Asthma is a chronic condition with great variability. It is characterized by intermittent episodes of wheeze, cough, chest tightness, dyspnea and backed by variable airflow limitation, airway inflammation and airway hyper-responsiveness. Asthma severity varies uniquely between individuals and may change over time. Stratification of asthma severity is an integral part of asthma management linking appropriate treatment to establish asthma control. Precision assessment of severe asthma is crucial for monitoring the health of people with this disease. The literature suggests multiple factors that impede the assessment of severe asthma, these can be grouped into health care professional, patient and organizational related barriers. These barriers do not exist in isolation but interact and influence one another. Recognition of these barriers is necessary to promote precision in the assessment and management of severe asthma in the era of targeted therapy. In this review, we discuss the current knowledge of the barriers that impede assessment in severe asthma and recommend potential strategies for overcoming these barriers. We highlight the relevance of multidimensional assessment as an ideal approach to the assessment and management of severe asthma.
The clinical and inflammatory associations of mast cells (MCs) and basophils in chronic obstructive pulmonary disease (COPD) are poorly understood. We previously developed and validated a qPCR-based MC/basophil gene signature in asthma to measure these cells in sputum samples. Here, we measured this gene signature in a COPD and control population to explore the relationship of sputum MCs/basophils to inflammatory and COPD clinical characteristics. Patients and Methods: MC/basophil signature genes (TPSAB1/TPSB2, CPA3, ENO2, GATA2, KIT, GPR56, HDC, SOCS2) were measured by qPCR in sputum from a COPD (n=96) and a non-respiratory control (n=17) population. Comparative analyses of gene expression between the COPD and the control population, and between eosinophilic COPD and non-eosinophilic COPD were tested. Logistic regression analysis and Spearman correlation were used to determine relationships of sputum MC/basophil genes to inflammatory (sputum eosinophil proportions, blood eosinophils) and clinical (age, body mass index, quality of life, lung function, past year exacerbations) characteristics of COPD. Results: MC/basophil genes were increased in COPD versus control participants (CPA3, KIT, GATA2, HDC) and between eosinophilic-COPD and non-eosinophilic COPD (TPSB2, CPA3, HDC, SOCS2). We found all MC/basophil genes were positively intercorrelated. In COPD, MC/basophil genes were associated with eosinophilic airway inflammation (GATA2, TPSB2, CPA3, GPR56, HDC, SOCS2), blood eosinophilia (all genes) and decreased lung function (KIT, GATA2, GPR56, HDC). Conclusion:We demonstrate associations of MCs and basophils with eosinophilic inflammation and lower lung function in COPD. These findings are consistent with prior results in asthma and may represent a new tool for endotyping eosinophilic-COPD.
Background Airway and systemic eosinophilia are important treatable traits in both severe asthma and COPD. The molecular basis of eosinophilia in COPD is poorly understood but could involve type 2 cytokines (IL5, IL13) and prostaglandin D2 (PGD2). Methods This study included non‐obstructive airways disease (OAD) controls (n = 19), a COPD cohort (n = 96) and a severe asthma cohort (n = 84). Demographics, exacerbation history, disease impact (SGRQ) and spirometry were assessed. Participants were categorized as eosinophilic using either sputum eosinophil proportion (≥3%) or blood eosinophil count (≥300/μL). Sputum type 2 inflammatory measures included PGD2 by ELISA and gene expression (qPCR) of IL5, IL13 and the haematopoietic PGD2 synthase (HPGDS). Results Type 2 markers did not differ across groups except HPGDS mRNA which was highest in non‐OAD controls and lowest in COPD. IL5 and IL13 mRNA and PGD2 levels were significantly increased in eosinophilic vs non‐eosinophilic severe asthma but did not differ between eosinophilic COPD and eosinophilic severe asthma or non‐eosinophilic COPD. HPGDS expression was higher in eosinophilic severe asthma compared with eosinophilic COPD. Results were similar using sputum or blood eosinophil cut‐offs. Sputum IL5 and IL13 were highly intercorrelated in severe asthma (r = 0.907, p < 0.001) and COPD (r = 0.824, p < 0.001), were moderately correlated with sputum eosinophils in severe asthma (IL5 r = 0.440, p < 0.001; IL13 r = 0.428, p < 0.001) and were weakly correlated in COPD (IL5 r = 0.245, p < 0.05; IL13 r = 0.317, p < 0.05). Conclusions Molecular markers of type 2 airway inflammation do not differ between eosinophilic asthma and eosinophilic COPD; however, the relationship between eosinophilia and type 2 airway markers appears weaker in COPD than in severe asthma.
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