Six gene and TH2 signature expression in endobronchial biopsies of participants with asthma

Bioinformatics analysis revealed underlying molecular mechanisms associated with asthma severity and identified GABAergic related pathway as a potential therapy for Th2-high endotype asthma

Background

Asthma, a principally T helper 2 (Th2) cell mediated immunological disease, is categorized into Th2-high and Th2-low endotypes. The influence of these endotypes on clinical characteristics and treatment responsiveness in asthma is yet to be completely understood. This study delves into the underlying molecular mechanisms of Th2 endotypes on asthma.

Methods

Transcriptomics data of airway epithelial and corresponding clinical information were sourced from the GEO. The co-expression modules were established by WGCNA. Cytoscape was applied to construct PPI networks, and hub genes were determined via the Cytohubba plugin. Additionally, a functional enrichment analysis was conducted on the co-expressed genes from the relevant modules. The relative abundances levels of 22 different types of immune cells in asthma patients were evaluated by CIBERSORT algorithm.

Results

There were 471 genes in the pink module significantly correlated with Th2 endotype. Overall, 151 DEGs were identified in the various Th2 endotypes, and 66 were obtained through intersection with the pink module. In the PPI network, the ten most important genes that regulate Th2 endotypes were selected as hub genes. In Th2-high endotype asthma, the hub genes were significantly related to γ-aminobutyric acid (GABA) pathways, indicating that hub genes can mainly regulate Th2-high endotype asthma through GABAergic system.

Conclusions

The severity of asthma is influenced by different Th2 endotypes. GABAergic related hub genes may provide innovative insights for the treatment of Th2-high asthma.

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.

Pathways linked to unresolved inflammation and airway remodelling characterize the transcriptome in two independent severe asthma cohorts

Background and objective

Severe asthma (SA) is a heterogeneous disease. Transcriptomic analysis contributes to the understanding of pathogenesis necessary for developing new therapies. We sought to identify and validate mechanistic pathways of SA across two independent cohorts.

Methods

Transcriptomic profiles from U‐BIOPRED and Australian NOVocastrian Asthma cohorts were examined and grouped into SA, mild/moderate asthma (MMA) and healthy controls (HCs). Differentially expressed genes (DEGs), canonical pathways and gene sets were identified as central to SA mechanisms if they were significant across both cohorts in either endobronchial biopsies or induced sputum.

Results

Thirty‐six DEGs and four pathways were shared across cohorts linking to tissue remodelling/repair in biopsies of SA patients, including SUMOylation, NRF2 pathway and oxidative stress pathways. MMA presented a similar profile to HCs. Induced sputum demonstrated IL18R1 as a shared DEG in SA compared with healthy subjects. We identified enrichment of gene sets related to corticosteroid treatment; immune‐related mechanisms; activation of CD4⁺ T cells, mast cells and IL18R1; and airway remodelling in SA.

Conclusion

Our results identified differentially expressed pathways that highlight the role of CD4⁺ T cells, mast cells and pathways linked to ongoing airway remodelling, such as IL18R1, SUMOylation and NRF2 pathways, as likely active mechanisms in the pathogenesis of SA.

Transcriptome analysis from endobronchial biopsies and induced sputum from two independent cohorts of adults with severe asthma (SA) (U‐BIOPRED and Australian NOVocastrian Asthma cohort) demonstrated shared differentially expressed pathways previously linked to persistent unresolved inflammation and novel mechanisms of airway remodelling, which may represent potential novel mechanistic pathways involved in the pathogenesis of SA.

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Construction of Severe Eosinophilic Asthma Related Competing Endogenous RNA Network by Weighted Gene Co-Expression Network Analysis

Background: Currently, disease control in patients with severe eosinophilic asthma is not optimistic. Competing endogenous RNA (ceRNA) networks have been found to play a key role in asthma in recent years. However, it is unclear whether ceRNA networks play an important part in severe eosinophilic asthma. Methods: Firstly, gene expression profiles related to severe eosinophilic asthma were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, the key modules were identified by the weighted gene co-expression network analysis (WGCNA). Thirdly, genes in modules highly associated with severe eosinophilic asthma were selected for further construction of the ceRNA network. Fourthly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on hub genes. Finally, the results of this study were validated on the GSE143303, GSE137268, and GSE147878 datasets. Results: 22 severe eosinophilic asthmatics and 13 healthy controls were extracted for WGCNA. We found that the genes in the black module (r = -0.75, p < 0.05) and yellow module (r = 0.65, p < 0.05) were highly associated with severe eosinophilic asthma. EP300 was discovered to serve the key connecting function in the ceRNA network. Surprisingly, lncRNAs seem to eliminate the role of EP300 in the black module and we discovered that CCT8 and miRNA-mRNA formed a circRNA-miRNA-mRNA network in the yellow module. We found that EP300 and FOXO3 in the black module were regulated by steroid hormones in the enrichment analysis, which were related to the medication used by the patient. Through validation of other datasets, we found that the hub genes in the yellow module were the key genes in the treatment of severe eosinophilic asthma. In particular, RPL17 and HNRNPK might specifically regulate severe eosinophilic asthma. Conclusion: RPL17 and HNRNPK might particularly regulate severe eosinophilic asthma. Our results could be useful to provide potential immunotherapy targets and prognostic markers for severe eosinophilic asthma.

The Transcriptome Characteristics of Severe Asthma From the Prospect of Co-Expressed Gene Modules

Rationale: Severe asthma is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of asthmatic bronchial epithelial cells have provided biological insights and underscored possible pathological mechanisms; however, the molecular basis in severe asthma is still poorly understood.

Objective: The objective of this study was to identify the features of asthma and uncover the molecular basis of severe asthma in distinct molecular phenotype.

Methods: The k-means clustering and differentially expressed genes (DEGs) were performed in 129 asthma individuals in the Severe Asthma Research Program. The DEG profiles were analyzed by weighted gene co-expression network analysis (WGCNA), and the expression value of each gene module in each individual was annotated by gene set variation analysis (GSVA).

Results: Expression analysis defined five stable asthma subtype (AS): 1) Phagocytosis-Th2, 2) Normal-like, 3) Neutrophils, 4) Mucin-Th2, and 5) Interferon-Th1 and 15 co-expressed gene modules. “Phagocytosis-Th2” enriched for receptor-mediated endocytosis, upregulation of Toll-like receptor signal, and myeloid leukocyte activation. “Normal-like” is most similar to normal samples. “Mucin-Th2” preferentially expressed genes involved in O-glycan biosynthesis and unfolded protein response. “Interferon-Th1” displayed upregulation of genes that regulate networks involved in cell cycle, IFN gamma response, and CD8 TCR. The dysregulation of neural signal, REDOX, apoptosis, and O-glycan process were related to the severity of asthma. In non-TH2 subtype (Neutrophils and Interferon-Th1) with severe asthma individuals, the neural signals and IL26-related co-expression module were dysregulated more significantly compared to that in non-severe asthma. These data infer differences in the molecular evolution of asthma subtypes and identify opportunities for therapeutic development.

Conclusions: Asthma is a heterogeneous disease. The co-expression analysis provides new insights into the biological mechanisms related to its phenotypes and the severity.

Transcriptomics of biopsies identifies novel genes and pathways linked to neutrophilic inflammation in severe asthma

BACKGROUND

Severe asthma is a complex disease. Transcriptomic profiling has contributed to understanding the pathogenesis of asthma, especially type-2 inflammation. However, there is still poor understanding of non-type-2 asthma, and consequently, there are limited treatment options.

OBJECTIVE

The aim of this study was to identify differentially expressed genes (DEGs) and pathways in endobronchial biopsies associated with inflammatory phenotypes of severe asthma.

METHODS

This cross-sectional study examined endobronchial biopsies from 47 adults with severe asthma (neutrophilic asthma (NA) n = 9, eosinophilic asthma (EA) n = 22 and paucigranulocytic asthma (PGA) n = 16) and 13 healthy controls (HC). RNA was extracted and transcriptomic profiles generated (Illumina Humanref-12 V4) and analysed using GeneSpring GX14.9.1. Pathway identification using Ingenuity Pathway Analysis.

RESULTS

NA had the most distinct profile, with signature of 60 top-ranked DEGs (FC >±2) including genes associated with innate immunity response, neutrophil degranulation and IL-10 signalling. NA presented enrichment to pathways previously linked to neutrophilic inflammation; dendritic cell maturation, Th1, TREM1, inflammasome, Th17 and p38 MAPK, as well as novel links to neuroinflammation, NFAT and PKCθ signalling. EA presented similar transcriptomic profiles to PGA and HC. Despite the higher proportion of bacterial colonization in NA, no changes were observed in the transcriptomic profiles of severe asthma culture positive compared with severe asthma culture negative.

CONCLUSIONS & CLINICAL RELEVANCE

NA features a distinct transcriptomic profile with seven pathways enriched in NA compared to EA, PGA and HC. All those with severe asthma had significant enrichment for SUMOylation, basal cell carcinoma signalling and Wnt/β-catenin pathways compared to HC, despite high-dose inhaled corticosteroids. These findings contribute to the understanding of mechanistic pathways in endobronchial biopsies associated with NA and identify potential novel treatment targets for severe asthma.

Proteome profiling reveals the efficacy and targets of sophocarpine against asthma

Sophocarpine (SPC) as a quinolizidine alkaloid displays powerful effects on inflammatory diseases through regulating multiple targets. Asthma is a complex heterogeneous and inflammatory disease with an increasing incidence worldwide. Here we established a mice asthma model and investigated the effect of SPC. Mice induced by ovalbumin (OVA) exhibits exacerbated Th1/Th2 immune imbalance and allergic lung inflammation. SPC treatment regulated Th1/Th2 cytokines production (IL-4, IL-5 and INF-γ) in BALF, reduced IgE level in serum, inhibited inflammatory cell infiltration, and improved the lung tissue pathology. Proteomic results showed that 5064 proteins in lung tissue were detected and among them 223 preliminary therapeutic targets of SPC were selected. Subsequently, excluding non-human genes, 109 targets with established crystal structures were harvested. Meanwhile, the molecular docking results showed that the binding energy of 87 targets with SPC was varied from -9.72 kcal/mol to 227.16 kcal/mol. Further, SPC suppressed arrb2, anxa1, myd88 and sphk1 expression and activated p-stat1. All of the five targets based on the screened results of proteomics and molecular docking are critical in allergic asthma. Thus, our data revealed that SPC alleviated bronchial asthma via targeting multi-targets.

A deoxyribonuclease 1-like 3 genetic variant associates with asthma exacerbations

The analysis of genetic variants from six genes whose expression is predictive of asthma exacerbations revealed a novel association of a regulatory polymorphism from DNASE1L3 in African-Americans and Latinos.

Six gene and TH2 signature expression in endobronchial biopsies of participants with asthma

BACKGROUND

Both the six gene signature (6GS: CPA3, DNASE1L3, CLC, IL1B, ALPL, and CXCR2) and T-helper 2 signature (TH2S: CLCA1, SERPINB2, and POSTN) are proposed as biomarkers in the identification of inflammatory phenotypes of asthma in induced sputum and epithelial brushings, respectively. The aim of this study was to explore patterns of gene expression of known signatures, 6GS and TH2S in endobronchial biopsies.

METHODS

This was an exploratory cross-sectional study of gene expression in endobronchial biopsies of 55 adults with asthma and 9 healthy controls (HC). The expression of the 6GS and TH2S was determined by quantitative polymerase chain reaction. Correlations with clinical and cellular characteristics were performed, and receiver operating characteristic was utilized to assess signatures' ability to predict asthma from HC and inflammatory phenotypes.

RESULTS

Gene expression of DNASE1L3 (P = .045) was upregulated in asthma compared with HC, and IL1B (P = .017) was upregulated in neutrophilic asthma compared with non-neutrophilic asthma. In asthma, the expression of CPA3 was negatively associated with ICS daily dose (r = -.339; P = .011), IL1B expression was positively associated with bronchial lavage fluid (BLF) total cell count (r = .340; P = .013) and both CLC and POSTN expression were associated with lymphocytes percentage in BLF (r = -.355, P = .009; r = -.300, P = .025, respectively). Both 6GS (area under curve [AUC] = 86.3%; P = .017) and TH2S (AUC = 72.7%; P = .037) could significantly predict asthma from HC. In addition, 6GS can identify neutrophilic (AUC = 93.2%; P = .005) and TH2S identifies eosinophilic (AUC = 62.7%; P = .033) asthma.

CONCLUSIONS AND CLINICAL RELEVANCE

There was increased expression of DNASE1L3 in asthma and IL1B in neutrophilic asthma. These results show similar upregulated patterns of expression in two genes of the 6GS in endobronchial biopsies, previously identified in sputum. The upregulation of DNASE1L3 and IL1B suggests that common mechanisms may be at play throughout the airway.