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.

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.

Background There is microscopic spatial and temporal heterogeneity of pathologic changes in idiopathic pulmonary fibrosis (IPF) lung tissue, which may relate to heterogeneity in pathophysiological mediators of disease and clinical progression. We assessed relationships between gene expression patterns, pathological features, and systemic biomarkers to identify biomarkers that reflect the aggregate disease burden in IPF patients. Methods Gene expression microarrays (N=40 IPF; 8 controls) and immunohistochemical analyses (N=22 IPF; 8 controls) of lung biopsies. Clinical characterization and blood biomarker levels of MMP3 and CXCL13 in a separate cohort of IPF patients (N=80). Results 2940 genes were significantly differentially expressed between IPF and control samples (|fold change| > 1.5, p < 0.05). Two clusters of co-regulated genes related to bronchiolar epithelium or lymphoid aggregates exhibited substantial heterogeneity within the IPF population. Gene expression in bronchiolar and lymphoid clusters corresponded to the extent of bronchiolization and lymphoid aggregates determined by immunohistochemistry in adjacent tissue sections. Elevated serum levels of MMP3, encoded in the bronchiolar cluster, and CXCL13, encoded in the lymphoid cluster, corresponded to disease severity and shortened survival time (p < 10−7 for MMP3 and p < 10−5 for CXCL13; Cox proportional hazards model). Conclusions Microscopic pathological heterogeneity in IPF lung tissue corresponds to specific gene expression patterns related to bronchiolization and lymphoid aggregates. MMP3 and CXCL13 are systemic biomarkers that reflect the aggregate burden of these pathological features across total lung tissue. These biomarkers may have clinical utility as prognostic and/or surrogate biomarkers of disease activity in interventional studies in IPF.

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BackgroundPeriostin levels are associated with airway eosinophilia and are suppressed by corticosteroid treatment in asthma. This study sought to determine the relationship between serum and sputum periostin, airway inflammatory phenotype and asthma control.MethodsAdults with poorly-controlled asthma (n = 83) underwent a clinical assessment, sputum induction and blood sampling. Dispersed sputum was used for a differential cell count and periostin assessment (ELISA). Serum periostin was determined by the Elecsys® immunoassay.ResultsPeriostin levels were significantly higher in serum (median (IQR) of 51.6 (41.8, 62.6) ng/mL) than in sputum (1.1 (0.5, 2.0) ng/mL) (p < 0.001). Serum and sputum periostin were significantly higher in patients with eosinophilic asthma (n = 37) compared with non-eosinophilic asthma. Both serum and sputum periostin levels were significantly associated with proportion of sputum eosinophils (r = 0.422, p < 0.001 and r = 0.364, p = 0.005 respectively) but were not associated with asthma control. In receiver operator characteristic curve analysis, the area under the curve (AUC) for serum periostin (n = 83) was 0.679, p = 0.007. Peripheral blood eosinophils assessed in 67 matched samples, had a numerically greater AUC of 0.820 compared with serum periostin, p = 0.086 for the detection of eosinophilic asthma.ConclusionIn poorly-controlled asthma, sputum and serum periostin levels are significantly related to sputum eosinophil proportions while their ability to predict the presence of eosinophilic asthma is modest.Electronic supplementary materialThe online version of this article (doi:10.1186/s12890-016-0230-4) contains supplementary material, which is available to authorized users.

Highlights d Increased tryptase levels in asthma that is independent of type 2 inflammation d Higher active allele b-tryptase count associated with lesser omalizumab response d Discovery, biochemistry, and structure of a noncompetitive inhibitory anti-tryptase d Favorable PK and potent inhibition of tryptase activity in mouse and primate models