Abstract
Background
Asthma-like features, defined as a high blood eosinophil count (BEC), atopy, and bronchodilator reversibility, characterize patients with chronic obstructive pulmonary disease (COPD) under optimal treatment. However, whether these features contribute to the phenotype of mucus plugging has not been elucidated. In this study, we aimed to examine the functional and clinical outcomes related to mucus plugging in patients with and without asthma-like features.
Methods
Mucus plug score was assessed using inspiratory computed tomography (CT) scans in participants from the Hokkaido COPD cohort study who underwent CT examinations using the same protocol, were categorized based on asthma-like features, and completed the St. George’s Respiratory Questionnaire (SGRQ). To evaluate the association between mucus plug score and pulmonary function indices, multivariate analyses were performed to examine the relationships between the mucus plug score and percent predicted forced expiratory volume in 1 s (%FEV1) or residual volume (RV)/total lung capacity (TLC). These analyses were adjusted for BEC or CT-derived airway indices (total airway wall volume, functional small airway disease, and emphysema index) based on asthma-like feature categorization, in addition to univariate analyses.
Results
The mucus plug score was negatively associated with %FEV1 and FEV1/forced vital capacity in patients with (N = 45) and without (N = 46) asthma-like features and was positively associated with RV/TLC in those without asthma-like features. As the mucus plug score increased, the SGRQ score worsened in both groups. Multivariate analysis revealed a correlation between mucus plug score and RV/TLC (estimate [95% confidence interval], 1.27 [0.30, 2.25]), but not %FEV1, in patients without asthma-like features, and between mucus plug score and %FEV1 (− 1.26 [− 2.33, − 0.20]), but not RV/TLC, in patients with asthma-like features, after adjusting for proximal airway, small airway, and emphysema indices.
Conclusions
Asthma-like features may differentiate the functional role of mucus plugging observed on CT scans in patients with COPD. Further studies are needed to validate these findings and clarify the underlying pathophysiology for improved disease management.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12890-026-04472-z.
Keywords: Asthma, Chronic obstructive pulmonary disease, Computed tomography, Eosinophil, Percent predicted forced expiratory volume in 1 s, Mucus plugging, Residual volume, Total lung capacity
Background
Mucus plugging is a distinct trait in patients with chronic obstructive pulmonary disease (COPD) [1] and is similar to that in patients with asthma and other respiratory diseases [2]. Mucus plugging impairs lung function by obstructing the airflow [3]. Computed tomography (CT) is a clinically accessible modality for assessing mucus plugging in the proximal airways and provides useful information for predicting the response to biologics [4], including improvement in lung function, asthma-related symptoms, and quality of life (QoL) in patients with asthma [5]. This suggests that mucus plugging may represent a therapeutically modifiable target. An additional aspect of mucus plugging in the proximal airways, assessed using CT-derived scores, predicts exacerbations [6], loss of life independence, and mortality in patients with COPD [7, 8]. Previous studies implicate Mucin 5B (MUC5B) in patients with COPD, whereas MUC5AC is involved in patients with asthma [9]. However, further evidence regarding its pathogenesis is needed to optimize the management of patients with COPD.
Mucus plugging in asthma has been recognized as a treatable trait [10], highlighting the need for biologic treatments targeting type 2 inflammation. However, the inflammatory pattern may differentiate the pathology of mucus plugging. Eosinophilic inflammation produces mucus with intense viscosity, which may explain the stronger correlation with impaired lung function in patients with eosinophilic inflammation than in those with non-eosinophilic inflammation in asthma [11]. A recent large-scale study demonstrated the impact of mucus plugging and its association with inflammatory patterns, type 2 or non-type 2, based on blood eosinophil count (BEC) in patients with COPD [12]. Severe mucus plugging with non-type 2 inflammation, but not type 2 inflammation, is associated with airflow limitation in two independent cohorts. These findings suggest the existence of differential phenotypes of mucus plugging based on type 2 or non-type 2 inflammation in patients with COPD. However, few studies have addressed the functional or clinical diversity of mucus plugging in patients with COPD.
We have previously reported that asthma-like features, defined as high BEC, atopy, and bronchodilator reversibility (BDR), do not deteriorate forced expiratory volume in 1 s (FEV1) changes, exacerbate disease, or improve prognosis in patients with COPD under optimal treatment [13]. Furthermore, high BEC was associated with sustained FEV1 for over 5 years. These observations support a phenotypic role of asthma-like features, suggesting that type 2-prone COPD under optimal treatment does not exacerbate functional or clinical outcomes in patients with COPD, unlike in patients with asthma. Another study suggested a therapeutic role of high IgE levels in reducing the risk of exacerbation in patients with COPD treated with inhaled corticosteroids (ICS) [14], further highlighting the potential clinical relevance of asthma-like features.
Thus, we hypothesized that asthma-like features may affect mucus plugging in patients with COPD. In this study, we aimed to compare functional and clinical outcomes of mucus plugging in patients with COPD using the same cohort as in our previous report by Suzuki et al. Particularly, we examined the relationship between mucus plugging and lung function parameters in a way complementary to BEC.
Methods
Participants
All patients who participated in the Hokkaido COPD cohort study [15, 16] were recruited from Hokkaido University Hospital and its nine affiliated hospitals.
This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of Hokkaido University Hospital (reference: med 02 − 001, December 2002; 018–0392, February 20, 2019; 025–0143, August 12, 2025). All participants provided written informed consent according to the Hokkaido COPD cohort protocol, which was announced online with an opt-out option approved by the IRB of Hokkaido University Hospital, as described in previous reports.
Information on clinical outcomes, including asthma-like features and clinical course
Respirologists confirmed that participants had no past history of asthma or variable respiratory symptoms, such as wheezing, shortness of breath, chest tightness, or cough. Patients with any of these features were excluded [13]. Medications prescribed for COPD were recorded through interviews and reviewed by the coordinators. This study adopted a classification of asthma-like features identical to that in Suzuki’s report [13]. Briefly, asthma-like features comprised three components: blood eosinophilia, atopy, and the presence of BDR. Blood eosinophilia was defined as ≥ 300/µL. Atopy was defined as the presence of specific serum IgE to at least one of 14 inhaled allergens, measured at entry using a multiple-allergen simultaneous test–26 chemiluminescent assay system (Hitachi Chemical Co., Tokyo, Japan). BDR was defined as a ΔFEV1 ≥200 mL and ≥ 12% following inhalation of 400 µg of salbutamol. We averaged the values from three consecutive visits at 6-month intervals [17]. The St. George’s Respiratory Questionnaire (SGRQ) was used to assess health-related QoL annually [18]. Exacerbation was defined as meeting symptom-based criteria, along with the need for antibiotics, systemic steroids, or hospital admission [19]. As previously reported, exacerbation incidence was assessed via postcards, with a response rate of > 99% over 5 years. The annual ΔFEV1 was calculated using a mixed-effects linear model over the 5-year follow-up in patients with at least three spirometry measurements [16].
Chest CT
CT scans were performed at full inspiration with a 1.25-mm slice thickness at Hokkaido University Hospital using a Somatom Plus Volume Zoom scanner (Siemens AG, Berlin, Germany). The study protocol was as follows: 140 kVp, 150 mA, 4 × 1 mm detector collimation, and a helical pitch of six or seven. Reconstruction was performed using a soft algorithm (standard kernel, B30f; sharp kernel, B60f) [20].
Mucus plugs were visually assessed in all segments of both lungs based on the scoring system described by Dunican et al. [2, 21]. The mucus plug score reflected the number of segments with mucus plugs. A mucus plug was identified when the airway was completely obstructed in an area > 20 mm away from the costal and diaphragmatic pleura. Quantitative analysis of Digital Imaging and Communications in Medicine (DICOM) data was performed using A-VIEW software (Coreline Soft Inc., Seoul, South Korea) [22]. Quantification of the percentage low-attenuation volume and airway wall volume (AWV) was performed using A-VIEW software. We used the ratio of low-attenuation volume with a cutoff of − 950 Hounsfield units (HU) to lung volume (LV) as the emphysema index. The airway tree was constructed based on the prolongation of airway images extracted in an AI-based manner. According to sample points six voxels away from the endpoints, possible pathways were generated, accompanied by the selection of airways. Subsequently, the airway structures were prolonged and completely constructed. Bronchi partially located within masked lung regions were recognized as intrapulmonary bronchi. The total AWV was determined as the total wall volume of the intrapulmonary airway in the lungs.
The airway tree was segmented and skeletonized along its centerline. Branching points were identified by the generation number of each branch, starting from the right and left main bronchi (Generation 1) and extending to the peripheral airway branches. This was performed using the Python package “Skan” and a custom script with manual modifications as required. The total airway count (TAC) was calculated by counting all branches of the skeletonized trees [23].
Using the SYNAPSE VINCENT software (FUJIFILM, Tokyo, Japan), pairs of inspiratory and expiratory lung images were nonrigidly registered, enabling calculation of functional small airway disease (fSAD), defined as voxels with CT values > − 950 HU on inspiratory CT and < − 856 HU on registered expiratory CT [24].
Pulmonary function tests
Spirometry was performed using a Chestac-8900 (Chest M.I., Tokyo, Japan). This maneuver followed the recommendations of the American Thoracic Society/European Respiratory Society [25, 26]. The diffusing capacity of the lungs for carbon monoxide (DLco) and the transfer coefficient of the lungs for carbon monoxide (Kco) were calculated using the single-breath method, as per the Japanese Respiratory Society (JRS) pulmonary function test guidelines [27], and corrected for hemoglobin concentration. DLco and Kco were expressed as percentages of the predicted values based on Burrow’s Eqs [28, 29]. LV was measured using the multi-breath helium dilution method and the prediction equation of Nishida [30]. The predicted values for spirometric measurements were based on the JRS guidelines. Patients were instructed to refrain from any respiratory medication during the examination [13].
Statistical analysis
Anthropometric characteristics and asthma-like features, BEC, indices based on pulmonary function tests and CT scans, and medications were compared between groups based on the presence of asthma-like features using the Wilcoxon test or chi-square test. The relationship between asthma-like features and mucus plug scores was explored using multivariate analysis adjusted for age, sex, body mass index (BMI), and smoking status (current/past smokers). Spearman’s correlation coefficient was used to examine the relationships between the mucus plug score and indices of pulmonary function tests, CT scans, BEC or blood neutrophil count, and between BEC and CT-based indices. The relationships between the mucus plug score, %FEV1, and residual volume (RV)/total lung capacity (TLC) were assessed using multiple linear regression, adjusted for BEC (Model 1) and AWV, fSAD, and percentage of low-attenuation volume (%LAV) (Model 2). The correlations between the mucus plug score and SGRQ score were examined using multivariate analysis, adjusted for age, sex, BMI, and smoking status. A Cox proportional hazards model was constructed to demonstrate the relationship between the mucus plug score and the time to first exacerbation during the 5-year follow-up, using age, sex, BMI, and smoking status (Model 1) and SGRQ (Model 2) as covariates. Univariate analysis was performed to explore the relationship between the mucus plug score and annual ΔFEV1 during the 5-year follow-up. Blood eosinophil [31] or neutrophil counts at the same time point as the CT examination were used. Statistical significance was defined as p < 0.05. All analyses were performed using JMP Student Edition (SAS Institute, Cary, NC, USA).
Results
Characteristics of the participants
Additional file 1 shows a flowchart of the participants included in this analysis. Of the participants in the Hokkaido COPD cohort, 117 underwent CT either at entry or at year 1 using the same protocol. Furthermore, 19 patients had different reconstruction kernels, two had abnormal chest shadows, and five had inadequate data for the classification of asthma-like features.
Table 1 and Additional file 2 show the anthropometric characteristics, asthma-like features, pulmonary function test results, and CT-derived parameters in all patients and in groups stratified by asthma-like features. In comparisons between patients without and with asthma-like features (≥ 1 feature), BEC at the time of CT examination and all components of asthma-like features categorized based on baseline data were significantly higher in patients with asthma-like features, whereas the proportion of ICS use tended to be higher in patients with asthma-like features (p = 0.06).
Table 1.
Characteristics of participants based on asthma-like features
| All participants | Without features | With features | |
|---|---|---|---|
| N | 91 | 45 | 46 |
| Age, years | 71 (54,76) | 71 (63.5, 77) | 71.5 (65.8, 75.3) |
| Male/Female, n | 84/7 | 42/3 | 42/4 |
| BMI, kg/m2 | 22.5 (20.9, 24.5) | 22.5 (21.0, 24.5) | 22.6 (20.8, 24.2) |
| Pack-years | 56 (43, 76) | 56 (42.5, 68.3) | 58.5 (42.3, 80.1) |
| BEC, /µLa | 178.6 (90.4, 286.2) | 125.3 (76.5, 187.4) | 251.6 (127.1, 379.5) |
| BEC, n (Y/N)a | 22/69 | 0/45 | 22/24 |
| Atopy, n (Y/N)a | 15/76 | 0/45 | 15/31 |
| BDR, n (Y/N)a | 20/71 | 0/45 | 20/26 |
| %FEV1, % predicted | 65.3 (53.5, 82.2) | 89.8 (49.6, 86.5) | 62.0 (54.4, 76.0) |
| FEV1/FVC, % | 50.8 (43.3, 63.2) | 56.6 (44.9, 65.1) | 40.3 (42.3, 59.2) |
| %FRC, % predicted | 115.9 (102.8, 137.4) | 112.8 (99.8, 112.8) | 121.1 (106.0, 140.6) |
| %TLC, % predicted | 110.3 (97.3, 122.0) | 105.3 (94.1, 119.1) | 115.7 (101.0, 125.5) |
| RV/TLC, % | 45.3 (37.3, 54.7) | 43.1 (36.4, 56.4) | 45.8 (39.4, 54.0) |
| %DLco, % predicted | 85.9 (69.5, 101.2) | 87.7 (66.8, 103.8) | 83.6 (73.1, 100.1) |
| %Kco, % predicted | 74.8 (61.0, 91.0) | 76.3 (53.7, 98.0) | 73.8 (65.3, 89.8) |
|
Beta-agonist use, n (%) number()()number |
32 (35.2) | 15 (33.3) | 17 (37.0) |
| Teo use, n (%) | 28 (31.0) | 14 (31.1) | 14 (30.4) |
| ICS use, n (%) | 12 (13.2) | 3 (6.7) | 9 (20.0) |
| OCS use, n (%) | 1 (1.1) | 1 (2.2) | 0 (0) |
| Mp | 1 (0, 3) | 0 (0, 3) | 1 (0, 3) |
| Airway wall volume | 111.4 (69.6, 156.2) | 117.0 (90.0, 185.7) | 107.8 (65.7, 140.6) |
| TAC | 267 (200.3, 328.5) | 280 (216, 336) | 260 (94, 203.3) |
| %fSAD, % | 29.0 (19.8, 37.7) | 26.9 (16.6, 37.4) | 32.1 (22.9, 39.9) |
| %LAV, % | 18.6 (12.5, 32.4) | 17.3 (12.3, 28.1) | 23.1 (14.2, 31.1) |
Abbreviations: BMI Body mass index, BEC Blood eosinophil count at the time of CT examination, BEC a number of BEC > 300/µL at the entry, BDR Bronchodilator reversibility, FEV1 Forced expiratory volume in 1 s, FVC Forced vital capacity, FRC Functional residual capacity, TLC Total lung capacity, RV Residual volume, DLco Diffusing capacity of the lungs for carbon monoxide, Kco Transfer capacity of the lungs for carbon monoxide, Teo Theophylline, ICS Inhaled corticosteroids, OCS Oral corticosteroids, Mp mucus plug score, TAC Total airway count, fSAD Functional small airway disease, LAV Low-attenuation volume
aStatistically significant difference between groups without and with asthma-like features
Mucus plugs in patients with or without asthma-like features
No significant difference was observed in the mucus plug scores between patients with and without asthma-like features (Table 1) or between patients with one feature and those with two features (Additional file 2). In the categories of 0, 1, and 2 positive features, but not in the comparison of patients with (≥ 1) or without asthma-like features, positivity for asthma-like features was associated with an increased mucus plug score in multivariate analysis (Additional file 3).
Relationship of mucus plug score with indices derived from pulmonary function tests, CT scans, and blood eosinophil or neutrophil count
The mucus plug score negatively correlated with %FEV1 and FEV1/forced vital capacity (FVC) in both patients with and without asthma-like features and positively correlated with RV/TLC or %RV in those without asthma-like features (Fig. 1; Additional file 4). BEC tended to be positively related to mucus plug score in patients with asthma-like features (Additional file 4). When BEC was included as a covariate, a negative correlation of the mucus plug score and a positive correlation of BEC with %FEV1 were observed in patients with asthma-like features (Table 2). Moreover, a significant negative correlation was observed between the mucus plug score and %FEV1 in patients with asthma-like features, and a significant positive correlation was observed between the mucus plug score and RV/TLC in patients without asthma-like features, after adjustment for total AWV, fSAD, and %LAV (Table 2). Regarding the relationships between the mucus plug score and CT-derived indices, total AWV was negatively associated with the mucus plug score in patients without asthma-like features (Additional file 4).
Fig. 1.
Relationship of the mucus plug score with pulmonary function. The mucus plug score was associated with %FEV1 or FEV1/FVC, regardless of the presence or absence of asthma-like features, and with RV/TLC in patients without asthma-like features. Abbreviations: FEV1: forced expiratory volume in 1 s, RV: residual volume, TLC: total lung capacity
Table 2.
Relationship of mucus plug score with FEV1 or RV/TLC, adjusted for blood eosinophil count or intra-indices (multivariate analysis)
| (a) %FEV1 | |||||
|---|---|---|---|---|---|
| Without asthma-like features | With asthma-like features | ||||
| Model 1 | Model 2 | Model 1 | Model 2 | ||
| Estimate (95% CI) | |||||
| Mp | -5.0 (-7.45, -2.55) | -1.56 (-3.44, 0.32) | -2.27 (-3.37, -1.17) | -1.26 (-2.33, -0.20) | |
| BEC | -0.02(-0.08, 0.05) | 0.03(0.00, 0.06) | |||
| AWV | 0.19 (0.11, 0.26) | -0.01 (-0.11, 0.09) | |||
| %fSAD | -0.12 (-0.50, 0.26) | -0.67 (-1.13, -0.20) | |||
| %LAV | -0.53 (-0.86, -0.20) | -0.32 (-0.70, 0.07) | |||
| (b) RV/TLC | |||||
|---|---|---|---|---|---|
| Without asthma-like features | With asthma-like features | ||||
| Model 1 | Model 2 | Model 1 | Model 2 | ||
| Estimate (95% CI) | |||||
| Mp | 2.88 (1.67, 4.11) | 1.27 (0.30, 2.25) | 0.69 (0.10, 1.27) | 0.06 (-0.44, 0.56) | |
| BEC | 0.01 (-0.03, 0.04) | -0.02 (-0.03, 0.00) | |||
| AWV | -0.05 (-0.08, -0.01) | -0.01 (-0.05, 0.04) | |||
| %fSAD | 0.28 (0.08, 0.47) | 0.45 (0.23, 0.67) | |||
| %LAV | 0.25 (0.08, 0.42) | 0.13 (-0.05, 0.31) | |||
Estimates and 95% confidence intervals are presented
Abbreviations: CI confidence interval, Mp mucus plug score, BEC Blood eosinophil count, TAC Total airway count, fSAD Functional small airway disease, LAV Low-attenuation volume
Relationships among mucus plug score with SGRQ, exacerbation, and annual decline in FEV1
As the mucus plug score increased, SGRQ scores worsened in patients with and without asthma-like features (Table 3). However, there was no significant association between the mucus plug score and the time to first exacerbation after adjustment for age, sex, BMI, smoking status, and SGRQ score in both groups. Meanwhile, a higher mucus plug score was associated with a shorter time to first exacerbation after adjustment for age, sex, BMI, and smoking status in patients with asthma-like features, considering the association between mucus plug score and SGRQ. The mucus plug score showed no association with annual decline in FEV1 during the 5-year follow-up in patients with and without asthma-like features (Additional file 5).
Table 3.
Relationship of mucus plug score with SGRQ or time to first exacerbation
| (a) SGRQ score | |||||
|---|---|---|---|---|---|
| Without asthma-like features | With asthma-like features | ||||
| Estimate (95% CI) | |||||
| Mp | 3.79 (1.95, 5.63) | 1.75 (0.55, 2.96) | |||
| (b) Time to first exacerbation (hazard ratio) | |||||
|---|---|---|---|---|---|
| Without asthma-like features | With asthma-like features | ||||
| Hazard Ratio (95% CI) | |||||
| Mp | Model 1 | 1.04 (0.80, 1.31) | 1.17 (1.02, 1.31) | ||
| Model 2 | 1.08 (0.76, 1.46) | 1.10 (0.93, 1.32) | |||
Estimates and 95% confidencetial intervals are presented
Adjusted for age, sex, body mass index, and smoking status
Model 1: Adjusted for age, sex, body mass index, and smoking status
Model 2: Adjusted for age, sex, body mass index, smoking status, and SGRQ score
Abbreviations: M: mucus plug score, SGRQ St. George’s Respiratory Questionnaire
Relationship of BEC with CT-derived indices
Weak but significant negative correlations were observed between BEC, %LAV, and fSAD in patients with asthma-like features but not in those without asthma-like features (Fig. 2). BEC showed no significant correlation with the total AWV or TAC (Additional file 6).
Fig. 2.
Blood eosinophil count and CT-derived indices. A significant negative correlation was observed between blood eosinophil count and %LAV or fSAD in patients with asthma-like features, but not in those without asthma-like features. Abbreviations: LAV: low-attenuation volume; fSAD, functional small airway disease; CT, computed tomography
Discussion
We demonstrated that the presence of asthma-like features may differentiate the relationship between mucus plugging and pulmonary function indices, including %FEV1 and RV/TLC. Mucus plugging in the absence of asthma-like features was negatively associated with %FEV1 and FEV1/FVC, and positively associated with RV/TLC and %RV, whereas mucus plugging in the presence of asthma-like features was associated with %FEV1 and FEV1/FVC. Moreover, multivariate analysis revealed a significant correlation between mucus plugging and RV/TLC in patients without asthma-like features, and %FEV1 in patients with asthma-like features, when adjusted for other intrapulmonary morphological indices, such as proximal AWV, fSAD, and %LAV. Notably, the SGRQ score was impaired owing to the burden of mucus plugging, regardless of the presence or absence of asthma-like features. Additionally, mucus plugging and BEC were both inversely - oppositely correlated with %FEV1 in patients with asthma-like features, where high BEC was associated with lower fSAD and %LAV.
Asthma-like features may contribute to the phenotyping of mucus plugging in COPD, which may facilitate the exploration of the diverse pathophysiologies of mucus plugging [32]. Mucus plugging in the presence of asthma-like features is associated with proximal physiological indices, including %FEV1, adjusted for proximal or small airway morphological indices, and emphysema [1]. In contrast, mucus plugging in the absence of asthma-like features was correlated with the small airway-related index of RV/TLC [33], along with the airway and emphysema indices. This novel finding suggests the differential functional contribution of mucus plugging based on the presence or absence of asthma-like features. Non-type 2-related mucus is presumed to affect small airway ventilation, complementary to airway and parenchymal alterations. This implies that the mucus plug score in the proximal airway on CT scans might serve as a potential morphological marker for mucus plugging in the small airways in patients without asthma-like features. Given the lack of mucus-targeted therapies, novel interventions for mucus plugging, particularly in small airway disease, are desirable. The predominant proximal contribution of mucus plugging in patients with asthma-like features does not necessarily indicate the absence of mucus plugging in the small airways. A discrepancy between mucus plugging in the proximal and small airways in patients with asthma-like features may exist, accompanied by a clinically relevant contribution of mucus plugging to proximal airway function. Future studies should further characterize the phenotype of mucus plugging in the lungs of patients with COPD.
The burden of mucus plugging was associated with worse SGRQ scores, regardless of the presence or absence of asthma-like features, which may support the potential therapeutic value of targeting mucus plugging. Elucidating the mechanisms underlying mucus plugging is fundamental to establishing a therapeutic strategy. The results of this study broaden our knowledge of the heterogeneous characteristics of mucus plugging. It is plausible that mucus plugging requires non-type 2-related interventions in patients without asthma-like features, whereas type 2-related interventions may play a role in the management of mucus plugging in a subset of patients with asthma-like features. In particular, a subset of patients with asthma-like features suffer from a severe burden of mucus plugging. Mucus plug scores tended to positively correlate with BEC in patients with asthma-like features, suggesting that a subset of patients may benefit from type 2-related therapy. This phenomenon may be supported by findings that different inflammatory cells are involved in the proximal and small airways [34]. Moreover, previous reports have shown the preferential involvement of MUC5B in patients with COPD and MUC5AC in patients with asthma. The results of this study may augment the need for further evidence on the heterogeneity of mucus formation in patients with COPD.
Diaz et al. suggested a consistent burden of mucus plugging on decreasing FEV1 in patients with comorbid low BEC in two large-scale studies, whereas severe mucus plugging associated with high BEC impaired airflow more strongly than less mucus with low BEC in only one cohort, consistent with the results of this study in terms of a differential functional traits. Mucus plug score was negatively associated with %FEV1, in contrast to the positive effect of BEC. Suzuki et al. specified the optimal effect of high BEC on sustaining FEV1 over a 5-year follow-up period in our cohort. The current analysis validates the positive association between BEC and %FEV1 in patients with asthma-like features. We have previously reported an accelerated annual decline in FEV1 in patients with COPD and prominent emphysema. Therefore, the weak but significant correlation between high BEC and less emphysema and fSAD is presumably attributable to preserved FEV1 both cross-sectionally and longitudinally.
We have previously reported that mucus plugging and prominent emphysema are poor prognostic predictors in patients with COPD [7] In contrast, the presence of multiple asthma-like features predicted better prognosis during a 10-year follow-up. Collectively, patients with mucus combined with emphysematous lungs have a poor prognosis, whereas patients with multiple positive asthma-like features combined with less mucus plugging and emphysema have a good prognosis. In this study, there was no significant association between mucus plugging and the annual decline in FEV1. In addition, the impact of mucus plugging on the time to first exacerbation was significant after adjustment for age, sex, BMI, and smoking status in patients with asthma-like features, but not in those without asthma-like features. However, the association between mucus plugging and the time to first exacerbation was not significant when SGRQ was added as a covariate during the 5-year follow-up [35], while a previous report suggested a predictive role for mucus plugging in exacerbations. This might be explained by the emphysema-dominant phenotype, which is typical in Japanese cohorts, and differences in treatment intensity. Moreover, the morphological relationships between mucus plugging and intrapulmonary indices reflecting proximal or small airways and emphysema should be elucidated in a prospective large-scale study in terms of mucus formation and preservation. Moreover, inhaled or oral corticosteroids are not sufficient to eliminate mucus plugging in patients with obstructive lung diseases. The efficacy of feasible anti-inflammatory treatments, such as corticosteroids or biologics, for the management of mucus plugging or related clinical outcomes should be determined.
This study has some limitations. First, this analysis was based on 91 participants who underwent CT scans using the same vendor and protocol, a part of participants that Suzuki analyzed in the Hokkaido COPD cohort (N = 262). In the entire cohort, 135 patients (51.5%) had no asthma-like features, 96 (36.6%) had one positive, 31 (11.9%) had two positive asthma-like features, whereas 45 patients (49.5%) had no asthma-like features, 35 (38.5%) had one positive, and 11 (12.0%) had two positive for asthma-like features in this analysis. Given the similar distribution of the subgroups based on asthma-like features, these results may capture the characteristics of the cohort. Second, this cohort was substantially composed of male and emphysema-dominant phenotypes of COPD under optimal treatment, which limits the generalizability of the findings. Third, we did not have information on sputum analysis in the Hokkaido COPD cohort, which may offer a more detailed analysis of mucus plugging characteristics in patients with and without asthma-like features. However, this study took advantage of the incorporated assessments of blood, pulmonary function, and CT scans, all of which were clinically accessible.
Conclusion
In conclusion, asthma-like features may characterize mucus plugging in patients with COPD in terms of differential impairment of ventilation. The burden of mucus plugging is clinically relevant, based on the impairment of lung function and health-related QoL, as assessed by SGRQ, regardless of the presence or absence of asthma-like features. The impact of mucu plugging on the time to first exacerbation was significant in patients with asthma-like features, adjustment for age, sex, BMI, and smoking status. This analysis may have generated the hypothesis of heterogeneous traits of mucus plugging, together with the need for a personalized therapeutic approach to mucus plugging for better management of patients with COPD.
Supplementary Information
Additional file 1. Flow chart of participants. Of all participants in the Hokkaido COPD cohort, 91 with CT scans obtained using the same protocol and characterization for asthma-like features were included in this analysis.
Additional file 2. Characteristics of participants with one and two asthma-like features.
Additional file 3. Relationship of categorization of asthma-like features with mucus plug score.
Additional file 4. Mucus plug score and pulmonary function, CT-derived indices, and blood eosinophil or neutrophil count.
Additional file 5. Mucus plug score and longitudinal FEV1 changes.
Additional file 6. Relationship of blood eosinophil count with CT-derived airway indices.
Acknowledgements
The authors express their sincere gratitude to Dr. Masaru Suzuki, former associate professor at the Department of Respiratory Medicine, Faculty of Medicine, Hokkaido University, who passed away in January 2024, for his scientific contribution to respiratory medicine. The authors would also like to thank all of the Hokkaido COPD cohort study investigators for patient recruitment and follow-up, along with Hideka Ashikaga, Ayako Kondo, and Yuko Takagi of the Central Office of the Hokkaido COPD cohort study (Sapporo, Japan) and staff of Exam Co., Ltd. (Sapporo, Japan) for data management, and members of J-RIFneT for their collaboration in this study. We would like to thank Editage (www.editage.jp) for English language editing.
Abbreviations
- AWV
Airway wall volume
- BDR
Bronchodilator reversibility
- BEC
Blood eosinophil count
- BMI
Body mass index
- CI
Confidence interval
- COPD
Chronic obstructive pulmonary disease
- CT
Computed tomography
- DLco
Diffusing capacity of the lungs for carbon monoxide
- %FEV1
Percent predicted forced expiratory volume in 1 s
- fSAD
Functional small airway disease
- FVC
Forced vital capacity
- HU
Hounsfield units
- ICS
Inhaled corticosteroids
- IRB
Institutional Review Board
- JRS
Japanese Respiratory Society
- Kco
Transfer coefficient of the lungs for carbon monoxide
- %LAV
Percentage of low-attenuation volume
- LV
lung volume
- MUC5AC
Mucin 5AC
- MUC5B
Mucin 5B
- QoL
Quality of life
- RV
Residual volume
- SGRQ
St. George’s Respiratory Questionnaire
- TAC
Total airway count
- TLC
Total lung capacity
Authors’ contributions
K.S.: conception and design of the study, interpretation of data, statistical analysis, and drafting of the manuscript; N.T., S.S., S.C., K.T., N.F., and H.I.: conception and design of the study, interpretation of data, and editing of the manuscript; N.W.: CT analysis and data analysis; I.Y.: statistical analysis; Y.A., K.K., S.N., H.K., HG, T.H., and I.T.: interpretation of data and editing of the manuscript; H.M., M.N., and S.K.: conception and design of the study, acquisition and interpretation of data, and finalization of the manuscript.
Funding
This study was supported by a scientific research grant provided to the Hokkaido COPD cohort study by the Ministry of Education, Culture, Sports, Science, and Technology of Japan (17390239 and 2139053 to M.N., 23K2760603 to S.K.), as well as by Nippon Boehringer Ingelheim, Pfizer Inc., and a grant provided to the Respiratory Failure Research Group of the Ministry of Health, Labour and Welfare, Japan. The sponsors were not involved in the study design, data collection, data analysis, data interpretation, or manuscript writing.
Data availability
The dataset of the Hokkaido COPD cohort used in this analysis is available by contacting the corresponding author.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the principles of the Declaration of Helsinki. This study was approved by the Institutional Review Board of Hokkaido University Hospital (reference: med 02 − 001: December 2002, 018–0392:20th of February 2019, 025–0143:12th of August 2025). Written informed consent to participate was obtained from all of the patients in the original study including all the patients involved in the current study. The protocol of the current study was informed via the internet for the patients, based on the instructions of an Institutional Review Board.
Consent for publication
Not applicable.
Competing interests
The authors report the following: K.S. was supported by grants from Daiwa Health Development, Inc. and received honoria from AstraZeneca, outside the submitted work. N.T. was supported by grants from FUJIFILM Co., Ltd. and Daiichi Sankyo Co., Ltd., and received honoraria from GlaxoSmithKline K.K, outside the submitted work. K.T. received honoria from AstraZeneca.N.F. reveived honoria from AstraZeneca and Sanofy Co. Ltd. outside the submitted work I.T. was supported by grants from Mochida Pharmaceuticals K.K., Nippon Shinyaku Co., Ltd., Nippon Boehringer Ingelheim Co., Ltd., Medical System Network Co., Ltd., Kaneka Corp., and Takeyama Co., Ltd., and received honoraria from Nippon Shinyaku Co., Ltd. and Janssen Pharmaceutical K.K. outside the submitted work. S.M. was supported by grants from ROHTO Pharmaceutical Co., Ltd. and FUKUDA Life Tech Co., Ltd., and received honoraria from Nippon Boehringer Ingelheim Co., Ltd., AstraZeneca, and GlaxoSmithKline outside the submitted work.S.S. was supported by grants from Nippon Boehringer Ingelheim Co., Philips-Respironics, Fukuda Denshi, Fukuda Lifetec Keiji, and ResMed outside the submitted work. S.K. was supported by grants from Mochida Pharmaceuticals K.K., Nippon Shinyaku Co., Ltd., Nippon Boehringer Ingelheim Co., Ltd., Medical System Network Co., Ltd., Kaneka Corp., Takeyama Co., Ltd., and Novartis, and received honoraria from AstraZeneca and KYORIN Pharmaceutical outside the submitted work. None of these companies played a role in the design or analysis of the study or in the writing of the manuscript. N.W.,S.C., H.I., ,I.Y., Y.A., K.K., S.N., H.M., and M.N. declare no conflict of interest.
Footnotes
Publisher’s note
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Additional file 1. Flow chart of participants. Of all participants in the Hokkaido COPD cohort, 91 with CT scans obtained using the same protocol and characterization for asthma-like features were included in this analysis.
Additional file 2. Characteristics of participants with one and two asthma-like features.
Additional file 3. Relationship of categorization of asthma-like features with mucus plug score.
Additional file 4. Mucus plug score and pulmonary function, CT-derived indices, and blood eosinophil or neutrophil count.
Additional file 5. Mucus plug score and longitudinal FEV1 changes.
Additional file 6. Relationship of blood eosinophil count with CT-derived airway indices.
Data Availability Statement
The dataset of the Hokkaido COPD cohort used in this analysis is available by contacting the corresponding author.