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- Brinkman, Paul, et al.
(författare)
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Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma
- 2019
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Ingår i: Journal of Allergy and Clinical Immunology. - : Elsevier. - 0091-6749 .- 1097-6825. ; 143:5, s. 1811-1820.e7
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Tidskriftsartikel (refereegranskat)abstract
- Background: Severe asthma is a heterogeneous condition, as shown by independent cluster analyses based on demographic, clinical, and inflammatory characteristics. A next step is to identify molecularly driven phenotypes using “omics” technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes.Objectives: We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the stability of eNose-derived phenotypes in relation to withinpatient clinical and inflammatory changes.Methods: In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability.Results: Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNosedriven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045).Conclusions: We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma.
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| 2. |
- 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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