Airway gene expression identifies subtypes of type 2 inflammation in severe asthma.

BACKGROUND: Type 2 inflammation is characterized by enhanced activity of interleukin (IL)-4, -5 and -13, and treatments targeting these pathways are available for treatment of severe asthma. At present, the pattern of pathway activity and the implications overlapping of pathway activity are unknown. OBJECTIVE: We hypothesized that clustering of airway mRNA expression would identify distinct molecular subtypes of severe asthma and thereby uncover the prevalence and overlap of pathway activity. METHODS: Sputum mRNA expression of genes related to expression of IL-5(CLC, CPA3 and DNASE1L3), IL-13(IL13Ra1, TNFSF14 and SERPINB2), T1/Th17 activity(IL1B, ALPL and CXCR2) and in vitro response to corticosteroids (FKBP512) and mepolizumab (ARAP3) was analysed in patients (n = 109) with severe asthma and healthy controls (n = 22). A cluster analysis of gene expression was performed. The response to a short course of OCS was assessed in a subset of patients (n = 29). RESULTS: Five molecular clusters were identified. Three had abundant T2 gene expression of which two (n = 39 and n = 9) were characterized by abundant expression of both IL-13- and IL-5-related genes. The last (n = 6) had only abundant IL-5-related gene expression. These T2-high molecular clusters could not be distinguished using T2 biomarkers. T2- and Th1/Th17-related mRNA expression were co-expressed across all clusters. OCS significantly reduced T2 gene expression (CLC, IL13Ra1, SERPINB2 and ARAP3) and significantly increase expression of Th1/Th17-related genes (ALPL and CXCR2). CONCLUSIONS AND CLINICAL RELEVANCE: Clustering of airway mRNA expression identified five molecular clusters of severe asthma of which three were considered T2 high. Co-expression of IL-5- and IL-13-related genes at moderate levels was present in almost half of patients, while marked elevated expression of both was rare. In contrast to IL-5, clusters with isolated IL-13- and Th1/Th17-related gene expression were not identified.

Treating severe asthma: Targeting the IL-5 pathway.

Severe asthma is a heterogeneous disease with different phenotypes based on clinical, functional or inflammatory parameters. In particular, the eosinophilic phenotype is associated with type 2 inflammation and increased levels of interleukin (IL)-4, IL-5 and IL-13). Monoclonal antibodies that target the eosinophilic inflammatory pathways (IL-5R and IL-5), namely mepolizumab, reslizumab, and benralizumab, are effective and safe for severe eosinophilic asthma. Eosinophils threshold represents the most indicative biomarker for response to treatment with all three monoclonal antibodies. Improvement in asthma symptoms scores, lung function, the number of exacerbations, history of late-onset asthma, chronic rhinosinusitis with nasal polyposis, low oral corticosteroids use and low body mass index represent predictive clinical markers of response. Novel Omics studies are emerging with proteomics data and exhaled breath analyses. These may prove useful as biomarkers of response and non-response biologics. Moreover, future biomarker studies need to be undertaken in paediatric patients affected by severe asthma. The choice of appropriate biologic therapy for severe asthma remains challenging. The importance of finding biomarkers that can predict response continuous an open issue that needs to be further explored. This review describes the clinical effects of targeting the IL-5 pathway in severe asthma in adult and paediatric patients, focusing on predictors of response and non-response.

The six-gene expression signature in whole sampled sputum provides clinically feasible inflammatory phenotyping of asthma.

Processing of induced sputum is time consuming and requires trained personnel, and consequently the use of induced sputum is limited to few sites globally. The six-gene signature (6GS) is an mRNA-based gene signature that was developed to provide a clinically feasible method for inflammatory phenotyping. In this study, we assessed whether the 6GS would perform similarly in induced sputum sampled using a simplified method, by which induced sputum can be sampled and stored directly for later qPCR analyses, to the conventional method of manual plug selection. Two separate sputum samples were collected from 27 patients with asthma; one processed as a whole sample in an Oragene-RNA RE 100 vial and one processed using manual plug selection. Expression of 6GS was measured in both samples, of which 20 pairs (74%) had enough samples and results of sufficient quality of gene expression for further analyses. We found a significantly higher median RNA concentration in whole sampled sputum and consistently stronger gene expression compared to the plug method. Further, we found the two methods to agree, as 97% of observations were within the limits of agreement, as well as having a good-to-excellent reliability using intraclass correlation. Finally, we found 6GS in the whole sampled sputum to perform equal to or better than the manually selected plugs for discriminating inflammatory phenotypes defined by sputum differential count. In conclusion, whole sampling of induced sputum provides a clinically feasible method for inflammatory phenotyping.