Clinical and transcriptomic features of persistent exacerbation-prone severe asthma in U-BIOPRED cohort.

BACKGROUND: Exacerbation-prone asthma is a feature of severe disease. However, the basis for its persistency remains unclear. OBJECTIVES: To determine the clinical and transcriptomic features of frequent exacerbators (FEs) and persistent FEs (PFEs) in the U-BIOPRED cohort. METHODS: We compared features of FE (≥2 exacerbations in past year) to infrequent exacerbators (IE, <2 exacerbations) and of PFE with repeat ≥2 exacerbations during the following year to persistent IE (PIE). Transcriptomic data in blood, bronchial and nasal epithelial brushings, bronchial biopsies and sputum cells were analysed by gene set variation analysis for 103 gene signatures. RESULTS: Of 317 patients, 62.4% had FE, of whom 63.6% had PFE, while 37.6% had IE, of whom 61.3% had PIE. Using multivariate analysis, FE was associated with short-acting beta-agonist use, sinusitis and daily oral corticosteroid use, while PFE was associated with eczema, short-acting beta-agonist use and asthma control index. CEA cell adhesion molecule 5 (CEACAM5) was the only differentially expressed transcript in bronchial biopsies between PE and IE. There were no differentially expressed genes in the other four compartments. There were higher expression scores for type 2, T-helper type-17 and type 1 pathway signatures together with those associated with viral infections in bronchial biopsies from FE compared to IE, while there were higher expression scores of type 2, type 1 and steroid insensitivity pathway signatures in bronchial biopsies of PFE compared to PIE. CONCLUSION: The FE group and its PFE subgroup are associated with poor asthma control while expressing higher type 1 and type 2 activation pathways compared to IE and PIE, respectively.

Medication Adherence in Patients With Severe Asthma Prescribed Oral Corticosteroids in the U-BIOPRED Cohort.

BACKGROUND: Although estimates of suboptimal adherence to oral corticosteroids in asthma range from 30% to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high. RESEARCH QUESTIONS: What is the prevalence of suboptimal adherence detected by self-reporting and direct measures? Is suboptimal adherence associated with disease activity? STUDY DESIGN AND METHODS: Data were included from individuals with severe asthma taking part in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study and prescribed daily oral corticosteroids. Participants completed the Medication Adherence Report Scale, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid chromatography-mass spectrometry. RESULTS: Data from 166 participants were included in this study: mean (SD) age, 54.2 (± 11.9) years; FEV1, 65.1% (± 20.5%) predicted; female, 58%; 37% completing the Medication Adherence Report Scale reported suboptimal adherence; and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in 49 of the 142 (35%) of participants in whom both methods were performed; adherence detection did not match between methods in 53%. Self-reported high adherers had better asthma control and quality of life, whereas directly measured high adherers had lower blood eosinophil levels. INTERPRETATION: Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods, suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice.

Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma.

BACKGROUND: Severe asthma is a heterogeneous condition, as shown by independent cluster analyses based on demographic, clinical, and inflammatory characteristics. A next step is to identify molecularly driven phenotypes using "omics" technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes. OBJECTIVES: We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the stability of eNose-derived phenotypes in relation to within-patient clinical and inflammatory changes. METHODS: In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability. RESULTS: Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNose-driven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045). CONCLUSIONS: We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma.

"T2-high" in severe asthma related to blood eosinophil, exhaled nitric oxide and serum periostin.

Type-2 (T2) immune responses in airway epithelial cells (AECs) classifies mild-moderate asthma into a T2-high phenotype. We examined whether currently available clinical biomarkers can predict AEC-defined T2-high phenotype within the U-BIOPRED cohort.The transcriptomic profile of AECs obtained from brushings of 103 patients with asthma and 44 healthy controls was obtained and gene set variation analysis used to determine the relative expression score of T2 asthma using a signature from interleukin (IL)-13-exposed AECs.37% of asthmatics (45% nonsmoking severe asthma, n=49; 33% of smoking or ex-smoking severe asthma, n=18; and 28% mild-moderate asthma, n=36) were T2-high using AEC gene expression. They were more symptomatic with higher exhaled nitric oxide fraction (F eNO) and blood and sputum eosinophils, but not serum IgE or periostin. Sputum eosinophilia correlated best with the T2-high signature. F eNO (≥30 ppb) and blood eosinophils (≥300 cells·µL-1) gave a moderate prediction of T2-high asthma. Sputum IL-4, IL-5 and IL-13 protein levels did not correlate with gene expression.T2-high severe asthma can be predicted to some extent from raised levels of F eNO, blood and sputum eosinophil counts, but serum IgE or serum periostin were poor predictors. Better bedside biomarkers are needed to detect T2-high.

Sputum proteomics and airway cell transcripts of current and ex-smokers with severe asthma in U-BIOPRED: an exploratory analysis.

Severe asthma patients with a significant smoking history have airflow obstruction with reported neutrophilia. We hypothesise that multi-omic analysis will enable the definition of smoking and ex-smoking severe asthma molecular phenotypes.The U-BIOPRED cohort of severe asthma patients, containing current-smokers (CSA), ex-smokers (ESA), nonsmokers and healthy nonsmokers was examined. Blood and sputum cell counts, fractional exhaled nitric oxide and spirometry were obtained. Exploratory proteomic analysis of sputum supernatants and transcriptomic analysis of bronchial brushings, biopsies and sputum cells was performed.Colony-stimulating factor (CSF)2 protein levels were increased in CSA sputum supernatants, with azurocidin 1, neutrophil elastase and CXCL8 upregulated in ESA. Phagocytosis and innate immune pathways were associated with neutrophilic inflammation in ESA. Gene set variation analysis of bronchial epithelial cell transcriptome from CSA showed enrichment of xenobiotic metabolism, oxidative stress and endoplasmic reticulum stress compared to other groups. CXCL5 and matrix metallopeptidase 12 genes were upregulated in ESA and the epithelial protective genes, mucin 2 and cystatin SN, were downregulated.Despite little difference in clinical characteristics, CSA were distinguishable from ESA subjects at the sputum proteomic level, with CSA patients having increased CSF2 expression and ESA patients showing sustained loss of epithelial barrier processes.

Risk factors and outcome differences in hypoglycaemia-related hospital admissions: A case-control study in England.

AIMS: To evaluate risk factors for hospital admissions for hypoglycaemia and compare length of hospitalization, inpatient mortality and hospital readmission between hypoglycaemia- and non-hypoglycaemia-related admissions. MATERIALS AND METHODS: We used all admissions for hypoglycaemia in individuals with diabetes to English NHS hospital trusts between 2005 and 2014 (101 475 case admissions) and 3 random admissions per case in individuals with diabetes without hypoglycaemia (304 425 control admissions). Risk factors and differences in the 3 outcomes were estimated with logistic and negative binomial regressions. RESULTS: A U-shaped relationship between age and risk of admission for hypoglycaemia was observed until the age of 85 years; compared to the nadir at 60 years, the risk was progressively higher in younger and older patients and steadily declined after 85 years. Social deprivation (positively) and comorbidities (negatively) were associated with the risk of admission for hypoglycaemia. Compared to Caucasians, other ethnic groups had lower (Bangladeshi, Pakistani, Indians) or higher (Caribbean) risk of admission for hypoglycaemia. Length of hospitalization was 26% shorter while risk of rehospitalization was 65% higher in individuals admitted for hypoglycaemia. Compared to admissions for hypoglycaemia, risk of inpatient mortality was 50% lower for unstable angina but higher for acute myocardial infarction (3 times), acute renal failure (5 times) or pneumonia (8 times). CONCLUSIONS: Among hospital-admitted individuals with diabetes, age, social deprivation, comorbidities and ethnicity are associated with higher frequency of hospitalization for hypoglycaemia. Admission for hypoglycaemia is associated with a greater risk of readmission, a shorter length of hospitalisation and a generally lower inpatient mortality compared to admissions for other medical conditions. These results could help in identifying at-risk groups to reduce the burden of hospitalization for hypoglycaemia.

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics.

BACKGROUND: 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.

Trends in hospital admissions for hypoglycaemia in England: a retrospective, observational study.

BACKGROUND: Studies in the USA and Canada have reported increasing or stable rates of hospital admissions for hypoglycaemia. Some data from small studies are available for other countries. We aimed to gather information about long-term trends in hospital admission for hypoglycaemia and subsequent outcomes in England to help widen understanding for the global burden of hospitalisation for hypoglycaemia. METHODS: We collected data for all hospital admissions listing hypoglycaemia as primary reason of admission between Jan 1, 2005, and Dec 31, 2014, using the Hospital Episode Statistics database, which contains details of all admissions to English National Health Service (NHS) hospital trusts. We calculated trends in crude and adjusted (for age, sex, ethnic group, social deprivation, and Charlson comorbidity score) admissions for hypoglycaemia; in admissions for hypoglycaemia per total hospital admissions and per diabetes prevalence in England; and in length of stay, in-hospital mortality, and 1 month readmissions for hypoglycaemia. FINDINGS: 79 172 people had 101 475 admissions for hypoglycaemia between 2005 and 2014, of which 72 568 (72%) occurred in people aged 60 years or older. 13 924 (18%) people had more than one admission for hypoglycaemia during the study period. The number of admissions increased steadily from 7868 in 2005, to 11 756 in 2010 (49% increase) and then remained more stable until 2014 (10 977; 39% increase from baseline, range across English regions 11-89%); the trend was similar after adjustment for risk factors, with a rate ratio of 1·53 (95% CI 1·29-1·81) for 2014 versus 2005. Admissions for hypoglycaemia per 100 000 total hospital admissions increased from 63·6 to 78·9 between 2005-06 and 2010-11 (24% increase), and then fell to 72·3 per 100 000 in 2013-14 (14% overall increase). Accounting for diabetes prevalence data, rates declined from 4·64 to 3·86 admissions per 1000 person-years with diabetes between 2010-11 and 2013-14. We were unable to compare prevalence rates with data prior to 2010, as the populations were not comparable; data were available for all individuals prior to 2010 but only for those aged 17 years or older after 2010. With some differences across regions, from 2005 to 2014, the adjusted proportion of admissions to receive same-day discharge increased by 43·8% (from 18·9 to 27·1 same-day discharges per 100 admissions); in-hospital mortality decreased by 46·3% (from 4·2 to 2·3 deaths per 100 admissions); and 1 month readmissions decreased by 63·0% (from 48·1 to 17·8 per 100 readmissions). INTERPRETATION: Over 10 years, hospital admissions in England for hypoglycaemia increased by 39% in absolute terms and by 14% considering the general increase in hospitalisation; however, accounting for diabetes prevalence, there was a reduction of admission rates. Hospital length of stay, mortality, and 1 month readmissions decreased progressively and consistently during the study period. Given the continuous rise of diabetes prevalence, ageing population, and costs associated with hypoglycaemia, individual and national initiatives should be implemented to reduce the burden of hospital admissions for hypoglycaemia. FUNDING: None.

Extra-cellular matrix proteins induce matrix metalloproteinase-1 (MMP-1) activity and increase airway smooth muscle contraction in asthma.

Airway remodelling describes the histopathological changes leading to fixed airway obstruction in patients with asthma and includes extra-cellular matrix (ECM) deposition. Matrix metalloproteinase-1 (MMP-1) is present in remodelled airways but its relationship with ECM proteins and the resulting functional consequences are unknown. We used airway smooth muscle cells (ASM) and bronchial biopsies from control donors and patients with asthma to examine the regulation of MMP-1 by ECM in ASM cells and the effect of MMP-1 on ASM contraction. Collagen-I and tenascin-C induced MMP-1 protein expression, which for tenascin-C, was greater in asthma derived ASM cells. Tenascin-C induced MMP-1 expression was dependent on ERK1/2, JNK and p38 MAPK activation and attenuated by function blocking antibodies against the ß1 and ß3 integrin subunits. Tenascin-C and MMP-1 were not expressed in normal airways but co-localised in the ASM bundles and reticular basement membrane of patients with asthma. Further, ECM from asthma derived ASM cells stimulated MMP-1 expression to a greater degree than ECM from normal ASM. Bradykinin induced contraction of ASM cells seeded in 3D collagen gels was reduced by the MMP inhibitor ilomastat and by siRNA knockdown of MMP-1. In summary, the induction of MMP-1 in ASM cells by tenascin-C occurs in part via integrin mediated MAPK signalling. MMP-1 and tenascin-C are co-localised in the smooth muscle bundles of patients with asthma where this interaction may contribute to enhanced airway contraction. Our findings suggest that ECM changes in airway remodelling via MMP-1 could contribute to an environment promoting greater airway narrowing in response to broncho-constrictor stimuli and worsening asthma symptoms.

The use of exhaled nitric oxide in the management of asthma.

It has recently become clear that airways disease associated with eosinophilic airway inflammation, but not other patterns of inflammation, is closely associated with favourable short-and long-term responses to corticosteroid therapy, irrespective of the clinical context in which it occurs. Moreover, a raised exhaled nitric oxide (FE(NO)) is a reasonable marker of eosinophilic airway inflammation, which has a number of advantages as a diagnostic and monitoring tool. In this review we outline essential background information on the use of FE(NO) in clinical practice and discuss some recent work evaluating the clinical value of this technique.

Cluster analysis and clinical asthma phenotypes.

RATIONALE: Heterogeneity in asthma expression is multidimensional, including variability in clinical, physiologic, and pathologic parameters. Classification requires consideration of these disparate domains in a unified model. OBJECTIVES: To explore the application of a multivariate mathematical technique, k-means cluster analysis, for identifying distinct phenotypic groups. METHODS: We performed k-means cluster analysis in three independent asthma populations. Clusters of a population managed in primary care (n = 184) with predominantly mild to moderate disease, were compared with a refractory asthma population managed in secondary care (n = 187). We then compared differences in asthma outcomes (exacerbation frequency and change in corticosteroid dose at 12 mo) between clusters in a third population of 68 subjects with predominantly refractory asthma, clustered at entry into a randomized trial comparing a strategy of minimizing eosinophilic inflammation (inflammation-guided strategy) with standard care. MEASUREMENTS AND MAIN RESULTS: Two clusters (early-onset atopic and obese, noneosinophilic) were common to both asthma populations. Two clusters characterized by marked discordance between symptom expression and eosinophilic airway inflammation (early-onset symptom predominant and late-onset inflammation predominant) were specific to refractory asthma. Inflammation-guided management was superior for both discordant subgroups leading to a reduction in exacerbation frequency in the inflammation-predominant cluster (3.53 [SD, 1.18] vs. 0.38 [SD, 0.13] exacerbation/patient/yr, P = 0.002) and a dose reduction of inhaled corticosteroid in the symptom-predominant cluster (mean difference, 1,829 mug beclomethasone equivalent/d [95% confidence interval, 307-3,349 mug]; P = 0.02). CONCLUSIONS: Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms.