Purpose of Review
Obesity-associated difficult asthma continues to be a substantial problem and, despite a move to address treatable traits affecting asthma morbidity and mortality, it remains poorly ...understood with limited phenotype-specific treatments. The complex association between asthma, obesity, and inflammation is highlighted and recent advances in treatment options explored.
Recent Findings
Obesity negatively impacts asthma outcomes and has a causal link in the pathogenesis of adult-onset asthma. Imbalance in the adipose organ found in obesity favours a pro-inflammatory state both systemically and in airways. Obesity may impact currently available asthma biomarkers, and obesity-associated asthma specific biomarkers are needed. Whilst surgical weight loss interventions are associated with improvements in asthma control and quality of life, evidence for pragmatic conservative options are sparse. Innovative approaches tackling obesity-mediated airway inflammation may provide novel therapies.
Summary
The immunopathological mechanisms underlying obesity-associated asthma require further research that may lead to novel therapeutic options for this disease. However, weight loss appears to be effective in improving asthma in this cohort and focus is also needed on non-surgical treatments applicable in the real-world setting.
Background Airway inflammation is associated with asthma exacerbation risk, treatment response, and disease mechanisms. Objective This study aimed to identify and validate a sputum gene expression ...signature that discriminates asthma inflammatory phenotypes. Methods An asthma phenotype biomarker discovery study generated gene expression profiles from induced sputum of 47 asthmatic patients. A clinical validation study (n = 59 asthmatic patients) confirmed differential expression of key genes. A 6-gene signature was identified and evaluated for reproducibility (n = 30 asthmatic patients and n = 20 control subjects) and prediction of inhaled corticosteroid (ICS) response (n = 71 asthmatic patients). Receiver operating characteristic curves were calculated, and area under the curve (AUC) values were reported. Results From 277 differentially expressed genes between asthma inflammatory phenotypes, we identified 23 genes that showed highly significant differential expression in both the discovery and validation populations. A signature of 6 genes, including Charcot-Leydon crystal protein (CLC) ; carboxypeptidase A3 (CPA3) ; deoxyribonuclease I-like 3 (DNASE1L3) ; IL-1β (IL1B) ; alkaline phosphatase, tissue-nonspecific isozyme (ALPL) ; and chemokine (C-X-C motif) receptor 2 (CXCR2) , was reproducible and could significantly ( P < .0001) discriminate eosinophilic asthma from other phenotypes, including patients with noneosinophilic asthma (AUC, 89.6%), paucigranulocytic asthma (AUC, 92.6%), or neutrophilic asthma (AUC, 91.4%) and healthy control subjects (AUC, 97.6%), as well as discriminating patients with neutrophilic asthma from those with paucigranulocytic asthma (AUC, 85.7%) and healthy control subjects (AUC, 90.8). The 6-gene signature predicted ICS response (>12% change in FEV1 ; AUC, 91.5%). ICS treatment reduced the expression of CLC , CPA3 , and DNASE1L3 in patients with eosinophilic asthma. Conclusions A sputum gene expression signature of 6 biomarkers reproducibly and significantly discriminates inflammatory phenotypes of asthma and predicts ICS treatment response. This signature has the potential to become a useful diagnostic tool to assist in the clinical diagnosis and management of asthma.
Biomarker-based asthma phenotypes of corticosteroid response Cowan, Douglas C., BMedSci, MBChB, MRCP, PhD; Taylor, D. Robin, MD, DSc, FRCP (Ed); Peterson, Laura E., BA ...
Journal of allergy and clinical immunology,
04/2015, Letnik:
135, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Background Asthma is a heterogeneous disease with different phenotypes. Inhaled corticosteroid (ICS) therapy is a mainstay of treatment for asthma, but the clinical response to ICSs is variable. ...Objective We hypothesized that a panel of inflammatory biomarkers (ie, fraction of exhaled nitric oxide F eno , sputum eosinophil count, and urinary bromotyrosine BrTyr level) might predict steroid responsiveness. Methods The original study from which this analysis originates comprised 2 phases: a steroid-naive phase 1 and a 28-day trial of ICSs (phase 2) during which F eno values, sputum eosinophil counts, and urinary BrTyr levels were measured. The response to ICSs was based on clinical improvements, including a 12% or greater increase in FEV1 , a 0.5-point or greater decrease in Asthma Control Questionnaire score, and 2 doubling dose or greater increase in provocative concentration of adenosine 5′-monophosphate causing a 20% decrease in FEV1 (PC20 AMP). Healthy control subjects were also evaluated in this study for comparison of biomarkers with those seen in asthmatic patients. Results Asthmatic patients had higher than normal F eno values, sputum eosinophil counts, and urinary BrTyr levels during the steroid-naive phase and after ICS therapy. After 28-day trial of ICSs, F eno values decreased in 82% of asthmatic patients, sputum eosinophil counts decreased in 60%, and urinary BrTyr levels decreased in 58%. Each of the biomarkers at the steroid-naive phase had utility for predicting steroid responsiveness, but the combination of high F eno values and high urinary BrTyr levels had the best power (13.3-fold, P < .01) to predict a favorable response to ICS therapy. However, the magnitude of the decrease in biomarker levels was unrelated to the magnitude of clinical response to ICS therapy. Conclusion A noninvasive panel of biomarkers in steroid-naive asthmatic patients predicts clinical responsiveness to ICS therapy.
Type 2 (T2) inflammation offers a therapeutic target for biologics. Previous trials suggest obesity influences T2-biomarker levels in asthma, though have not accounted for key variables, e.g. inhaled ...(ICS)/oral corticosteroid (OCS) use. We hypothesized that body mass index (BMI) would affect T2-biomarker levels, after adjusting for covariates.
A retrospective analysis of data from two recent local trials of 153 participants with asthma (102 difficult-to-treat, 51 mild). Measurements included BMI, fractional exhaled nitric oxide (FeNO) and eosinophils. Correlation and regression analysis were performed for each biomarker to describe their relationship with BMI. Data was analyzed overall, and by asthma severity, T2-status and BMI tertile.
Increasing BMI was associated with reduction in FeNO when stratified by BMI tertile (25 ppb lowest tertile, 18 ppb highest tertile; p = 0.014). Spearmans rank showed a negative correlation between BMI and FeNO in difficult-to-treat asthma (ρ= −0.309, p = 0.002). Linear regression adjusting for sex, age, smoking, atopy, allergic/perennial rhinitis, ICS and OCS confirmed BMI as a predictor of FeNO overall (β= −2.848, p = 0.019). Eosinophils were reduced in the highest BMI tertile versus lowest in difficult-to-treat asthma (0.2x10
9
/L, 0.3x10
9
/L respectively; p = 0.02).
Increasing BMI is associated with lower FeNO in asthma when adjusted for relevant covariates, including steroid use. There also appears to be an effect on eosinophil levels. Obesity, therefore, affects T2 biomarker levels with implications for disease endotyping and determination of eligibility for biologic therapy. Whether this is due to masking of underlying T2-high status or development of a truly T2-low endotype requires further research.
Asthma treatment guidelines recommend increasing corticosteroid dose to control symptoms and reduce exacerbations. This approach is potentially flawed because symptomatic asthma can occur without ...corticosteroid responsive type-2 (T2)-driven eosinophilic inflammation, and inappropriately high-dose corticosteroid treatment might have little therapeutic benefit with increased risk of side-effects. We compared a biomarker strategy to adjust corticosteroid dose using a composite score of T2 biomarkers (fractional exhaled nitric oxide FENO, blood eosinophils, and serum periostin) with a standardised symptom–risk-based algorithm (control).
We did a single-blind, parallel group, randomised controlled trial in adults (18–80 years of age) with severe asthma (at treatment steps 4 and 5 of the Global Initiative for Asthma) and FENO of less than 45 parts per billion at 12 specialist severe asthma centres across England, Scotland, and Northern Ireland. Patients were randomly assigned (4:1) to either the biomarker strategy group or the control group by an online electronic case-report form, in blocks of ten, stratified by asthma control and use of rescue systemic steroids in the previous year. Patients were masked to study group allocation throughout the entirety of the study. Patients attended clinic every 8 weeks, with treatment adjustment following automated treatment-group-specific algorithms: those in the biomarker strategy group received a default advisory to maintain treatment and those in the control group had their treatment adjusted according to the steps indicated by the trial algorithm. The primary outcome was the proportion of patients with corticosteroid dose reduction at week 48, in the intention-to-treat (ITT) population. Secondary outcomes were inhaled corticosteroid (ICS) dose at the end of the study; cumulative dose of ICS during the study; proportion of patients on maintenance oral corticosteroids (OCS) at study end; rate of protocol-defined severe exacerbations per patient year; time to first severe exacerbation; number of hospital admissions for asthma; changes in lung function, Asthma Control Questionnaire-7 score, Asthma Quality of Life Questionnaire score, and T2 biomarkers from baseline to week 48; and whether patients declined to progress to OCS. A secondary aim of our study was to establish the proportion of patients with severe asthma in whom T2 biomarkers remained low when corticosteroid therapy was decreased to a minimum ICS dose. This study is registered with ClinicalTrials.gov, NCT02717689 and has been completed.
Patients were recruited from Jan 8, 2016, to July 12, 2018. Of 549 patients assessed, 301 patients were included in the ITT population and were randomly assigned to the biomarker strategy group (n=240) or to the control group (n=61). 28·4% of patients in the biomarker strategy group were on a lower corticosteroid dose at week 48 compared with 18·5% of patients in the control group (adjusted odds ratio aOR 1·71 95% CI 0·80–3·63; p=0·17). In the per-protocol (PP) population (n=121), a significantly greater proportion of patients were on a lower corticosteroid dose at week 48 in the biomarker strategy group (30·7% of patients) compared with the control group (5·0% of patients; aOR 11·48 95% CI 1·35–97·83; p=0·026). Patient choice to not follow treatment advice was the principle reason for loss to PP analysis. There was no difference in secondary outcomes between study groups and no loss of asthma control among patients in the biomarker strategy group who reduced their corticosteroid dose.
Biomarker-based corticosteroid adjustment did not result in a greater proportion of patients reducing corticosteroid dose versus control. Understanding the reasons for patients not following treatment advice in both treatment strategies is an important area for future research. The prevalence of T2 biomarker-low severe asthma was low.
This study was funded, in part, by the Medical Research Council UK.
RATIONALE Airway inflammation in asthma is heterogeneous with different phenotypes. The inflammatory cell phenotype is modified by corticosteroids and smoking. Steroid therapy is beneficial in ...eosinophilic asthma (EA), but evidence is conflicting regarding non-eosinophilic asthma (NEA). OBJECTIVES To assess the inflammatory cell phenotypes in asthma after eliminating potentially confounding effects; to compare steroid response in EA versus NEA; and to investigate changes in sputum cells with inhaled corticosteroid (ICS). METHODS Subjects undertook ICS withdrawal until loss of control or 28 days. Those with airway hyper-responsiveness (AHR) took inhaled fluticasone 1000 microg daily for 28+ days. Cut-off points were > or = or <2% for sputum eosinophils and > or = or <61% for neutrophils. RESULTS After steroid withdrawal (n=94), 67% of subjects were eosinophilic, 31% paucigranulocytic and 2% mixed; there were no neutrophilic subjects. With ICS (n=88), 39% were eosinophilic, 46% paucigranulocytic, 3% mixed and 5% neutrophilic. Sputum neutrophils increased from 19.3% to 27.7% (p=0.024). The treatment response was greater in EA for symptoms (p<0.001), quality of life (p=0.012), AHR (p=0.036) and exhaled nitric oxide (p=0.007). Lesser but significant changes occurred in NEA (ie, paucigranulocytic asthma). Exhaled nitric oxide was the best predictor of steroid response in NEA for AHR (area under the curve 0.810), with an optimum cut-off point of 33 ppb. CONCLUSIONS After eliminating the effects of ICS and smoking, a neutrophilic phenotype could be identified in patients with moderate stable asthma. ICS use led to phenotype misclassification. Steroid responsiveness was greater in EA, but the absence of eosinophilia did not indicate the absence of a steroid response. In NEA this was best predicted by baseline exhaled nitric oxide.
Mast cells are a resident inflammatory cell of the airways, involved in both the innate and adaptive immune response. The relationship between mast cells and inflammatory phenotypes and treatment ...response of asthma is not clear.Clinical characteristics of subjects with stable asthma (n=55), inflammatory cell counts and gene expression microarrays in induced sputum were analysed. Sputum mast cell subtypes were determined by molecular phenotyping based on expression of mast cell biomarkers (tryptase (TPSAB1), chymase (CMA1) and carboxypeptidase A3 (CPA3)). Effects of mast cell subtypes on steroid response were observed in a prospective cohort study (n=50).MCT(n=18) and MCT/CPA3(mRNA expression of TPSAB1 and CPA3; n=29) subtypes were identified, as well as a group without mast cell gene expression (n=8). The MCT/CPA3 subtype had elevated exhaled nitric oxide fraction, sputum eosinophils, bronchial sensitivity and reactivity, and poorer asthma control. This was accompanied by upregulation of 13 genes. Multivariable logistic regression identified CPA3(OR 1.21, p=0.004) rather than TPSAB1(OR 0.92, p=0.502) as a determinant of eosinophilic asthma. The MCT/CPA3 subtype had a better clinical response and reduced signature gene expression with corticosteroid treatment.Sputum mast cell subtypes of asthma can be defined by a molecular phenotyping approach. The MCT/CPA3 subtype demonstrated increased bronchial sensitivity and reactivity, and signature gene expression, which was associated with airway eosinophilia and greater corticosteroid responsiveness.
Poor sleep health is associated with increased asthma morbidity and mortality. Accelerometers have been validated to assess sleep parameters though studies using this method in patients with asthma ...are sparse and none have compared mild to difficult-to-treat asthma populations.
We performed a retrospective analysis from two recent in-house trials comparing sleep metrics between patients with mild and difficult-to-treat asthma. Participants wore accelerometers for 24-hours/day for seven days.
Of 124 participants (44 mild, 80 difficult-to-treat), no between-group differences were observed in sleep-window, sleep-time, sleep efficiency or wake time. Sleep-onset time was ~ 40 min later in the difficult-to-treat group (p = 0.019).
Broadly, we observed no difference in accelerometer-derived sleep-metrics between mild and difficult-to-treat asthma. This is the largest analysis of accelerometer-derived sleep parameters in asthma and the first comparing groups by asthma severity. Sleep-onset initiation may be delayed in difficult-to-treat asthma but a dedicated study is needed to confirm.
Understanding why patients with severe asthma do not follow healthcare provider (HCP) advice to adjust treatment is critical to achieving personalised disease management.
We reviewed patient choice ...to follow HCP advice to adjust asthma treatment in a UK-based randomised, controlled, single-blind (study participant), multicentre, parallel group 48-week clinical study comparing biomarker-directed treatment adjustment with standard care in severe asthma.
Of 1572 treatment advisories (291 participants), instructions were followed in 1377 cases (87.6%). Patients were more likely to follow advice to remain on treatment (96.7%) than to either reduce (70.3%) or increase (67.1%) their treatment, with 64% of patients following all treatment advice. Multivariate analysis associated belonging to an ethnic minority group (OR 3.10, 95% CI 1.68-5.73) and prior study medication changes (two or more changes: OR 2.77, 95% CI 1.51-5.10) with failure to follow treatment advice. In contrast, emergency room attendance in the prior year (OR 0.54, 95% CI 0.32-0.92) was associated with following treatment advice. The largest effect was seen with transition onto or off oral corticosteroids (OR 29.28, 95% CI 16.07-53.36) when compared with those requested to maintain treatment. Centre was also an important determinant regarding the likelihood of patients to follow treatment advice.
Belonging to an ethnic minority group and multiple prior treatment adjustments were associated with not following HCP treatment advice. Patients also responded differently to HCP advice across UK specialist centres. These findings have implications for the generalisability of models of care in severe asthma and require further focused studies.
Patients with asthma may feel limited in physical activity (PA). Reduced PA has been demonstrated in asthmatics versus healthy controls, and increasing PA associated with improved asthma outcomes. ...Obesity is commonly found with difficult-to-control asthma and worsens outcomes. We compared PA levels in participants with difficult-to-control asthma and elevated body mass index (BMI) (DOW group) and two mild-moderate asthma groups: one with BMI <25 kg/m
2
(MHW) and one with BMI ≥25 (MOW).
This cross-sectional study used 7-day recordings from wrist-worn accelerometers to compare PA between groups. Inactive time, light (LPA), moderate-vigorous PA (MVPA) were measured, along with two novel metrics: intensity gradient (IG) reflecting PA intensity, and average acceleration (AA) reflecting PA volume. PA parameters were compared using ANOVA or Kruskall-Wallis testing. Correlation and linear regression analyses explored associations between PA parameters and asthma outcomes. As AA was the PA parameter correlated most closely with asthma-related outcomes, an exploratory analysis compared outcomes in highest and lowest AA quartiles.
75 participants were recruited; 57 accelerometer readings were valid and included in analysis. Inactive time was significantly higher (p < 0.001), and LPA (p < 0.007), MVPA (p < 0.001), IG (p < 0.001) and AA (p < 0.001) all significantly lower in DOW versus MHW and MOW groups, even after adjusting for age and BMI. Quartiles based on AA had significantly different asthma profiles.
Overweight/obese participants with difficult-to-control asthma performed less PA, and activity of reduced intensity and volume. Increased AA is associated with improvement in several asthma-related outcomes. Increased PA should be recommended to relevant patients.
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