- Open Access
Long-term smoking alters abundance of over half of the proteome in bronchoalveolar lavage cell in smokers with normal spirometry, with effects on molecular pathways associated with COPD
Respiratory Research volume 19, Article number: 40 (2018)
Smoking represents a significant risk factor for many chronic inflammatory diseases, including chronic obstructive pulmonary disease (COPD).
To identify dysregulation of specific proteins and pathways in bronchoalveolar lavage (BAL) cells associated with smoking, isobaric tags for relative and absolute quantitation (iTRAQ)-based shotgun proteomics analyses were performed on BAL cells from healthy never-smokers and smokers with normal lung function from the Karolinska COSMIC cohort. Multivariate statistical modeling, multivariate correlations with clinical data, and pathway enrichment analysis were performed.
Smoking exerted a significant impact on the BAL cell proteome, with more than 500 proteins representing 15 molecular pathways altered due to smoking. The majority of these alterations occurred in a gender-independent manner. The phagosomal- and leukocyte trans endothelial migration (LTM) pathways significantly correlated with FEV1/FVC as well as the percentage of CD8+ T-cells and CD8+CD69+ T-cells in smokers. The correlations to clinical parameters in healthy never-smokers were minor.
The significant correlations of proteins in the phagosome- and LTM pathways with activated cytotoxic T-cells (CD69+) and the level of airway obstruction (FEV1/FVC) in smokers, both hallmarks of COPD, suggests that these two pathways may play a role in the molecular events preceding the development of COPD in susceptible smokers. Both pathways were found to be further dysregulated in COPD patients from the same cohort, thereby providing further support to this hypothesis. Given that not all smokers develop COPD in spite of decades of smoking, it is also plausible that some of the molecular pathways associated with response to smoking exert protective mechanisms to smoking-related pathologies in resilient individuals.
ClinicalTrials.gov identifier NCT02627872; Retrospectively registered on December 9, 2015.
The number of habitual smokers is estimated to one billion worldwide . The direct effect of tobacco smoking was responsible for the death of 6 million people in 2015, with 27% of them resulting from COPD . Although one-third of long-term smokers develop COPD , the molecular mechanisms by which smoking-induced inflammation triggers the development of disease remain unclear.
Proteomic profiling of blood, urine and lung tissue from smokers has improved our understanding of the molecular impact of smoking [4,5,6]. Lung immune cells, especially alveolar macrophages, play a key role in the immune responses to smoking . However, quantitative proteomics analysis of resident immune cells in the lung, particularly with respect to the inflammatory disorder in the response to smoking, are scarce. Our previous work revealed specific alterations of the bronchoalveolar lavage (BAL) cell proteome in current-smoker COPD patients . However, in order to define molecular disease mechanisms occurring prior to disease manifestations, alterations of the BAL cell proteome in response to smoking needs to be defined.
The aim of this study was to investigate the impact of long-term habitual smoking on the BAL immune cell proteome. The proteomes of long-term smokers at elevated risk of developing COPD were contrasted to healthy never-smokers, with the specific emphasis on identifying alterations of molecular pathways occurring prior to the presentation of symptoms or decline of lung function associated with COPD diagnosis.
The details of methods are provided in Supplemental materials.
Study subjects and design
This study was carried out on subjects from the Karolinska COSMIC cohort [8,9,10,11,12,13], a three-group cross-sectional study including age- (45–65 years) and sex-matched groups of healthy never-smokers (hereafter referred to as Never-smokers), smokers with normal lung function (hereafter referred to as Smokers; >10 pack years; >10 cigarettes/day the past 6 months), and smokers with COPD (GOLD stage I-II/A-B, FEV1 > 50% of predicted and FEV1/FVC < 0.7). Sixty-nine subjects were selected for proteome analyses (Fig. 1). The current segment included Never-smokers (n = 17) and Smokers (n = 25). Acute effects of smoking were excluded by requesting that participants to refrain from smoking at least 8 h prior to biospecimen collection, as confirmed by exhaled carbon monoxide monitoring . Results from the Smokers compared to the COPD group are presented in the companion paper . All subjects underwent extensive clinical examinations, including computed tomography [10, 13] and spirometry (Table 1, Additional file 1: Table S1). BAL cells were collected during bronchoscopy as previously described . Clinical characteristics are summarized in Table 1. The study was approved by the Stockholm regional ethical board (Case no. 2006/959–31/1), and written informed consent was obtained from all subjects.
Trypsinized protein extracted from 1.5 × 106 BAL cells, were used for 4-plexed iTRAQ labeling (AB SCIEX). The 114 tag was dedicated to a pooled reference sample in all sets, other samples were randomized and labeled with the 115, 116 and 117 tags. iTRAQ labeled peptides were fractionated into 5 fractions and reconstituted, then separated in Dionex Ultimate NCR-3000RS (LC system, Sunnyvale, California, USA) and analyzed on an LTQ-Orbitrap Velos Pro (Thermo Scientific, Sunnyvale, California, USA). The iTRAQ MS/MS data was searched against UniProt human database (2015_12) using Proteome Discoverer 2.1 (Thermo Fisher Scientific). The abundance ratio data of sample to reference was log2 transformed before statistical analysis.
Univariate statistical analyses were performed by Student’s test followed by correction for multiple testing according to Storey (q) . Multivariate statistical modeling was performed using SIMCA 14.1 (MKS Umetrics, Umeå, Sweden) using principal component analysis (PCA), orthogonal projection to latent structure-discriminant analysis (OPLS-DA)  and partial least square (PLS) regression.
In contrast to the more commonly used PCA modeling, OPLS analysis is a supervised method designed to separate structured noise unrelated (orthogonal, often intra-group variance) to the predictive variance of interest (e.g., COPD patients vs healthy subjects). The resulting “noise filter” increases the interpretability of the multivariate model, particularly in deriving the observed group separation back to the specific proteins driving the separation. For more information of how to interpret these models, or the related model statistics, please see .
Proteins with a value of the scaled loadings of the first predictive component (|p(corr)|) greater than the critical value of the Pearson correlation coefficient (p < 0.05) was considered significant for OPLS-DA models. Model performance is reported as the goodness of fit (R2), the goodness of prediction based on 7-fold cross validation (Q2), the cross-validated ANOVA (CV-ANOVA)  indicating the significance of group separation, and 200 times permutation test to determine the level of model statistics that may occur by random for the specific data set . Multivariate correlation analysis between the specific proteins from identified pathways with clinical data was performed using PLS, and inner relations with Pearson correlation coefficient of R2 > 0.5 and p < 0.05 were considered significant.
Pathway enrichment analysis was performed based on proteins found to be significantly altered in OPLS-DA models, as defined by OPLS-DA p(corr) above, using KOBAS 2.0 , with pathway enrichment analysis performed based on the KEGG pathway database .
FEV1 and percentage of neutrophils were lower (p < 0.05), while the proportion of macrophages was higher (p < 0.01) in Smokers compared to Never-smokers. No other differences between Smokers and Never-smokers, or between genders, were observed (Additional file 1: Table S1).
Proteome alteration due to smoking
Univariate analysis comparing Never-smoker vs. Smoker groups revealed 610 significantly altered proteins (q < 0.05). Multivariate analysis using OPLS-DA showed a highly significant separation between the two groups (p[CV-ANOVA] = 6.2 × 10−19; Fig. 2a, Additional file 2: Figure S1) with 91% predictive power (R2 = 0.95, Q2 = 0.91), driven by 506 significant proteins (|p(corr)| > 0.34, Additional file 1: Table S2).
To investigate the presence of any gender differences in response to smoking, statistical analyses were also performed following stratification by gender. Comparing female Smoker vs. Never-smoker groups, univariate statistical analysis showed 399 significantly altered proteins (q < 0.05). OPLS-DA models suggested that 401 proteins were significantly altered (|p[corr]| > 0.43, n = 23; Additional file 1: Table S3), driving a highly significant separation between groups (p[CV-ANOVA] = 2.1 × 10−10; Fig. 2b, Additional file 2: Figure S1) with a predictive power of 94% (R2 = 0.98, Q2 = 0.94,). For male Smoker vs. Never-smoker groups, univariate analysis identified 251 significantly altered proteins (q < 0.05). OPLS-DA modeling showed 301 significant proteins (|p(corr)| > 0.50, n = 19; Additional file 1: Table S4), also here with significant separation between groups (p[CV-ANOVA] = 4.5 × 10−6; Fig. 2c; Additional file 2: Figure S1) and 87% predictive power (R2 = 0.95, Q2 = 0.87).
There was a considerable overlap of the proteins altered in males and females due to smoking (199 proteins, Fig. 2d). The majority of significant proteins in both gender smokers, 286 in male (95%) and 345 in female smokers (86%), were significantly altered also in the joint gender model.
Alteration of pathway
Pathway analysis based on the 506 proteins found significant in the OPLS-DA model between Smokers and Never-smokers resulted in 15 significantly enriched pathways (pFDR < 0.05; Table 2, Additional file 1: Table S5). The majority of proteins in metabolic pathways such as oxidative phosphorylation, and citrate cycle were up-regulated, while ribosomal and antigen presentation were down-regulated in Smokers compared to Never-smokers. Proteins involved in the phagosomal (Fig. 3), LTM (Additional file 2: Figure S2) and lysosomal pathways were both up- and down-regulated (Table 2, Additional file 1: Table S5).
Gender-stratified pathway analysis showed that the majority of pathways mentioned above was altered in both genders in a similar fashion (Table 2, Additional file 1: Table S6), except the ribosomal- and glycolysis/gluconeogenesis pathways. In glycolysis/gluconeogenesis, five proteins were up-regulated in female Smokers (Fig. 4a), while four proteins were down-regulated in males (Fig. 4b).
Four pathways altered in Smokers were found to be altered in female Smokers with COPD: citrate cycle, oxidative phosphorylation, lysosome and phagosome . The majority of protein levels in oxidative phosphorylation and citrate cycle increased in female Smokers (Fig. 5a, c) were further increased in COPD patients (Fig. 5b, d). For the lysosomal pathway, the majority of proteins increased in female Smokers, with the opposite trend in female smoking COPD patients, as indicated by the one shared protein (Fig. 5f).
Phagosome and LTM pathways correlate with CD8+ T-cells and FEV1/FVC in smokers
The proportion of CD8+ and CD4+ T-cells and several T-cell sub-phenotypes from BAL cells were quantified using flow cytometry [9, 11]. The proportion of CD8+ T-cells increased and CD4+ decreased (Fig. 6a, both p < 0.0001) in Smokers compared to Never-smokers. Accordingly, the ratio of CD4+ to CD8+ T-cells was lowered in Smokers as well (p < 0.0001). Correlation analyses revealed that proteins from the LTM- and phagosomal pathways significantly correlated with the proportion of CD8+ T-cells (R2 = 0.72, Fig. 6b; R2 = 0.52, Fig. 6c; both p < 0.0001, respectively, PLS inner relation) and FEV1/FVC (R2 = 0.50, Fig. 6d; R2 = 0.51, both p < 0.0001, respectively) in Smokers.
Several additional pathways showed correlations with CD8+ T-cells and FEV1/FVC. Further correlation analysis with CD8+ subpopulations showed that both the proteins of the LTM- and phagosomal pathways significantly correlated with the percentage of CD8+CD69+ cells (R2 = 0.67, Fig. 6e; R2 = 0.59, Fig. 6f; both p < 0.0001, respectively). No significant correlations were found with any of the other CD8+ sub-phenotype markers measured, including CD8+CXCR3, CD8+CCR5, CD8+CXCR4, CD8+CD103+.
Proteomes identified by the iTRAQ vs. 2D–DIGE platforms
In complementary proteome investigations using 2D–DIGE on the same biospecimens from the same cohort, 149 proteins were identified . Comparison of the proteomes investigated with the bottom-up iTRAQ peptidomics platform and the top-down 2D–DIGE intact proteomics platform indicates that the majority of proteins identified with iTRAQ (90%) were novel as compared to the previously published 2D–DIGE analyses Fig. 7a.
From the DIGE perspective, the majority of the proteins identified in the DIGE workflow were also identified using iTRAQ. However, it should be noted that there is a bias towards overlap since only proteins of interest are identified in the DIGE workflow. The proteins that overlapped were generally altered in a similar fashion, thereby providing validation across platforms. Some examples are given in Fig. 7b-g, showing the levels of six proteins from six pathways significantly altered in both platforms.
Here we used high-resolution iTRAQ based proteomics to investigate the BAL cell proteome of smokers with normal lung function (Smokers) vs. healthy never-smokers (Never-smokers), with the aim to explore alterations in specific proteins and molecular pathways occurring in response to long-term cigarette smoking in otherwise healthy individuals. The results clearly show that smoking exerted a considerable impact on the BAL cell proteome, with the abundances of half of the detected proteins being altered in long-term smokers. Downstream pathway enrichment analyses revealed that the 506 significantly altered proteins were associated with 15 molecular pathways (q < 0.05). Two of these pathways, the phagosome and leukocyte transendothelial migration, were significantly correlated with the proportion of CD8+ T-cell in BAL, as well as with the level of airway obstruction (FEV1/FVC) in the Smoker group. Some of the identified molecular pathways may represent molecular events preceding the development of smoking-related disease in susceptible individuals, while others may represent protective mechanisms in individuals that prove to be resilient to disease development in spite of decades of smoking.
The increase of CD8+ (cytotoxic) T-cells is one of the culprits of the inflammation and tissue destruction in the lung induced by long-term smoking in mice . The level of lung cytotoxicity of CD8+ cells has been reported to increase with COPD severity , indicating that these cells were contributing to the pathogenesis of COPD. Increased levels of CD8+ T cells in lung parenchyma and pulmonary arteries have been reported as well . In these studies, we observed an increase in the proportion of CD8+ T-cells in BAL cells of Smokers compared to Never-smokers, which is in line with our previous reports from the full Karolinska COSMIC cohort . CD69 is a leukocyte activation marker, involved in the pathogenesis of chronic inflammation and activation of leukocyte subpopulations . Recent studies have shown that CD69 is required for cigarette smoking-induced inflammation in the lung as well as the development of COPD [28, 29]. The significant correlations of proteins in the phagosome- and LTM pathways with activated cytotoxic T-cells (CD69+) and the level of obstruction (FEV1/FVC) in smokers, both hallmarks of COPD, suggest that dysregulation of these two pathways may play an important role in the molecular events preceding the development of COPD in susceptible smokers. The observations of further dysregulation in the phagosomal pathways in female smokers with mild to moderate COPD  further supports this theory.
The phagosome is formed by the fusion of cell membrane around large particles or pathogens , followed by invagination (phagocytosis). Nascent phagosomes interact with recycling endosomes, early endosomes and lysosomes, thereby acquiring digestive capacity and becoming phagolysosomes , where pathogens are killed and subsequently degraded into fragments. The levels of three phagocytotic proteins were altered in Smokers compared to Never-smokers: Syntaxin 12 and transferrin receptor 1, co-localize in the recycling endosome, with the function of facilitating the fusion of the early phagosome with early endosome . LAMP2 is required for fusion of late phagosomes with lysosomes . The dysregulation of these three proteins may indicated a disturbance in phagosome maturation due to smoking. Acidification is essential for the phagosomes to mature . The observed increase in V-ATPases, which pump protons across the phagosomal membranes to maintain homeostasis of acidification, may indicate a dysregulation also in the local microenvironment of the phagosome. The decrease in F-actin and several receptors mediated in phagocytosis, including FcγR, SPA2, SRA1 and MARCO, may also contribute to defective phagocytosis in BAL immune cells due to smoking. Reduced protein levels of phagocytosis have been observed in female smokers with COPD . Further dysregulation of the phagocytotic pathway in female smoking COPD patients compared to the Smokers studied here is reported in the companion paper . As such, the level of dysregulation of the phagocytotic pathway in smokers may be of use as prognostic indicators of disease development.
The cell count of macrophages increased significantly in BAL fluid in Smokers. Alveolar macrophages predominantly originate from circulating blood monocytes , and are recruited to the lung by a mechanism involving leukocyte transendothelial migration (LTM), an inflammatory response to tissue damage. Recruitment of leukocytes from the blood to the site of injury includes several steps, including adhesion of leukocytes to the blood vessel wall, traversing the endothelial basement membrane, and migrating through the interstitial tissue . Alterations of the LTM pathway were observed in the Smoker group, with a number of proteins being both up- and down-regulated.
Platelet/endothelial cell adhesion molecule 1 (PECAM-1, CD31), is expressed on platelets and leukocytes and concentrated at the borders of endothelial cells. PECAM-1 regulates the start of diapedesis and is required for transendothelial migration [38, 39]. The level of PECAM-1 decreased in BAL cells in Smokers, suggesting that LTM decreased in Smokers. PECAM-1 has previously been reported to be decreased in the serum of smoker compared with nonsmokers . Myosin light-chain kinase (MLCK) and actin involve the actin-myosin fiber contraction, which helps endothelial cells separate . The levels of these two molecules were reduced in BAL cells of smokers, further supporting that LTM may be reduced due to smoking.
Macrophage-1 antigen (Mac-1, CD11b, ITGAM) is expressed on the surface of many leukocytes including monocytes, neutrophils and macrophages. CD11b plays a key role in the regulation of leukocyte adhesion and migration in the inflammatory response , and in the recruitment of alveolar macrophage during e.g., pneumococcal infection . Integrin beta-2 (CD18, ITGB2) pairs with CD11b to form the CR3 heterodimer of integrin. The higher expression levels of CD11b and CD18 indicated that, while the recruitment of leukocytes to the lung is impaired, leukocyte adhesion in the lungs increased due to smoking.
Four of the pathways (lysosome, citrate cycle, oxidative phosphorylation and phagosome) altered due to smoking were also found to be significantly altered in female smokers with COPD compared to smokers with normal spirometry, [8, 15]. The levels of the majority of proteins increased in the citrate cycle and oxidative phosphorylation pathways due to smoking were further increased in female smokers with COPD. The decreased levels of proteins in the lysosomal pathway observed in the female Smoker vs. Never-smoker groups were further decreased in female smoking COPD patients. As such, alteration of these pathways in smokers, with further enhanced dysregulation in smokers with mild to moderate COPD suggests that dysregulation of these pathways in healthy smokers may represent early signs of disease development in susceptible individuals. Even though the risk of developing COPD has been shown to increase linearly with the number of years smoked , it is curious that many smokers may never develop COPD in spite of decades of smoking. It is therefore plausible that some of the molecular pathways altered in long-term smokers represent protective mechanisms in resilient individuals, rather than disease mechanisms. These associations will be investigated following the completion of the on-going 10-year clinical follow-up of the Karolinska COSMIC cohort.
Our high-resolution iTRAQ proteomics investigations of BAL cells from smokers with normal lung function and healthy never-smokers revealed that long-term smoking exerted a considerable impact on the BAL cell proteome, with almost half of the detected proteins representing 15 different molecular pathways being significantly altered. In contrast to the significant gender differences in proteome alterations observed between smokers with and without COPD diagnosis, the gender differences observed between Smokers and Never-smokers were minor. Proteins in the phagosome- and LTM pathways significantly correlated with the proportion of CD8+ T-cells, its subtype CD8+CD69+ cells as well as the level of airway obstruction (FEV1/FVC) in the Smoker group, stressing the importance these pathways may play both in the protection against as well as the early pathophysiology of smoking-induced inflammatory lung disorders such as COPD.
Two-dimensional difference gel electrophoresis
Chronic obstructive pulmonary disease
False discovery rate
Isobaric tags for relative and absolute quantitation
Kyoto encyclopedia of genes and genomes
Leukocyte transendothelial migration
Orthogonal projection to latent structure-discriminant analysis
Scaled loadings of the predictive component of OPLS-DA model
p-value of cross-validated ANOVA
Principal component analysis
Corrected p-value using Benjamini and Hochberg’s FDR method
Partial least square regression
- Q2 :
Goodness of prediction (based on 7-fold cross-validation)
- R2 :
Goodness of fit (determination coefficient)
- SUS plot:
The plot of shared and unique structure
Ng M, Freeman MK, Fleming TD, et al. Smoking prevalence and cigarette consumption in 187 countries, 1980-2012. JAMA. 2014;311(2):183–92.
Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 2006;3(11):e442.
Crotty Alexander LE, Shin S, Hwang JH. Inflammatory diseases of the lung induced by conventional cigarette smoke: a review. Chest. 2015;148(5):1307–22.
Bortner JD, Jr., Richie JP, Jr., Das A, et al. Proteomic profiling of human plasma by iTRAQ reveals down-regulation of ITI-HC3 and VDBP by cigarette smoking. J Proteome Res 2011;10(3):1151-1159.
Airoldi L, Magagnotti C, Iannuzzi AR, et al. Effects of cigarette smoking on the human urinary proteome. Biochem Biophys Res Commun. 2009;381(3):397–402.
Kelsen SG, Duan X, Ji R, Perez O, Liu C, Merali S. Cigarette smoke induces an unfolded protein response in the human lung: a proteomic approach. Am J Respir Cell Mol Biol. 2008;38(5):541–50.
Sopori M. Effects of cigarette smoke on the immune system. Nat Rev Immunol. 2002;2(5):372–7.
Kohler M, Sandberg A, Kjellqvist S, et al. Gender differences in the bronchoalveolar lavage cell proteome of patients with chronic obstructive pulmonary disease. J Allergy Clin Immunol. 2013;131(3):743–51. e749
Forsslund H, Mikko M, Karimi R, et al. Distribution of T-cell subsets in BAL fluid of patients with mild to moderate COPD depends on current smoking status and not airway obstruction. Chest. 2014;145(4):711–22.
Karimi R, Tornling G, Forsslund H, et al. Lung density on high resolution computer tomography (HRCT) reflects degree of inflammation in smokers. Respir Res. 2014;15:23.
Forsslund H, Yang M, Mikko M, et al. Gender differences in the T-cell profiles of the airways in COPD patients associated with clinical phenotypes. Int J Chron Obstruct Pulmon Dis. 2017;12:35–48.
Balgoma D, Yang M, Sjodin M, et al. Linoleic acid-derived lipid mediators increase in a female-dominated subphenotype of COPD. Eur Respir J. 2016;47(6):1645–56.
Karimi R, Tornling G, Forsslund H, et al. Differences in regional air trapping in current smokers with normal spirometry. Eur Respir J. 2017;49(1).
Sandberg A, Skold CM, Grunewald J, Eklund A, Wheelock AM. Assessing recent smoking status by measuring exhaled carbon monoxide levels. PLoS One. 2011;6(12):e28864.
Yang M, Kohler M, Heyder T, Forsslund H, Garberg HK, Grunewald J, et al. Proteomic profiling of lung immune cells reveals dysregulation of phagocytotic pathways in female-dominated molecular COPD phenotype. Respir Res. 2018;19(1). https://doi.org/10.1186/s12931-017-0699-2.
Lofdahl JM, Cederlund K, Nathell L, Eklund A, Skold CM. Bronchoalveolar lavage in COPD: fluid recovery correlates with the degree of emphysema. Eur Respir J. 2005;25(2):275–81.
Storey JD. A direct approach to false discovery rates. J Royal Stat Soc. 2002;64(3):479–98.
Bylesjö M, Rantalainen M, Cloarec O, Nicholson JK, Holmes E, Trygg J. OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification. J Chemom. 2006;20(8–10):341–51.
Wheelock AM, Wheelock CE. Trials and tribulations of ‘omics data analysis: assessing quality of SIMCA-based multivariate models using examples from pulmonary medicine. Mol BioSyst. 2013;9(11):2589–96.
Eriksson L, Trygg J, Wold S. CV-ANOVA for significance testing of PLS and OPLS® models. J Chemom. 2008;22(11–12):594–600.
Levanen B, Bhakta NR, Torregrosa Paredes P, et al. Altered microRNA profiles in bronchoalveolar lavage fluid exosomes in asthmatic patients. J Allergy Clin Immunol. 2013;131(3):894–903.
Xie C, Mao X, Huang J, et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 2011;39(Web Server issue):W316–22.
Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 2012;40(Database issue):D109–14.
Maeno T, Houghton AM, Quintero PA, Grumelli S, Owen CA, Shapiro SD. CD8+ T cells are required for inflammation and destruction in cigarette smoke-induced emphysema in mice. J Immunol. 2007;178(12):8090–6.
Freeman CM, Han MK, Martinez FJ, et al. Cytotoxic potential of lung CD8(+) T cells increases with chronic obstructive pulmonary disease severity and with in vitro stimulation by IL-18 or IL-15. J Immunol. 2010;184(11):6504–13.
Chung KF, Adcock IM. Multifaceted mechanisms in COPD: inflammation, immunity, and tissue repair and destruction. Eur Respir J. 2008;31(6):1334–56.
Gonzalez-Amaro R, Cortes JR, Sanchez-Madrid F, Martin P. Is CD69 an effective brake to control inflammatory diseases? Trends Mol Med. 2013;19(10):625–32.
Tsuyusaki J, Kuroda F, Kasuya Y, et al. Cigarette smoke-induced pulmonary inflammation is attenuated in CD69-deficient mice. J Recept Signal Transduct Res. 2011;31(6):434–9.
Fujita T, Yoshioka K, Umezawa H, et al. Role of CD69 in the pathogenesis of elastase-induced pulmonary inflammation and emphysema. Biochem Biophys Rep. 2016;7:400–7.
Haas A. The phagosome: compartment with a license to kill. Traffic. 2007;8(4):311–30.
Fairn GD, Grinstein S. How nascent phagosomes mature to become phagolysosomes. Trends Immunol. 2012;33(8):397–405.
Collins RF, Schreiber AD, Grinstein S, Trimble WS. Syntaxins 13 and 7 function at distinct steps during phagocytosis. J Immunol. 2002;169(6):3250–6.
Huynh KK, Eskelinen EL, Scott CC, Malevanets A, Saftig P, Grinstein S. LAMP proteins are required for fusion of lysosomes with phagosomes. EMBO J. 2007;26(2):313–24.
Kinchen JM, Ravichandran KS. Phagosome maturation: going through the acid test. Nat Rev Mol Cell Biol. 2008;9(10):781–95.
Hodge S, Hodge G, Ahern J, Jersmann H, Holmes M, Reynolds PN. Smoking alters alveolar macrophage recognition and phagocytic ability: implications in chronic obstructive pulmonary disease. Am J Respir Cell Mol Biol. 2007;37(6):748–55.
Kennedy DW, Abkowitz JL. Mature monocytic cells enter tissues and engraft. Proc Natl Acad Sci U S A. 1998;95(25):14944–9.
Muller WA. Mechanisms of leukocyte transendothelial migration. Annu Rev Pathol. 2011;6:323–44.
Mamdouh Z, Chen X, Pierini LM, Maxfield FR, Muller WA. Targeted recycling of PECAM from endothelial surface-connected compartments during diapedesis. Nature. 2003;421(6924):748–53.
Muller WAPECAM. Regulating the start of diapedesis. In: Ley K, editor. Adhesion Molecules: Function and Inhibition. Basel: Birkhäuser Basel; 2007. p. 201–20.
Blidberg K, Palmberg L, James A, et al. Adhesion molecules in subjects with COPD and healthy non-smokers: a cross sectional parallel group study. Respir Res. 2013;14:47.
Solovjov DA, Pluskota E, Plow EF. Distinct roles for the alpha and beta subunits in the functions of integrin alphaMbeta2. J Biol Chem. 2005;280(2):1336–45.
Kirby AC, Raynes JG, Kaye PM. CD11b regulates recruitment of alveolar macrophages but not pulmonary dendritic cells after pneumococcal challenge. J Infect Dis. 2006;193(2):205–13.
Amaral AFS, Strachan DP, Burney PGJ, Jarvis DL. Female smokers are at greater risk of airflow obstruction than male smokers. UK biobank. Am J Respir Crit Care Med. 2017;195(9):1226–35.
We would like to thank research nurses Heléne Blomqvist, Margitha Dahl, and Gunnel de Forest as well as biomedical technician Benita Engvall for excellent assistance in collection and work-up of BAL samples. We would also like to extend our appreciation to the volunteer subjects that participated in the Karolinska COSMIC study.
This study was funded by the Swedish Heart-Lung Foundation, Swedish Foundation for Strategic Research (SSF), VINNOVA (VINN-MER), EU FP6 Marie Curie, AFA Insurances, the King Oscar II Jubilee Foundation, the King Gustaf V and Queen Victoria’s Freemasons Foundation, the Swedish Research Council (VR), the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet.
Availability of data and materials
The datasets used in this study are available from the corresponding authors upon request.
Ethics approval and consent to participate
The study was approved by the Stockholm regional ethical board (Case no. 2006/959–31/1), and written informed consent was obtained from all subjects.
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Additional file 1:
Table S1. Clinical characteristics of subjects, stratified by gender. Table S2. Proteins significantly altered between Smoker vs Never-smoker groups. Table S3. Proteins significantly altered between female Smoker vs Never-smoker groups. Table S4. Proteins significantly altered between male Smoker vs Never-smoker groups. Table S5. Significantly enriched pathways and associated proteins when comparing Smoker and Never-smoker groups. Table S6. Significantly enriched pathways following stratification by gender when comparing Smoker and Never-smoker groups. (XLSX 1321 kb)
Additional file 2:
Figure S1. The OPLS-DA modeling parameters for joint gender, female and male Smoker vs. Never-smoker. Permutation test was performed 200 times for each model. Figure S2. Leukocyte transendothelial migration was significantly altered in joint smokers. ITGAM, P11215, Integrin alpha-M (CD11b); ITGB2, P05107, Integrin beta-2 (CD18); PECAM1, P16284, Platelet endothelial cell adhesion molecule; JAM-A, Q9Y624, Junctional adhesion molecule A; MLC-2, O14950, Myosin regulatory light chain 12B; CDC42, P60953, Cell division control protein 42 homolog; Actin, P60709, actin cytoplasmic 1; α-actin, P12814, O43707, α-actinin-1, α-actinin-4, respectively; NOX2, P04839, Cytochrome b-245 heavy chain; p40phox, Q15080, Neutrophil cytosol factor 4; RAC2, P15153, Ras-related C3 botulinum toxin substrate 2; RAP1A, P62834, Ras-related protein Rap-1A. (DOC 1606 kb)
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
About this article
Cite this article
Yang, M., Kohler, M., Heyder, T. et al. Long-term smoking alters abundance of over half of the proteome in bronchoalveolar lavage cell in smokers with normal spirometry, with effects on molecular pathways associated with COPD. Respir Res 19, 40 (2018). https://doi.org/10.1186/s12931-017-0695-6
- Bronchoalveolar lavage