Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation.

RATIONALE: Asthma phenotyping requires novel biomarker discovery. OBJECTIVES: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). METHODS: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. RESULTS: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-ß and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. CONCLUSIONS: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.

Phenotypic predictors of response to oral glucocorticosteroids in severe asthma.

BACKGROUND: Systemic glucocorticosteroids are side-effect prone but often necessary for the treatment of severe asthma (SA). Our goal was to assess the usefulness of medical history, physiological variables and biomarkers as predictors of response to oral steroids. METHODS: After 4 weeks of treatment optimization, 84 patients with SA and 62 with mild-to-moderate asthma (MA) underwent a 2 week double-blind placebo-controlled oral prednisolone intervention (0.5 mg/kg BW daily) (NCT00555607). RESULTS: Responders had a lower FEV1% (73.7 vs. 88.0), lower FEV1/FVC ratio (0.65 vs. 0.73), lower quality of life (SGRQ score 39.1 vs. 31.4), lower total sputum cell number (1.0 vs. 4.5×10(6)) and higher number of sputum eosinophils (16.8% vs. 6.3%) (p<0.05). For all asthmatics, the degree of improvement in FEV1 correlated with sputum eosinophils, level of asthma control, FeNO, quality of life, age of asthma onset and blood eosinophils. In SA, sputum eosinophils≥3% (OR 9.91), FEV1≤60% (OR 3.7), and SGRQ>42.2 (OR 3.25) were associated with a good response to oral prednisolone. The highest sensitivity and specificity to predict more than 12% increase in FEV1 in SA after oral prednisolone was found for sputum eosinophils≥3% and FeNO>45 ppb. CONCLUSIONS: Sputum eosinophils and FeNO were the best predictors of favorable response to oral prednisolone in severe asthmatics. A guided approach to glucocorticosteroid treatment should be recommended as it favors better control of the disease and presumably a lower rate of adverse events. The study has been registered at the site: clinicaltrials.gov with number: NCT00555607.

Detection of exacerbations in asthma based on electronic diary data: results from the 1-year prospective BIOAIR study.

BACKGROUND: Objective measures are required that may be used as a proxy for exacerbations in asthma. The aim was to determine the sensitivity and specificity of electronic diary data to detect severe exacerbations (SEs) of asthma. A secondary aim was to identify phenotypic variables associated with a higher risk of exacerbation. METHODS: In the BIOAIR study, 169 patients with asthma (93 severe (SA); 76 mild to moderate (MA)) recorded lung function, symptoms and medication use in electronic diaries for 1 year. Data were analysed using receiver-operator characteristics curves and related to physician-diagnosed exacerbations. Medical history and baseline clinical data were used to assess risk of exacerbation. RESULTS: Of 122 physician-diagnosed exacerbations, 104 occurred in the SA group (1.1 per patient/year), 18 in the MA group (0.2 per patient/year) and 63 were severe using American Thoracic Society/European Respiratory Society criteria. During exacerbations, peak expiratory flow (PEF) and forced expiratory volume in 1 s significantly decreased, whereas day and night symptoms significantly increased. An algorithm combining a 20% decrease in PEF or a 20% increase in day symptoms on 2 consecutive days was able to detect SEs with 65% sensitivity and 95% specificity. The strongest risk factors for SEs were low Asthma Control Questionnaire score, sputum eosinophils ≥ 3%, body mass index >25 and low quality of life (St George's Respiratory Questionnaire), with ORs between 3.61 and 2.22 (p<0.05). CONCLUSIONS: Regular electronic monitoring of PEF and asthma symptoms provides an acceptable sensitivity and specificity for the detection of SEs and may be suitable for personal internet-based monitoring of asthma control.