Association between peripheral airway function and neutrophilic inflammation in asthma

Farah, Claude S.; Keulers, Laurien; Hardaker, Kate; Peters, Matthew J.; Berend, Norbert; Postma, Dirkje S.; Salome, Cheryl M.; King, Gregory G.

doi:10.1111/resp.12550

Cited by 26 publications

(27 citation statements)

References 36 publications

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“…The current imaging-based cluster analysis supports the statement that the neutrophilic asthma is more strongly associated with severe asthma (7). Provided that air-trapping is indicative of small airway diseases, the current investigation is consistent with the inter-relationship, discussed by Farah et al (45), between small airway diseases and neutrophilic inflammation. It is also known that neutrophilic asthma may be insensitive to high-dose ICS (46) which is consistent with the medication history of Cluster 4 (Table 5).…”

Section: Discussionsupporting

confidence: 91%

Quantitative computed tomographic imaging–based clustering differentiates asthmatic subgroups with distinctive clinical phenotypes

Choi

Hoffman

Wenzel

et al. 2017

Journal of Allergy and Clinical Immunology

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Background Imaging variables including airway diameter, wall thickness and air-trapping have been found to be important metrics when differentiating severe asthmatics from nonsevere asthmatics and healthy subjects. Objective The objective of this study was to identify imaging-based clusters and to explore the association of the clusters with existing clinical metrics. Methods We performed an imaging-based cluster analysis using quantitative computed tomography-based structural and functional variables extracted from the respective inspiration and expiration scans of 248 asthmatics. The imaging-based metrics included a broader-set of multiscale variables such as inspiratory airway dimension, expiratory air-trapping and registration-based lung deformation (inspiration vs. expiration). Asthma subgroups derived from a clustering method were associated with subject demography, questionnaire, medication history, and biomarker variables. Results Cluster 1 patients were early-onset younger nonsevere asthmatics with reversible airflow obstruction, who showed normal airway structure; Cluster 2 patients were a mix of nonsevere and severe asthmatics with marginal inflammation, who exhibited airway luminal narrowing without wall thickening. Cluster 3 and 4 patients were dominated by severe asthmatics. Cluster 3 patients were obese females with reversible airflow obstruction who exhibited airway wall thickening without airway narrowing. Cluster 4 patients were late-onset older males with persistent airflow obstruction, exhibiting significant air-trapping and reduced regional deformation. Clusters 3 and 4 patients also showed decreased lymphocyte and increased neutrophils, respectively. Conclusions Four image-based clusters were identified and shown to be correlated with clinical characteristics. Such clustering serves to differentiate asthma subgroups which may be used as a basis for the development of new therapies.

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Section: Discussionsupporting

confidence: 91%

Quantitative computed tomographic imaging–based clustering differentiates asthmatic subgroups with distinctive clinical phenotypes

Choi

Hoffman

Wenzel

et al. 2017

Journal of Allergy and Clinical Immunology

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“…The sputum neutrophils that we found in our groups of asthma patients is slightly lower than previous reports 29–32 , but these differences may relate to methods of sputum collection 33 , ICS doses or underlying severity of asthma. Nonetheless, our groups of younger and aged patients received comparable doses of ICS, and no relationship was found between ICS and sputum neutrophils.…”

Section: Discussioncontrasting

confidence: 89%

Effect of aging on sputum inflammation and asthma control

Busse

Birmingham

Calatroni

et al. 2017

Journal of Allergy and Clinical Immunology

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Background Aged asthma patients experience increased morbidity and mortality. Knowledge of the aging effect on airway inflammation and asthma control is limited. Objective To compare airway inflammation and its relationship with asthma control in aged vs. younger patients and determine if differences are asthma-specific or due to “inflamm-aging.” Methods Prospective study of aged (>60 years) and younger (21–40 years) inner-city asthma patients. After a run-in period to control for inhaled corticosteroid use, induced sputum was collected. Aged-matched, non-asthma controls were included to measure age-related inflammatory changes. Results Aged (mean age 67.9±5.1 years, n=35) compared to younger (mean age 30.8±5.9 years, n=37) asthma patients had significantly worse asthma control and lower forced expiratory volume in one-second (FEV1). Aged asthma patients had higher sputum neutrophil number and percent (30.5 ×104/mL and 23.1%) and eosinophils (7.0×104/mL and 3.8%) compared to younger patients (neutrophils, 13.0 ×104/mL [P<0.01] and 6.9% [P<0.01]; eosinophils, 2.0×104/mL [P <0.01] and 1.2% [P<0.01]). Aged asthma patients had higher sputum interleukin-6 (IL-6) (P <0.01) and IL-8 (P =0.01). No significant inflammatory differences between aged and younger controls were observed. In aged asthma patients, elevated sputum IL-6 and MIP3α/CCL20 were significantly associated with decreased asthma control; elevated sputum neutrophils, IL-1β, IL-6 and MIP3α/CCL20 with hospitalization. Conclusions The inflammatory patterns of aged vs. younger asthma patients are associated with increased sputum neutrophils and eosinophils and cytokines related to neutrophil recruitment. Differences in airway inflammation may contribute to diminished asthma control in the aged. Further understanding of asthma pathophysiology in aged patients is needed to improve management of this vulnerable population.

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“…Thus, the acinar airways play a significant role in airflow obstruction in asthma. MBNW indices are also associated with different airway inflammatory profiles in asthma [66]; Scond with airway eosinophilia and Sacin with airway neutrophilia. These associations may have implications on future treatment modalities such as the new biologicals.…”

Section: Relationship With Symptoms and Disease Statusmentioning

confidence: 99%

Dismantling airway disease with the use of new pulmonary function indices

2019

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We are currently limited in our abilities to diagnose, monitor disease status and manage chronic airway disease like asthma and chronic obstructive pulmonary disease (COPD). Conventional lung function measures often poorly reflect patient symptoms or are insensitive to changes, particularly in the small airways where disease may originate or manifest. Novel pulmonary function tests are becoming available which help us better characterise and understand chronic airway disease, and their translation and adoption from the research arena would potentially enable individualised patient care.In this article, we aim to describe two emerging lung function tests yielding novel pulmonary function indices, the forced oscillation technique (FOT) and multiple breath nitrogen washout (MBNW). With a particular focus on asthma and COPD, this article demonstrates how chronic airway disease mechanisms have been dismantled with the use of the FOT and MBNW. We describe their ability to assess detailed pulmonary mechanics for diagnostic and management purposes including response to bronchodilation and other treatments, relationship with symptoms, evaluation of acute exacerbations and recovery, and telemonitoring. The current limitations of both tests, as well as open questions/directions for further research, are also discussed.

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Association between peripheral airway function and neutrophilic inflammation in asthma

Cited by 26 publications

References 36 publications

Quantitative computed tomographic imaging–based clustering differentiates asthmatic subgroups with distinctive clinical phenotypes

Quantitative computed tomographic imaging–based clustering differentiates asthmatic subgroups with distinctive clinical phenotypes

Effect of aging on sputum inflammation and asthma control

Dismantling airway disease with the use of new pulmonary function indices

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