Asthma can be divided into at least two distinct molecular phenotypes defined by degree of Th2 inflammation. Th2 cytokines are likely to be a relevant therapeutic target in only a subset of patients with asthma. Furthermore, current models do not adequately explain non-Th2-driven asthma, which represents a significant proportion of patients and responds poorly to current therapies.

The difference in exacerbation frequency between omalizumab and placebo was greatest in the three high-biomarker subgroups, probably associated with the greater risk for exacerbations in high subgroups. Additional studies are required to explore the value of these biomarkers in clinical practice. Clinical trial registered with www.clinicaltrials.gov (NCT00314574).

Background Asthma is heterogeneous, and airway dysbiosis is associated with clinical features in mild-moderate asthma. Whether similar relationships exist among patients with severe asthma is unknown. Objective To evaluate relationships between the bronchial microbiome and features of severe asthma. Methods Bronchial brushings from 40 participants in the BOBCAT study (Bronchoscopic Exploratory Research Study of Biomarkers in Corticosteroid-refractory Asthma) were evaluated using 16S rRNA-based methods. Relationships to clinical and inflammatory features were analyzed among microbiome-profiled subjects. Secondarily, bacterial compositional profiles were compared between severe asthmatics, and previously studied healthy controls (n=7), and mild-moderate asthma subjects (n=41). Results In severe asthma, bronchial bacterial composition was associated with several disease-related features, including body-mass index (BMI; Bray-Curtis distance PERMANOVA, p < 0.05), changes in Asthma Control Questionnaire (ACQ) scores (p < 0.01), sputum total leukocytes (p = 0.06) and bronchial biopsy eosinophils (per mm2; p = 0.07). Bacterial communities associated with worsening ACQ and sputum total leukocytes (predominantly Proteobacteria) differed markedly from those associated with BMI (Bacteroidetes/Firmicutes). In contrast, improving/stable ACQ and bronchial epithelial gene expression of FKBP5, an indicator of steroid responsiveness, correlated with Actinobacteria. Mostly negative correlations were observed between biopsy eosinophils and Proteobacteria. No taxa were associated with a T-helper type 2-related epithelial gene expression signature, but expression of Th17-related genes was associated with Proteobacteria. Severe asthma subjects, compared to healthy controls or mild-moderate asthmatics, were significantly enriched in Actinobacteria, although the largest differences observed involved a Klebsiella genus member (7.8 fold-increase in severe asthma, padj < 0.001) Conclusions Specific microbiota are associated with and may modulate inflammatory processes in severe asthma and related phenotypes. Airway dysbiosis in severe asthma appears to differ from that observed in milder asthma in the setting of inhaled corticosteroid use.

Background Eosinophilic airway inflammation is heterogeneous in asthmatic patients. We recently described a distinct subtype of asthma defined by the expression of genes inducible by TH2 cytokines in bronchial epithelium. This gene signature, which includes periostin, is present in approximately half of asthmatic patients and correlates with eosinophilic airway inflammation. However, identification of this subtype depends on invasive airway sampling, and hence noninvasive biomarkers of this phenotype are desirable. Objective We sought to identify systemic biomarkers of eosinophilic airway inflammation in asthmatic patients. Methods We measured fraction of exhaled nitric oxide (Feno), peripheral blood eosinophil, periostin, YKL-40, and IgE levels and compared these biomarkers with airway eosinophilia in asthmatic patients. Results We collected sputum, performed bronchoscopy, and matched peripheral blood samples from 67 asthmatic patients who remained symptomatic despite maximal inhaled corticosteroid treatment (mean FEV1, 60% of predicted value; mean Asthma Control Questionnaire [ACQ] score, 2.7). Serum periostin levels are significantly increased in asthmatic patients with evidence of eosinophilic airway inflammation relative to those with minimal eosinophilic airway inflammation. A logistic regression model, including sex, age, body mass index, IgE levels, blood eosinophil numbers, Feno levels, and serum periostin levels, in 59 patients with severe asthma showed that, of these indices, the serum periostin level was the single best predictor of airway eosinophilia (P = .007). Conclusion Periostin is a systemic biomarker of airway eosinophilia in asthmatic patients and has potential utility in patient selection for emerging asthma therapeutics targeting TH2 inflammation.

Concurrent blockade of IL-13 and IL-17A may improve control of asthma.