Abstract
BackgroundTargeted approaches may not account for the complexity of inflammation involved in children with severe asthma (SA), highlighting the need to consider more global analyses. We aimed to identify sets of immune constituents that distinguish children with SA from disease-control subjects through a comprehensive analysis of cells and immune constituents measured in bronchoalveolar lavage (BAL) and blood.MethodsTwenty children with SA and 10 age-matched control subjects with chronic respiratory disorders other than asthma were included. Paired blood and BAL samples were collected and analyzed for a large set of cellular (eosinophils, neutrophils, and subsets of lymphocytes and innate lymphoid cells) and soluble (chemokines, cytokines, and total antibodies) immune constituents. First, correlations of all immune constituents between BAL and blood and with demographic and clinical data were assessed (Spearman correlations). Then, all data were modelled using supervised multivariate analyses (partial least squares discriminant analysis, PLS-DA) to identify immune constituents that significantly discriminate between SA and control subjects. Univariate analyses were performed (Mann-Whitney tests) and then PLS-DA and univariate analyses were combined to identify the most discriminative and significant constituents.ResultsConcentrations of soluble immune constituents poorly correlated between BAL and blood. Certain constituents correlated with age or body mass index and, in asthmatics, with clinical symptoms, such as the number of exacerbations in the previous year, asthma control test score, or forced expiratory volume. Multivariate supervised analysis allowed construction of a model capable of distinguishing children with SA from control subjects with 80% specificity and 100% sensitivity. All immune constituents contributed to the model but some, identified by variable-important-in-projection values > 1 and p < 0.1, contributed more strongly, including BAL Th1 and Th2 cells and eosinophilia, CCL26 (Eotaxin 3), IgA and IL-19 concentrations in blood. Blood concentrations of IL-26, CCL13, APRIL, and Pentraxin-3 may also help in the characterization of SA.ConclusionsThe analysis of a large set of immune constituents may allow the identification of a biological immune signature of SA. Such an approach may provide new leads for delineating the pathogenesis of SA in children and identifying new targets for its diagnosis, prediction, and personalized treatment.
Highlights
Asthma encompasses multiple phenotypes characterized by common symptoms and variable degrees of airflow limitation [1, 2]
Children with severe asthma (SA) used higher doses of inhaled corticosteroids (ICS) and had a higher post-bronchodilator forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) and higher blood eosinophil counts than control subjects
Certain control subjects were being treated with ICS at the time of inclusion, the diagnosis of asthma was excluded based on history, response to bronchodilators, spirometry, and nasal nitric oxide testing or tomodensitometry
Summary
Asthma encompasses multiple phenotypes characterized by common symptoms and variable degrees of airflow limitation [1, 2]. Recent studies have shown that bronchoalveolar lavage (BAL) from children with SA may instead display a dominant Th1 signature, with Th17 and Th2 cells in a mixed cytokine milieu and rare ILC2 [10]. We recently evidenced that children with SA and frequent exacerbations exhibited a mixed T2/T17 phenotype, whereas those with less frequent exacerbations were characterized by a more pronounced T1 phenotype [17]. Overall, this suggests that different asthma phenotypes may result from various pathophysiological mechanisms, i.e. various. We aimed to identify sets of immune constituents that distinguish children with SA from disease-control subjects through a comprehensive analysis of cells and immune constituents measured in bronchoalveolar lavage (BAL) and blood
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