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Asthma is characterised by heterogeneous clinical phenotypes. Our objective was to determine molecular phenotypes of asthma by analysing sputum cell transcriptomics from 104 moderate-to-severe asthmatic subjects and 16 nonasthmatic subjects.After filtering on the differentially expressed genes between eosinophil- and noneosinophil-associated sputum inflammation, we used unbiased hierarchical clustering on 508 differentially expressed genes and gene set variation analysis of specific gene sets.We defined three transcriptome-associated clusters (TACs): TAC1 (characterised by immune receptors IL33R, CCR3 and TSLPR), TAC2 (characterised by interferon-, tumour necrosis factor-α- and inflammasome-associated genes) and TAC3 (characterised by genes of metabolic pathways, ubiquitination and mitochondrial function). TAC1 showed the highest enrichment of gene signatures for interleukin-13/T-helper cell type 2 (Th2) and innate lymphoid cell type 2. TAC1 had the highest sputum eosinophilia and exhaled nitric oxide fraction, and was restricted to severe asthma with oral corticosteroid dependency, frequent exacerbations and severe airflow obstruction. TAC2 showed the highest sputum neutrophilia, serum C-reactive protein levels and prevalence of eczema. TAC3 had normal to moderately high sputum eosinophils and better preserved forced expiratory volume in 1 s. Gene-protein coexpression networks from TAC1 and TAC2 extended this molecular classification.We defined one Th2-high eosinophilic phenotype TAC1, and two non-Th2 phenotypes TAC2 and TAC3, characterised by inflammasome-associated and metabolic/mitochondrial pathways, respectively.
Patients and carers of someone with severe asthma have been involved across U-BIOPRED's activities via the project's Patient Input Platform (PIP). Members of the PIP have worked with the paper's author, Louise Fleming , and project lead, Peter Sterk, to produce a lay abstract for the paper, to ensure that the findings of the study are also accessible to patients and the public.
The U-BIOPRED consortium aims to improve our understanding of severe asthma and identify distinct groups of asthmatics (phenotypes). The identification of phenotypes can help to decide which treatments may be most effective in which group of patients and predict long term outcomes. In order to define these phenotypes information about factors which are important when considering asthma, including asthma control, lung function (blowing tests) and measures of inflammation, are collected. Usually a limited number of items are analysed, however U-BIOPRED is taking a novel approach by combining these measures with large amounts of data obtained from analysis of samples including sputum (phlegm), blood, exhaled breath, urine and throat swabs. Central to this process has been the recruitment of patients with asthma. In this paper we report on the characteristics of the paediatric cohorts and how asthma affects the lives of children with asthma and their parents.
Four groups of children and young people were recruited from 6 centres (London, Southampton, Manchester, Amsterdam, Bern and Copenhagen). All the children had been under follow up in these centres for at least six months and were only included in the study if both the child and the parent(s) were happy to participate. The four groups were:
Children with severe asthma and pre-school wheeze had poor control despite lots of asthma treatment, including high doses of inhaled steroids (500mcg per day or more of fluticasone or equivalent for school aged children and 200mcg per day or more for pre-school children) and other preventer medications (such as long acting beta agonists, montelukast or theophylline) whereas the mild to moderate groups were well controlled and prescribed a low dose of inhaled steroids and no more than one other preventer medication.
The children were divided into different age groups as asthma in younger children (usually called pre-school wheeze) can be very different to asthma in older children and adults. Asthma treatments are much less effective in this age group. It is also difficult to know which of these children will continue to have asthma when they are older. Very few asthma studies include young children. There is a huge unmet need in this age group in terms of our understanding of the type of asthma that they have and finding effective treatments, which is why we wanted to include these children in the U-BIOPRED study.
For each of the age groups we recruited children with severe disease and also those with mild to moderate asthma. This was done to help us understand more about severe asthma and how it is different from milder forms of the disease.
At the study visit, children and their parent(s) were asked lots of questions about their asthma, exposure to second hand smoke, other allergic diseases (such as eczema and hay fever) and whether other family members had asthma.
They completed questionnaires about asthma control and how asthma affects their life. They participated in a series of assessments and samples were collected. These samples will be analysed in the future and combined with the clinical data that are presented in this paper.
301 children and their parents agreed to participate and 271 completed this first part of the study. The children in the two severe groups had more asthma attacks and more symptoms than the mild to moderate groups. Almost a fifth of those with severe school aged asthma had previously been admitted to intensive care. They also had worse quality of life scores (both the children and their parents) than the mild to moderate groups. We found that poor asthma control and low lung function have the biggest effect on reducing quality of life in children with asthma.
We also found that most of the children in all groups were allergic (atopic) and it was common to have other allergic diseases such as eczema and hay fever. Atopy was more common as the children got older.
Lots of the children were exposed to second hand smoke and almost a fifth of children in the severe pre school wheeze cohort had a positive urine test which demonstrated that they had recently been exposed to tobacco smoke.
In this paper we have shown that we have recruited children with severe disease and that there are important differences when comparing the severe groups with children with mild to moderate asthma and pre school wheeze. We can therefore be confident that results obtained from future analysis of the samples are relevant to severe asthma and pre school wheeze.
This work helps us to understand the features of asthma that have the biggest impact for children and their families. Despite high amounts of treatment these children continue to have frequent symptoms and asthma attacks and this has a negative impact of their quality of life.
We hope that combining and analysing all the information and samples that we have collected as part of this clinical study will enable us to find better ways of treating these children leading to improvements in their asthma control and their quality of life.
We would like to thank all the children and their parents who participated in this study.
The IPCRG is a network of organisations committed to improving primary care assessment and treatment of chronic respiratory disease. We developed an evidence-based resource, SIMPLES (Ryan D, et al. Prim Care Respir J 2013;22:365-73) to aid structured asthma review for difficult to manage asthma. An educational initiative was introduced to disseminate research findings from U-BIOPRED and promote improved primary care management. We aimed to support participants from seven European countries to design and plan local programmes of education:teaching clinical colleagues key messages about difficult to manage asthma, encouraging local adaptation of existing IPCRG resources. These took place in autumn 2015 involving over 230 health professionals - including early career and GPs with a special interest in asthma/COPD, specialist nurses and others. We proposed an evaluation framework(Guskey,T.Teachers&Teaching 2002;8:3, 381-391) which includes - i) participant reaction, ii) learning, iii) organisational changes, iv) use of new knowledge and v) impact on practice and service users. Programmes were well received by participants. There were many challenges encountered: in assessing local learning needs, setting up education programmes and supporting clinical practice change. The impact on participants' clinical practice and service users is more challenging to demonstrate and will require more time to evaluate. We reflect on the challenge of meaningful evaluation of practice change. These insights are important in thinking about the design, implementation and evaluation of clinical educational programmes globally.
The SARP, ADEPT, and U-BIOPRED programs are all significant efforts in characterizing asthma and reporting clusters that will assist in designing personalized therapies for asthma, and especially severe asthma. Key aspects of the design of these programs are summarized and major findings are reported in this review.
A proportion of severe asthma patients suffers from persistent airflow limitation (PAL), often associated with more symptoms and exacerbations. Little is known about the underlying mechanisms. Here, our aim was to discover unexplored potential mechanisms using Gene Set Variation Analysis (GSVA), a sensitive technique that can detect underlying pathways in heterogeneous samples.Severe asthma patients from the U-BIOPRED cohort with PAL (post-bronchodilator forced expiratory volume in 1 s/forced vital capacity ratio below the lower limit of normal) were compared with those without PAL. Gene expression was assessed on the total RNA of sputum cells, nasal brushings, and endobronchial brushings and biopsies. GSVA was applied to identify differentially enriched predefined gene signatures based on all available gene expression publications and data on airways disease.Differentially enriched gene signatures were identified in nasal brushings (n=1), sputum (n=9), bronchial brushings (n=1) and bronchial biopsies (n=4) that were associated with response to inhaled steroids, eosinophils, interleukin-13, interferon-α, specific CD4+ T-cells and airway remodelling.PAL in severe asthma has distinguishable underlying gene networks that are associated with treatment, inflammatory pathways and airway remodelling. These findings point towards targets for the therapy of PAL in severe asthma.
The 2nd Cross Company Respiratory Symposium (CCRS), held in Horsham, U.K. in 2012, brought together representatives from across the pharmaceutical industry with expert academics, in the common interest of improving the design and translational predictiveness of in vivo models of respiratory disease. Organized by the respiratory representatives of the European Federation of Pharmaceutical Industries and Federations (EFPIA) group of companies involved in the EU-funded project (U-BIOPRED), the aim of the symposium was to identify state-of-the-art improvements in the utility and design of models of respiratory disease, with a view to improving their translational potential and reducing wasteful animal usage. The respiratory research and development community is responding to the challenge of improving translation in several ways: greater collaboration and open sharing of data, careful selection of the species, complexity and chronicity of the models, improved practices in preclinical research, continued refinement in models of respiratory diseases and their sub-types, greater understanding of the biology underlying human respiratory diseases and their sub-types, and finally greater use of human (and especially disease-relevant) cells, tissues and explants. The present review highlights these initiatives, combining lessons from the symposium and papers published in Clinical Science arising from the symposium, with critiques of the models currently used in the settings of asthma, idiopathic pulmonary fibrosis and COPD. The ultimate hope is that this will contribute to a more rational, efficient and sustainable development of a range of new treatments for respiratory diseases that continue to cause substantial morbidity and mortality across the world.
Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided.
OBJECTIVES:We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum.
METHODS:Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data.
RESULTS:Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels.
CONCLUSION:Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.
Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) was initiated in the first year of the Innovative Medicines Initiative (IMI). It was an ambitious plan to tackle the understanding of asthma through an integration of clinical and multi-'omics approaches that necessitated the bringing together of industry, academic, and patient representatives because it was too large to be managed by any one of the partners in isolation. It was a novel experience for all concerned. In this review, we describe the main features of the U-BIOPRED experience from the industry perspective. We list some of the key advantages and learnings from the perspective of the authors, and also improvements that we feel could be made in future projects.
Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED.
METHODS:Fuzzy partition-around-medoid clustering was performed on pre-specified data from the ADEPT participants (n = 156) and independently on data from a subset of U-BIOPRED asthma participants (n = 82) for whom the same variables were available. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and to a larger subset of the U-BIOPRED asthma dataset (n = 397). High and low type-2 inflammation phenotypes were defined as high or low Th2 activity, indicated by endobronchial biopsies gene expression changes downstream of IL-4 or IL-13.
RESULTS:Four phenotypes were identified in the ADEPT (training) cohort, with distinct clinical and biomarker profiles. Phenotype 1 was "mild, good lung function, early onset", with a low-inflammatory, predominantly Type-2, phenotype. Phenotype 2 had a "moderate, hyper-responsive, eosinophilic" phenotype, with moderate asthma control, mild airflow obstruction and predominant Type-2 inflammation. Phenotype 3 had a "mixed severity, predominantly fixed obstructive, non-eosinophilic and neutrophilic" phenotype, with moderate asthma control and low Type-2 inflammation. Phenotype 4 had a "severe uncontrolled, severe reversible obstruction, mixed granulocytic" phenotype, with moderate Type-2 inflammation. These phenotypes had good longitudinal stability in the ADEPT cohort. They were reproduced and demonstrated high classification probability in two subsets of the U-BIOPRED asthma cohort.
CONCLUSIONS:Focusing on the biology of the four clinical independently-validated easy-to-assess ADEPT asthma phenotypes will help understanding the unmet need and will aid in developing tailored therapies.
TRIAL REGISTRATION:NCT01274507 (ADEPT), registered October 28, 2010 and NCT01982162 (U-BIOPRED), registered October 30, 2013.
