Multi-level immune response network in mild-moderate Chronic Obstructive Pulmonary Disease (COPD)

Meta-analysis of single-cell RNA-sequencing data for depicting the transcriptomic landscape of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a respiratory disease characterized by airflow limitation and chronic inflammation of the lungs that is a leading cause of death worldwide. Since the complete pathological mechanisms at the single-cell level are not fully understood yet, an integrative approach to characterizing the single-cell-resolution landscape of COPD is required. To identify the cell types and mechanisms associated with the development of COPD, we conducted a meta-analysis using three single-cell RNA-sequencing datasets of COPD. Among the 154,011 cells from 16 COPD patients and 18 healthy subjects, 17 distinct cell types were observed. Of the 17 cell types, monocytes, mast cells, and alveolar type 2 cells (AT2 cells) were found to be etiologically implicated in COPD based on genetic and transcriptomic features. The most transcriptomically diversified states of the three etiological cell types showed significant enrichment in immune/inflammatory responses (monocytes and mast cells) and/or mitochondrial dysfunction (monocytes and AT2 cells). We then identified three chemical candidates that may potentially induce COPD by modulating gene expression patterns in the three etiological cell types. Overall, our study suggests the single-cell level mechanisms underlying the pathogenesis of COPD and may provide information on toxic compounds that could be potential risk factors for COPD.

A Macrophage-Related Gene Signature for Identifying COPD Based on Bioinformatics and ex vivo Experiments

Background

This study aims to investigate the association between immune cells and the development of COPD, while providing a new method for the diagnosis of COPD according to the changes in immune microenvironment.

Methods

In this study, the "CIBERSORT" algorithm was used to estimate the tissue infiltration of 22 types of immune cells in GSE20257 and GSE10006. The "limma" package was used for differentially expressed analysis. The key modules associated with vital immune cells were identified using WGCNA. GO and KEGG enrichment analysis revealed the biological functions of the candidate genes. Ultimately, a novel diagnostic prediction model was constructed via machine learning methods and multivariate logistic regression analysis based on GSE20257. Furthermore, we examined the stability of the model on one internal test set (GSE10006), three external test sets (GSE8545, GSE57148 and GSE76925), one single-cell transcriptome dataset (GSE167295), macrophages (THP-M cells) and lung tissue from COPD patients.

Results

M0 macrophages (AUC > 0.7 in GSE20257 and GSE10006) were considered as the most important immune cells through exploring the immune microenvironment landscapes in COPD patients and healthy controls. The differentially expressed genes from GSE20257 and GSE10006 were divided into six and five modules via WGCNA, respectively. The green module in GSE20257 (cor = 0.41, P < 0.001) and the brown module in GSE10006 (cor = 0.67, P < 0.001) were highly correlated with M0 macrophages and were selected as key modules. Forty-one intersected genes obtained from two modules were primarily involved in regulation of cytokine production, regulation of innate immune response, specific granule, phagosome, lysosome, ferroptosis, and other biological processes. On the basis of the candidate genetic markers further characterized via the "Boruta" and "LASSO" algorithm for COPD, a diagnostic model comprising CLEC5A, FTL and SLC2A3 was constructed, which could accurately distinguish COPD patients from healthy controls in multiple datasets. GSE20257 as the training set has an AUC of 0.916. The AUCs of the internal test set and three external test sets were 0.873, 0.932, 0.675 and 0.688, respectively. Single-cell sequencing analysis suggested that CLEC5A, FTL and SLC2A3 were expressed in macrophages from COPD patients. The expressions of CLEC5A, FTL and SLC2A3 were up-regulated in THP-M cells and lung tissue from COPD patients.

Conclusion

According to the variations of immune microenvironment in COPD patients, we constructed and validated a novel macrophage M0-associated diagnostic model with satisfactory predictive value. CLEC5A, FTL and SLC2A3 are expected to be promising targets of immunotherapy in COPD.

End-Stage Idiopathic Pulmonary Fibrosis Lung Microenvironment Promotes Impaired NK Activity

Idiopathic pulmonary fibrosis (IPF) is a fibrotic age-related chronic lung disease characterized by the accumulation of senescent cells. Whether impaired immune response is responsible for the accumulation of senescent cells in the IPF lung remains unknown. In this study, we characterized the NK phenotype in IPF lungs via flow cytometry using 5-dodecanoylaminofluorescein di-β-d-galactopyranoside, markers of tissue residence, and chemokine receptors. The effect of the lung microenvironment was evaluated using lung fibroblast (LF) conditioned media (CM), and the bleomycin-induced pulmonary fibrosis mouse model was used to assess the in vivo relationship between NK cells and the accumulation of senescent cells. We found that NK cells from the lower lobe of IPF patients exhibited immune-senescent and impaired CD57-NKG2A+ phenotype. We also observed that culture of NK cells from healthy donors in CM from IPF lower lobe lung fibroblasts induced a senescent-like phenotype and impaired cytotoxic capacity. There is an impaired NK recruitment by LF, and NKs presented decreased migration toward their CM. In addition, NK cell-depleted mice treated with bleomycin showed increased collagen deposition and accumulation of different populations of senescent cells compared with controls. The IPF lung microenvironment induces a dysfunctional NK phenotype limiting the clearance of lung senescent cells and the resolution of lung fibrosis. We propose that impaired NK activity could be one of the mechanisms responsible for perpetuating the accumulation of senescent cells in IPF lungs.

Lung immune signatures define two groups of end-stage IPF patients

BACKGROUND

The role of the immune system in the pathobiology of Idiopathic Pulmonary Fibrosis (IPF) is controversial.

METHODS

To investigate it, we calculated immune signatures with Gene Set Variation Analysis (GSVA) and applied them to the lung transcriptome followed by unbiased cluster analysis of GSVA immune-enrichment scores, in 109 IPF patients from the Lung Tissue Research Consortium (LTRC). Results were validated experimentally using cell-based methods (flow cytometry) in lung tissue of IPF patients from the University of Pittsburgh (n = 26). Finally, differential gene expression and hypergeometric test were used to explore non-immune differences between clusters.

RESULTS

We identified two clusters (C#1 and C#2) of IPF patients of similar size in the LTRC dataset. C#1 included 58 patients (53%) with enrichment in GSVA immune signatures, particularly cytotoxic and memory T cells signatures, whereas C#2 included 51 patients (47%) with an overall lower expression of GSVA immune signatures (results were validated by flow cytometry with similar unbiased clustering generation). Differential gene expression between clusters identified differences in cilium, epithelial and secretory cell genes, all of them showing an inverse correlation with the immune response signatures. Notably, both clusters showed distinct features despite clinical similarities.

CONCLUSIONS

In end-stage IPF lung tissue, we identified two clusters of patients with very different levels of immune signatures and gene expression but with similar clinical characteristics. Weather these immune clusters differentiate diverse disease trajectories remains unexplored.

Association of Smoking and Respiratory Disease History with Pancreatic Pathologies Requiring Surgical Resection

BACKGROUND

The purpose of this study was to examine the relationship between various respiratory conditions, including hypercapnic respiratory disease, and a multitude of resected pancreatic lesions.

METHODS

This retrospective case-control study queried a prospectively maintained database of patients who underwent pancreaticoduodenectomy between January 2015 and October 2021. Patient data, including smoking history, medical history, and pathology reports, were recorded. Patients with no smoking history and no concomitant respiratory conditions were designated as the control group.

RESULTS

A total of 723 patients with complete clinical and pathological data were identified. Male current smokers showed increased rates of PDAC (OR 2.33, 95% CI 1.07-5.08, p = 0.039). Male patients with COPD had a markedly increased association with IPMN (OR 3.02, CI 1.08-8.41, p = 0.039), while females with obstructive sleep apnea had a four-fold increase in risk of IPMN compared to women in the control group (OR 3.89, CI 1.46-10.37, p = 0.009). Surprisingly, female patients with asthma had a decreased incidence of pancreatic and periampullary adenocarcinoma (OR 0.36, 95% CI 0.18-0.71. p < 0.01).

CONCLUSION

This large cohort study reveals possible links between respiratory pathologies and various pancreatic mass-forming lesions.

Exploring the shared gene signatures of smoking-related osteoporosis and chronic obstructive pulmonary disease using machine learning algorithms

Objectives: Cigarette smoking has been recognized as a predisposing factor for both osteoporosis (OP) and chronic obstructive pulmonary disease (COPD). This study aimed to investigate the shared gene signatures affected by cigarette smoking in OP and COPD through gene expression profiling. Materials and methods: Microarray datasets (GSE11784, GSE13850, GSE10006, and GSE103174) were obtained from Gene Expression Omnibus (GEO) and analyzed for differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) regression method and a random forest (RF) machine learning algorithm were used to identify candidate biomarkers. The diagnostic value of the method was assessed using logistic regression and receiver operating characteristic (ROC) curve analysis. Finally, immune cell infiltration was analyzed to identify dysregulated immune cells in cigarette smoking-induced COPD. Results: In the smoking-related OP and COPD datasets, 2858 and 280 DEGs were identified, respectively. WGCNA revealed 982 genes strongly correlated with smoking-related OP, of which 32 overlapped with the hub genes of COPD. Gene Ontology (GO) enrichment analysis showed that the overlapping genes were enriched in the immune system category. Using LASSO regression and RF machine learning, six candidate genes were identified, and a logistic regression model was constructed, which had high diagnostic values for both the training set and external validation datasets. The area under the curves (AUCs) were 0.83 and 0.99, respectively. Immune cell infiltration analysis revealed dysregulation in several immune cells, and six immune-associated genes were identified for smoking-related OP and COPD, namely, mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1), tissue-type plasminogen activator (PLAT), sodium channel 1 subunit alpha (SCNN1A), sine oculis homeobox 3 (SIX3), sperm-associated antigen 9 (SPAG9), and vacuolar protein sorting 35 (VPS35). Conclusion: The findings suggest that immune cell infiltration profiles play a significant role in the shared pathogenesis of smoking-related OP and COPD. The results could provide valuable insights for developing novel therapeutic strategies for managing these disorders, as well as shedding light on their pathogenesis.

Cigarette smoke extract-induced inflammatory response via inhibition of the TFEB-mediated autophagy in NR8383 cells

Objective: Chronic pulmonary inflammation caused by long-term smoking is the core pathology of COPD. Alveolar macrophages (AMs) are involved in the pulmonary inflammation of COPD. The accumulation of damaged materials caused by impaired autophagy triggers inflammatory response in macrophages. As a key transcription regulator, transcription factor EB (TFEB) activates the transcription of target genes related autophagy and lysosome by binding to promoters, whereas it is unclarified for the relationship between inflammatory response induced by cigarette smoke extract (CSE) and TFEB-mediated autophagy. Thus, we investigated the role of TFEB-mediated autophagy in inflammatory response induced by CSE in NR8383 cells, and to explore its potential mechanism. Methods: Based on cell viability and autophagy, cells treated with 20% concentration of CSE for 24 h were selected for further studies. Cells were divided into control group, chloroquine (CQ, the autophagy inhibitor) group, CSE group, CSE + rapamycin (the autophagy inducer) group and CSE + fisetin (the TFEB inducer) group. The levels of tumor necrosis factor α (TNF-α), interleukin 1β (IL-1β), and IL-6 in supernatant were detected by ELISA kits. The protein expressions were tested by western blot. The intensity of fluorescence of Lysosome-associated membrane protein 1 (LAMP1) and TFEB was detected by immunofluorescence. Lyso-Tracker Red staining was applied to detect the lysosome environment. Results: CSE inhibited the cell viability, increased the contents of TNF-α, IL-1β, IL-6, the ratio of LC3II/I, and the level of P62 protein. Besides, CSE decreased the fluorescence intensity of LAMP1 protein and Lyso-Tracker Red staining, as well as the ratio of nucleus/cytosol of TFEB protein. Activating autophagy with rapamycin alleviated CSE-induced inflammatory response. The activation of TFEB via fisetin alleviated CSE-induced autophagy impairment and lysosomal dysfunction, thus alleviated inflammatory response in NR8383 cells. Conclusion: CSE-induced inflammatory response in NR8383 cells, which may be related to the inhibition of TFEB-mediated autophagy.

Recent evidence from omic analysis for redox signalling and mitochondrial oxidative stress in COPD

COPD is driven by exogenous and endogenous oxidative stress derived from inhaled cigarette smoke, air pollution and reactive oxygen species from dysregulated mitochondria in activated inflammatory cells within the airway and lung. This is compounded by the loss in antioxidant defences including FOXO and NRF2 and other antioxidant transcription factors together with various key enzymes that attenuate oxidant effects. Oxidative stress enhances inflammation; airway remodelling including fibrosis and emphysema; post-translational protein modifications leading to autoantibody generation; DNA damage and cellular senescence. Recent studies using various omics technologies in the airways, lungs and blood of COPD patients has emphasised the importance of oxidative stress, particularly that derived from dysfunctional mitochondria in COPD and its role in immunity, inflammation, mucosal barrier function and infection. Therapeutic interventions targeting oxidative stress should overcome the deleterious pathologic effects of COPD if targeted to the lung. We require novel, more efficacious antioxidant COPD treatments among which mitochondria-targeted antioxidants and Nrf2 activators are promising.

Identification of Ferroptosis-Related Hub Genes and Their Association with Immune Infiltration in Chronic Obstructive Pulmonary Disease by Bioinformatics Analysis

Purpose

Ferroptosis and immune infiltration are involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). We aim to identify ferroptosis-related hub genes and analyze their association with immune infiltration in COPD through bioinformatics methods.

Materials and Methods

The mRNA microarray data of GSE38974 were downloaded from Gene Expression Omnibus to obtain differentially expressed genes (DEGs). The DEGs were intersected with ferroptosis-related genes (FRGs) from FerrDb to obtain differentially expressed FRGs. GO and KEGG enrichment and protein–protein interaction (PPI) analyses of differentially expressed FRGs were conducted in R software and STRING database. The key module and hub genes were screened by Cytoscape software. MiRNAs, transcription factors and signal molecules were predicted in miRNet and NetworkAnalyst. The disease correlation in the Comparative Toxicomics Database (CTD) and the receiver operating characteristic (ROC) curves of hub genes were analyzed. Immune infiltration was evaluated by CIBERSORT algorithm. Spearman correlation analyses were conducted between hub genes and differentially infiltrated immune cells.

Results

Fifteen differentially expressed FRGs were identified, which were enriched in some terms involving airway inflammatory responses and structural remodeling. Five hub genes were selected including HIF1A, IL6, PTGS2, CDKN1A and ATM. Inference scores in CTD indicated their association with COPD. Two miRNAs, five transcription factors and one signal molecule were predicted. The combination of hub genes could be a fine diagnostic indicator of COPD (AUC: 0.981, CI: 0.940-1.000). Immune infiltration evaluation showed that monocytes and M0 macrophages were upregulated in COPD lung tissues, while CD8 T cells, activated NK cells, M2 macrophages, resting dendritic cells and resting mast cells were downregulated. The hub genes were significantly associated with differentially infiltrated immune cells.

Conclusion

We identified five ferroptosis-related hub genes (HIF1A, IL6, PTGS2, CDKN1A and ATM) in COPD, and found that they may influence the pathogenesis of COPD by regulating ferroptosis and thus affecting infiltrating immune cells.

Pathogenesis of chronic obstructive pulmonary disease: understanding the contributions of gene-environment interactions across the lifespan

The traditional view of chronic obstructive pulmonary disease (COPD) as a self-inflicted disease caused by tobacco smoking in genetically susceptible individuals has been challenged by recent research findings. COPD can instead be understood as the potential end result of the accumulation of gene-environment interactions encountered by an individual over the life course. Integration of a time axis in pathogenic models of COPD is necessary because the biological responses to and clinical consequences of different exposures might vary according to both the age of an individual at which a given gene-environment interaction occurs and the cumulative history of previous gene-environment interactions. Future research should aim to understand the effects of dynamic interactions between genes (G) and the environment (E) by integrating information from basic omics (eg, genomics, epigenomics, proteomics) and clinical omics (eg, phenomics, physiomics, radiomics) with exposures (the exposome) over time (T)-an approach that we refer to as GETomics. In the context of this approach, we argue that COPD should be viewed not as a single disease, but as a clinical syndrome characterised by a recognisable pattern of chronic symptoms and structural or functional impairments due to gene-environment interactions across the lifespan that influence normal lung development and ageing.

Machine-Learning Algorithm-Based Prediction of Diagnostic Gene Biomarkers Related to Immune Infiltration in Patients With Chronic Obstructive Pulmonary Disease

Objective

This study aims to identify clinically relevant diagnostic biomarkers in chronic obstructive pulmonary disease (COPD) while exploring how immune cell infiltration contributes towards COPD pathogenesis.

Methods

The GEO database provided two human COPD gene expression datasets (GSE38974 and GSE76925; n=134) along with the relevant controls (n=49) for differentially expressed gene (DEG) analyses. Candidate biomarkers were identified using the support vector machine recursive feature elimination (SVM-RFE) analysis and the LASSO regression model. The discriminatory ability was determined using the area under the receiver operating characteristic curve (AUC) values. These candidate biomarkers were characterized in the GSE106986 dataset (14 COPD patients and 5 controls) in terms of their respective diagnostic values and expression levels. The CIBERSORT program was used to estimate patterns of tissue infiltration of 22 types of immune cells. Furthermore, the in vivo and in vitro model of COPD was established using cigarette smoke extract (CSE) to validated the bioinformatics results.

Results

80 genes were identified via DEG analysis that were primarily involved in cellular amino acid and metabolic processes, regulation of telomerase activity and phagocytosis, antigen processing and MHC class I-mediated peptide antigen presentation, and other biological processes. LASSO and SVM-RFE were used to further characterize the candidate diagnostic markers for COPD, SLC27A3, and STAU1. SLC27A3 and STAU1 were found to be diagnostic markers of COPD in the metadata cohort (AUC=0.734, AUC=0.745). Their relevance in COPD were validated in the GSE106986 dataset (AUC=0.900 AUC=0.971). Subsequent analysis of immune cell infiltration discovered an association between SLC27A3 and STAU1 with resting NK cells, plasma cells, eosinophils, activated mast cells, memory B cells, CD8+, CD4+, and helper follicular T-cells. The expressions of SLC27A3 and STAU1 were upregulated in COPD models both in vivo and in vitro. Immune infiltration activation was observed in COPD models, accompanied by the enhanced expression of SLC27A3 and STAU1. Whereas, the knockdown of SLC27A3 or STAU1 attenuated the effect of CSE on BEAS-2B cells.

Conclusion

STUA1 and SLC27A3 are valuable diagnostic biomarkers of COPD. COPD pathogenesis is heavily influenced by patterns of immune cell infiltration. This study provides a molecular biology insight into COPD occurrence and in exploring new therapeutic means useful in COPD.

Identification of Dysregulated Mechanisms and Candidate Gene Markers in Chronic Obstructive Pulmonary Disease

Purpose

This study aimed to identify candidate gene markers that may facilitate chronic obstructive pulmonary disease (COPD) diagnosis and treatment.

Methods

The GSE47460 and GSE151052 datasets were analyzed to identify differentially expressed mRNAs (DEmRs) between COPD patients and controls. DEmRs that were differentially expressed in the same direction in both datasets were analyzed for functional enrichment and for coexpression. Genes from the largest three modules were tested for their ability to diagnose COPD based on the area under the receiver operating characteristic curve (AUC). Genes with AUC > 0.7 in both datasets were used to perform regression based on the "least absolute shrinkage and selection operator" in order to identify feature genes. We also identified differentially expressed miRNAs (DEmiRs) between COPD patients and controls using the GSE38974 dataset, then constructed a regulatory network. We also examined associations between feature genes and immune cell infiltration in COPD, and we identified methylation markers of COPD using the GSE63704 dataset.

Results

A total of 1350 genes differentially regulated in the same direction in the GSE47460 and GSE151052 datasets were found. The genes were significantly enriched in immune-related biological functions. Of 186 modules identified using MEGENA, the largest were C1_ 6, C1_ 3, and C1_ 2. Of the 22 candidate genes screened based on AUC, 11 feature genes emerged from analysis of a subset of GSE47460 data, which we validated using another subset of GSE47460 data as well as the independent GSE151052 dataset. Feature genes correlated significantly with infiltration by immune cells. The feature genes GPC4 and RS1 were predicted to be regulated by miR-374a-3p. We identified 117 candidate methylation markers of COPD, including PRRG4.

Conclusion

The feature genes we identified may be potential diagnostic markers and therapeutic targets in COPD. These findings provide new leads for exploring disease mechanisms and targeted treatments.

Impact of Smoking on COVID-19 Symptoms in Non-Vaccinated Patients: A Matched Observational Study from Qatar

Purpose

Predisposition to acute illness from COVID-19 is suggested to correlate with cigarette smoking as it augments the risk of developing cardiovascular and respiratory illnesses, including infections. However, the effects of smoking on COVID-19 symptoms are not well described and controversial. In this study, we aim to explore the associations between smoking and COVID-19 symptoms.

Subjects and Methods

A cross-sectional study using the Ministry of Public Health (MoPH), Qatar database was administered to a Qatari population with confirmed COVID-19 disease who filled in pre-defined phone-call questionnaire between 27th February 2020 and 31st December 2020. We analyzed 11,701 non-vaccinated COVID-19 individuals (2952 smokers and 8749 non-smokers) with confirmed RT-PCR test results. The association of smoking and the presence of symptoms as well as patient characteristics was calculated using Pearson’s Chi-square and Fisher’s exact tests, adjusting for potential covariates.

Results

Compared with the non-smokers, symptomatic COVID-19 infection is significantly higher in smokers. In addition, we found fever as the most common symptom developed in COVID-19 patients followed by cough, headache, muscle ache, and sore throat. As compared to other symptoms, association of smoking with chills and abdominal pain was less evident (P < 0.05 and P < 0.001, respectively). However, both groups showed similar rates of developing cough.

Conclusion

In conclusion, smoking is associated with COVID-19 symptoms frequency in non-vaccinated patients; nevertheless, further investigations are necessary to understand the mechanism of this association which could generate new targets for the management of COVID-19 in smoker patients.

Pathogenesis, clinical features of asthma COPD overlap (ACO), and therapeutic modalities

Both asthma and COPD are heterogeneous diseases identified by characteristic symptoms and functional abnormalities, with airway obstruction common in both diseases. Asthma COPD overlap (ACO) does not define a single disease but is a descriptive term for clinical use that includes several overlapping clinical phenotypes of chronic airways disease with different underlying mechanisms. This literature review was initiated to describe published studies, identify gaps in knowledge, and propose future research goals regarding the disease pathology of ACO, especially the airway remodelling changes and inflammation aspects. Airway remodelling occurs in asthma and COPD, but there are differences in the structures affected and the prime anatomic site at which they occur. Reticular basement membrane thickening and cellular infiltration with eosinophils and T-helper (CD4+) lymphocytes are prominent features of asthma. Epithelial squamous metaplasia, airway wall fibrosis, emphysema, bronchoalveolar lavage (BAL) neutrophilia and (CD8+) T-cytotoxic lymphocyte infiltrations in the airway wall are features of COPD. There is no universally accepted definition of ACO, nor are there clearly defined pathological characteristics to differentiate from asthma and COPD. Understanding etiological concepts within the purview of inflammation and airway remodelling changes in ACO would allow better management of these patients.

Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.

Dysbalance of ACE2 levels - a possible cause for severe COVID-19 outcome in COPD

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious threat to healthcare systems worldwide. Binding of the virus to angiotensin-converting enzyme 2 (ACE2) is an important step in the infection mechanism. However, it is unknown if ACE2 expression in patients with chronic lung diseases (CLDs), such as chronic obstructive pulmonary disease (COPD), idiopathic pulmonary arterial hypertension (IPAH), or pulmonary fibrosis (PF), is changed as compared to controls. We used lung samples from patients with COPD (n = 28), IPAH (n = 10), and PF (n = 10) as well as healthy control donor (n = 10) tissue samples to investigate the expression of ACE2 and related cofactors that might influence the course of SARS-CoV-2 infection. Expression levels of the ACE2 receptor, the putative receptor CD147/BSG, and the viral entry cofactors TMPRSS2 (transmembrane serine protease 2), EZR, and FURIN were determined by quantitative PCR and in open-access RNA sequencing datasets. Immunohistochemical and single-cell RNA sequencing (scRNAseq) analyses were used for localization and coexpression, respectively. Soluble ACE2 (sACE2) plasma levels were analyzed by enzyme-linked immunosorbent assay. In COPD as compared to donor, IPAH, and PF lung tissue, gene expression of ACE2, TMPRSS2, and EZR was significantly elevated, but circulating sACE2 levels were significantly reduced in COPD and PF plasma compared to healthy control and IPAH plasma samples. Lung tissue expressions of FURIN and CD147/BSG were downregulated in COPD. None of these changes were associated with changes in pulmonary hemodynamics. Histological analysis revealed coexpression of ACE2, TMPRSS2, and Ezrin in bronchial regions and epithelial cells. This was confirmed by scRNAseq analysis. There were no significant expression changes of the analyzed molecules in the lung tissue of IPAH and idiopathic PF as compared to control. In conclusion, we reveal increased ACE2 and TMPRSS2 expression in lung tissue with a concomitant decrease of protective sACE2 in COPD patients. These changes represent the possible risk factors for an increased susceptibility of COPD patients to SARS-CoV-2 infection.

Alteration of immune profiles is associated with pulmonary function and symptoms in patients with chronic obstructive pulmonary disease

Inflammation serves a key role in chronic obstructive pulmonary disease (COPD). However, changes in the immune profiles of patients with COPD remain unclear. The present prospective observational study aimed to determine the expression profiles of immune cells and inflammatory factors of patients with COPD and healthy controls, and to analyze the relationship between immune profiles and smoking history. A total of 140 subjects were enrolled in the present study between September 2018 and April 2019 at West China Hospital of Sichuan University (Chengdu, China). These included 87 patients with stable COPD and 24 patients with acute exacerbated COPD, as well as 29 healthy controls. Baseline characteristics were recorded during the screening period, and levels of immune cells were examined using flow cytometry. In addition, levels of inflammatory factors were measured using ELISAs. The results revealed increased expression of the CD64⁺/CD14⁺ mononuclear phagocyte system (MPS) and CD16⁺CD66⁺ neutrophils, and decreased expression of CD3⁺CD4⁺ T cells and CD3⁺ CD8⁺ T cells (all P<0.05) in the peripheral blood of patients with COPD and smokers relative to non-smoking controls. In addition, significant differences were observed in protein levels of IL-6, IL-1β, TNF-α, TGF-α, IFN-γ, IL-8, IL-17A and CRP among the three groups (all P<0.05). Furthermore, the IL-17A, TNF and NF-κB signaling pathways were found to serve a key role in the inflammatory network of COPD. Pearson's correlation analysis revealed a positive correlation between CD3⁺T lymphocyte counts and pulmonary function, and a negative correlation with smoking and exacerbations. Furthermore, neutrophils and MPS were negatively associated with pulmonary function, and IL-8 was positively associated with cough. There was also a negative association between CRP and IL-17A with pulmonary function but a positive correlation with symptoms and exacerbation. Club cell secretory protein was also negatively associated with emphysema parameters. In conclusion, the present findings revealed significant differences in profiles of immune factors among patients with COPD, smokers and non-smoking controls and their association with clinical characteristics. The clinical trial registration number of the present study is: ChiCTR1800015700 (registered with http://www.chictr.org.cn/index.aspx, 2018/04/16).

Exposure to biomass smoke induces pulmonary Th17 cell differentiation by activating TLR2 on dendritic cells in a COPD rat model

Almost three billion people in developing countries are exposed to biomass smoke (BS), which predisposes them to developing chronic obstructive pulmonary disease (COPD). COPD is associated with abnormal innate and adaptive immune responses in the lungs and systemic circulation, but the mechanisms underlying BS-COPD development are uncertain. We investigated the role of dendritic cells (DCs) and interleukin (IL)-17A in BS-COPD. We investigated T helper cell responses in the BS-exposed COPD rat model by flow cytometry, quantitative PCR, and enzyme-linked immunosorbent assays. We conducted ex vivo experiments to determine which antigen-presenting cells induce Th17 cell responses. We evaluated the in vitro effects of BS-related particulate matter (BRPM) (2.5 μm) on the function of bone marrow-derived dendritic cells (BMDCs). We found that BS exposure enhanced Th17 responses in the lungs of the COPD-modelled rats, and the stimulated DCs (but not the macrophages) were sufficient to induce naïve CD4 + T cells to produce IL-17A in ex vivo experiments. BRPM significantly enhanced the maturation and activation of DCs through Toll-like receptor 2 (TLR2), but not TLR4, and induced Th17 responses. Therefore, BS activated lung DCs through TLR2, which led to Th17 responses and emphysema in the rats. This process is possibly therapeutically targetable.

Chronic bronchial infection and incident cardiovascular events in chronic obstructive pulmonary disease patients: A long-term observational study

BACKGROUND AND OBJECTIVE

Cardiovascular (CV) diseases are frequent in patients with chronic obstructive pulmonary disease (COPD). Likewise, chronic bronchial infection (CBI) is also frequent in COPD and it is associated with systemic inflammation, a well-known CV risk factor. The objective of this study was to investigate the relationship between CBI, systemic inflammation and incident CV events.

METHODS

A post hoc analysis of prospectively collected cohort of 201 COPD patients [Global Initiative for Chronic Obstructive Lung Disease (GOLD) II-IV] followed up every 3-6 months for 84 months was conducted. CBI was defined as ≥3 positive pathogenic microorganisms sputum cultures over 1 year, separated by ≥3 months. Systemic inflammation was assessed by circulating levels of C-reactive protein and fibrinogen. Fatal and non-fatal CV events, including coronary and cerebrovascular events as well as arrhythmia episodes, were prospectively recorded. For analysis, they were analysed separately and combined in a composite variable.

RESULTS

As hypothesized, CBI was associated with persistent systemic inflammation and a significantly higher incidence of CV events (HR: 3.88; 95% CI: 1.83-8.22), mainly of coronary origin independent of age, number and severity of exacerbations, comorbidities, other CV risk factors, lung function, BMI, smoking status and treatments. These associations were particularly significant in patients with CBI by Pseudomonas aeruginosa (PA).

CONCLUSION

CBI, particularly by PA, is associated with sustained and enhanced systemic inflammation and a higher incidence of CV events (especially coronary events). The possibility that treating CBI may decrease systemic inflammation and CV events in COPD deserves prospective, interventional studies.

Risk Factors and Relation with Mortality of a New Acquisition and Persistence of Pseudomonas aeruginosa in COPD Patients

The isolation of Pseudomonas aeruginosa (PA) in patients with chronic obstructive pulmonary disease (COPD) is associated with increased mortality. Yet, factors associated with first PA sputum isolation, and PA persistence have not been investigated before. The objective of the present study was to investigate risk factors for new acquisition and persistence of PA infection and their relationship with all-cause mortality in patients with COPD. Post-hoc analysis of prospectively collected cohort of 170 COPD patients (GOLD II-IV) who were free of previous PA isolation and followed up every 3-6 months for 85 [50.25-110.25] months. PA was isolated for the first time in 41 patients (24.1%) after 36 [12-60] months of follow-up. Risk factor for first PA isolation were high cumulative smoking exposure, severe airflow limitation, previous severe exacerbations, high fibrinogen levels and previous isolation of Haemophilus Influenzae. PA was isolated again one or more times during follow-up in 58.5% of these patients. This was significantly associated with the presence of CT bronchiectasis and persistence of severe exacerbations, whereas the use of inhaled antibiotic treatment after the first PA isolation (at the discretion of the attending physician) reduced PA persistence. During follow-up, 79 patients (46.4%) died. A single PA isolation did not increase mortality, but PA persistence did (HR 3.06 [1.8-5.2], p = 0.001). We conclude that PA occurs frequently in clinically stable COPD patients, risk factors for a first PA isolation and PA persistence are different, and the latter (but not the former) is associated with increased all-cause mortality.

SARS-CoV-2 infection and smoking: What is the association? A brief review

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The link between smoking and the expression of SARS-CoV-2 key entry genes is discussed.

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Smoking-related cardiac and respiratory diseases are risk factors for COVID-19.

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The impact of smoking on ACE-2 and TMPRSS2 receptors expression is controversial.

Susceptibility to severe illness from COVID-19 is anticipated to be associated with cigarette smoking as it aggravates the risk of cardiovascular and respiratory illness, including infections. This is particularly important with the advent of a new strain of coronaviruses, the severe acute respiratory syndrome coronavirus (SARS-CoV-2) that has led to the present pandemic, coronavirus disease 2019 (COVID-19). Although, the effects of smoking on COVID-19 are less described and controversial, we presume a link between smoking and COVID-19. Smoking has been shown to enhance the expression of the angiotensin-converting enzyme-2 (ACE-2) and transmembrane serine protease 2 (TMPRSS2) key entry genes utilized by SARS-CoV-2 to infect cells and induce a ‘cytokine storm’, which further increases the severity of COVID-19 clinical course. Nevertheless, the impact of smoking on ACE-2 and TMPRSS2 receptors expression remains paradoxical. Thus, further research is necessary to unravel the association between smoking and COVID-19 and to pursue the development of potential novel therapies that are able to constrain the morbidity and mortality provoked by this infectious disease. Herein we present a brief overview of the current knowledge on the correlation between smoking and the expression of SARS-CoV-2 key entry genes, clinical manifestations, and disease progression.

Progress and challenge for computational quantification of tissue immune cells

Tissue immune cells have long been recognized as important regulators for the maintenance of balance in the body system. Quantification of the abundance of different immune cells will provide enhanced understanding of the correlation between immune cells and normal or abnormal situations. Currently, computational methods to predict tissue immune cell compositions from bulk transcriptomes have been largely developed. Therefore, summarizing the advantages and disadvantages is appropriate. In addition, an examination of the challenges and possible solutions for these computational models will assist the development of this field. The common hypothesis of these models is that the expression of signature genes for immune cell types might represent the proportion of immune cells that contribute to the tissue transcriptome. In general, we grouped all reported tools into three groups, including reference-free, reference-based scoring and reference-based deconvolution methods. In this review, a summary of all the currently reported computational immune cell quantification tools and their applications, limitations, and perspectives are presented. Furthermore, some critical problems are found that have limited the performance and application of these models, including inadequate immune cell type, the collinearity problem, the impact of the tissue environment on the immune cell expression level, and the deficiency of standard datasets for model validation. To address these issues, tissue specific training datasets that include all known immune cells, a hierarchical computational framework, and benchmark datasets including both tissue expression profiles and the abundances of all the immune cells are proposed to further promote the development of this field.

Precision Prevention and Cancer Interception: The New Challenges of Liquid Biopsy

Despite major therapeutic progress, most advanced solid tumors are still incurable. Cancer interception is the active way to combat cancer onset, and development of this approach within high-risk populations seems a logical first step. Until now, strategies for the identification of high-risk subjects have been based on low-sensitivity and low-specificity assays. However, new liquid biopsy assays, "the Rosetta Stone of the new biomedicine era," with the ability to identify circulating biomarkers with unprecedented sensitivity, promise to revolutionize cancer management. This review focuses on novel liquid biopsy approaches and the applications to cancer interception. Cancer interception involves the identification of biomarkers associated with developing cancer, and includes genetic and epigenetic alterations, as well as circulating tumor cells and circulating epithelial cells in individuals at risk, and the implementation of therapeutic strategies to prevent the beginning of cancer and to stop its development. Large prospective studies are needed to confirm the potential role of liquid biopsy for early detection of precancer lesions and tumors.

Sonic hedgehog signalling as a potential endobronchial biomarker in COPD

BACKGROUND

The hedgehog (HH) pathway has been associated with chronic obstructive pulmonary disease (COPD) in genome-wide association studies and recent studies suggest that HH signalling could be altered in COPD. We therefore used minimally invasive endobronchial procedures to assess activation of the HH pathway including the main transcription factor, Gli2, and the ligand, Sonic HH (Shh).

METHODS

Thirty non-COPD patients and 28 COPD patients were included. Bronchial brushings, bronchoalveolar lavage fluid (BALF) and bronchial biopsies were obtained from fiberoptic bronchoscopy. Characterization of cell populations and subcellular localization were evaluated by immunostaining. ELISA and RNAseq analysis were performed to identify Shh proteins in BAL and transcripts on lung tissues from non-COPD and COPD patients with validation in an external and independent cohort.

RESULTS

Compared to non-COPD patients, COPD patients exhibited a larger proportion of basal cells in bronchial brushings (26 ± 11% vs 13 ± 6%; p < 0.0001). Airway basal cells of COPD subjects presented less intense nuclear staining for Gli2 in bronchial brushings and biopsies (p < 0.05). Bronchial BALF from COPD patients contained lower Shh concentrations than non-COPD BALF (12.5 vs 40.9 pg/mL; p = 0.002); SHH transcripts were also reduced in COPD lungs in the validation cohort (p = 0.0001).

CONCLUSION

This study demonstrates the feasibility of assessing HH pathway activation in respiratory samples collected by bronchoscopy and identifies impaired bronchial epithelial HH signalling in COPD.

Cigarette Smoke Exposure and Inflammatory Signaling Increase the Expression of the SARS-CoV-2 Receptor ACE2 in the Respiratory Tract

The factors mediating fatal SARS-CoV-2 infections are poorly understood. Here, we show that cigarette smoke causes a dose-dependent upregulation of angiotensin converting enzyme 2 (ACE2), the SARS-CoV-2 receptor, in rodent and human lungs. Using single-cell sequencing data, we demonstrate that ACE2 is expressed in a subset of secretory cells in the respiratory tract. Chronic smoke exposure triggers the expansion of this cell population and a concomitant increase in ACE2 expression. In contrast, quitting smoking decreases the abundance of these secretory cells and reduces ACE2 levels. Finally, we demonstrate that ACE2 expression is responsive to inflammatory signaling and can be upregulated by viral infections or interferon treatment. Taken together, these results may partially explain why smokers are particularly susceptible to severe SARS-CoV-2 infections. Furthermore, our work identifies ACE2 as an interferon-stimulated gene in lung cells, suggesting that SARS-CoV-2 infections could create positive feedback loops that increase ACE2 levels and facilitate viral dissemination.

COVID-19, an opportunity to reevaluate the correlation between long-term effects of anthropogenic pollutants on viral epidemic/pandemic events and prevalence

Occupational, residential, dietary and environmental exposures to mixtures of synthetic anthropogenic chemicals after World War II have a strong relationship with the increase of chronic diseases, health cost and environmental pollution. The link between environment and immunity is particularly intriguing as it is known that chemicals and drugs can cause immunotoxicity (e.g., allergies and autoimmune diseases). In this review, we emphasize the relationship between long-term exposure to xenobiotic mixtures and immune deficiency inherent to chronic diseases and epidemics/pandemics. We also address the immunotoxicologic risk of vulnerable groups, taking into account biochemical and biophysical properties of SARS-CoV-2 and its immunopathological implications. We particularly underline the common mechanisms by which xenobiotics and SARS-CoV-2 act at the cellular and molecular level. We discuss how long-term exposure to thousand chemicals in mixtures, mostly fossil fuel derivatives, exposure toparticle matters, metals, ultraviolet (UV)–B radiation, ionizing radiation and lifestyle contribute to immunodeficiency observed in the contemporary pandemic, such as COVID-19, and thus threaten global public health, human prosperity and achievements, and global economy. Finally, we propose metrics which are needed to address the diverse health effects of anthropogenic COVID-19 crisis at present and those required to prevent similar future pandemics.

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Developmental exposure to environmental factors can disrupt the immune system.

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Long-term low-dose exposure to chemical mixtures is linked to imunodeficiency

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Immunodeficiency contributes to chronic diseases and the current Covid-19 pandemics.

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Environmental chemicals and microorganisms share similar molecular pathomechanisms (AhR pathway).

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Understanding the underlying pathomechanisms helps to improve public health.

The variances in cytokine production profiles from non- or activated THP-1, Kupffer cell and human blood derived primary macrophages following exposure to either alcohol or a panel of engineered nanomaterials

The portfolio of cytokines is key to the function of macrophages as sentries of the innate immune system as well as being critical for the transition from innate to adaptive immunity. Cytokine bias is critical in the fate of macrophages into a continuum of inflammatory to anti-inflammatory macrophages. Due to advances in the field of toxicology, increasingly advanced multi-cellular in vitro safety assessment models are being developed in order to allow for a better predication of potential adverse effects in humans with many of these models include a macrophage population. The selection of the correct macrophage cells in these advanced in vitro models is critical for a physiologically relevant and realistic immune response. In this study we investigated cytokine response profile (IL1-β, IL6, IL10 and TNF-α) of activated and non-activated THP-1 (immortalized monocyte-like cell line), primary human Kupffer cells (liver resident macrophages) and human primary peripheral blood mononuclear cells following exposure of a panel of nanomaterials or ethanol. The data demonstrated that the THP-1 cell line are not great cytokine producers. The PBMC appear to be a good in vitro surrogate for circulating/pro-inflammatory macrophages but are not a suitable replacement for Kupffer cells. The findings from this study highlight the necessity for the selection of appropriate macrophages populations to meet the specific physiological requirements of in vitro experiment.