BackgroundDisease heterogeneity in patients with severe asthma and its relationship to inflammatory mechanisms remain poorly understood.ObjectiveWe aimed to identify and replicate clinicopathologic endotypes based on analysis of blood and sputum parameters in asthmatic patients.MethodsOne hundred ninety-four asthmatic patients and 21 control subjects recruited from 2 separate centers underwent detailed clinical assessment, sputum induction, and phlebotomy. One hundred three clinical, physiologic, and inflammatory parameters were analyzed by using topological data analysis and Bayesian network analysis.ResultsSevere asthma was associated with anxiety and depression, obesity, sinonasal symptoms, decreased quality of life, and inflammatory changes, including increased sputum chitinase 3–like protein 1 (YKL-40) and matrix metalloproteinase (MMP) 1, 3, 8, and 12 levels. Topological data analysis identified 6 clinicopathobiologic clusters replicated in both geographic cohorts: young, mild paucigranulocytic; older, sinonasal disease; obese, high MMP levels; steroid resistant TH2 mediated, eosinophilic; mixed granulocytic with severe obstruction; and neutrophilic, low periostin levels, severe obstruction. Sputum IL-5 levels were increased in patients with severe particularly eosinophilic forms, whereas IL-13 was suppressed and IL-17 levels did not differ between clusters. Bayesian network analysis separated clinical features from intricately connected inflammatory pathways. YKL-40 levels strongly correlated with neutrophilic asthma and levels of myeloperoxidase, IL-8, IL-6, and IL-6 soluble receptor. MMP1, MMP3, MMP8, and MMP12 levels were associated with severe asthma and were correlated positively with sputum IL-5 levels but negatively with IL-13 levels.ConclusionIn 2 distinct cohorts we have identified and replicated 6 clinicopathobiologic clusters based on blood and induced sputum measures. Our data underline a disconnect between clinical features and underlying inflammation, suggest IL-5 production is relatively steroid insensitive, and highlight the expression of YKL-40 in patients with neutrophilic inflammation and the expression of MMPs in patients with severe asthma.

MicroRNAs are short non-coding single stranded RNAs that regulate gene expression. While much is known about the effects of individual microRNAs, there is now growing evidence that they can work in co-operative networks. MicroRNAs are known to be dysregulated in many diseases and affect pathways involved in the pathology. We investigated dysregulation of microRNA networks using asthma as the disease model. Asthma is a chronic inflammatory disease of the airways characterized by bronchial hyperresponsiveness and airway remodelling. The airway epithelium is a major contributor to asthma pathology and has been shown to produce an excess of inflammatory and pro-remodelling cytokines such as TGF-β, IL-6 and IL-8 as well as deficient amounts of anti-viral interferons. After performing microRNA arrays, we found that microRNAs -18a, -27a, -128 and -155 are down-regulated in asthmatic bronchial epithelial cells, compared to cells from healthy donors. Interestingly, these microRNAs are predicted in silico to target several components of the TGF-β, IL-6, IL-8 and interferons pathways. Manipulation of the levels of individual microRNAs in bronchial epithelial cells did not have an effect on any of these pathways. Importantly, knock-down of the network of microRNAs miR-18a, -27a, -128 and -155 led to a significant increase of IL-8 and IL-6 expression. Interestingly, despite strong in silico predictions, down-regulation of the pool of microRNAs did not have an effect on the TGF-β and Interferon pathways. In conclusion, using both bioinformatics and experimental tools we found a highly relevant potential role for microRNA dysregulation in the control of IL-6 and IL-8 expression in asthma. Our results suggest that microRNAs may have different roles depending on the presence of other microRNAs. Thus, interpretation of in silico analysis of microRNA function should be confirmed experimentally in the relevant cellular context taking into account interactions with other microRNAs when studying disease.

Rationale: Asthma is one of the most common chronic diseases worldwide, and individuals with severe asthma experience recurrent exacerbations. Exacerbations are predominantly viral associated and have been linked to defective airway IFN responses. Ascertaining the molecular mechanisms underlying this deficiency is a major research goal to identify new therapeutic targets.Objectives: We investigated the hypothesis that reduced Toll-like receptor 7 (TLR7)-derived signaling drove the impaired IFN responses to rhinovirus by asthmatic alveolar macrophages (AMs); the molecular mechanisms underlying this deficiency were explored.Methods: AMs were recovered from bronchoalveolar lavage from healthy subjects and patients with severe asthma. Expression of pattern-recognition receptors and microRNAs was evaluated by quantitative polymerase chain reaction and Western blotting. A TLR7-luciferase reporter construct was created to evaluate binding of microRNAs to the 39 untranslated region of TLR7. IFN production was measured by quantitative polymerase chain reaction and ELISA.Measurements and Main Results: The expression of TLR7 was significantly reduced in severe asthma AMs and was associated with reduced rhinovirus and imiquimod-induced IFN responses by these cells compared with healthy AMs. Severe asthma AMs also expressed increased levels of three microRNAs, which we showed were able to directly reduce TLR7 expression. Ex vivo knockdown of these microRNAs restored TLR7 expression with concomitant augmentation of virus-induced IFN production.Conclusions: In severe asthma, TLR7 deficiency drives impaired innate immune responses to virus by AMs. Blocking a group of microRNAs that are up-regulated in these cells can restore antiviral innate responses, providing a novel approach for therapy in asthma.