Sputum gene expression signature of 6 biomarkers discriminates asthma inflammatory phenotypes

Revealing the regulation of allergic asthma airway epithelial cell inflammation by STEAP4 targeting MIF through machine learning algorithms and single-cell sequencing analysis

Asthma comprises one of the most common chronic inflammatory conditions, yet still lacks effective diagnostic markers and treatment targets. To gain deeper insights, we comprehensively analyzed microarray datasets of airway epithelial samples from asthmatic patients and healthy subjects in the Gene Expression Omnibus database using three machine learning algorithms. Our investigation identified a pivotal gene, STEAP4. The expression of STEAP4 in patients with allergic asthma was found to be reduced. Furthermore, it was found to negatively correlate with the severity of the disease and was subsequently validated in asthmatic mice in this study. A ROC analysis of STEAP4 showed the AUC value was greater than 0.75. Functional enrichment analysis of STEAP4 indicated a strong correlation with IL-17, steroid hormone biosynthesis, and ferroptosis signaling pathways. Subsequently, intercellular communication analysis was performed using single-cell RNA sequencing data obtained from airway epithelial cells. The results revealed that samples exhibiting low levels of STEAP4 expression had a richer MIF signaling pathway in comparison to samples with high STEAP4 expression. Through both in vitro and in vivo experiments, we further confirmed the overexpression of STEAP4 in airway epithelial cells resulted in decreased expression of MIF, which in turn caused a decrease in the levels of the cytokines IL-33, IL-25, and IL-4; In contrast, when the STEAP4 was suppressed in airway epithelial cells, there was an upregulation of MIF expression, resulting in elevated levels of the cytokines IL-33, IL-25, and IL-4. These findings suggest that STEAP4 in the airway epithelium reduces allergic asthma Th2-type inflammatory reactions by inhibiting the MIF signaling pathway.

Advances in non-type 2 severe asthma: from molecular insights to novel treatment strategies

Asthma is a prevalent pulmonary disease that affects more than 300 million people worldwide and imposes a substantial economic burden. While medication can effectively control symptoms in some patients, severe asthma attacks, driven by airway inflammation induced by environmental and infectious exposures, continue to be a major cause of asthma-related mortality. Heterogeneous phenotypes of asthma include type 2 (T2) and non-T2 asthma. Non-T2 asthma is often observed in patients with severe and/or steroid-resistant asthma. This review covers the molecular mechanisms, clinical phenotypes, causes and promising treatments of non-T2 severe asthma. Specifically, we discuss the signalling pathways for non-T2 asthma including the activation of inflammasomes, interferon responses and interleukin-17 pathways, and their contributions to the subtypes, progression and severity of non-T2 asthma. Understanding the molecular mechanisms and genetic determinants underlying non-T2 asthma could form the basis for precision medicine in severe asthma treatment.

Activated non-neuronal cholinergic system correlates with non-type 2 inflammation and exacerbations in severe asthma

BACKGROUND

Non-neuronal cholinergic system (NNCS) contributes to various inflammatory airway diseases. However, the role of NNCS in severe asthma (SA) remains largely unexplored.

OBJECTIVE

To explore airway NNCS in SA.

METHODS

In this prospective cohort study based on the Australasian Severe Asthma Network in a real-world setting, patients with SA (n = 52) and non-SA (n = 104) underwent clinical assessment and sputum induction. The messenger RNA (mRNA) levels of NNCS components and proinflammatory cytokines in the sputum were detected using real-time quantitative polymerase chain reaction, and the concentrations of acetylcholine (Ach)-related metabolites were evaluated using liquid chromatography coupled with tandem mass spectrometry. Asthma exacerbations were prospectively investigated during the next 12 months. The association between NNCS and future asthma exacerbations was also analyzed.

RESULTS

Patients with SA were less controlled and had worse airway obstruction, a lower bronchodilator response, higher doses of inhaled corticosteroids, and more add-on treatments. The sputum mRNA levels of NNCS components, such as muscarinic receptors M1R-M5R, OCT3, VACHT, and ACHE; proinflammatory cytokines; and Ach concentration in the SA group were significantly higher than those in the non-SA group. Furthermore, most NNCS components positively correlated with non-type (T) 2 inflammatory profiles, such as sputum neutrophils, IL8, and IL1B. In addition, the mRNA levels of sputum M2R, M3R, M4R, M5R, and VACHT were independently associated with an increased risk of moderate-to-severe asthma exacerbations.

CONCLUSION

This study indicated that the NNCS was significantly activated in SA, leading to elevated Ach and was associated with clinical features, non-T2 inflammation, and future exacerbations of asthma, highlighting the potential role of the NNCS in the pathogenesis of SA.

CLINICAL TRIAL REGISTRATION

ChiCTR-OOC-16009529 (http://www.chictr.org.cn).

The Role of Galectins in Asthma Pathophysiology: A Comprehensive Review

Galectins are a group of β-galactoside-binding proteins with several roles in immune response, cellular adhesion, and inflammation development. Current evidence suggest that these proteins could play a crucial role in many respiratory diseases such as pulmonary fibrosis, lung cancer, and respiratory infections. From this standpoint, an increasing body of evidence have recognized galectins as potential biomarkers involved in several aspects of asthma pathophysiology. Among them, galectin-3 (Gal-3), galectin-9 (Gal-9), and galectin-10 (Gal-10) are the most extensively studied in human and animal asthma models. These galectins can affect T helper 2 (Th2) and non-Th2 inflammation, mucus production, airway responsiveness, and bronchial remodeling. Nevertheless, while higher Gal-3 and Gal-9 concentrations are associated with a stronger degree of Th-2 phlogosis, Gal-10, which forms Charcot-Leyden Crystals (CLCs), correlates with sputum eosinophilic count, interleukin-5 (IL-5) production, and immunoglobulin E (IgE) secretion. Finally, several galectins have shown potential in clinical response monitoring after inhaled corticosteroids (ICS) and biologic therapies, confirming their potential role as reliable biomarkers in patients with asthma.

Establishment of a diagnostic model based on immune-related genes in children with asthma

Objective

Allergic asthma is driven by an antigen-specific immune response. This study aimed to identify immune-related differentially expressed genes in childhood asthma and establish a classification diagnostic model based on these genes.

Methods

GSE65204 and GSE19187 were downloaded and served as training set and validation set. The immune cell composition was evaluated with ssGSEA algorithm based on the immune-related gene set. Modules that significantly related to the asthma were selected by WGCNA algorithm. The immune-related differentially expressed genes (DE-IRGs) were screened, the protein-protein interaction network and diagnostic model of DE-IRGs was constructed. The pathway and immune correlation analysis of hub DE-IRGs was analyzed.

Results

Eight immune cell types exhibited varying levels of abundance between the asthma and control groups. A total of 112 differentially expressed immune-related genes (DE-IRGs) was identified. Through the application of four ranking methods (MCC, MNC, DEGREE, and EPC), 17 hub DE-IRGs with overlapping significance were further selected. Subsequently, 8 optimized were identified using univariate logistic regression analysis and the LASSO regression algorithm, based on which a robust diagnostic model was constructed. Notably, TNF and CD40LG emerged as direct participants in asthma-related signaling pathways, displaying a positive correlation with the immune cell types of immature B cells, activated B cells, activated CD8 T cells, activated CD4 T cells, and myeloid-derived suppressor cells.

Conclusion

The diagnostic model constructed using the DE-IRGs (CCL5, CCR5, CD40LG, CD8A, IL2RB, PDCD1, TNF, and ZAP70) exhibited high and specific diagnostic value for childhood asthma. The diagnostic model may contribute to the diagnosis of childhood asthma.

Endotypes of Paediatric Cough-Do They Exist and Finding New Techniques to Improve Clinical Outcomes

Chronic cough is a common symptom of many childhood lung conditions. Given the phenotypic heterogeneity of chronic cough, better characterization through endotyping is required to provide diagnostic certainty, precision therapies and to identify pathobiological mechanisms. This review summarizes recent endotype discoveries in airway diseases, particularly in relation to children, and describes the multi-omic approaches that are required to define endotypes. Potential biospecimens that may contribute to endotype and biomarker discoveries are also discussed. Identifying endotypes of chronic cough can likely provide personalized medicine and contribute to improved clinical outcomes for children.

Sputum Transcriptomics Reveals FCN1+ Macrophage Activation in Mild Eosinophilic Asthma Compared to Non-Asthmatic Eosinophilic Bronchitis

PURPOSE

Eosinophilic asthma (EA) and non-asthmatic eosinophilic bronchitis (EB) share similar eosinophilic airway inflammation. Unlike EA, EB did not present airway hyperresponsiveness or airflow obstruction. We aimed to compare the mechanism underlying the different manifestations between EA and EB via sputum transcriptomics analysis.

METHODS

Induced-sputum cells from newly physician-diagnosed EA, EB patients, and healthy controls (HCs) were collected for RNA sequencing.

RESULTS

Bulk RNA sequencing was performed using sputum cells from patients with EA (n = 18), EB (n = 15) and HCs (n = 28). Principal component analysis revealed similar gene expression patterns in EA and EB. The most differentially expressed genes in EB compared with HC were also shared by EA, including IL4, IL5 IL13, CLC, CPA3, and DNASE1L3. However, gene set enrichment analysis showed that the signatures regulating macrophage activation were enriched in EA compared to EB. Sputum cells were profiled using single-cell RNA sequencing. FABP4+ macrophages, SPP1+ macrophages, FCN1+ macrophages, dendritic cells, T cells, B cells, mast cells, and epithelial cells were identified based on gene expression profiling. Analysis of cell-cell communication revealed that interactions between FCN1+ macrophages and other cells were higher in EA than in EB. A wealth of transforming growth factor beta (TGF-β) and vascular endothelial growth factor (VEGF) interactions between FCN1+ macrophages and other cells have been shown in EA. The gene expression levels of EREG, TGFBI, and VEGFA in FCN1+ macrophages of EA were significantly higher than those of EB. Furthermore, signatures associated with the response to TGF-β, cellular response to VEGF stimulus and developmental cell growth were enriched in FCN1+ macrophages of EA compared to those of EB.

CONCLUSIONS

FCN1+ macrophage activation associated with airway remodeling processes was upregulated in EA compared to that in EB, which may contribute to airway hyperresponsiveness and airflow obstruction.

A five-gene qPCR signature can classify type 2 asthma comparably to microscopy of induced sputum from severe asthma patients

Asthma is a heterogenous disease characterized by airway inflammation and variable expiratory airflow limitation resulting in variable respiratory symptoms. Characterization of airway inflammation is important to choose the optimal treatment for severe asthma patients eligible for biological treatment. However, counting cells in induced sputum samples are a time-consuming process, highly dependent on personal skills. Replacing eosinophil and neutrophil cell counting with qPCR for transcripts of selected mast cell, and basophil genes may provide more reproducible results.

Aims

The objective of this study was to compare qPCR with microscopy in asthma endotyping.

Methods

A qPCR method measuring five mast cell/basophil genes was applied on induced sputum samples from 30 severe asthma patients and compared with microscopy. Target gene Ct-values (CPA3, GATA2, HDC, MS4A2, TPSAB1/TPSB2) were referenced to household β-actin Ct values as a measure of relative mRNA abundance of the target in each sample. Target/β-actin-ratios in eosinophilic and non-eosinophilic groups determined by microscopy with an eosinophil threshold of 3% in 400 cells were compared using Mann-Whitney U Test. Spearman´s correlations were used to test for correlation between targets vs. FENO and targets vs. blood eosinophil counts.

Results

The study demonstrated a statistical difference in relative mRNA abundance for four mast cell/basophil specific genes. CPA3, GATA2, HDC and MS4A2 were elevated in eosinophilic asthma versus non-eosinophilic asthma patients. The study found that GATA2, CPA3, MS4A2 and TPSAB1/TPSB2 transcripts are positively correlated with FENO. Neither the five mast cell genes nor the five-gene signature correlated with blood eosinophils. The five-gene signature with a target/β-actin-ratio cut-off ≥2 generated sensitivity = 87%, specificity = 94%, NPV = 88% and PPV = 92% compared to microscopy.

Conclusion

This study confirms the contribution of mast cells in the pathogenesis of EA and suggests that mast cell mRNA markers could be one of the biomarkers used to identify EA.

RNA Sequencing and Bioinformatics Analysis to Reveal Potential Biomarkers in Patients with Combined Allergic Rhinitis and Asthma Syndrome

Introduction

Combined allergic rhinitis and asthma syndrome (CARAS) is a concurrent clinical or subclinical allergic symptom of diseases of the upper and lower respiratory tract. This study is the first to explore the expression profiles of mRNA, lncRNA, and circRNA in CARAS using RNA sequencing, which may provide insight into the mechanisms underlying CARAS.

Material and Methods

Whole blood samples from nine participants (three CARAS patients, three AR patients, and three normal control participants) were subjected to perform RNA sequencing, followed by identification of differentially expressed lncRNAs (DElncRNAs), circRNAs (DEcircRNAs) and mRNAs (DEmRNAs). Then, lncRNA/circRNA-mRNA regulatory pairs were constructed, followed by functional analysis, immune infiltration analysis, drug prediction, and expression validation with RT-qPCR and ELISA.

Results

The results showed that 61 DEmRNAs, 23 DElncRNAs and 3 DEcircRNAs may be related to the occurrence and development of CARAS. KRT8 may be implicated in the development of AR into CARAS. Three immunity-related mRNAs (IDO1, CYSLTR2, and TEC) and two hypoxia-related mRNAs (TKTL1 and VLDLR) were associated with the occurrence and development of CARAS. TEC may be considered a drug target for Dasatinib in treating CARAS. Several lncRNA/circRNA-mRNA regulatory pairs were identified in CARAS, including LINC00452/MIR4280HG/hsa_circ_0007272/hsa_circ_0070934-CLC, HEATR6-DT/LINC00639/LINC01783/hsa_circ_0008903-TEC, RP11-71L14.3-IDO1/SMPD3, RP11-178F10.2-IDO1/HRH4, and hsa_circ_0008903-CYSLTR2, which may indicate potential regulatory effects of lncRNAs/circRNAs in CARAS. Dysregulated levels of immune cell infiltration may be closely related to CARAS.

Conclusion

The regulating effect of lncRNA/circRNA-immunity/hypoxia-related mRNA regulatory pairs may be involved in the occurrence and development of CARAS.

Eosinophils-from cradle to grave: An EAACI task force paper on new molecular insights and clinical functions of eosinophils and the clinical effects of targeted eosinophil depletion

Over the past years, eosinophils have become a focus of scientific interest, especially in the context of their recently uncovered functions (e.g. antiviral, anti-inflammatory, regulatory). These versatile cells display both beneficial and detrimental activities under various physiological and pathological conditions. Eosinophils are involved in the pathogenesis of many diseases which can be classified into primary (clonal) and secondary (reactive) disorders and idiopathic (hyper)eosinophilic syndromes. Depending on the biological specimen, the eosinophil count in different body compartments may serve as a biomarker reflecting the underlying pathophysiology and/or activity of distinct diseases and as a therapy-driving (predictive) and monitoring tool. Personalized selection of an appropriate therapeutic strategy directly or indirectly targeting the increased number and/or activity of eosinophils should be based on the understanding of eosinophil homeostasis including their interactions with other immune and non-immune cells within different body compartments. Hence, restoring as well as maintaining homeostasis within an individual's eosinophil pool is a goal of both specific and non-specific eosinophil-targeting therapies. Despite the overall favourable safety profile of the currently available anti-eosinophil biologics, the effect of eosinophil depletion should be monitored from the perspective of possible unwanted consequences.

Epithelial CST1 Promotes Airway Eosinophilic Inflammation in Asthma via the AKT Signaling Pathway

PURPOSE

Epithelial cystatin SN (CST1), a type 2 cysteine protease inhibitor, was significantly upregulated in asthma. In this study, we aimed to investigate the potential role and mechanism of CST1 in eosinophilic inflammation in asthma.

METHODS

Bioinformatics analysis on Gene Expression Omnibus datasets were used to explore the expression of CST1 in asthma. Sputum samples were collected from 76 asthmatics and 22 control subjects. CST1 mRNA and protein expression in the induced sputum were measured by real-time polymerase chain reaction, enzyme-linked immunosorbent assay, and western blotting. The possible function of CST1 was explored in ovalbumin (OVA)-induced eosinophilic asthma. Transcriptome sequencing (RNA-seq) was used to predict the possible regulated mechanism of CST1 in bronchial epithelial cells. Overexpression or knockdown of CST1 was further used to verify potential mechanisms in bronchial epithelial cells.

RESULTS

CST1 expression was significantly increased in the epithelial cells and induced sputum of asthma. Increased CST1 was significantly associated with eosinophilic indicators and T helper cytokines. CST1 aggravated airway eosinophilic inflammation in the OVA-induced asthma model. In addition, overexpression of CST1 significantly enhanced the phosphorylation of AKT and the expression of serpin peptidase inhibitor, clade B, member 2 (SERPINB2), while knockdown using anti-CST1 siRNA reversed the trend. Furthermore, AKT had a positive effect on SERPINB2 expression.

CONCLUSIONS

Increased sputum CST1 may play a key role in the pathogenesis of asthma through involvement in eosinophilic and type 2 inflammation through activation of the AKT signaling pathway, further promoting SERPINB2 expression. Therefore, targeting CST1 might be of therapeutic value in treating asthma with severe and eosinophilic phenotypes.

Increased expression of CSF1 in patients with eosinophilic asthma

BACKGROUND

The link between colony-stimulating factor 1 (CSF1) and asthma was reported recently. However, the role and mechanism of CSF1 in asthma remain poorly understood. In this study, we aimed to explore the expression and its potential mechanism of CSF1 in asthma.

METHODS

CSF1 expression in the airway samples from asthmatics and healthy controls were examined, then the correlations between CSF1 and eosinophilic indicators were analyzed. Subsequently, bronchial epithelial cells (BEAS-2B) with CSF1 overexpression and knockdown were constructed to investigate the potential molecular mechanism of CSF1. Finally, the effect of CSF1R inhibitor on STAT1 was investigated.

RESULTS

The expression of CSF1 was significantly increased in patients with asthma compared to healthy controls, especially in patients with severe and eosinophilic asthma. Upregulated CSF1 positively correlated with airway-increased eosinophil inflammation. In vitro, cytokines interleukin 13 (IL-13) and IL-33 can stimulate the upregulation of CSF1 expression. CSF1 overexpression enhanced p-CSF1R/CSF1R and p-STAT1/STAT1 expression, while knockdown CSF1 using anti-CSF1 siRNAs decreased p-CSF1R/CSF1R and p-STAT1/STAT1 expression. Furthermore, the inhibitor of CSF1R significantly decreased p-STAT1/STAT1 expression.

CONCLUSIONS

Sputum CSF1 may be involved in asthmatic airway eosinophil inflammation by interacting with CSF1R and further activating the STAT1 signaling. Interfering this potential pathway could serve as an anti-inflammatory therapy for asthma.

Delineating asthma according to inflammation phenotypes with a focus on paucigranulocytic asthma

ABSTRACT

Asthma is characterized by chronic airway inflammation and airway hyper-responsiveness. However, the differences in pathophysiology and phenotypic symptomology make a diagnosis of "asthma" too broad hindering individualized treatment. Four asthmatic inflammatory phenotypes have been identified based on inflammatory cell profiles in sputum: eosinophilic, neutrophilic, paucigranulocytic, and mixed-granulocytic. Paucigranulocytic asthma may be one of the most common phenotypes in stable asthmatic patients, yet it remains much less studied than the other inflammatory phenotypes. Understanding of paucigranulocytic asthma in terms of phenotypic discrimination, distribution, stability, surrogate biomarkers, underlying pathophysiology, clinical characteristics, and current therapies is fragmented, which impedes clinical management of patients. This review brings together existing knowledge and ongoing research about asthma phenotypes, with a focus on paucigranulocytic asthma, in order to present a comprehensive picture that may clarify specific inflammatory phenotypes and thus improve clinical diagnoses and disease management.

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 β-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.

What Have Mechanistic Studies Taught Us About Childhood Asthma?

Childhood asthma is a chronic heterogeneous syndrome consisting of different disease entities or phenotypes. The immunologic and cellular processes that occur during asthma development are still not fully understood but represent distinct endotypes. Mechanistic studies have examined the role of gene expression, protein levels, and cell types in early life development and the manifestation of asthma, many under the influence of environmental stimuli, which can be both protective and risk factors for asthma. Genetic variants can regulate gene expression, controlled partly by different epigenetic mechanisms. In addition, environmental factors, such as living space, nutrition, and smoking, can contribute to these mechanisms. All of these factors produce modifications in gene expression that can alter the development and function of immune and epithelial cells and subsequently different trajectories of childhood asthma. These early changes in a partially immature immune system can have dramatic effects (e.g., causing dysregulation), which in turn contribute to different disease endotypes and may help to explain differential responsiveness to asthma treatment. In this review, we summarize published studies that have aimed to uncover distinct mechanisms in childhood asthma, considering genetics, epigenetics, and environment. Moreover, a discussion of new, powerful tools for single-cell immunologic assays for phenotypic and functional analysis is included, which promise new mechanistic insights into childhood asthma development and therapeutic and preventive strategies.

The upper-airway microbiome as a biomarker of asthma exacerbations despite inhaled corticosteroid treatment

BACKGROUND

The response to inhaled corticosteroids (ICS) in asthma is affected by the interplay of several factors. Among these, the role of the upper-airway microbiome has been scarcely investigated. We aimed to evaluate the association between the salivary, pharyngeal, and nasal microbiome with asthma exacerbations despite receipt of ICS.

METHODS

Samples from 250 asthma patients from the Genomics and Metagenomics of Asthma Severity (GEMAS) study treated with ICS were analyzed. Control/case subjects were defined by the absence/presence of asthma exacerbations in the past 6 months despite being treated with ICS. The bacterial microbiota was profiled by sequencing the V3-V4 region of the 16S rRNA gene. Differences between groups were assessed by PERMANOVA and regression models adjusted for potential confounders. A false discovery rate (FDR) of 5% was used to correct for multiple comparisons. Classification models of asthma exacerbations despite ICS treatment were built with machine learning approaches based on clinical, genetic, and microbiome data.

RESULTS

In nasal and saliva samples, case subjects had lower bacterial diversity (Richness, Shannon, and Faith indices) than control subjects (.007 ≤ P ≤ .037). Asthma exacerbations accounted for 8% to 9% of the interindividual variation of the salivary and nasal microbiomes (.003 ≤ P ≤ .046). Three, 4, and 11 bacterial genera from the salivary, pharyngeal, and nasal microbiomes were differentially abundant between groups (4.09 × 10^-12 ≤ FDR ≤ 0.047). Integrating clinical, genetic, and microbiome data showed good discrimination for the development of asthma exacerbations despite receipt of ICS (AUC_training: 0.82 and AUC_validation: 0.77).

CONCLUSION

The diversity and composition of the upper-airway microbiome are associated with asthma exacerbations despite ICS treatment. The salivary microbiome has a potential application as a biomarker of asthma exacerbations despite receipt of ICS.

Co-Expression Analysis of Airway Epithelial Transcriptome in Asthma Patients with Eosinophilic vs. Non-Eosinophilic Airway Infiltration

Asthma heterogeneity complicates the search for targeted treatment against airway inflammation and remodeling. We sought to investigate relations between eosinophilic inflammation, a phenotypic feature frequent in severe asthma, bronchial epithelial transcriptome, and functional and structural measures of airway remodeling. We compared epithelial gene expression, spirometry, airway cross-sectional geometry (computed tomography), reticular basement membrane thickness (histology), and blood and bronchoalveolar lavage (BAL) cytokines of n = 40 moderate to severe eosinophilic (EA) and non-eosinophilic asthma (NEA) patients distinguished by BAL eosinophilia. EA patients showed a similar extent of airway remodeling as NEA but had an increased expression of genes involved in the immune response and inflammation (e.g., KIR3DS1), reactive oxygen species generation (GYS2, ATPIF1), cell activation and proliferation (ANK3), cargo transporting (RAB4B, CPLX2), and tissue remodeling (FBLN1, SOX14, GSN), and a lower expression of genes involved in epithelial integrity (e.g., GJB1) and histone acetylation (SIN3A). Genes co-expressed in EA were involved in antiviral responses (e.g., ATP1B1), cell migration (EPS8L1, STOML3), cell adhesion (RAPH1), epithelial-mesenchymal transition (ASB3), and airway hyperreactivity and remodeling (FBN3, RECK), and several were linked to asthma in genome- (e.g., MRPL14, ASB3) or epigenome-wide association studies (CLC, GPI, SSCRB4, STRN4). Signaling pathways inferred from the co-expression pattern were associated with airway remodeling (e.g., TGF-β/Smad2/3, E2F/Rb, and Wnt/β-catenin).

Identification of hub genes and potential biomarkers of neutrophilic asthma: evidence from a bioinformatics analysis

OBJECTIVE

Asthma is a chronic airway inflammatory disease caused by multiple genetic and environmental factors. This study mainly sought to provide potential therapeutic targets and biomarkers for neutrophilic asthma (NA).

METHODS

Three gene expression profiling datasets were obtained from the Genome Expression Omnibus (GEO) database. GSE45111 and GSE41863 were used to identify hub genes and potential biomarkers, and GSE137268 was used for data verification. We verified the repeatability of intragroup data and identified differentially expressed genes (DEGs). Then, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the DEGs, and a protein-protein interaction (PPI) network was constructed to identify the hub genes. Finally, receiver operating characteristic (ROC) analysis was used to verify the ability of the hub genes to differentiate between NA and eosinophilic asthma (EA).

RESULTS

In this study, we identified 411 DEGs by comprehensive analysis of NA/EA patients and NA/healthy controls (HCs). Ten hub genes (CXCR1, FCGR3B, CXCR2, SELL, S100A12, CSF3R, IL6R, JAK3, CD48, and GNG2) were identified from the PPI network. Finally, based on the ROC analysis, 7 genes showed good diagnostic value for discriminating NA from EA-CXCR1, FCGR3B, CXCR2, SELL, S100A12, CSF3R, and IL6R (AUC > 0.7).

CONCLUSION

We identified 7 hub genes that can distinguish NA from EA. The IL-8-mediated signaling may be the primary pathway to determine the NA phenotype in asthma. CXCR1/2 and S100A12 may be the primary genes determining the NA phenotype. CXCR1/2 and S100A12 might be biomarkers and new therapeutic targets for NA.

Supplemental data for this article is available online at at.

Heterogeneity of Treatment Response to Asthma

The definition of asthma has evolved over the years with significant heterogeneity of the disease increasingly recognized. Complex gene and environment interactions result in different pheno-endotypes of asthma that respond differently to the same treatment. Multiple studies have revealed pharmacogenomic and endophenotypic factors that predict treatment response to standard therapies for asthma. Recent advances in biologic medications have enabled a more tailored approach to the care of patients with moderate to severe asthma, taking into consideration clinical traits and measurable biomarkers. This chapter will review heterogeneity in treatment response to different medication classes for asthma: inhaled and systemic corticosteroids, beta-2 agonists, leukotriene modifiers, muscarinic antagonists, macrolides, and biologics.

Simulated Microgravity Influences Immunity-Related Biomarkers in Lung Cancer

Microgravity is a novel strategy that may serve as a complementary tool to develop future cancer therapies. In lung cancer, the influence of microgravity on cellular processes and the migratory capacity of cells is well addressed. However, its effect on the mechanisms that drive lung cancer progression remains in their infancy. In this study, 13 differentially expressed genes were shown to be associated with the prognosis of lung cancer under simulated microgravity (SMG). Using gene set enrichment analysis, these genes are enriched in humoral immunity pathways. In lieu, alveolar basal-epithelial (A549) cells were exposed to SMG via a 2D clinostat system in vitro. In addition to morphology change and decrease in proliferation rate, SMG reverted the epithelial-to-mesenchymal transition (EMT) phenotype of A549, a key mechanism in cancer progression. This was evidenced by increased epithelial E-cadherin expression and decreased mesenchymal N-cadherin expression, hence exhibiting a less metastatic state. Interestingly, we observed increased expression of FCGBP, BPIFB, F5, CST1, and CFB and their correlation to EMT under SMG, rendering them potential tumor suppressor biomarkers. Together, these findings reveal new opportunities to establish novel therapeutic strategies for lung cancer treatment.

Determining asthma endotypes and outcomes: Complementing existing clinical practice with modern machine learning

There is unprecedented opportunity to use machine learning to integrate high-dimensional molecular data with clinical characteristics to accurately diagnose and manage disease. Asthma is a complex and heterogeneous disease and cannot be solely explained by an aberrant type 2 (T2) immune response. Available and emerging multi-omics datasets of asthma show dysregulation of different biological pathways including those linked to T2 mechanisms. While T2-directed biologics have been life changing for many patients, they have not proven effective for many others despite similar biomarker profiles. Thus, there is a great need to close this gap to understand asthma heterogeneity, which can be achieved by harnessing and integrating the rich multi-omics asthma datasets and the corresponding clinical data. This article presents a compendium of machine learning approaches that can be utilized to bridge the gap between predictive biomarkers and actual causal signatures that are validated in clinical trials to ultimately establish true asthma endotypes.

Influence of the environment on the characteristics of asthma

Few studies have compared the prevalence of asthma in urban and rural settings or explored the issue of whether these two manifestations of the disease may represent different phenotypes. The aim of this study was: (a) to establish whether the prevalence of asthma differs between rural and urban settings, and b) to identify differences in the clinical presentation of asthma in these two environments. Descriptive epidemiological study involving individuals aged 18 or over from a rural (n = 516) and an urban population (n = 522). In the first phase, individuals were contacted by letter in order to organize the administration of a first validated questionnaire (Q1) designed to establish the possible prevalence of bronchial asthma. In the second phase, patients who had presented association patterns in the set of variables related to asthma in Q1 completed a second validated questionnaire (Q2), designed to identify the characteristics of asthma. According to Q1, the prevalence of asthma was 15% (n = 78) and 11% (n = 59) in rural and urban populations respectively. Sixty-five individuals with asthma from the rural population and all 59 individuals from the urban population were contacted and administered the Q2. Thirty-seven per cent of the individuals surveyed had previously been diagnosed with bronchial asthma (35% in the rural population and 40% in the urban setting). In the urban asthmatic population there was a predominance of women, a greater personal history of allergic rhinitis and a family history of allergic rhinitis and/or eczema. Asthma was diagnosed in adulthood in 74.8% of the patients, with no significant differences between the two populations. Regarding symptoms, cough (morning, daytime and night) and expectoration were more frequent in the urban population. The prevalence of asthma does not differ between urban and rural settings. The differences in exposure that characterize each environment may lead to different manifestations of the disease and may also affect its severity.

Transcriptome analysis of sputum cells reveals two distinct molecular phenotypes of “asthma and chronic obstructive pulmonary disease overlap” in the elderly

Background

Little is known about the pathogenesis of asthma and chronic obstructive pulmonary disease (COPD) overlap (ACO). This study examined the molecular phenotypes of ACO in the elderly.

Methods

A genome-wide investigation of gene expression in sputum cells from the elderly with asthma, ACO, or COPD was performed using gene set variation analysis (GSVA) with predefined asthma- or COPD-specific gene signatures. We then performed a subsequent cluster analysis using enrichment scores (ESs) to identify molecular clusters in the elderly with ACO. Finally, a second GSVA was conducted with curated gene signatures to gain insight into the pathogenesis of ACO associated with the identified molecular clusters.

Results

Seventy elderly individuals were enrolled (17 with asthma, 41 with ACO, and 12 with COPD). Two distinct molecular clusters of ACO were identified. Clinically, ACO cluster 1 (N = 23) was characterized by male and smoker dominance, more obstructive lung function, and higher proportions of both neutrophil and eosinophil in induced sputum compared to ACO cluster 2 (N = 18). ACO cluster 1 had molecular features similar to both asthma and COPD, with mitochondria and peroxisome dysfunction as important mechanisms in the pathogenesis of these diseases. The molecular features of ACO cluster 2 differed from those of asthma and COPD, with enhanced innate immune reactions to microorganisms identified as being important in the pathogenesis of this form of ACO.

Conclusion

Recognition of the unique biological pathways associated with the two distinct molecular phenotypes of ACO will deepen our understanding of ACO in the elderly.

Identification of miRNA-mRNA-TFs regulatory network and crucial pathways involved in asthma through advanced systems biology approaches

Asthma is a life-threatening and chronic inflammatory lung disease that is posing a true global health challenge. The genetic basis of the disease is fairly well examined. However, the molecular crosstalk between microRNAs (miRNAs), target genes, and transcription factors (TFs) networks and their contribution to disease pathogenesis and progression is not well explored. Therefore, this study was aimed at dissecting the molecular network between mRNAs, miRNAs, and TFs using robust computational biology approaches. The transcriptomic data of bronchial epithelial cells of severe asthma patients and healthy controls was studied by different systems biology approaches like differentially expressed gene detection, functional enrichment, miRNA-target gene pairing, and mRNA-miRNA-TF molecular networking. We detected the differential expression of 1703 (673 up-and 1030 down-regulated) genes and 71 (41 up-and 30 down-regulated) miRNAs in the bronchial epithelial cells of asthma patients. The DEGs were found to be enriched in key pathways like IL-17 signaling (KEGG: 04657), Th1 and Th2 cell differentiation (KEGG: 04658), and the Th17 cell differentiation (KEGG: 04659) (p-values = 0.001). The results from miRNAs-target gene pairs-transcription factors (TFs) have detected the key roles of 3 miRs (miR-181a-2-3p; miR-203a-3p; miR-335-5p), 6 TFs (TFAM, FOXO1, GFI1, IRF2, SOX9, and HLF) and 32 miRNA target genes in eliciting autoimmune reactions in bronchial epithelial cells of the respiratory tract. Through systemic implementation of comprehensive system biology tools, this study has identified key miRNAs, TFs, and miRNA target gene pairs as potential tissue-based asthma biomarkers.

The Role of Systems Biology in Deciphering Asthma Heterogeneity

Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma.

Omics technologies in allergy and asthma research: An EAACI position paper

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Galectin-10 as a Potential Biomarker for Eosinophilic Diseases

Galectin-10 is a member of the lectin family and one of the most abundant cytoplasmic proteins in human eosinophils. Except for some myeloid leukemia cells, basophils, and minor T cell populations, galectin-10 is exclusively present in eosinophils in the human body. Galectin-10 forms Charcot–Leyden crystals, which are observed in various eosinophilic diseases. Accumulating studies have indicated that galectin-10 acts as a new biomarker for disease activity, diagnosis, and treatment effectiveness in asthma, eosinophilic esophagitis, rhinitis, sinusitis, atopic dermatitis, and eosinophilic granulomatosis with polyangiitis. The extracellular release of galectin-10 is not mediated through conventional secretory processes (piecemeal degranulation or exocytosis), but rather by extracellular trap cell death (ETosis), which is an active cell death program. Eosinophils undergoing ETosis rapidly disintegrate their plasma membranes to release the majority of galectin-10. Therefore, elevated galectin-10 levels in serum and tissue suggest a high degree of eosinophil ETosis. To date, several studies have shown that galectin-10/Charcot–Leyden crystals are more than just markers for eosinophilic inflammation, but play functional roles in immunity. In this review, we focus on the close relationship between eosinophils and galectin-10, highlighting this protein as a potential new biomarker in eosinophilic diseases.

Identification of key modules and hub genes for eosinophilic asthma by weighted gene co-expression network analysis

Objective: Eosinophilic asthma (EA) is one of the most important asthma phenotypes with distinct features. However, its genetic characteristics are not fully understood. This study aimed to investigate the transcriptome features and to identify hub genes of EA.Methods: Differentially expressed genes (DEGs) analysis, weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were performed to construct gene networks and to identify hub genes. Enrichment analyses were performed to investigate the biological processes, pathways and immune status of EA. The hub genes were validated in another dataset. The diagnostic value of the identified hub genes was assessed by receiver operator characteristic curve (ROC) analysis.Results: Compared with NEA, EA had a different gene expression pattern, in which 81 genes were differentially expressed. WGCNA identified two gene modules significantly associated with EA. Intersections of the DEGs and the genes in the modules associated with EA were mainly enriched in chemotaxis and signal transduction by GO and KEGG enrichment analyses. Single-sample gene set enrichment analysis indicated that EA had different immune infiltration and functions compared with NEA. Seven hub genes of EA were identified and validated, including CCL17, CCL26, CD1C, CXCL11, CXCL10, CCL22 and CCR7, all of which have diagnostic value for distinguishing EA from NEA (All AUC >0.7) .Conclusions: This study demonstrated the distinct gene expression patterns, biological processes and immune status of EA. Hub genes of EA were identified and validated. Our study could provide a framework of co-expression gene modules and potential therapeutic targets for EA.

Epithelial cell responses to rhinovirus identify an early-life-onset asthma phenotype in adults

BACKGROUND

The study of pathogenic mechanisms in adult asthma is often marred by a lack of precise information about the natural history of the disease. Children who have persistent wheezing (PW) during the first 6 years of life and whose symptoms start before age 3 years (PW+) are much more likely to have wheezing illnesses due to rhinovirus (RV) in infancy and to have asthma into adult life than are those who do not have PW (PW-).

OBJECTIVE

Our aim was to determine whether nasal epithelial cells from PW+ asthmatic adults as compared with cells from PW- asthmatic adults show distinct biomechanistic processes activated by RV exposure.

METHODS

Air-liquid interface cultures derived from nasal epithelial cells of 36-year old participants with active asthma with and without a history of PW in childhood (10 PW+ participants and 20 PW- participants) from the Tucson Children's Respiratory Study were challenged with a human RV-A strain (RV-A16) or control, and their RNA was sequenced.

RESULTS

A total of 35 differentially expressed genes involved in extracellular remodeling and angiogenesis distinguished the PW+ group from the PW- group at baseline and after RV-A stimulation. Notably, 22 transcriptomic pathways showed PW-by-RV interactions; the pathways were invariably overactivated in PW+ patients, and were involved in Toll-like receptor- and cytokine-mediated responses, remodeling, and angiogenic processes.

CONCLUSIONS

Asthmatic adults with a history of persistent wheeze in the first 6 years of life have specific biomolecular alterations in response to RV-A that are not present in patients without such a history. Targeting these mechanisms may slow the progression of asthma in these patients.

Lung function, airway and peripheral basophils and eosinophils are associated with molecular pharmacogenomic endotypes of steroid response in severe asthma

INTRODUCTION

Asthma is a complex disease with heterogeneous expression/severity. There is growing interest in defining asthma endotypes consistently associated with different responses to therapy, focusing on type 2 inflammation (Th2) as a key pathological mechanism. Current asthma endotypes are defined primarily by clinical/laboratory criteria. Each endotype is likely characterised by distinct molecular mechanisms that identify optimal therapies.

METHODS

We applied unsupervised (without a priori clinical criteria) principal component analysis on sputum airway cells RNA-sequencing transcriptomic data from 19 asthmatics from the Severe Asthma Research Program at baseline and 6-8 weeks follow-up after a 40 mg dose of intramuscular corticosteroids. We investigated principal components PC1, PC3 for association with 55 clinical variables.

RESULTS

PC3 was associated with baseline Th2 clinical features including blood (rank-sum p=0.0082) and airway (rank-sum p=0.0024) eosinophilia, FEV₁ change (Kendall tau-b R=-0.333 (-0.592 to -0.012)) and follow-up FEV₁ albuterol response (Kendall tau-b R=0.392 (0.079 to 0.634)). PC1 with blood basophlia (rank-sum p=0.0191). The top 5% genes contributing to PC1, PC3 were enriched for distinct immune system/inflammation ontologies suggesting distinct subject-specific clusters of transcriptomic response to corticosteroids. PC3 association with FEV₁ change was reproduced in silico in a comparable independent 14-subject (baseline, 8 weeks after daily inhaled corticosteroids (ICS)) airway epithelial cells microRNAome dataset.

CONCLUSIONS

Transcriptomic PCs from this unsupervised methodology define molecular pharmacogenomic endotypes that may yield novel biology underlying different subject-specific responses to corticosteroid therapy in asthma, and optimal personalised asthma care. Top contributing genes to these PCs may suggest new therapeutic targets.

Exploration of induced sputum BIRC3 levels and clinical implications in asthma

BACKGROUND

Baculoviral IAP repeat-containing 3 (BIRC3) which encodes a member of the IAP family of proteins upregulated in the asthma expression profile dataset. However, there was few research on studying the clinical implication of BIRC3 in asthma.

OBJECTIVE

To validate BIRC3 expression and its clinical implications in induced sputum of asthma.

METHODS

Based on the GSE76262 (118 asthma cases and 21 healthy controls) dataset, differentially expressed genes were screened using R software. Subsequently, BIRC3 mRNA and protein were clinically verified in induced sputum samples through quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA). Besides, the correlations between BIRC3 expression and asthmatic eosinophilic/allergic inflammation indicators (FeNO, IgE, and EOS%), pulmonary function (FEV₁, FEV₁% pred, FVC% pred, and FEV₁/FVC), and inflammatory cytokines (IL-4, IL-5, IL-13, IL-25, IL-10, IL-33, and TSLP) were analyzed. Finally, BIRC3 mRNA was detected in human primary bronchial epithelial cells stimulated by cytokines (IL-4 or IL-13).

RESULTS

BIRC3 was screened as a candidate gene in the GSE76262, which was highly expressed in asthma. Highly expressed BIRC3 was positively correlated with eosinophilic and allergic indicators, including FeNO, blood eosinophil, and serum IgE. Moreover, BIRC3 protein was positively associated with inflammation cytokines, like IL-4, IL-5, IL-13, IL-25, IL-10, IL-33, and TSLP, while negatively correlated with FEV1, FEV1%pred, FVC% pred, and FEV1/FVC. Furthermore, the expression of BIRC3 could be induced in primary bronchial epithelial cells treated by cytokines IL-4 or IL-13.

CONCLUSIONS

BIRC3 significantly increased in induced sputum of asthma and positively correlated with airway eosinophilic and peripheral blood allergic inflammation, type 2 cytokines, and airway obstruction. Increased BIRC3 might be involved in the pathogenesis of asthma by affecting the eosinophilic and allergic inflammation.

A sputum 6-gene signature predicts airway inflammation endotypes and exacerbation frequency in chronic obstructive pulmonary disease

Aim: To validate a sputum 6-gene signature (6GS), comprising of CLC, CPA, DNASE1L3, IL-1B, ALPL and CXCR2, for identifying different endotypes in chronic obstructive pulmonary disease. Methodology & results: Sputum cell CLC, CPA3 and DNASE1L3 gene expression correlated with eosinophil percentage, while IL-1B, ALPL and CXCR2 correlated with neutrophil percentage. Hierarchical cluster analyses of IL-1B, ALPL and CXCR2, and CLC, CPA3 and DNASE1L3, identified patient groups that differed in their sputum neutrophil and eosinophil levels, respectively. Multiple logistic regressions demonstrated that the 6GS could distinguish between eosinophil^High and eosinophil^Low patients, as well as neutrophil^High and neutrophil^Low, and could also predict exacerbation history. Conclusion: The 6GS may have applications in clinical practice or for stratifying patients for clinical trials.

Identification of Key Signaling Pathways and Genes in Eosinophilic Asthma and Neutrophilic Asthma by Weighted Gene Co-Expression Network Analysis

Background: Asthma is a heterogeneous disease with different subtypes including eosinophilic asthma (EA) and neutrophilic asthma (NA). However, the mechanisms underlying the difference between the two subtypes are not fully understood.

Methods: Microarray datasets (GSE45111 and GSE137268) were acquired from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in induced sputum between EA (n = 24) and NA (n = 15) were identified by “Limma” package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and Gene set enrichment analysis (GSEA) were used to explore potential signaling pathways. Weighted gene co-expression network analysis (WGCNA) were performed to identify the key genes that were strongly associated with EA and NA.

Results: A total of 282 DEGs were identified in induced sputum of NA patients compared with EA patients. In GO and KEGG pathway analyses, DEGs were enriched in positive regulation of cytokine production, and cytokine-cytokine receptor interaction. The results of GSEA showed that ribosome, Parkinson’s disease, and oxidative phosphorylation were positively correlated with EA while toll-like receptor signaling pathway, primary immunodeficiency, and NOD-like receptor signaling pathway were positively correlated with NA. Using WGCNA analysis, we identified a set of genes significantly associated NA including IRFG, IRF1, STAT1, IFIH1, IFIT3, GBP1, GBP5, IFIT2, CXCL9, and CXCL11.

Conclusion: We identified potential signaling pathways and key genes involved in the pathogenesis of the asthma subsets, especially in neutrophilic asthma.

Effects of azithromycin on bronchial remodeling in the natural model of severe neutrophilic asthma in horses

Steroid resistance in asthma has been associated with neutrophilic inflammation and severe manifestations of the disease. Macrolide add-on therapy can improve the quality of life and the exacerbation rate in refractory cases, possibly with greater effectiveness in neutrophilic phenotypes. The mechanisms leading to these beneficial effects are incompletely understood and whether macrolides potentiate the modulation of bronchial remodeling induced by inhaled corticosteroids (ICS) is unknown. The objective of this study was to determine if adding azithromycin to ICS leads to further improvement of lung function, airway inflammation and bronchial remodeling in severe asthma. The combination of azithromycin (10 mg/kg q48h PO) and inhaled fluticasone (2500 µg q12h) was compared to the sole administration of fluticasone for five months in a randomized blind trial where the lung function, airway inflammation and bronchial remodeling (histomorphometry of central and peripheral airways and endobronchial ultrasound) of horses with severe neutrophilic asthma were assessed. Although the proportional reduction of airway neutrophilia was significantly larger in the group receiving azithromycin, the lung function and the peripheral and central airway smooth muscle mass decreased similarly in both groups. Despite a better control of airway neutrophilia, azithromycin did not potentiate the other clinical effects of fluticasone.

Identification of the molecular subgroups in asthma by gene expression profiles: airway inflammation implications

Background

Asthma is a heterogeneous disease and different phenotypes based on clinical parameters have been identified. However, the molecular subgroups of asthma defined by gene expression profiles of induced sputum have been rarely reported.

Methods

We re-analyzed the asthma transcriptional profiles of the dataset of GSE45111. A deep bioinformatics analysis was performed. We classified 47 asthma cases into different subgroups using unsupervised consensus clustering analysis. Clinical features of the subgroups were characterized, and their biological function and immune status were analyzed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and single sample Gene Set Enrichment Analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) network were performed to identify key gene modules and hub genes.

Results

Unsupervised consensus clustering of gene expression profiles in asthma identified two distinct subgroups (Cluster I/II), which were significantly associated with eosinophilic asthma (EA) and paucigranulocytic asthma (PGA). The differentially expressed genes (DEGs) between the two subgroups were primarily enriched in immune response regulation and signal transduction. The ssGSEA suggested the different immune infiltration and function scores between the two clusters. The WGCNA and PPI analysis identified three hub genes: THBS1, CCL22 and CCR7. ROC analysis further suggested that the three hub genes had a good ability to differentiate the Cluster I from the Cluster II.

Conclusions

Based on the gene expression profiles of the induced sputum, we identified two asthma subgroups, which revealed different clinical characteristics, gene expression patterns, biological functions and immune status. The transcriptional classification confirms the molecular heterogeneity of asthma and provides a framework for more in-depth research on the mechanisms of asthma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01824-3.

Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma

Background

Asthma is a heterogeneous disease that can be divided into four inflammatory phenotypes: eosinophilic asthma (EA), neutrophilic asthma (NA), mixed granulocytic asthma (MGA), and paucigranulocytic asthma (PGA). While research has mainly focused on EA and NA, the understanding of PGA is limited. In this study, we aimed to identify underlying mechanisms and hub genes of PGA.

Methods

Based on the dataset from Gene Expression Omnibus(GEO), weighted gene coexpression network analysis (WGCNA), differentially expressed genes (DEGs) analysis and protein–protein interaction (PPI) network analysis were conducted to construct a gene network and to identify key gene modules and hub genes. Functional enrichment analyses were performed to investigate the biological process, pathways and immune status of PGA. The hub genes were validated in a separate dataset.

Results

Compared to non-PGA, PGA had a different gene expression pattern, in which 449 genes were differentially expressed. One gene module significantly associated with PGA was identified. Intersection between the differentially expressed genes (DEGs) and the genes from the module that were most relevant to PGA were mainly enriched in inflammation and immune response regulation. The single sample Gene Set Enrichment Analysis (ssGSEA) suggested a decreased immune infiltration and function in PGA. Finally six hub genes of PGA were identified, including ADCY2, CXCL1, FPRL1, GPR109B, GPR109A and ADCY3, which were validated in a separate dataset of GSE137268.

Conclusions

Our study characterized distinct gene expression patterns, biological processes and immune status of PGA and identified hub genes, which may improve the understanding of underlying mechanism and provide potential therapeutic targets for PGA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01711-3.

Increased MMP12 mRNA expression in induced sputum was correlated with airway eosinophilic inflammation in asthma patients: evidence from bioinformatic analysis and experiment verification

BACKGROUND

Asthma is a common chronic airway inflammatory disease worldwide. Studies on gene expression profiles in induced sputum may provide noninvasive diagnostic biomarkers and therapeutic targets for asthma.

OBJECTIVE

To investigate mRNA expression of MMP12 in induced sputum and its relationship with asthma airway eosinophilic inflammation.

METHODS

GSE76262 dataset was analyzed using R software, weighted gene coexpression network analysis (WGCNA), and protein-protein interaction (PPI) network construction. The top ten hub genes were screened with Cytoscape software (version 3.8.4). We then verified the mRNA expression of MMP12 in two other datasets (GSE137268 and GSE74075) via ROC curve estimates and our induced sputum samples using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Finally, we explored the correlation between MMP12 with asthmatic eosinophilic-related indicators.

RESULTS

We obtained the top ten hub genes, namely, CCL17, CCL2, CSF1, CCL22, CCR3, CD69, FCGR2B, CD1C, CD1E, and MMP12 via expression profile screening and validation on the GSE76262 dataset. MMP12 was selected as the candidate gene through further validation on GSE137268 and GSE74075 datasets. Finally, we demonstrated that the mRNA expression of MMP12 is significantly upregulated in induced sputum of asthmatic patients (p<0.05) and significantly correlated with eosinophilic-related indicators (p<0.05). These findings indicated that MMP12 can act as a diagnostic biomarker for asthma.

CONCLUSION

Our study successfully identified and demonstrated that MMP12 is a potential diagnostic biomarker for asthma due to its high expression and association with eosinophilic-related indicators. The results of this study can provide novel insights into asthmatic diagnosis and therapy in the future.

Management Strategies to Reduce Exacerbations in non-T2 Asthma

There have been considerable advances in our understanding of asthmatic airway inflammation, resulting in a paradigm shift of classifying individuals on the basis of either the presence or the absence of type 2 (T2) inflammatory markers. Several novel monoclonal antibody therapies targeting T2 cytokines have demonstrated significant clinical effects including reductions in acute exacerbations and improvements in asthma-related quality of life and lung function for individuals with T2-high asthma. However, there have been fewer advancements in developing therapies for those without evidence of T2 airway inflammation (so-called non-T2 asthma). Here, we review the heterogeneity of molecular mechanisms responsible for initiation and regulation of non-T2 inflammation and discuss both current and potential future therapeutic options for individuals with non-T2 asthma.

Sputum Gene Expression Reveals Dysregulation of Mast Cells and Basophils in Eosinophilic COPD

Purpose

The clinical and inflammatory associations of mast cells (MCs) and basophils in chronic obstructive pulmonary disease (COPD) are poorly understood. We previously developed and validated a qPCR-based MC/basophil gene signature in asthma to measure these cells in sputum samples. Here, we measured this gene signature in a COPD and control population to explore the relationship of sputum MCs/basophils to inflammatory and COPD clinical characteristics.

Patients and Methods

MC/basophil signature genes (TPSAB1/TPSB2, CPA3, ENO2, GATA2, KIT, GPR56, HDC, SOCS2) were measured by qPCR in sputum from a COPD (n=96) and a non-respiratory control (n=17) population. Comparative analyses of gene expression between the COPD and the control population, and between eosinophilic COPD and non-eosinophilic COPD were tested. Logistic regression analysis and Spearman correlation were used to determine relationships of sputum MC/basophil genes to inflammatory (sputum eosinophil proportions, blood eosinophils) and clinical (age, body mass index, quality of life, lung function, past year exacerbations) characteristics of COPD.

Results

MC/basophil genes were increased in COPD versus control participants (CPA3, KIT, GATA2, HDC) and between eosinophilic-COPD and non-eosinophilic COPD (TPSB2, CPA3, HDC, SOCS2). We found all MC/basophil genes were positively intercorrelated. In COPD, MC/basophil genes were associated with eosinophilic airway inflammation (GATA2, TPSB2, CPA3, GPR56, HDC, SOCS2), blood eosinophilia (all genes) and decreased lung function (KIT, GATA2, GPR56, HDC).

Conclusion

We demonstrate associations of MCs and basophils with eosinophilic inflammation and lower lung function in COPD. These findings are consistent with prior results in asthma and may represent a new tool for endotyping eosinophilic-COPD.

The effects of increasing fruit and vegetable intake in children with asthma: A randomized controlled trial

BACKGROUND

A high fruit and vegetable (F&V) diet reduces asthma exacerbations in adults; this has not been examined in children to date.

OBJECTIVE

To investigate the effect of a 6-month, high F&V diet on the time to first asthma exacerbation in children with asthma, in a parallel-group, randomized, controlled trial.

METHODS

Children (aged 3-11 years) with asthma, history of exacerbations and usual low F&V intake (≤3 serves/day) were randomized to the intervention (high F&V diet) or control group (usual diet) for 6 months. The primary outcome was time to first exacerbation requiring medical intervention. Secondary outcomes included exacerbation rate, lung function, plasma TNF-α, CRP, and IL-6, faecal microbiota and peripheral blood mononuclear cell (PBMC) histone deacetylase (HDAC) activity and G-protein coupled receptor (GPR) 41/43 and HDAC (1-11) expression.

RESULTS

67 children were randomized between September 2015 and July 2018. F&V intake (difference in change (∆): 3.5 serves/day, 95% CI: [2.6, 4.4] p < 0.001) and plasma total carotenoids (∆: 0.44 µg/ml [0.19, 0.70] p = 0.001) increased after 6 months (intervention vs control). Time to first exacerbation (HR: 0.81, 95% CI: [0.38, 1.69], p = 0.569) and exacerbation rate (IRR: 0.84, [0.47, 1.49], p = 0.553) were similar between groups. In per-protocol analysis, airway reactance z-scores increased (X₅ ∆: 0.76 [0.04, 1.48] p = 0.038, X₂₀ ∆: 0.93 [0.23, 1.64] p = 0.009) and changes in faecal microbiota were observed, both in the intervention versus control group, though there was no difference between groups in systemic inflammation or molecular mechanisms. In the control group, CRP and HDAC enzyme activity increased, while GPR41 expression decreased. No adverse events attributable to the interventions were observed.

CONCLUSION & CLINICAL RELEVANCE

A high F&V diet did not affect asthma exacerbations over the 6-month intervention, though warrants further investigation as a strategy for improving lung function and protecting against systemic inflammation in children with asthma.

Molecular markers of type 2 airway inflammation are similar between eosinophilic severe asthma and eosinophilic chronic obstructive pulmonary disease

BACKGROUND

Airway and systemic eosinophilia are important treatable traits in both severe asthma and COPD. The molecular basis of eosinophilia in COPD is poorly understood but could involve type 2 cytokines (IL5, IL13) and prostaglandin D₂ (PGD₂ ).

METHODS

This study included non-obstructive airways disease (OAD) controls (n = 19), a COPD cohort (n = 96) and a severe asthma cohort (n = 84). Demographics, exacerbation history, disease impact (SGRQ) and spirometry were assessed. Participants were categorized as eosinophilic using either sputum eosinophil proportion (≥3%) or blood eosinophil count (≥300/μL). Sputum type 2 inflammatory measures included PGD₂ by ELISA and gene expression (qPCR) of IL5, IL13 and the haematopoietic PGD₂ synthase (HPGDS).

RESULTS

Type 2 markers did not differ across groups except HPGDS mRNA which was highest in non-OAD controls and lowest in COPD. IL5 and IL13 mRNA and PGD₂ levels were significantly increased in eosinophilic vs non-eosinophilic severe asthma but did not differ between eosinophilic COPD and eosinophilic severe asthma or non-eosinophilic COPD. HPGDS expression was higher in eosinophilic severe asthma compared with eosinophilic COPD. Results were similar using sputum or blood eosinophil cut-offs. Sputum IL5 and IL13 were highly intercorrelated in severe asthma (r = 0.907, p < 0.001) and COPD (r = 0.824, p < 0.001), were moderately correlated with sputum eosinophils in severe asthma (IL5 r = 0.440, p < 0.001; IL13 r = 0.428, p < 0.001) and were weakly correlated in COPD (IL5 r = 0.245, p < 0.05; IL13 r = 0.317, p < 0.05).

CONCLUSIONS

Molecular markers of type 2 airway inflammation do not differ between eosinophilic asthma and eosinophilic COPD; however, the relationship between eosinophilia and type 2 airway markers appears weaker in COPD than in severe asthma.

The sputum transcriptome better predicts COPD exacerbations after the withdrawal of inhaled corticosteroids than sputum eosinophils

INTRODUCTION

Continuing inhaled corticosteroid (ICS) use does not benefit all patients with COPD, yet it is difficult to determine which patients may safely sustain ICS withdrawal. Although eosinophil levels can facilitate this decision, better biomarkers could improve personalised treatment decisions.

METHODS

We performed transcriptional profiling of sputum to explore the molecular biology and compared the predictive value of an unbiased gene signature versus sputum eosinophils for exacerbations after ICS withdrawal in COPD patients. RNA-sequencing data of induced sputum samples from 43 COPD patients were associated with the time to exacerbation after ICS withdrawal. Expression profiles of differentially expressed genes were summarised to create gene signatures. In addition, we built a Bayesian network model to determine coregulatory networks related to the onset of COPD exacerbations after ICS withdrawal.

RESULTS

In multivariate analyses, we identified a gene signature (LGALS12, ALOX15, CLC, IL1RL1, CD24, EMR4P) associated with the time to first exacerbation after ICS withdrawal. The addition of this gene signature to a multiple Cox regression model explained more variance of time to exacerbations compared to a model using sputum eosinophils. The gene signature correlated with sputum eosinophil as well as macrophage cell counts. The Bayesian network model identified three coregulatory gene networks as well as sex to be related to an early versus late/nonexacerbation phenotype.

CONCLUSION

We identified a sputum gene expression signature that exhibited a higher predictive value for predicting COPD exacerbations after ICS withdrawal than sputum eosinophilia. Future studies should investigate the utility of this signature, which might enhance personalised ICS treatment in COPD patients.

Potential Metabolic Biomarkers in Adult Asthmatics

Asthma is the most common chronic airway inflammation, with multiple phenotypes caused by complicated interactions of genetic, epigenetic, and environmental factors. To date, various determinants have been suggested for asthma pathogenesis by a new technology termed omics, including genomics, transcriptomics, proteomics, and metabolomics. In particular, the systematic analysis of all metabolites in a biological system, such as carbohydrates, amino acids, and lipids, has helped identify a novel pathway related to complex diseases. These metabolites are involved in the regulation of hypermethylation, response to hypoxia, and immune reactions in the pathogenesis of asthma. Among them, lipid metabolism has been suggested to be related to lung dysfunction in mild-to-moderate asthma. Sphingolipid metabolites are an important mediator contributing to airway inflammation in obese asthma and aspirin-exacerbated respiratory disease. Although how these molecular variants impact the disease has not been completely determined, identification of new causative factors may possibly lead to more-personalized and precise pathway-specific approaches for better diagnosis and treatment of asthma. In this review, perspectives of metabolites related to asthma and clinical implications have been highlighted according to various phenotypes.

The Enigma of Eosinophil Degranulation

Eosinophils are specialized white blood cells, which are involved in the pathology of diverse allergic and nonallergic inflammatory diseases. Eosinophils are traditionally known as cytotoxic effector cells but have been suggested to additionally play a role in immunomodulation and maintenance of homeostasis. The exact role of these granule-containing leukocytes in health and diseases is still a matter of debate. Degranulation is one of the key effector functions of eosinophils in response to diverse stimuli. The different degranulation patterns occurring in eosinophils (piecemeal degranulation, exocytosis and cytolysis) have been extensively studied in the last few years. However, the exact mechanism of the diverse degranulation types remains unknown and is still under investigation. In this review, we focus on recent findings and highlight the diversity of stimulation and methods used to evaluate eosinophil degranulation.

Airway gene expression identifies subtypes of type 2 inflammation in severe asthma

BACKGROUND

Type 2 inflammation is characterized by enhanced activity of interleukin (IL)-4, -5 and -13, and treatments targeting these pathways are available for treatment of severe asthma. At present, the pattern of pathway activity and the implications overlapping of pathway activity are unknown.

OBJECTIVE

We hypothesized that clustering of airway mRNA expression would identify distinct molecular subtypes of severe asthma and thereby uncover the prevalence and overlap of pathway activity.

METHODS

Sputum mRNA expression of genes related to expression of IL-5(CLC, CPA3 and DNASE1L3), IL-13(IL13Ra1, TNFSF14 and SERPINB2), T1/Th17 activity(IL1B, ALPL and CXCR2) and in vitro response to corticosteroids (FKBP512) and mepolizumab (ARAP3) was analysed in patients (n = 109) with severe asthma and healthy controls (n = 22). A cluster analysis of gene expression was performed. The response to a short course of OCS was assessed in a subset of patients (n = 29).

RESULTS

Five molecular clusters were identified. Three had abundant T2 gene expression of which two (n = 39 and n = 9) were characterized by abundant expression of both IL-13- and IL-5-related genes. The last (n = 6) had only abundant IL-5-related gene expression. These T2-high molecular clusters could not be distinguished using T2 biomarkers. T2- and Th1/Th17-related mRNA expression were co-expressed across all clusters. OCS significantly reduced T2 gene expression (CLC, IL13Ra1, SERPINB2 and ARAP3) and significantly increase expression of Th1/Th17-related genes (ALPL and CXCR2).

CONCLUSIONS AND CLINICAL RELEVANCE

Clustering of airway mRNA expression identified five molecular clusters of severe asthma of which three were considered T2 high. Co-expression of IL-5- and IL-13-related genes at moderate levels was present in almost half of patients, while marked elevated expression of both was rare. In contrast to IL-5, clusters with isolated IL-13- and Th1/Th17-related gene expression were not identified.

Stability of sputum inflammatory phenotypes in childhood asthma during stable and exacerbation phases

BACKGROUND

Management strategies based on airway inflammation phenotypes are increasingly used for adults with asthma. While sputum-based phenotypes are relatively stable in adults with asthma, there is little such data in childhood asthma. Hence, we aimed to evaluate the stability of sputum inflammatory phenotypes in children with asthma both in the stable and during exacerbation phases.

METHODS

Sputum cellularity data from two previous prospective studies involving children with asthma were re-evaluated and categorized into two inflammatory phenotypes: eosinophilic (>2.5% eosinophils) and noneosinophilic (≤2.5% eosinophils). Baseline values and follow-up sputum inflammatory phenotype classification were compared in children with asthma during stable and exacerbation phases.

RESULTS

Thirteen of 32 children (41%) with stable asthma demonstrated a change in sputum inflammatory phenotype 8 weeks later. In a different second cohort, both sputum eosinophils and neutrophils percentages increased and peaked on Day 1 of asthma exacerbation, but compared with baseline, 22% (2/9) and 13% (1/8) of these children had their sputum phenotype categorization changed on Day 1 and Day 3 of exacerbation, respectively.

CONCLUSION

In children with asthma, sputum inflammatory phenotypes are variable in both stable and exacerbation phases, in contrast to data in adults.

Single-cell characterization of a model of poly I:C-stimulated peripheral blood mononuclear cells in severe asthma

Background

Asthma has been associated with impaired interferon response. Multiple cell types have been implicated in such response impairment and may be responsible for asthma immunopathology. However, existing models to study the immune response in asthma are limited by bulk profiling of cells. Our objective was to Characterize a model of peripheral blood mononuclear cells (PBMCs) of patients with severe asthma (SA) and its response to the TLR3 agonist Poly I:C using two single-cell methods.

Methods

Two complementary single-cell methods, DropSeq for single-cell RNA sequencing (scRNA-Seq) and mass cytometry (CyTOF), were used to profile PBMCs of SA patients and healthy controls (HC). Poly I:C-stimulated and unstimulated cells were analyzed in this study.

Results

PBMCs (n = 9414) from five SA (n = 6099) and three HC (n = 3315) were profiled using scRNA-Seq. Six main cell subsets, namely CD4 + T cells, CD8 + T cells, natural killer (NK) cells, B cells, dendritic cells (DCs), and monocytes, were identified. CD4 + T cells were the main cell type in SA and demonstrated a pro-inflammatory profile characterized by increased JAK1 expression. Following Poly I:C stimulation, PBMCs from SA had a robust induction of interferon pathways compared with HC. CyTOF profiling of Poly I:C stimulated and unstimulated PBMCs (n = 160,000) from the same individuals (SA = 5; HC = 3) demonstrated higher CD8 + and CD8 + effector T cells in SA at baseline, followed by a decrease of CD8 + effector T cells after poly I:C stimulation.

Conclusions

Single-cell profiling of an in vitro model using PBMCs in patients with SA identified activation of pro-inflammatory pathways at baseline and strong response to Poly I:C, as well as quantitative changes in CD8 + effector cells. Thus, transcriptomic and cell quantitative changes are associated with immune cell heterogeneity in this model to evaluate interferon responses in severe asthma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-021-01709-9.

High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status

Clinical definitions of asthma fail to capture the heterogeneity of immune dysfunction in severe, treatment-refractory disease. Applying mass cytometry and machine learning to bronchoalveolar lavage (BAL) cells, we find that corticosteroid-resistant asthma patients cluster largely into two groups: one enriched in interleukin (IL)-4+ innate immune cells and another dominated by interferon (IFN)-γ+ T cells, including tissue-resident memory cells. In contrast, BAL cells of a healthier population are enriched in IL-10+ macrophages. To better understand cellular mediators of severe asthma, we developed the Immune Cell Linkage through Exploratory Matrices (ICLite) algorithm to perform deconvolution of bulk RNA sequencing of mixed-cell populations. Signatures of mitosis and IL-7 signaling in CD206-FcεRI+CD127+IL-4+ innate cells in one patient group, contrasting with adaptive immune response in T cells in the other, are preserved across technologies. Transcriptional signatures uncovered by ICLite identify T-cell-high and T-cell-poor severe asthma patients in an independent cohort, suggesting broad applicability of our findings.