Rationale Airway inflammation in asthma is heterogeneous with different phenotypes. The inflammatory cell phenotype is modified by corticosteroids and smoking. Steroid therapy is beneficial in eosinophilic asthma (EA), but evidence is conflicting regarding non-eosinophilic asthma (NEA). Objectives To assess the inflammatory cell phenotypes in asthma after eliminating potentially confounding effects; to compare steroid response in EA versus NEA; and to investigate changes in sputum cells with inhaled corticosteroid (ICS). Methods Subjects undertook ICS withdrawal until loss of control or 28 days. Those with airway hyperresponsiveness (AHR) took inhaled fluticasone 1000 mg daily for 28+ days. Cut-off points were $/<2% for sputum eosinophils and $/<61% for neutrophils. Results After steroid withdrawal (n¼94), 67% of subjects were eosinophilic, 31% paucigranulocytic and 2% mixed; there were no neutrophilic subjects. With ICS (n¼88), 39% were eosinophilic, 46% paucigranulocytic, 3% mixed and 5% neutrophilic. Sputum neutrophils increased from 19.3% to 27.7% (p¼0.024). The treatment response was greater in EA for symptoms (p<0.001), quality of life (p¼0.012), AHR (p¼0.036) and exhaled nitric oxide (p¼0.007). Lesser but significant changes occurred in NEA (ie, paucigranulocytic asthma). Exhaled nitric oxide was the best predictor of steroid response in NEA for AHR (area under the curve 0.810), with an optimum cut-off point of 33 ppb. Conclusions After eliminating the effects of ICS and smoking, a neutrophilic phenotype could be identified in patients with moderate stable asthma. ICS use led to phenotype misclassification. Steroid responsiveness was greater in EA, but the absence of eosinophilia did not indicate the absence of a steroid response. In NEA this was best predicted by baseline exhaled nitric oxide.

Background Asthma is a heterogeneous disease with different phenotypes. Inhaled corticosteroid (ICS) therapy is a mainstay of treatment for asthma but the clinical response to ICS is variable. Objective We hypothesized that a panel of inflammatory biomarkers i.e. FENO, sputum eosinophils and urinary BromoTyrosine (BrTyr) might predict steroid responsiveness. Methods The original study, from which this analysis originates, comprised 2 phases: a steroid naïve phase 1 and a 28-day trial of ICS (phase 2) during which times, FENO, sputum eosinophils, and urinary BrTyr were measured. Response to ICS was based on clinical improvements including: ≥12% increase in FEV1; ≥0.5 point decrease in Asthma Control Questionnaire; and ≥2 doubling dose increase in provocation concentration of adenosine 5′-monophosphate causing a 20% fall in FEV1 (PC20 AMP). Healthy controls were also evaluated in this study for comparison of biomarkers to asthmatics. Results Asthmatics had higher than normal FENO, sputum eosinophils and urinary BrTyr at steroid naïve phase and after ICS. After 28-day trial of ICS, FENO decreased in 82% of asthmatics, sputum eosinophils decreased in 60% and urinary BrTyr decreased in 58%. Each of the biomarkers at steroid naïve phase had utility for predicting steroid- responsiveness, but the combination of high FENO and high urinary BrTyr had the best power (13.3 fold; p<0.01) to predict a favorable response to ICS. However, the magnitude of decrease of biomarkers was unrelated to the magnitude of clinical response to ICS. Conclusion A noninvasive panel of biomarkers in steroid naïve asthmatics predicts clinical responsiveness to ICS.

Background Statins have anti-inflammatory actions which in theory are potentially beneficial in asthma. Small trials have failed to show a significant benefit, but a systematic study to evaluate the steroid-sparing effect of statin treatment has not been carried out. Methods A randomised, placebo-controlled, crossover trial was conducted of simvastatin 40 mg at night with simultaneous stepwise reduction of fluticasone propionate dose until loss of control occurred, followed by an increase until regain of control ('minimum' dose required) in 51 patients with asthma and sputum eosinophils (steroid-free) $2%.

Breath analysis by eNose can identify asthmatic patients and may be used to predict their response to steroids with greater accuracy than sputum eosinophils or FeNO. This implies a potential role for breath analysis in the tailoring of treatment for asthma patients.

The phenotypic classification of asthma changes frequently. A diagnosis of non-eosinophilic asthma should not be based on a single sputum sample.