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. Author manuscript; available in PMC: 2018 Apr 1.
Published in final edited form as: Eur Respir J. 2017 May 1;49(5):1601507. doi: 10.1183/13993003.01507-2016

Associations in asthma between quantitative computed tomography and bronchial biopsy-derived airway remodelling

Rachid Berair 1,*, Ruth Hartley 1,*, Vijay Mistry 1, Ajay Sheshadri 2, Sumit Gupta 1, Amisha Singapuri 1, Sherif Gonem 1, Richard P Marshall 3, Ana R Sousa 3, Aarti Shikotra 1, Richard Kay 4, Andrew Wardlaw 1, Peter Bradding 1, Salman Siddiqui 1, Mario Castro 2, Christopher E Brightling 1
PMCID: PMC5744590  NIHMSID: NIHMS928136  PMID: 28461289

Abstract

Airway remodelling in asthma remains poorly understood. This study aimed to determine the association of airway remodelling measured on bronchial biopsies with i) lung function impairment and ii) quantitative thoracic CT (QCT)-derived morphometry and densitometry measures of proximal airway remodelling and air-trapping.

Subjects were recruited from a single centre Bronchial biopsy remodelling features that were the strongest predictors of lung function impairment and QCT-derived proximal airway morphometry and air-trapping markers were determined by step-wise multiple regression. The best predictor of air-trapping was validated in an independent replication group.

Airway smooth muscle percentage (ASM %) was the only predictor of post-bronchodilator FEV1 % predicted, while both ASM % and vascularity were predictors of FEV1/FVC. Epithelial thickness and ASM % were predictors of mean segmental bronchial luminal area (R2=0.12; p=0.02 and R2=0.12; p=0.015). Whereas epithelial thickness was the only predictor of % wall area (R2=0.13; p=0.018). Vascularity was the only significant predictor of air-trapping (R2=0.24; p=0.001), which was validated in the replication group (R2=0.19; p=0.031).

In asthma, airway smooth muscle content and vascularity were both associated with airflow obstruction. QCT-derived proximal airway morphometry was most strongly associated with epithelial thickness and airway smooth muscle content, whereas air-trapping was related to vascularity.

Keywords: asthma, airway remodelling, asthma airway smooth muscle, quantitative CT of asthma, air-trapping, angiogenesis

Introduction

Asthma remains an important health problem with significant morbidity, mortality and economic burden (1, 2). In addition to symptoms, asthma is characterized by variable airflow obstruction, airway inflammation and remodelling (2, 3). Airway remodelling is a collective term for the structural changes in the airway wall including epithelial thickness and integrity, airway smooth muscle mass, neoangiogenesis and subepithelial fibrosis (2–4) and is related to persistent airflow limitation and airflow obstruction (4–6). It is a feature even in childhood disease (7) demonstrating that it can occur early in disease and post-mortem studies of asthma deaths demonstrate airway remodelling in the large and small airways (8, 9).

Macroscopic airway remodelling can be assessed non-invasively by quantitative computed tomography (QCT). This has become an established technique to determine airway morphometry and lung densitometry in asthma (10–19). This approach allows for quantification of proximal airway remodelling by assessment of airway geometry and air-trapping as an indirect measure of small airway disease. QCT in asthma has revealed that the key features of airway remodelling including luminal narrowing, wall thickening and moreover air-trapping are important determinants of airflow obstruction. Some studies have begun to explore the associations between proximal airway geometry and histological features of airway remodelling (10–12). However, asthma is a heterogeneous condition with considerable variability in the degree of disordered airway physiology, and the relative changes in airway wall composition and QCT parameters. Thus, these structure-function relationships in asthma remain poorly understood.

Our hypothesis was that airway remodelling determined in bronchial biopsies is associated with i) lung function impairment (post-bronchodilator FEV1 % predicted) and ii) QCT morphometry and densitometry measures of proximal airway remodelling and air-trapping. The co-primary QCT outcome variables were: - (i) for proximal airway remodelling: mean airway lumen area/body surface area and wall area % and; (ii) for air-trapping: mean lung density expiratory to inspiratory ratio. To test our hypothesis we undertook a single-centre observational study across the spectrum of disease severity to determine the strongest independent histological features in bronchial biopsies associated with lung function and QCT parameters of airway remodelling. The best immunohistological predictor of air-trapping was validated in an independent replication group of asthmatics from a second centre.

Methods

Subjects

Subjects were recruited into either test (n=70) or replication (n=24) groups at two independent centres Glenfield Hospital, Leicester, UK and Washington University School of Medicine, St Louis, MO, USA respectively. All subjects were non-smokers with <10 pack-years. All included subjects fulfilled the criteria for the diagnosis of asthma which was defined as: a physician diagnosis of asthma with objective evidence of variable airflow obstruction as indicated by 1 or more of the following: (1) a positive methacholine challenge test defined as a concentration of nebulized methacholine causing a 20% drop in FEV1 of <8 mg/mL, (2) diurnal maximum peak flow variability of >20% over 2 week time, and (3) improvement of >15% in FEV1 15 minutes after bronchodilator therapy. Subjects underwent pre- and post-bronchodilator spirometry (albuterol 400mcg), skin prick tests or allergen specific IgE to assess for atopy and those in the test group also underwent sputum induction and processing. Persistent airflow limitation was defined as a post-bronchodilator therapy FEV1<80% predicted. Written informed consent was obtained from all the participants. All subjects were on optimal asthma treatment and free of exacerbation for at least 6 weeks prior to recruitment into the study. All the assessments and tests included in this study were approved by the local research ethics committee (The Leicestershire, Northamptonshire, and Rutland Research Ethics Committee and the Washington University School of Medicine Institutional Review Board).

Computed tomography

All subjects underwent either limited or full lung CT scans performed following administration of albuterol using standardised acquisition protocols as described previously (11, 16). Limited only scans from the aortic arch to the carina done at full inspiration (near total lung capacity) were undertaken in 14 asthmatics (13, 14). All other subjects had full lung inspiratory and expiratory (near functional residual capacity) CT scans. Scans were analysed using semi-automated software, Apollo in the test group and Pulmonary Workstation, version 2.0 in the replication group (VIDA Diagnostics, Iowa).

In the test group all inspiratory scans were analysed for the right upper lobe apical segmental bronchus (RB1) morphometry while mean segmental bronchi morphometry was obtained in full lung scans only. 1st–5th generation airways were labelled and measured using the analysis software. Morphologic measurements of segmental airways (3rd generation airways) were obtained along each centre line voxel of the lumen perpendicular to the long axis on each airway and averaged over the middle third of the airway segment. Lumen area and total area were measured directly while wall area was the derived using the following calculation: wall area = total area - lumen area. Total, lumen and wall area were measured in mm2 and all corrected for body surface area, which was calculated using Mosteller formula and expressed as mm2/m2 body surface area (20). Percentage wall area was calculated as follows: wall area % = 100 x wall area/total area. Estimates of air-trapping were determined in the test and replication groups from the mean lung density on the expiratory/inspiratory scan (MLD E/I) and the percentage of lung voxels with a density lower than -856 HU on expiratory scans (VI-856 HU) (see figure S1). The co-primary QCT outcome variables were for proximal airway remodelling: mean segmental airway lumen area/body surface area and wall area % and for air-trapping MLD E/I.

Endobronchial biopsies

Fibre-optic bronchoscopy was performed according to the British Thoracic society guidelines [21]. All patients received albuterol prior to the procedure. Endobronchial biopsies were obtained from segmental and subsegmental carina and either embedded in glycol methacrylate for the test group or paraffin in the replication group as described previously (6, 11, 22, 23).

Two micrometre sections were cut from the glycol methacrylate embedded biopsies and stained with Haematoxylin & Eosin (H&E). Immunohistochemical staining was done with the following mAbs: anti–mast cell tryptase clone AA1 (Dako UK), anti-alpha smooth muscle actin clone 1A4 (Dako UK), anti-eosinophil major basic protein clone BMK-13 (Monosan, Netherlands), anti-neutrophil elastase clone NP57 (Dako UK), and anti-endothelium clone EN4 (Monosan, Netherlands) or appropriate isotype controls were used.

The endobronchial biopsies were assessed by a single observer blinded to the clinical characteristics (ZEN 2012 image analysis software for light microscopy, Carl Zeiss AG, Germany) and expressed as the mean of measurements undertaken from a minimum of two sections either from independent biopsies or as non-contiguous tissue sections at least 20μm apart from the same biopsy. Epithelial integrity was assessed by measuring the lengths of intact and denuded epithelium. These were expressed as percentage of all the reticular basement membrane (RBM) length present in the section. RBM and epithelial thickness were measured as described previously (24, 25). Vascularity was measured using the Chalkley count, a surrogate of both vessel density and vascular area. As previously described, a Chalkley eyepiece graticule (NG52 Chalkley Point Array, Pyser-SGI Ltd, UK) was used at x200 to measure Chalkley counts in four non-overlapping vascular hotspots (1–2/section) (see figure S2) (6). The mean Chalkley count was calculated from the four measurements. In 24 biopsies we compared the Chalkley count with computerised pixel counting in the lamina propria and found these measures were strongly correlated (r=0.83; p<0.0001). Airway smooth muscle content was determined as the proportion of the total area. Inflammatory cells were expressed as the number of nucleated cells/area of lamina propria.

The intra-class correlation coefficients (ICC) for the within donor measurements made by a single-blinded observer were for airway smooth muscle % area (ICC=0.87), epithelial thickness (ICC=0.85) and vascularity (ICC=0.65).

The strongest independent immunohistological feature of airway remodelling associated with QCT-derived air-trapping identified in the test group was validated in the replication group. Four micrometre sections were cut from the paraffin embedded biopsies and stained with appropriate mAb or corresponding isotype control.

Statistical analysis

Statistical analysis was performed using GraphPad Prism version 6.00 for Windows (GraphPad Software, La Jolla, California) and IBM SPSS Statistics for Windows, Version 22.0 (IBM Corp, Released 2013, Armonk, NY). Parametric data were expressed as mean (standard deviation, SD) and non-parametric data as median (interquartile range, IQR). Groups were compared using unpaired student t-test and Mann-Whitney U test for parametric and non-parametric data respectively. Proportions were compared using chi-squared test (χ2). Correlations between variables were expressed using Pearson’s correlation. A step-wise multiple regression analysis was undertaken to determine the bronchial biopsy features that were the strongest predictors of post-bronchodilator FEV1, FEV1/FVC, and QCT-derived mean segmental bronchial morphometry and air-trapping. Regression data are presented as model-adjusted R2 Pearson correlations alongside the standardized regression coefficient (β) of the modelled independent variable. A p-value of <0.05 was considered statistically significant.

Results

Baseline demographics and clinical characteristics of subjects with (n=30) and without persistent airflow limitation (post-bronchodilator FEV1 <80% and ≥80% predicted) (n=40) are shown in Table 1. There was no difference between the two groups in sex, age, duration of asthma, age of disease onset, smoking status, smoking pack-years, BMI, sputum eosinophils or sputum neutrophils.

Table 1.

Demographics, clinical and laboratory characteristics

Characteristic All patients (n = 70) Post-bronchodilator FEV1<80% (n =30) Post-bronchodilator FEV1≥80% (n = 40) p-value
Age (y) 49 (12) 52 (12) 47 (13) 0.095
Male (%) 57 67 50 0.163
Caucasian (%) 93 93 93 0.893
Asthma duration (y) 24 (18) 29 (20) 20 (15) 0.059
BMI (kg/m2) 29.9 (5.6) 30.3 (5.9) 29.6 (5.4) 0.644
Ex-smokers (%) 19 27 13 0.131
Smoking pack-years 0.0 [0.0–0.0] 0.0 [0.0–3.9] 0.0 [0.0–0.0] 0.109
Atopy (%) 81 77 81 0.659
GINA class GINA 5, n (%) 22 (31) 13 (43.3) 9 (23) 0.084
GINA 4, n (%) 34 (49) 15 (50.0) 19 (48)
GINA 3, n (%) 6 (9) 0 (0.0) 6 (15)
GINA 1&2, n (%) 8 (11) 2 (6.7) 6 (16)
Inhaled BDP equivalent (μg/24h) 1289 (689) 1444 (658) 1173 (698) 0.104
Pre-Bronchodilator FEV1 (L) 2.46 (0.92) 1.76 (0.65) 2.98 (0.73) <0.001
Pre-Bronchodilator FEV1 (% predicted) 78.8 (24.6) 55.1 (14.3) 96.5 (12.8) <0.001
Pre-Bronchodilator FEV1/FVC (%) 66.7 (13.3) 55.7 (11.2) 74.9 (7.7) <0.001
Post-Bronchodilator FEV1 (L) 2.63 (0.91) 1.98 (0.63) 3.14 (0.77) <0.001
Post-Bronchodilator FEV1 (% predicted) 84.8 (23.3) 62.1 (12.8) 101.8 (12.0) <0.001
Post-Bronchodilator FEV1/FVC (%) 69.5 (12.5) 59.3 (11.0) 77.1 (6.8) <0.001
Induced sputum
Sputum eosinophils (%)# 4.5 [1.4–18.8] 5.3 [2.0–23.1] 4.2 [0.03–10.0] 0.185
Sputum neutrophils (%)# 46.5 [25.6–63.5] 49.7 [36.8–68.4] 44.1 [17.6–63.2] 0.066
Immunohistochemistry
Tissue eosinophils (cells/mm2 of lamina propria) # 19.6 [8.0–32.7] 19.2 [8.3–35.4] 19.9 [8.0–28.3] 0.947
Tissue neutrophils (cells/mm2 of lamina propria) # 5.8 [2.2–20.8] 4.3 [2.1–15.5] 9.6 [2.3–24.6] 0.924
Tissue mast cells (cells/mm2 of lamina propria) # 15.7 [5.4–33.6] 13.8 [6.2–37.1] 15.7 [5.3–22.9] 0.149
RBM thickness (μm) 12.3 (3.9) 12.3 (4.4) 12.3 (3.6) 0.974
Airway smooth muscle % 25.8 (15.4) 33.5 (15.6) 20.1 (12.6) <0.001
Vascularity (mean Chalkley count) 5.5 (1.8) 6.2 (1.6) 5.0 (1.9) 0.017
Epithelial Thickness (μm) 62.0 (16.8) 65.1 (17.5) 59.7 (16.2) 0.257
Intact epithelium % # 27.8 [12.5–49.7] 36.2 [15.2–54.2] 22.9 [9.8–45.0] 0.466
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Mean (SD) unless stated;

#

median [IQR].

BDP- Beclomethasone dipropionate

Airway inflammation and remodelling univariate correlation with lung function

Subjects with versus those without persistent airflow limitation had significantly higher airway smooth muscle % (33.5 [15.6] versus 20.1 [12.6]%; p<0.001) and increased vascularity (mean Chalkley count) (6.2 [1.6] versus 5.0 [1.9]; p=0.017) as shown in Table 1 and Figure 1. However, there was no difference between the two groups in the other measured markers of airway remodelling or inflammation. Airway smooth muscle % was inversely correlated with post-bronchodilator FEV1 % predicted (r=−0.49; p<0.001) and post-bronchodilator FEV1/FVC (r=−0.44; p<0.001) as shown in Figure 2. Vascularity was also inversely correlated, with post-bronchodilator FEV1 % predicted (r=−0.3; p=0.026) and post-bronchodilator FEV1/FVC (r=−0.35; p=0.008). There was no significant correlation between airway inflammation or the other airway remodelling markers in bronchial biopsies and spirometry measurements (Table S1). Smoking history including pack-years was not associated with any of the remodelling or inflammatory features in bronchial biopsies.

Figure 1.

Figure 1

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a) Airway smooth muscle % and b) vascularity (mean Chalkley count) in subjects with and without persistent airflow limitation (post-bronchodilator [BD] FEV1 <80% and ≥80% predicted).

Figure 2.

Figure 2

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Scatterplots showing correlations of post-bronchodilator [BD] FEV1 and FEV1/FVC with a) and b) airway smooth muscle % and c) and d) vascularity.

CT-derived quantitative morphometry and densitometry univariate correlation with lung function

Subjects with versus those without persistent airflow limitation had significantly narrower mean segmental bronchial luminal areas (9.7 (2.2) versus 11.0 (2.3) mm2/m2; p=0.047) and larger mean segmental bronchial wall area % (63.6 (2.0) versus 62.5 (2.1) %; p=0.039) (Table 2). These differences were more marked in the lower versus upper lobe bronchi (Table S2). There was significantly more air-trapping in those with versus without persistent airflow limitation as measured by MLD E/I (0.89 [0.05] versus 0.83 [0.05]; p<0.001), and VI-856 HU (%) (32.2 [19.8] versus 15.5 [10.1]; p<0.001) (Table 2).

Table 2.

QCT morphometry and air-trapping parameters

Characteristic All patients (n = 56) Post-bronchodilator FEV1<80% (n =29) Post-bronchodilator FEV1≥80% (n = 25) p-value
CT-derived quantitative morphometry
Mean segmental bronchial lumen area/BSA (mm2/m2) 10.4 (2.3) 9.7 (2.2) 11.0 (2.3) 0.047
Mean segmental bronchial wall area/BSA (mm2/m2) 17.0 (2.6) 16.5 (2.9) 17.5 (2.4) 0.133
Mean segmental bronchi wall area % 63.0 (2.2) 63.6 (2.0) 62.5 (2.1) 0.039
CT-derived measures of air-trapping
MLD E/I 0.85 (0.06) 0.89 (0.05) 0.83 (0.05) <0.001
VI-856HU (%) 22.6 (17.0) 32.2 (19.8) 15.5 (10.1) <0.001
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Mean (SD), BDP- Beclomethasone dipropionate, VI-856 HU- % of lung voxels with a density lower than −856 HU on expiratory scans

Univariate correlations between bronchial biopsy airway remodelling and QCT morphometry and air-trapping

Epithelial thickness was significantly correlated with mean segmental bronchial luminal area (r=−0.35; p=0.02), mean segmental bronchial wall area (r=−0.31; p=0.039) and mean segmental bronchial wall area % (r=0.35; p=0.018) (Figure 3). Similarly, airway smooth muscle % correlated significantly with mean segmental bronchial luminal area (r=−0.35; p=0.008), mean segmental bronchial wall area (r=−0.32; p=0.015) and mean segmental bronchial wall area % (r=0.27; p=0.045). All the other remodelling and inflammatory markers including vascularity, RBM and inflammatory cell counts in the lamina propria did not have any significant correlation with morphometry indices (Table S1).

Figure 3.

Figure 3

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Scatterplots showing correlations of epithelial thickness and airway smooth muscle % with a) and b) mean segmental bronchial luminal and c) and d) mean segmental wall area %.

Vascularity was strongly correlated with measures of air-trapping MLD E/I (r=0.49; p<0.001) and VI-856 HU (r=0.53; p<0.001). Airway smooth muscle % was also correlated with MLD E/I (r=0.3; p=0.03) and VI-856 HU (r=0.55; p<0.001) (Figure 4).

Figure 4.

Figure 4

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Scatterplots showing correlations of vascularity and airway smooth muscle % with a) and b) MLD E/I and c) and d) VI-856 HU.

Multivariate analysis of the association between bronchial biopsy immunohistology, lung function and QCT parameters

All airway remodelling and inflammation variables were included in a step-wise multiple regression analysis to examine the predictors of persistent airflow limitation, QCT segmental morphometry and air-trapping. Only airway smooth muscle % was an independent predictor of post-bronchodilator FEV1 % predicted (R2=0.24, β=−0.49, p=0.001), while both airway smooth muscle % and vascularity were significant predictors of post-bronchodilator FEV1/FVC (R2=0.19, β=−0.40, p=0.003 and R2=0.09, β=−0.31, p=0.026) respectively). Epithelial thickness and airway smooth muscle % were predictors of mean segmental bronchial luminal area (R2=0.12, β=−035, p=0.02 and R2=0.12, β=−0.35, p=0.015), and wall area (R2=0.10, β=−0.32, p=0.033 and R2= 0.10, β=0.31, p=0.032). Epithelial thickness was the only independent predictor of mean segmental bronchial wall area % (R2=0.13, β=0.35, p=0.018). Vascularity was the only predictor of MLD E/I (R2=0.24, β=0.49, p=0.001), while airway smooth muscle %, vascularity and epithelial thickness all significantly contributed to a model predicting VI-856 HU (R2=0.31, β=0.49, p<0.001; R2=0.22, β=0.54, p<0.001 and R2=0.05; β=0.24, p=0.045 respectively).

Validation group: replication of the correlation between vascularity and air-trapping

Vascularity in the bronchial biopsies was the only independent predictor of MLD E/I. Therefore the relationship between vascularity and MLD E/I was measured in an independent group of asthmatics (n=24). Baseline demographics and clinical characteristics of subjects in the validation group are described in Table S3. Similar to the primary study group, vascularity was positively correlated with MLD E/I (r=0.44; p=0.031) as well as VI-856 HU (r=0.50; p=0.014) (Figure 5).

Figure 5.

Figure 5

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Validation of the association between vascularity and air-trapping in the replication group showing scatterplots of vascularity with a) MLD E/I and b) VI-856 HU.

Discussion

We report here the associations in asthma between bronchial biopsy-derived features of airway inflammation and remodelling with lung function and QCT parameters of proximal airway morphometry and air-trapping. We found that neither airway inflammation nor RBM thickening were related to lung function and QCT parameters. However, airway smooth muscle % and vascularity were both associated with airflow obstruction. Proximal airway morphometry was most strongly associated with epithelial thickness and airway smooth muscle % and air-trapping was related to vascularity. This is the first study to suggest a relationship between airway vascularity and air-trapping. However, we are confident that this observation is robust as we were able to confirm this finding in an independent replication group.

Previous studies have explored the relationship between bronchial biopsy features of remodelling and both FEV1 % predicted and FEV1/FVC (reviewed in 4). As reported here airway smooth muscle mass is typically (4, 5), but not always (22), a major determinant of lung function impairment. Increased airway smooth muscle mass is a feature of severe childhood asthma (7) and is described in both the large and small airways in studies of asthma deaths (8, 9). Indeed increased airway smooth muscle mass in both the large and small airways is more common than in the large or small airway alone (9). The Chalkley count method used to assess vascularity in this study is a stereological method used commonly in cancer studies and is well validated for inter- and intra-observer variability, disease progression and mortality (26,27). Furthermore, the method has been previously used to measure vascular remodelling in asthma with studies showing greater mean Chalkley counts in asthmatics compared to control and correlation with asthma severity (6). Increased airway vascularity, neoangiogensis, has been consistently reported in endobronchial biopsies from asthmatics compared to healthy controls and in the small airways from lung resections for lung nodules in subjects with asthma (6, 28–32). However, increased vascularity was not a feature observed in fatal asthma (33). We and others have reported that increased vascularity is associated with lung function impairment (6) and confirmed this finding in the current study. The relationship between airway inflammation and lung function impairment is more contentious with some reports suggesting an association whereas others have not been able to reveal associations (reviewed in 4). Interestingly in our study, other features of remodelling namely epithelial thickening, RBM thickening and airway inflammation were not associated with lung function indices.

Proximal airway morphometry assessed by QCT is abnormal in asthma with luminal narrowing and airway wall thickening (16). These changes are weakly associated with lung function impairment. We found that epithelial thickening and airway smooth muscle % were related to QCT airway morphometry features of remodelling as described previously (10–12), but not other bronchial biopsy measures of remodelling or inflammation. Interestingly, although airway vascularity was associated with lung function impairment it was not associated with proximal airway morphometry.

We have extended previous studies of the relationship between endobronchial features of remodelling and QCT parameters to include measures of air-trapping. We found that both airway smooth muscle % and vascularity were associated with air-trapping in univariate analysis, but that vascularity alone was an independent and significant predictor of MLD E/I in our step wise linear regression. In comparative studies of asthma and chronic obstructive pulmonary disease we found that QCT measures of air-trapping are stronger predictors of lung function impairment than changes in proximal airway morphometry (19). It is therefore intriguing that increased vascularity measured in the proximal airway is related to air-trapping a measure of small airway dysfunction. Previous studies suggest that the degree of vascularity in the proximal airway tracks with findings in the small airway (28, 33), but of note we did not directly measure remodelling from small airway samples. Due to the novelty of our finding we sought to validate our finding in an independent replication group. In spite of differences in the processing of the endobronchial biopsies we found a remarkably similar relationship between airway vascularity and QCT-derived air-trapping in the replication group compared with our initial analyses.

Taken together these data support an important role for airway smooth muscle mass in proximal airway remodelling and possibly to a lesser extent in the smaller airway with both likely to be contributing to lung function impairment. Epithelial thickness plays a role in proximal airway remodelling, but is not related to airway dysfunction. Airway vascularity is not associated with proximal airway remodelling, but is associated with air-trapping and lung function impairment. Whether increased vascularity promotes small airway closure secondary to oedema or due to direct effects upon airway wall thickness is unknown. Interestingly, there are no reports of effects of corticosteroids upon airway smooth muscle mass, whereas in most although not all studies of the effects of corticosteroids upon airway vasculature demonstrate a decrease in vascularity with a concomitant improvement in lung function (29–32). Our study subjects were all receiving inhaled corticosteroid therapy suggesting that the remaining vascularity is resistant to corticosteroid therapy. Whether improvements in airway vascularity in response to corticosteroid or other therapies are related to improvements in air-trapping requires further study.

This study has a number of potential limitations. Although this is the largest study to date comparing immunohistology with QCT parameters of airway remodelling it remains a relatively small study. It is also cross-sectional and future longitudinal studies of the natural history of asthma and response to therapies should consider inclusion of endobronchial biopsy and imaging parameters to further determine the structure-function relationships. Importantly, we did not standardise the location of the sampling of the endobronchial biopsies with a corresponding airway identified by QCT and whether this is important to determine the heterogeneity within an individual will be important in future studies. However, we did reduce the variability of QCT parameters within an individual by using the mean airway morphometry derived from multiple airways and demonstrated good within donor repeatability of the key structural wall components in bronchial biopsies. Critically, our comparisons between QCT air-trapping were with proximal rather than distal airway samples. As discussed above it is likely that these proximal airway samples reflected similar changes in the smaller airways, but notwithstanding this likelihood further studies are required to compare QCT parameters of the small airway with distal sampling such as transbronchial biopsies. In contrast to Kasahara and colleagues our study has shown no correlation between RBM and QCT-derived morphometry parameters (10). However, similar to our observation, Saglani et al also failed to demonstrate such correlation (34). Another limitation of this study relates to using endobronchial biopsies to measure airway remodelling. These biopsies are small and only sample the superficial layer of the airway, thus cannot determine the changes in airway structure in relationship to the whole depth of the airway wall. However, despite this shortcoming, endobronchial biopsies remain the best in vivo tool to assess the structural changes in the airway wall contributing to airway remodelling (35).

In conclusion, we have found important associations between endobronchial biopsy and QCT measures of airway remodelling with lung function. We found that airway smooth muscle mass and airway vascularity are related to airflow obstruction with airway smooth muscle mass likely contributing more to large than small airway remodelling, whereas increased vascularity appears to be related to air-trapping possibly due to small airway remodelling.

Supplementary Material

Take-Home Message.

In asthma, airway remodelling in biopsies is closely associated with proximal airway QCT-derived morphometry and air-trapping

Acknowledgments

Funding

This work was part funded by Wellcome Trust Senior Fellowship (CEB), Airway Disease Predicting Outcomes through Patient Specific Computational Modelling (AirPROM) project (funded through FP7 EU grant), Leicester National Institute for Health Research (NIHR) Respiratory Biomedical Research Unit, Novartis and GlaxoSmithKline (GSK). Some of the biopsy and CT data mentioned here were baseline data for a proportion of patients who were enrolled into a phase II randomized controlled trial (QAW039A2208) that was sponsored by Novartis pharmaceuticals. Sumit Gupta is a National Institute for Health Research (NIHR) Clinical Lecturer and is funded by a research and career development training scheme. This paper presents independent research funded by the National Institute for Health Research (NIHR). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

Footnotes

Author contribution

Rachid Berair, Ruth Hartley and Chris Brightling contributed to study concept and design, acquisition, analysis and interpretation of data. Vijay Mistry, Ajay Sheshadri, Aarti Shikotra, Amisha Singapuri and Sherif Gonem contributed to data acquisition and analysis. Sumit Gupta, Richard Marshall, Ana Sousa, Richard Kay, Andrew Wardlaw, Peter Bradding, Salman Siddiqui and Mario Castro contributed to acquisition and interpretation of the data. All authors critically appraised and approved the final manuscript and are accountable for the work.

This article has an online data supplement, which is accessible from this issue’s table of content online

References

  • 1.World Health Organization. [Date last accessed: Jan 2016];Global surveillance, prevention and control of chronic respiratory diseases: A comprehensive approach. 2007 http://www.who.int/respiratory/publications/global_surveillance/en/index.html.
  • 2.Chung KF, Wenzel SE, Brozek JL, Bush A, Castro M, Sterk PJ, Adcock IM, Bateman ED, Bel EH, Bleecker ER, Boulet LP, Brightling C, Chanez P, Dahlen SE, Djukanovic R, Frey U, Gaga M, Gibson P, Hamid Q, Jajour NN, Mauad T, Sorkness RL, Teague WG. International ERS/ATS guidelines on definition, evaluation and treatment of severe asthma. Eur Respir J. 2014 Feb;43(2):343–73. doi: 10.1183/09031936.00202013. [DOI] [PubMed] [Google Scholar]
  • 3. [Accessed 11 Dec 2015];Global Initiative for Asthma guidelines. 2015 at www.ginasthma.org.)
  • 4.Berair R, Brightling CE. Asthma therapy and its effect on airway remodelling. Drugs. 2014;74:1345–1369. doi: 10.1007/s40265-014-0250-4. [DOI] [PubMed] [Google Scholar]
  • 5.Benayoun L, Druilhe A, Dombret MC, Aubier M, Pretolani M. Airway structural alterations selectively associated with severe asthma. Am J Respir Crit Care Med. 2003;167:1360–1368. doi: 10.1164/rccm.200209-1030OC. [DOI] [PubMed] [Google Scholar]
  • 6.Siddiqui S, Sutcliffe A, Shikotra A, Woodman L, Doe C, McKenna S, Wardlaw A, Bradding P, Pavord I, Brightling C. Vascular remodeling is a feature of asthma and nonasthmatic eosinophilic bronchitis. J Allergy Clin Immunol. 2007;120:813–819. doi: 10.1016/j.jaci.2007.05.028. [DOI] [PubMed] [Google Scholar]
  • 7.O’Reilly R, Ullmann N, Irving S, Bossley CJ, Sonnappa S, Zhu J, Oates T, Banya W, Jeffery PK, Bush A, Saglani S. Increased airway smooth muscle in preschool wheezers who have asthma at school age. J Allergy Clin Immunol. 2013 Apr;131(4):1024–32. 1032.e1–16. doi: 10.1016/j.jaci.2012.08.044. [DOI] [PubMed] [Google Scholar]
  • 8.James A, Elliot JG, Jones RL, Carroll ML, Mauad T, Bai TR, Abramson MJ, McKay KO, Green F. Airway smooth muscle hypertrophy and hyperplasia in asthma. Am J Respir Crit Care Med. 2012;185(10):1058–64. doi: 10.1164/rccm.201110-1849OC. [DOI] [PubMed] [Google Scholar]
  • 9.Elliot JG, Jones RL, Abramson MJ, Green FH, Mauad T, McKay KO, Bai TR, James AL. Distribution of airway smooth muscle remodelling in asthma: relation to airway inflammation. Respirology. 2015;20(1):66–72. doi: 10.1111/resp.12384. [DOI] [PubMed] [Google Scholar]
  • 10.Kasahara K, Shiba K, Ozawa T, Okuda K, Adachi M. Correlation between the bronchial subepithelial layer and whole airway wall thickness in patients with asthma. Thorax. 2002 Mar;57(3):242–6. doi: 10.1136/thorax.57.3.242. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Aysola RS, Hoffman EA, Gierada D, Wenzel S, Cook-Granroth J, Tarsi J, Zheng J, Schechtman KB, Ramkumar TP, Cochran R, Xueping E, Christie C, Newell J, Fain S, Altes TA, Castro M. Airway remodeling measured by multidetector CT is increased in severe asthma and correlates with pathology. Chest. 2008 Dec;134(6):1183–91. doi: 10.1378/chest.07-2779. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Montaudon M, Lederlin M, Reich S, Begueret H, Tunon-de-Lara JM, Marthan R, Berger P, Laurent F. Bronchial measurements in patients with asthma: comparison of quantitative thin-section CT findings with those in healthy subjects and correlation with pathologic findings. Radiology. 2009 Dec;253(3):844–53. doi: 10.1148/radiol.2533090303. [DOI] [PubMed] [Google Scholar]
  • 13.Siddiqui S, Gupta S, Cruse G, Haldar P, Entwisle J, Mcdonald S, Whithers PJ, Hainsworth SV, Coxson HO, Brightling C. Airway wall geometry in asthma and nonasthmatic eosinophilic bronchitis. Allergy. 2009;64:951–958. doi: 10.1111/j.1398-9995.2009.01951.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Haldar P, Brightling CE, Hargadon B, Gupta S, Monteiro W, Sousa A, Marshall RP, Bradding P, Green RH, Wardlaw AJ, Pavord ID. Mepolizumab and exacerbations of refractory eosinophilic asthma. N Engl J Med. 2009;360:973–984. doi: 10.1056/NEJMoa0808991. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Gupta S, Siddiqui S, Haldar P, Entwisle JJ, Mawby D, Wardlaw AJ, Bradding P, Pavord ID, Green RH, Brightling CE. Quantitative analysis of high-resolution computed tomography scans in severe asthma subphenotypes. Thorax. 2010;65:775–781. doi: 10.1136/thx.2010.136374. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Gupta S, Hartley R, Khan UT, Singapuri A, Hargadon B, Monteiro W, Pavord ID, Sousa AR, Marshall RP, Subramanian D, Parr D, Entwisle JJ, Siddiqui S, Raj V, Brightling CE. Quantitative computed tomography-derived clusters: redefining airway remodeling in asthmatic patients. J Allergy Clin Immunol. 2014 Mar;133(3):729–38.e18. doi: 10.1016/j.jaci.2013.09.039. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Gupta S, Hartley R, Singapuri A, Hargadon B, Monteiro W, Pavord ID, Sousa AR, Marshall RP, Subramanian D, Parr D, Entwisle JJ, Siddiqui S, Raj V, Brightling CE. Temporal assessment of airway remodeling in severe asthma using quantitative computed tomography. Am J Respir Crit Care Med. 2015 Jan 1;191(1):107–10. doi: 10.1164/rccm.201406-1128LE. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Haldar P, Brightling CE, Singapuri A, Hargadon B, Gupta S, Monteiro W, Bradding P, Green RH, Wardlaw AJ, Ortega H, Pavord ID. Outcomes after cessation of mepolizumab therapy in severe eosinophilic asthma: A 12-month follow-up analysis. J Allergy Clin Immunol. 2014;133:921–923. doi: 10.1016/j.jaci.2013.11.026. [DOI] [PubMed] [Google Scholar]
  • 19.Hartley RA, Barker BL, Newby C, Pakkal M, Baldi S, Kajekar R, Kay R, Laurencin M, Marshall RP, Sousa AR, Parmar H, Siddiqui S, Gupta S, Brightling CE. Relationship between lung function and quantitative computed tomographic parameters of airway remodeling, air trapping, and emphysema in patients with asthma and chronic obstructive pulmonary disease: A single-center study. J Allergy Clin Immunol. 2016 May;137(5):1413–1422. doi: 10.1016/j.jaci.2016.02.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Mosteller RD. Simplified calculation of body-surface area. N Engl J Med. 1987;317:1098. doi: 10.1056/NEJM198710223171717. [DOI] [PubMed] [Google Scholar]
  • 21.Du Rand IA, Blaikley J, Booton R, Chaudhuri N, Gupta V, Khalid S, Mandal S, Martin J, Mills J, Navani N, Rahman NM, Wrightson JM, Munavvar M. British Thoracic Society Bronchoscopy Guideline Group. British Thoracic Society guideline for diagnostic flexible bronchoscopy in adults: accredited by NICE. Thorax. 2013 Aug;68(Suppl 1):i1–i44. doi: 10.1136/thoraxjnl-2013-203618. [DOI] [PubMed] [Google Scholar]
  • 22.Brightling CE, Bradding P, Symon FA, Holgate ST, Wardlaw AJ, Pavord ID. Mast-cell infiltration of airway smooth muscle in asthma. N Engl J Med. 2002 May 30;346(22):1699–705. doi: 10.1056/NEJMoa012705. [DOI] [PubMed] [Google Scholar]
  • 23.Siddiqui S, Mistry V, Doe C, Roach K, Morgan A, Wardlaw A, Pavord I, Bradding P, Brightling C. Airway hyperresponsiveness is dissociated from airway wall structural remodeling. J Allergy Clin Immunol. 2008 Aug;122(2):335–41. 341.e1–3. doi: 10.1016/j.jaci.2008.05.020. Epub 2008 Jun 24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Sullivan P, Stephens D, Ansari T, Costello J, Jeffery P. Variation in the measurements of basement membrane thickness and inflammatory cell number in bronchial biopsies. Eur Respir J. 1998;12:811–815. doi: 10.1183/09031936.98.12040811. [DOI] [PubMed] [Google Scholar]
  • 25.Cohen L, EX, Tarsi J, Ramkumar T, Horiuchi TK, Cochran R, DeMartino S, Schechtman KB, Hussain I, Holtzman MJ, Castro M NHLBI Severe Asthma Research Program (SARP) Epithelial cell proliferation contributes to airway remodeling in severe asthma. Am J Respir Crit Care Med. 2007;176:138–145. doi: 10.1164/rccm.200607-1062OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Fox SB, Leek RD, Weekes MP, Whitehouse RM, Gatter KC, Harris AL. Quantitation and prognostic value of breast cancer angiogenesis: comparison of microvessel density, Chalkley count, and computer image analysis. J Pathol. 1995;177:275–283. doi: 10.1002/path.1711770310. [DOI] [PubMed] [Google Scholar]
  • 27.Hansen S, Grabau DA, Rose C, Bak M, Sorensen FB. Angiogenesis in breast cancer: a comparative study of the observer variability of methods for determining microvessel density. Lab Invest. 1998;78:1563–1573. [PubMed] [Google Scholar]
  • 28.Hashimoto M, Tanaka H, Abe S. Quantitative analysis of bronchial wall vascularity in the medium and small airways of patients with asthma and COPD. Chest. 2005 Mar;127(3):965–72. doi: 10.1378/chest.127.3.965. [DOI] [PubMed] [Google Scholar]
  • 29.Chetta A, Zanini A, Foresi A, Del Donno M, Castagnaro A, D’Ippolito R, Baraldo S, Testi R, Saetta M, Olivieri D. Vascular component of airway remodeling in asthma is reduced by high dose of fluticasone. Am J Respir Crit Care Med. 2003;167:751–757. doi: 10.1164/rccm.200207-710OC. [DOI] [PubMed] [Google Scholar]
  • 30.Hoshino M, Takahashi M, Takai Y, Sim J, Aoike N. Inhaled corticosteroids decrease vascularity of the bronchial mucosa in patients with asthma. Clin Exp Allergy. 2001;31:722–730. doi: 10.1046/j.1365-2222.2001.01071.x. [DOI] [PubMed] [Google Scholar]
  • 31.Orsida BE, Li X, Hickey B, Thien F, Wilson JW, Walters EH. Vascularity in asthmatic airways: relation to inhaled steroid dose. Thorax. 1999;54:289–295. doi: 10.1136/thx.54.4.289. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Orsida BE, Ward C, Li X, Bish R, Wilson JW, Thien F, Walters EH. Effect of a long-acting beta2-agonist over three months on airway wall vascular remodeling in asthma. Am J Respir Crit Care Med. 2001;164:117–21. doi: 10.1164/ajrccm.164.1.2006003. [DOI] [PubMed] [Google Scholar]
  • 33.Carroll NG, Cooke C, James AL. Bronchial blood vessel dimensions in asthma. Am J Respir Crit Care Med. 1997 Feb;155(2):689–95. doi: 10.1164/ajrccm.155.2.9032214. [DOI] [PubMed] [Google Scholar]
  • 34.Saglani S, Papaioannou G, Khoo L, Ujita M, Jeffery PK, Owens C, Hansell DM, Payne DN, Bush A. Can HRCT be used as a marker of airway remodelling in children with difficult asthma? Respir Res. 2006;7:46. doi: 10.1186/1465-9921-7-46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Jeffery P, Holgate S, Wenzel S Endobronchial Biopsy Workshop. Methods for the assessment of endobronchial biopsies in clinical research: application to studies of pathogenesis and the effects of treatment. Am J Respir Crit Care Med. 2003;168:S1–17. doi: 10.1164/rccm.200202-150WS. [DOI] [PubMed] [Google Scholar]

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