Consensus clustering with missing labels (ccml): a consensus clustering tool for multi-omics integrative prediction in cohorts with unequal sample coverage.

Multi-omics data integration is a complex and challenging task in biomedical research. Consensus clustering, also known as meta-clustering or cluster ensembles, has become an increasingly popular downstream tool for phenotyping and endotyping using multiple omics and clinical data. However, current consensus clustering methods typically rely on ensembling clustering outputs with similar sample coverages (mathematical replicates), which may not reflect real-world data with varying sample coverages (biological replicates). To address this issue, we propose a new consensus clustering with missing labels (ccml) strategy termed ccml, an R protocol for two-step consensus clustering that can handle unequal missing labels (i.e. multiple predictive labels with different sample coverages). Initially, the regular consensus weights are adjusted (normalized) by sample coverage, then a regular consensus clustering is performed to predict the optimal final cluster. We applied the ccml method to predict molecularly distinct groups based on 9-omics integration in the Karolinska COSMIC cohort, which investigates chronic obstructive pulmonary disease, and 24-omics handprint integrative subgrouping of adult asthma patients of the U-BIOPRED cohort. We propose ccml as a downstream toolkit for multi-omics integration analysis algorithms such as Similarity Network Fusion and robust clustering of clinical data to overcome the limitations posed by missing data, which is inevitable in human cohorts consisting of multiple data modalities. The ccml tool is available in the R language (https://CRAN.R-project.org/package=ccml, https://github.com/pulmonomics-lab/ccml, or https://github.com/ZhoulabCPH/ccml).

Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.

RATIONALE: Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker-signature to predict sputum eosinophilia in asthma. METHODS: VOCs emitted into the space above sputum samples (headspace) from severe asthmatics (n=36) were collected onto sorbent tubes and analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ≥3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: (I) acute asthmatics according to blood eosinophilia ≥0.3x109cells/L or sputum eosinophilia of ≥ 3% in the UK EMBER consortium (n=65) and U-BIOPRED-IMI consortium (n=42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analysed by gas-chromatography-mass spectrometry (GC×GC-MS -EMBER or GC-MS -U-BIOPRED). MAIN RESULTS: The in vitro headspace identified 19 VOCs associated with sputum eosinophilia and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ≥ 3% in headspace (AUROC (95% CI) 0.90(0.80-0.99), p<0.0001), correlated inversely with sputum eosinophil % (rs= -0.71, p<0.0001) and outperformed FeNO (AUROC (95% CI) 0.61(0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89(0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90(0.75-1.0) in U-BIOPRED - again outperforming FeNO in U-BIOPRED 0.62 (0.33-0.90). CONCLUSIONS: We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point of care clinical sensors.

Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study.

RATIONALE: Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. OBJECTIVES: To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. METHODS: This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. MEASUREMENTS AND MAIN RESULTS: Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. CONCLUSIONS: Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

Extracellular Matrix as a Driver of Chronic Lung Diseases.

The extracellular matrix (ECM) is not just a three-dimensional scaffold that provides stable support for all cells in the lungs, but also an important component of chronic fibrotic airway, vascular, and interstitial diseases. It is a bioactive entity that is dynamically modulated during tissue homeostasis and disease, that controls structural and immune cell functions and drug responses, and that can release fragments that have biological activity and that can be used to monitor disease activity. There is a growing recognition of the importance of considering ECM changes in chronic airway, vascular, and interstitial diseases, including 1) compositional changes, 2) structural and organizational changes, and 3) mechanical changes and how these affect disease pathogenesis. As altered ECM biology is an important component of many lung diseases, disease models must incorporate this factor to fully recapitulate disease-driver pathways and to study potential novel therapeutic interventions. Although novel models are evolving that capture some or all of the elements of the altered ECM microenvironment in lung diseases, opportunities exist to more fully understand cell-ECM interactions that will help devise future therapeutic targets to restore function in chronic lung diseases. In this perspective article, we review evolving knowledge about the ECM's role in homeostasis and disease in the lung.

Effects of toll-like receptor agonists and SARS-CoV-2 antigens on interferon (IFN) expression by peripheral blood CD3+ T cells from COVID-19 patients.

BACKGROUND: Signaling by toll-like receptors (TLRs) initiates important immune responses against viral infection. The role of TLRs in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is not well elucidated. Thus, we investigated the interaction of TLRs agonists and SARS-COV-2 antigens with immune cells in vitro. MATERIAL & METHODS: 30 coronavirus disease 2019 (COVID-19) patients (15 severe and 15 moderate) and 10 age and sex-matched healthy control (HC) were enrolled. Peripheral blood mononuclear cells (PBMCs) were isolated and activated with TLR3, 7, 8, and 9 agonists, the spike protein (SP) of SARS-CoV-2, and the receptor binding domain (RBD) of SP. Frequencies of CD3+IFN-ß+ T cells, and CD3+IFN-γ+ T cells were evaluated by flow cytometry. Interferon (IFN)-ß gene expression was assessed by qRT-PCR. RESULTS: The frequency of CD3+IFN-ß+ T cells was higher in PBMCs from moderate (p < 0.0001) and severe (p = 0.009) patients at baseline in comparison with HCs. The highest increase in the frequency of CD3+IFN-ß+ T cells in cell from moderate patients was induced by TLR8 agonist and SP (p < 0.0001 for both) when compared to HC, while, the highest increase of the frequency of CD3+IFN-ß+ T cells in sample of severe patients was seen with TLR8 and TLR7 agonists (both p = 0.002). The frequency of CD3+IFN-γ+ T cells was significantly increased upon stimulation with TLR agonists in cell from patients with moderate and severe COVID-19, compared with HC (all p < 0.01), except with TLR7 and TLR8 agonists. The TLR8 agonist did not significantly increase the frequency of CD3+IFN-γ+ T cells in PBMCs of severe patients, but did so in cells from patients with moderate disease (p = 0.01). Moreover, IFN-ß gene expression was significantly upregulated in CD3+T cells from moderate (p < 0.0001) and severe (p = 0.002) COVID-19 patients, compared to HC after stimulation with the TLR8 agonist, while, stimulation of T cells with SP, significantly up-regulated IFN-ß mRNA expression in cells from patients with moderate (p = 0.0003), but not severe disease. CONCLUSION: Stimulation of PBMCs from COVID-19 patients, especially patients with moderate disease, with TLR8 agonist and SP increased the frequency of IFN-ß-producing T cells and IFN-ß gene expression.

Prospective direct comparison of biologic treatments for severe eosinophilic asthma: Findings from the PRISM study.

BACKGROUND: Although various monoclonal antibodies have been used as add-on therapy for severe eosinophilic asthma (SEA), to the best of our knowledge, no direct head-to-head comparative study has evaluated their efficacy. OBJECTIVE: To compare the efficacy of reslizumab, mepolizumab, and dupilumab in patients with SEA. METHODS: This was a multicenter, prospective observational study in patients with SEA who had received 1 of these biologic agents for at least 6 months. Cox proportional hazard models were used to compare the risk of the first exacerbation event, adjusting for sputum or blood eosinophils and common asthma-related covariates. The annual exacerbation rate was analyzed using a negative binomial model, and a mixed-effect model was used to analyze changes in forced expiratory volume in 1 second and asthma control test score over time. RESULTS: A total of 141 patients with SEA were included in the analysis; 71 (50%) received dupilumab; 40 (28%) received reslizumab, and 30 (21%) received mepolizumab. During the 12-month follow-up, 27.5%, 43.3%, and 38.0% of patients in the reslizumab, mepolizumab, and dupilumab groups, respectively, experienced at least 1 exacerbation. However, after adjusting for confounding factors, the dupilumab and mepolizumab groups showed similar outcomes in time-to-first exacerbation, exacerbation rate, forced expiratory volume in 1 second, and asthma control test score to those of the reslizumab group. CONCLUSION: In patients with SEA, treatment with reslizumab, mepolizumab, and dupilumab resulted in comparable clinical outcomes within a 12-month period. TRIAL REGISTRATION: The cohort protocol was sanctioned by the Institutional Review Board of each study center (clinicaltrial.gov identifier NCT05164939).

Predictors of Early and Late Lung Function Improvement in Severe Eosinophilic Asthma on Type2-Biologics in the PRISM Study.

BACKGROUND: The determinants linked to the short- and long-term improvement in lung function in patients with severe eosinophilic asthma (SEA) on biological treatment (BioT) remain elusive. OBJECTIVE: We sought to identify the predictors of early and late lung function improvement in patients with SEA after BioT. METHODS: 140 adult patients with SEA who received mepolizumab, dupilumab, or reslizumab were followed up for 6 months to evaluate improvement in forced expiratory volume in one second (FEV1). Logistic regression was used to determine the association between potential prognostic factors and improved lung function at 1 and 6 months of treatment. RESULTS: More than a third of patients with SEA using BioT showed early and sustained improvements in FEV1 after 1 month. A significant association was found between low baseline FEV1 and high blood eosinophil count and sustained FEV1 improvement after 1 month (0.54 [0.37-0.79] and 1.88 [1.28-2.97] odds ratios and 95% confidence interval, respectively). Meanwhile, among patients who did not experience FEV1 improvement after 1 month, 39% exhibited improvement at 6 months follow-up. A high ACT score measured at this visit was the most reliable predictor of late response after 6 months of treatment (OR and 95% CI 1.75 [1.09-2.98]). CONCLUSION: Factors predicting the efficacy of biological agents that improve lung function in SEA vary according to the stage of response.

IL-33 Expression Is Lower in Current Smokers at both Transcriptomic and Protein Levels.

Rationale: IL-33 is a proinflammatory cytokine thought to play a role in the pathogenesis of asthma and chronic obstructive pulmonary disease (COPD). A recent clinical trial using an anti-IL-33 antibody showed a reduction in exacerbation and improved lung function in ex-smokers but not current smokers with COPD. Objectives: This study aimed to understand the effects of smoking status on IL-33. Methods: We investigated the association of smoking status with the level of gene expression of IL-33 in the airways in eight independent transcriptomic studies of lung airways. Additionally, we performed Western blot analysis and immunohistochemistry for IL-33 in lung tissue to assess protein levels. Measurements and Main Results: Across the bulk RNA-sequencing datasets, IL-33 gene expression and its signaling pathway were significantly lower in current versus former or never-smokers and increased upon smoking cessation (P < 0.05). Single-cell sequencing showed that IL-33 is predominantly expressed in resting basal epithelial cells and decreases during the differentiation process triggered by smoke exposure. We also found a higher transitioning of this cellular subpopulation into a more differentiated cell type during chronic smoking, potentially driving the reduction of IL-33. Protein analysis demonstrated lower IL-33 levels in lung tissue from current versus former smokers with COPD and a lower proportion of IL-33-positive basal cells in current versus ex-smoking controls. Conclusions: We provide strong evidence that cigarette smoke leads to an overall reduction in IL-33 expression in transcriptomic and protein level, and this may be due to the decrease in resting basal cells. Together, these findings may explain the clinical observation that a recent antibody-based anti-IL-33 treatment is more effective in former than current smokers with COPD.

Oropharyngeal Microbiota Clusters in Children with Asthma or Wheeze Associate with Allergy, Blood Transcriptomic Immune Pathways, and Exacerbation Risk.

Rationale: Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. Objectives: To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. Methods: Oropharyngeal swabs from the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) pediatric asthma or wheezing cohort were characterized using 16S ribosomal RNA gene sequencing, and unsupervised hierarchical clustering was performed on the Bray-Curtis ß-diversity. Enrichment scores of the Molecular Signatures Database hallmark gene sets were computed from the blood transcriptome using gene set variation analysis. Children with severe asthma or severe wheezing were followed up for 12-18 months, with assessment of the frequency of exacerbations. Measurements and Main Results: Oropharyngeal samples from 241 children (age range, 1-17 years; 40% female) revealed four taxa-driven clusters dominated by Streptococcus, Veillonella, Rothia, and Haemophilus. The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV1% predicted after salbutamol, and annual asthma exacerbation frequency during follow-up. The Veillonella cluster was the most allergic and included the highest percentage of children with two or more exacerbations per year during follow-up. The oropharyngeal clusters were different in the enrichment scores of TGF-ß (transforming growth factor-ß) (highest in the Veillonella cluster) and Wnt/ß-catenin signaling (highest in the Haemophilus cluster) transcriptomic pathways in blood (all q values <0.05). Conclusions: Analysis of the oropharyngeal microbiota of children with asthma or wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with risk for exacerbation and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiologic insights and potentially new treatment approaches.

Poxviridae Pneumonia.

Poxviridae family includes several viruses that infecting humans usually causes skin lesions only, but in some cases their clinical course is complicated by viral pneumonia (with or without bacterial superinfections). Historically variola virus has been the poxviridae most frequently associated with the development of pneumonia with many large outbreaks worldwide before its eradication in 1980. It is still considered a biological threat for its potential in biological warfare and bioterrorism. Smallpox pneumonia can be severe with the onset of acute respiratory distress syndrome (ARDS) and death. Vaccinia virus, used for vaccination against smallpox exceptionally, in immunocompromised patients, can induce generalized (with also lung involvement) severe disease after vaccination. MPXV virus occasionally can cause pneumonia particularly in immunocompromised patients. The pathophysiology of poxviridae pneumonia is still an area of active research; however, in animal models these viruses can cause both direct damage to the lower airways epithelium and a hyperinflammatory syndrome, like a cytokine storm. Multiple mechanisms of immune evasion have also been described. The treatment of poxviridae pneumonia is mainly based on careful supportive care. Despite the absence of randomized clinical trials in patients with poxviridae pneumonia there are antiviral drugs, such as tecovirimat, cidofovir and brincidofovir, FDA-approved for use in smallpox and also available under an expanded access protocol for treatment of MPXV. There are 2 (replication-deficient modified vaccinia Ankara and replication-competent vaccinia virus) smallpox vaccines FDA-approved with the first one also approved for prevention of MPXV in adults that are at high risk of infection.

Multidimensional endotyping using nasal proteomics predicts molecular phenotypes in the asthmatic airways.

BACKGROUND: Unsupervised clustering of biomarkers derived from noninvasive samples such as nasal fluid is less evaluated as a tool for describing asthma endotypes. OBJECTIVE: We sought to evaluate whether protein expression in nasal fluid would identify distinct clusters of patients with asthma with specific lower airway molecular phenotypes. METHODS: Unsupervised clustering of 168 nasal inflammatory and immune proteins and Shapley values was used to stratify 43 patients with severe asthma (endotype of noneosinophilic asthma) using a 2 "modeling blocks" machine learning approach. This algorithm was also applied to nasal brushings transcriptomics from U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes). Feature reduction and functional gene analysis were used to compare proteomic and transcriptomic clusters. Gene set variation analysis provided enrichment scores of the endotype of noneosinophilic asthma protein signature within U-BIOPRED sputum and blood. RESULTS: The nasal protein machine learning model identified 2 severe asthma endotypes, which were replicated in U-BIOPRED nasal transcriptomics. Cluster 1 patients had significant airway obstruction, small airways disease, air trapping, decreased diffusing capacity, and increased oxidative stress, although only 4 of 18 were current smokers. Shapley identified 20 cluster-defining proteins. Forty-one proteins were significantly higher in cluster 1. Pathways associated with proteomic and transcriptomic clusters were linked to TH1, TH2, neutrophil, Janus kinase-signal transducer and activator of transcription, TLR, and infection activation. Gene set variation analysis of the nasal protein and gene signatures were enriched in subjects with sputum neutrophilic/mixed granulocytic asthma and in subjects with a molecular phenotype found in sputum neutrophil-high subjects. CONCLUSIONS: Protein or gene analysis may indicate molecular phenotypes within the asthmatic lower airway and provide a simple, noninvasive test for non-type 2 immune response asthma that is currently unavailable.

Stratification of asthma by lipidomic profiling of induced sputum supernatant.

BACKGROUND: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. OBJECTIVE: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. METHODS: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. RESULTS: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. CONCLUSION: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.

Does Chronic Obstructive Pulmonary Disease Originate from Different Cell Types?

The onset of chronic obstructive pulmonary disease (COPD) is heterogeneous, and current approaches to define distinct disease phenotypes are lacking. In addition to clinical methodologies, subtyping COPD has also been challenged by the reliance on human lung samples from late-stage diseases. Different COPD phenotypes may be initiated from the susceptibility of different cell types to cigarette smoke, environmental pollution, and infections at early stages that ultimately converge at later stages in airway remodeling and destruction of the alveoli when the disease is diagnosed. This perspective provides discussion points on how studies to date define different cell types of the lung that can initiate COPD pathogenesis, focusing on the susceptibility of macrophages, T and B cells, mast cells, dendritic cells, endothelial cells, and airway epithelial cells. Additional cell types, including fibroblasts, smooth muscle cells, neuronal cells, and other rare cell types not covered here, may also play a role in orchestrating COPD. Here, we discuss current knowledge gaps, such as which cell types drive distinct disease phenotypes and/or stages of the disease and which cells are primarily affected by the genetic variants identified by whole genome-wide association studies. Applying new technologies that interrogate the functional role of a specific cell type or a combination of cell types as well as single-cell transcriptomics and proteomic approaches are creating new opportunities to understand and clarify the pathophysiology and thereby the clinical heterogeneity of COPD.

Macrophage migration inhibitory factor promotes glucocorticoid resistance of neutrophilic inflammation in a murine model of severe asthma.

BACKGROUND: Severe neutrophilic asthma is resistant to treatment with glucocorticoids. The immunomodulatory protein macrophage migration inhibitory factor (MIF) promotes neutrophil recruitment to the lung and antagonises responses to glucocorticoids. We hypothesised that MIF promotes glucocorticoid resistance of neutrophilic inflammation in severe asthma. METHODS: We examined whether sputum MIF protein correlated with clinical and molecular characteristics of severe neutrophilic asthma in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort. We also investigated whether MIF regulates neutrophilic inflammation and glucocorticoid responsiveness in a murine model of severe asthma in vivo. RESULTS: MIF protein levels positively correlated with the number of exacerbations in the previous year, sputum neutrophils and oral corticosteroid use across all U-BIOPRED subjects. Further analysis of MIF protein expression according to U-BIOPRED-defined transcriptomic-associated clusters (TACs) revealed increased MIF protein and a corresponding decrease in annexin-A1 protein in TAC2, which is most closely associated with airway neutrophilia and NLRP3 inflammasome activation. In a murine model of severe asthma, treatment with the MIF antagonist ISO-1 significantly inhibited neutrophilic inflammation and increased glucocorticoid responsiveness. Coimmunoprecipitation studies using lung tissue lysates demonstrated that MIF directly interacts with and cleaves annexin-A1, potentially reducing its biological activity. CONCLUSION: Our data suggest that MIF promotes glucocorticoid-resistance of neutrophilic inflammation by reducing the biological activity of annexin-A1, a potent glucocorticoid-regulated protein that inhibits neutrophil accumulation at sites of inflammation. This represents a previously unrecognised role for MIF in the regulation of inflammation and points to MIF as a potential therapeutic target for the management of severe neutrophilic asthma.

Th2 high and mast cell gene signatures are associated with corticosteroid sensitivity in COPD.

RATIONALE: Severe asthma and chronic obstructive pulmonary disease (COPD) share common pathophysiological traits such as relative corticosteroid insensitivity. We recently published three transcriptome-associated clusters (TACs) using hierarchical analysis of the sputum transcriptome in asthmatics from the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort comprising one Th2-high inflammatory signature (TAC1) and two Th2-low signatures (TAC2 and TAC3). OBJECTIVE: We examined whether gene expression signatures obtained in asthma can be used to identify the subgroup of patients with COPD with steroid sensitivity. METHODS: Using gene set variation analysis, we examined the distribution and enrichment scores (ES) of the 3 TACs in the transcriptome of bronchial biopsies from 46 patients who participated in the Groningen Leiden Universities Corticosteroids in Obstructive Lung Disease COPD study that received 30 months of treatment with inhaled corticosteroids (ICS) with and without an added long-acting ß-agonist (LABA). The identified signatures were then associated with longitudinal clinical variables after treatment. Differential gene expression and cellular convolution were used to define key regulated genes and cell types. MEASUREMENTS AND MAIN RESULTS: Bronchial biopsies in patients with COPD at baseline showed a wide range of expression of the 3 TAC signatures. After ICS±LABA treatment, the ES of TAC1 was significantly reduced at 30 months, but those of TAC2 and TAC3 were unaffected. A corticosteroid-sensitive TAC1 signature was developed from the TAC1 ICS-responsive genes. This signature consisted of mast cell-specific genes identified by single-cell RNA-sequencing and positively correlated with bronchial biopsy mast cell numbers following ICS±LABA. Baseline levels of gene transcription correlated with the change in RV/TLC %predicted following 30-month ICS±LABA. CONCLUSION: Sputum-derived transcriptomic signatures from an asthma cohort can be recapitulated in bronchial biopsies of patients with COPD and identified a signature of airway mast cells as a predictor of corticosteroid responsiveness.

Differential responses of pulmonary vascular cells from PAH patients and controls to TNFα and the effect of the BET inhibitor JQ1.

BACKGROUND: Pulmonary arterial hypertension (PAH) encompasses a group of diseases characterized by raised pulmonary vascular resistance, resulting from vascular remodelling and inflammation. Bromodomain and extra-terminal (BET) proteins are required for the expression of a subset of NF-κB-induced inflammatory genes which can be inhibited by the BET mimic JQ1+. We hypothesised that JQ+ would supress TNFα-driven inflammatory responses in human pulmonary vascular cells from PAH patients. METHODS: Immunohistochemical staining of human peripheral lung tissue (N = 14 PAH and N = 12 non-PAH) was performed for the BET proteins BRD2 and 4. Human pulmonary microvascular endothelial cells (HPMEC) and pulmonary artery smooth muscle cells (HPASMC) from PAH patients (N = 4) and non-PAH controls (N = 4) were stimulated with TNFα in presence or absence of JQ1+ or its inactive isomer JQ1-. IL-6 and -8 mRNA was measured by RT-qPCR and protein levels by ELISA. Chromatin immunoprecipitation analysis was performed using EZ-ChIP™ and NF-κB p65 activation determined using a TransAm kit. MTT assay was used to measure cell viability. RESULTS: Nuclear staining of BRD2 and BRD4 was significantly (p < 0.0001) increased in the lung vascular endothelial and smooth muscle cells from PAH patients compared to controls with normal lung function. TNFα-driven IL-6 release from both HPMECs and HPASMCs was greater in PAH cells than control cells. Levels of CXCL8/IL-8 protein release was higher in PAH HPASMCs than in control cells with similar release observed in HPMECs. TNFα-induced recruitment of activated NF-κB p65 to the IL-6 and CXCL8/IL-8 promoters were similar in both cell types and between subject groups. JQ1+ suppressed TNFα-induced IL-6 and CXCL8/IL-8 release and mRNA expression to a comparable extent in control and PAH HPMECs and HPASMCs. JQ1 had a greater efficacy on IL-6 release in HPMEC and on CXCL8/IL-8 release in HPASMC. CONCLUSION: BET inhibition decreases TNFα driven inflammation in primary pulmonary vascular cells. The anti-inflammatory actions of JQ1 suggests distinct cell-specific regulatory control of these genes. BET proteins could be a target for future therapies for PAH.

Role of mitochondrial fusion proteins MFN2 and OPA1 on lung cellular senescence in chronic obstructive pulmonary disease.

BACKGROUND: Mitochondrial dysfunction and lung cellular senescence are significant features involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). Cigarette smoke (CS) stands as the primary contributing factor to COPD. This study examined mitochondrial dynamics, mitophagy and lung cellular senescence in COPD patients and investigated the effects of modulation of mitochondrial fusion [mitofusin2 (MFN2) and Optic atrophy 1 (OPA1)] on CS extract (CSE)-induced lung cellular senescence. METHODS: Senescence-associated secretory phenotype (SASP) component mRNAs (IL-1ß, IL-6, CXCL1 and CXCL8), mitochondrial morphology, mitophagy and mitochondria-related proteins (including phosphorylated-DRP1(p-DRP1), DRP1, MFF, MNF2, OPA1, PINK1, PARK2, SQSTM1/p62 and LC3b) and senescence-related proteins (including P16, H2A.X and Klotho) were measured in lung tissues or primary alveolar type II (ATII) cells of non-smokers, smokers and COPD patients. Alveolar epithelial (A549) cells were exposed to CSE with either pharmacologic inducer (leflunomide and BGP15) or genetic induction of MFN2 and OPA1 respectively. RESULTS: There were increases in mitochondrial number, and decreases in mitochondrial size and activity in lung tissues from COPD patients. SASP-related mRNAs, DRP1 phosphorylation, DRP1, MFF, PARK2, SQSTM1/p62, LC3B II/LC3B I, P16 and H2A.X protein levels were increased, while MFN2, OPA1, PINK1 and Klotho protein levels were decreased in lung tissues from COPD patients. Some similar results were identified in primary ATII cells of COPD patients. CSE induced increases in oxidative stress, SASP-related mRNAs, mitochondrial damage and dysfunction, mitophagy and cellular senescence in A549 cells, which were ameliorated by both pharmacological inducers and genetic overexpression of MFN2 and OPA1. CONCLUSIONS: Impaired mitochondrial fusion, enhanced mitophagy and lung cellular senescence are observed in the lung of COPD patients. Up-regulation of MFN2 and OPA1 attenuates oxidative stress, mitophagy and lung cellular senescence, offering potential innovative therapeutic targets for COPD therapy.

Epithelium-derived cystatin SN inhibits house dust mite protease activity in allergic asthma.

BACKGROUND: Allergen source-derived proteases are a critical factor in the formation and development of asthma. The cysteine protease activity of house dust mite (HDM) disrupts the epithelial barrier function. The expression of cystatin SN (CST1) is elevated in asthma epithelium. CST1 inhibits the cysteine protease activity. We aimed to elucidate the role of epithelium-derived CST1 in the development of asthma caused by HDM. METHODS: CST1 protein levels in sputum supernatants and serum of patients with asthma and healthy volunteers were measured by ELISA. The ability of CST1 protein to suppress HDM-induced bronchial epithelial barrier function was examined in vitro. The effects of exogenous CST1 protein on abrogating HDM-induced epithelial barrier function and inflammation were examined in mice in vivo. RESULTS: CST1 protein levels were higher in sputum supernatants (142.4 ± 8.95 vs 38.87 ± 6.85 ng/mL, P < 0.0001) and serum (1129 ± 73.82 vs 703.1 ± 57.02 pg/mL, P = 0.0035) in patients with asthma than in healthy subjects. The levels were significantly higher in patients with not well- and very poorly controlled asthma than those with well-controlled asthma. Sputum and serum CST1 protein levels were negatively correlated with lung function in asthma. CST1 protein levels were significantly lower in the serum of HDM-specific IgE (sIgE)-positive asthmatics than in sIgE-negative asthmatics. The HDM-induced epithelial barrier function disruption was suppressed by recombinant human CST1 protein (rhCST1) in vitro and in vivo. CONCLUSION: Our data indicated that human CST1 protein suppresses asthma symptoms by protecting the asthmatic bronchial epithelial barrier through inhibiting allergenic protease activity. CST1 protein may serve as a potential biomarker for asthma control.

DEL-1, as an anti-neutrophil transepithelial migration molecule, inhibits airway neutrophilic inflammation in asthma.

BACKGROUND: Neutrophil migration into the airways is a key process in neutrophilic asthma. Developmental endothelial locus-1 (DEL-1), an extracellular matrix protein, is a neutrophil adhesion inhibitor that attenuates neutrophilic inflammation. METHODS: Levels of DEL-1 were measured in exhaled breath condensate (EBC) and serum in asthma patients by ELISA. DEL-1 modulation of neutrophil adhesion and transepithelial migration was examined in a co-culture model in vitro. The effects of DEL-1-adenoviral vector-mediated overexpression on ovalbumin/lipopolysaccharide (OVA/LPS)-induced neutrophilic asthma were studied in mice in vivo. RESULTS: DEL-1 was primarily expressed in human bronchial epithelial cells and was decreased in asthma patients. Serum DEL-1 concentrations were reduced in patients with severe asthma compared with normal subjects (567.1 ± 75.3 vs. 276.8 ± 29.36 pg/mL, p < .001) and were negatively correlated to blood neutrophils (r = -0.2881, p = .0384) and neutrophil-to-lymphocyte ratio (NLR) (r = -0.5469, p < .0001). DEL-1 concentrations in the EBC of severe asthmatic patients (113.2 ± 8.09 pg/mL) were also lower than normal subjects (193.0 ± 7.61 pg/mL, p < .001) and were positively correlated with the asthma control test (ACT) score (r = 0.3678, p = .0035) and negatively related to EBC IL-17 (r = -0.3756, p = .0131), myeloperoxidase (MPO) (r = -0.5967, p = .0055), and neutrophil elastase (NE) (r = -0.5488, p = .0009) expression in asthma patients. Neutrophil adhesion and transepithelial migration in asthma patients were associated with LFA-1 binding to ICAM-1 and inhibited by DEL-1. DEL-1 mRNA and protein expression in human bronchial epithelial cells were regulated by IL-17. Exogenous DEL-1 inhibited IL-17-enhanced neutrophil adhesion and migration. DEL-1 expression was decreased while neutrophil infiltration was increased in the airway of a murine model of neutrophilic asthma. This was prevented by DEL-1 overexpression. CONCLUSIONS: DEL-1 down-regulation leads to increased neutrophil migration across bronchial epithelial cells and is associated with neutrophilic airway inflammation in asthma.

EAACI guidelines on environmental science in allergic diseases and asthma - Leveraging artificial intelligence and machine learning to develop a causality model in exposomics.

Allergic diseases and asthma are intrinsically linked to the environment we live in and to patterns of exposure. The integrated approach to understanding the effects of exposures on the immune system includes the ongoing collection of large-scale and complex data. This requires sophisticated methods to take full advantage of what this data can offer. Here we discuss the progress and further promise of applying artificial intelligence and machine-learning approaches to help unlock the power of complex environmental data sets toward providing causality models of exposure and intervention. We discuss a range of relevant machine-learning paradigms and models including the way such models are trained and validated together with examples of machine learning applied to allergic disease in the context of specific environmental exposures as well as attempts to tie these environmental data streams to the full representative exposome. We also discuss the promise of artificial intelligence in personalized medicine and the methodological approaches to healthcare with the final AI to improve public health.