Data‐driven adult asthma phenotypes based on clinical characteristics are associated with asthma outcomes twenty years later

Abstract

Background: Research based on cluster analyses led to the identification of particular phenotypes confirming phenotypic heterogeneity of asthma. The long-term clinical course of asthma phenotypes defined by clustering analysis remains unknown, Abbreviations: ACT, asthma control test; AQLQ, asthma quality of life questionnaire; BHR, bronchial hyper-responsiveness; ECRHS, European Community Respiratory Health Survey; EGEA, epidemiological study of the genetics and environment of asthma, bronchial hyper-responsiveness and atopy; ICS, inhaled corticosteroids; LF, lung function; LTA, latent transition analysis; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity. Methods:The study relied on two cohorts of adults with asthma with 20-year follow-up, ECRHS (European Community Respiratory Health Survey) and EGEA (Epidemiological study on Genetics and Environment of Asthma). Regression models were used to compare asthma characteristics (current asthma, asthma exacerbations, asthma control, quality of life, and FEV 1 ) at follow-up and the course of FEV 1 between seven cluster-based asthma phenotypes identified 20 years earlier. Results:The analysis included 1325 adults with ever asthma. For each asthma characteristic assessed at follow-up, the risk for adverse outcomes differed significantly between the seven asthma clusters identified at baseline. As compared with the mildest asthma phenotype, ORs (95% CI) for asthma exacerbations varied from 0.9 (0.4 to 2.0) to 4.0 (2.0 to 7.8) and the regression estimates (95% CI) for FEV 1 % predicted varied from 0.6 (−3.5 to 4.6) to −9.9 (−14.2 to −5.5) between clusters. Change in FEV 1 over time did not differ significantly across clusters. Conclusion:Our findings show that the long-term risk for poor asthma outcomes differed between comprehensive adult asthma phenotypes identified 20 years earlier, and suggest a strong tracking of asthma activity and impaired lung function over time. K E Y W O R D Sasthma, clustering, follow-up, lung function, phenotypes

T cell requirement and phenotype stability of house dust mite–induced neutrophil airway inflammation in mice

“…Moreover, mice initially exposed to low-dose HDM (and thus representing the mixed AAI) which during the chronic phase received high-dose HDM challenges maintained their mixed inflammatory phenotype pattern.Similarly, mice initially exposed to high-dose HDM and thus showing a neutrophil-dominated inflammation did not show changes in their phenotype when later challenged with low-dose HDM even though a slight (nonsignificant) reduction in the number of both, eosinophils and neutrophils, was observed in these mice (Figure 2C-D). Taken together, this implies that the resulting inflammatory phenotype is mainly determined by the initial sensitization processes since modifications in exposure conditions during the chronification process did not change the inflammatory phenotype once it is established like also observed in human studies 6. This should not implicate that phenotypes are stable per se.…”

“…For milder reactions such as MPE, a so-called treating through strategy may be employed, reintroducing procarbazine with concomitant use of antihistamines and corticosteroids. 6 While desensitization protocols are available for direct, IgE-mediated DHR against several other chemotherapeutics, no such protocols exist for procarbazine.…”

Needs for Systems Approaches to Better Treat Individuals With Severe Asthma: Predicting Phenotypes and Responses to Treatments

“…Unbiased methods of clustering led to different phenotypes according to the clinical, functional and biological data chosen. Over time, the stability of those clusters was quite strong overall but varied across phenotypes (18). Although clusters might slightly differ according to the data sets used, some critical characteristics were common, including the age of onset (early vs. late onset of asthma), atopic status, obesity, comorbidities, and eosinophilic inflammation.…”

“…A retrospective study based on clinical and functional parameters in 1,325 asthmatic patients with a 20-year follow-up identified 7 baseline clusters of patients. An interesting point is that only 1/5 of the patients moved from a cluster to another during follow-up (18). This question has been addressed by preliminary unbiased studies using omics sciences, such as in the ADEPT cohort, in which a stable and reproducible clustering of patients was found through external validation in the U-BIOPRED cohort over a 12-month follow-up (101).…”

Asthma Case Cluster during Renovation of a Water-Damaged and Toxic Building

“…It is heterogeneous, and respiratory symptoms and airflow obstruction vary. Different categories of asthma have been identified based on clinical and physiological features [2][3][4]. From the point of immunopathology, for example, asthma can be divided into eosinophilic, non-eosinophilic, and mixed granulocytic disease [5].…”