: American Journal of Respiratory and Critical Care Medicine. - 1073-449X .- 1535-4970. ; 194:4, s. 443-455
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Tidskriftsartikel (refereegranskat)abstract
- RATIONALE AND OBJECTIVES: Asthma is a heterogeneous disease driven by diverse immunologic and inflammatory mechanisms. We used transcriptomic profiling of airway tissues to help define asthma phenotypes.METHODS: The transcriptome from bronchial biopsies and epithelial brushings of 107 moderate-to-severe asthmatics were annotated by gene-set variation analysis (GSVA) using 42 gene-signatures relevant to asthma, inflammation and immune function. Topological data analysis (TDA) of clinical and histological data was used to derive clusters and the nearest shrunken centroid algorithm used for signature refinement.RESULTS: 9 GSVA signatures expressed in bronchial biopsies and airway epithelial brushings distinguished two distinct asthma subtypes associated with high expression of T-helper type 2 (Th-2) cytokines and lack of corticosteroid response (Group 1 and Group 3). Group 1 had the highest submucosal eosinophils, high exhaled nitric oxide (FeNO) levels, exacerbation rates and oral corticosteroid (OCS) use whilst Group 3 patients showed the highest levels of sputum eosinophils and had a high BMI. In contrast, Group 2 and Group 4 patients had an 86% and 64% probability of having non-eosinophilic inflammation. Using machine-learning tools, we describe an inference scheme using the currently-available inflammatory biomarkers sputum eosinophilia and exhaled nitric oxide levels along with OCS use that could predict the subtypes of gene expression within bronchial biopsies and epithelial cells with good sensitivity and specificity.CONCLUSION: This analysis demonstrates the usefulness of a transcriptomic-driven approach to phenotyping that segments patients who may benefit the most from specific agents that target Th2-mediated inflammation and/or corticosteroid insensitivity.
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| 3. |
- Lefaudeux, Diane, et al.
(författare)
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U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
- 2017
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Ingår i: Journal of Allergy and Clinical Immunology. - : Elsevier BV. - 0091-6749 .- 1097-6825. ; 139:6, s. 1797-1807
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided.OBJECTIVES: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum.METHODS: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data.RESULTS: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels.CONCLUSION: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.
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| 4. |
- Perotin-Collard, Jeanne-Marie, et al.
(författare)
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Subtypes of eosinophilic asthma with discrete gene pathway phenotypes
- 2019
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Ingår i: European Respiratory Journal. - : European Respiratory Society Journals. - 0903-1936 .- 1399-3003. ; 54
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Blood eosinophil counts ≥0.3x109/L are used to define Type-2, eosinophilic asthma. However, differential responses to T2 biologics of patients with eosinophilic asthma suggests that this may be a heterogeneous phenotype with subsets driven by different molecular mechanisms.Methods: Blood transcriptomic data, acquired from 99 severe asthmatics from the U-BIOPRED study (62% female, mean age 54 yr, 41% on oral steroids), were clustered by topological data analysis and cluster boundaries defined by the MORSE method. Gene pathway signatures were identified by Ingenuity Pathway Analysis.Results: Analysis revealed 3 clusters with different modulated gene pathways, i.e. molecular phenotypes. Subtype 1 had high IFN-γ, low IL5, low IL13 and low IL17 gene expression, with reduced glucocorticoid-induced gene expression. Subtype 2 had low IFNγ, high IL5, high IL13 and low IL17 gene expression. Subtype 3 had low IFNγ, high IL5, high IL13 and high IL17 gene expression. Pathway analysis suggested a strong steroid response in Subtypes 2 and 3. Clinically, the three clusters were not different in respect of age, gender, prevalence of atopy, blood or sputum eosinophil counts. Subtype 3 was characterized by high neutrophil counts in blood and bronchial epithelium, frequent sinus disease and asthma exacerbations, OCS treatment, low allergic sensitisation and low exhaled NO. Subtype 1 was characterized by high exhaled NO and more frequent IgE therapy.Conclusion: This study suggests that eosinophilic severe asthma (≥0.3x109/L) can be stratified further into 3 subtypes with distinct gene expression profiles that could be developed as molecular diagnostic biomarkers to guide treatment and thereby improve patient outcomes.
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