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

Inflammation-induced loss of CFTR-expressing airway ionocytes in non-eosinophilic asthma

BACKGROUND AND OBJECTIVE

Severe asthma is a heterogeneous disease with subtype classification according to dominant airway infiltrates, including eosinophilic (Type 2 high), or non-eosinophilic asthma. Non-eosinophilic asthma is further divided into paucigranulocytic or neutrophilic asthma characterized by elevated neutrophils, and mixed Type 1 and Type 17 cytokines in the airways. Severe non-eosinophilic asthma has few effective treatments and many patients do not qualify for biologic therapies. The cystic fibrosis transmembrane conductance regulator (CFTR) is dysregulated in multiple respiratory diseases including cystic fibrosis and chronic obstructive pulmonary disease and has proven a valuable therapeutic target. We hypothesized that the CFTR may also play a role in non-eosinophilic asthma.

METHODS

Patient-derived human bronchial epithelial cells (hBECs) were isolated and differentiated at the air-liquid interface. Single cell RNA-sequencing (scRNAseq) was used to identify epithelial cell subtypes and transcriptional activity. Ion transport was investigated with Ussing chambers and immunofluorescent quantification of ionocyte abundance in human airway epithelial cells and murine models of asthma.

RESULTS

We identified that hBECs from patients with non-eosinophilic asthma had reduced CFTR function, and did not differentiate into CFTR-expressing ionocytes compared to those from eosinophilic asthma or healthy donors. Similarly, ionocytes were also diminished in the airways of a murine model of neutrophilic-dominant but not eosinophilic asthma. Treatment of hBECs from healthy donors with a neutrophilic asthma-like inflammatory cytokine mixture led to a reduction in ionocytes.

CONCLUSION

Inflammation-induced loss of CFTR-expressing ionocytes in airway cells from non-eosinophilic asthma may represent a key feature of disease pathogenesis and a novel drug target.

Role and regulators of N6-methyladenosine (m6A) RNA methylation in inflammatory subtypes of asthma: a comprehensive review

Asthma is a common chronic inflammatory disease of the lungs and airway, yet its inflammatory subtypes and potential pathogenesis have not been completely elucidated and require further study. With advances in epigenetic development, methylation has emerged as a new direction for identifying and decoding the occurrence and subtype manifestations of asthma. N6-methyladenosine (m6A), an RNA methylation modification occurring in the N6-position of adenosine, is a prevalent epigenetic modification observed in eukaryotes. It exerts significant control over mRNA metabolism by regulating alternative splicing, stability, export, and translation. The dynamic process of m6A methylation plays a crucial role in the pathogenesis of asthma and is tightly regulated by three types of regulators: writers, readers, and erasers. This article provides a comprehensive review of the association between m6A regulators and the pathogenesis of inflammatory subtypes of asthma, such as involvement of inflammatory cells and related inflammatory response. Furthermore, the findings presented herein provide new insights and a solid foundation for further research on m6A mRNA methylation as biomarkers for the diagnosis and development of personalized treatment for different subtypes of asthma, particularly neutrophilic asthma and eosinophilic asthma.

Nicotinamide mononucleotide attenuates airway epithelial barrier dysfunction via inhibiting SIRT3 SUMOylation in asthma

Nicotinamide adenine dinucleotide (NAD+) is an essential element in cellular metabolism that regulates fundamental biological processes. Growing evidence suggests that a decline in NAD+ is a common pathological factor in various diseases and aging. However, its role in airway epithelial barrier function in response to asthma remains underexplored. The current study aims to explore the efficacy of restoring cellular NAD+ concentration through supplementation with the NAD+ precursor, nicotinamide mononucleotide (NMN), in the treatment of allergic asthma and to investigate the role of SIRT3 in mediating the effects of NAD+ precursors. In this research, NMN alleviated airway inflammation and reduced mucus secretion in house dust mite (HDM)-induced asthmatic mice. It also mitigated airway epithelial barrier disruption in HDM-induced asthma in vitro and in vivo. But inhibition of SIRT3 expression abolished the effects of NMN. Mechanistically, HDM induced SIRT3 SUMOylation and proteasomal degradation. Mutation of these two SIRT3 SUMO modification sites enhanced the stability of SIRT3. Additionally, SIRT3 was targeted by SENP1 which acted to de-conjugate SUMO. And down-regulation of SENP1 expression in HDM-induced models was reversed by NMN. Collectively, these findings suggest that NMN attenuates airway epithelial barrier dysfunction via inhibiting SIRT3 SUMOylation in asthma. Blockage of SIRT3 SUMOylation emerges as for the treatment of allergic asthma.

SUMOylation of Rho-associated protein kinase 2 induces goblet cell metaplasia in allergic airways

Allergic asthma is characterized by goblet cell metaplasia and subsequent mucus hypersecretion that contribute to the morbidity and mortality of this disease. Here, we explore the potential role and underlying mechanism of protein SUMOylation-mediated goblet cell metaplasia. The components of SUMOylaion machinery are specifically expressed in healthy human bronchial epithelia and robustly upregulated in bronchial epithelia of patients or mouse models with allergic asthma. Intratracheal suppression of SUMOylation by 2-D08 robustly attenuates not only allergen-induced airway inflammation, goblet cell metaplasia, and hyperreactivity, but IL-13-induced goblet cell metaplasia. Phosphoproteomics and biochemical analyses reveal SUMOylation on K1007 activates ROCK2, a master regulator of goblet cell metaplasia, by facilitating its binding to and activation by RhoA, and an E3 ligase PIAS1 is responsible for SUMOylation on K1007. As a result, knockdown of PIAS1 in bronchial epithelia inactivates ROCK2 to attenuate IL-13-induced goblet cell metaplasia, and bronchial epithelial knock-in of ROCK2(K1007R) consistently inactivates ROCK2 to alleviate not only allergen-induced airway inflammation, goblet cell metaplasia, and hyperreactivity, but IL-13-induced goblet cell metaplasia. Together, SUMOylation-mediated ROCK2 activation is an integral component of Rho/ROCK signaling in regulating the pathological conditions of asthma and thus SUMOylation is an additional target for the therapeutic intervention of this disease.

Identification of autoantigens and their potential post-translational modification in EGPA and severe eosinophilic asthma

Background

The chronic airway inflammation in severe eosinophilic asthma (SEA) suggests potential autoimmune aetiology with unidentified autoantibodies analogous to myeloperoxidase (MPO) in ANCA-positive EGPA (eosinophilic granulomatosis with polyangiitis). Previous research has shown that oxidative post-translational modification (oxPTM) of proteins is an important mechanism by which autoantibody responses may escape immune tolerance. Autoantibodies to oxPTM autoantigens in SEA have not previously been studied.

Methods

Patients with EGPA and SEA were recruited as well as healthy control participants. Autoantigen agnostic approach: Participant serum was incubated with slides of unstimulated and PMA-stimulated neutrophils and eosinophils, and autoantibodies to granulocytes were identified by immunofluorescence with anti-human IgG FITC antibody. Target autoantigen approach: Candidate proteins were identified from previous literature and FANTOM5 gene set analysis for eosinophil expressed proteins. Serum IgG autoantibodies to these proteins, in native and oxPTM form, were detected by indirect ELISA.

Results

Immunofluorescence studies showed that serum from patients with known ANCA stained for IgG against neutrophils as expected. In addition, serum from 9 of 17 tested SEA patients stained for IgG to PMA-stimulated neutrophils undergoing NETosis. Immunofluorescent staining of eosinophil slides was evident with serum from all participants (healthy and with eosinophilic disease) with diffuse cytoplasmic staining except for one SEA individual in whom subtle nuclear staining was evident. FANTOM5 gene set analysis identified TREM1 (triggering receptor expressed on myeloid cells 1) and IL-1 receptor 2 (IL1R2) as eosinophil-specific targets to test for autoantibody responses in addition to MPO, eosinophil peroxidase (EPX), and Collagen-V identified from previous literature. Indirect ELISAs found high concentrations of serum autoantibodies to Collagen-V, MPO, and TREM1 in a higher proportion of SEA patients than healthy controls. High concentrations of serum autoantibodies to EPX were evident in serum from both healthy and SEA participants. The proportion of patients with positive autoantibody ELISAs was not increased when examining oxPTM compared to native proteins.

Discussion

Although none of the target proteins studied showed high sensitivity for SEA, the high proportion of patients positive for at least one serum autoantibody shows the potential of more research on autoantibody serology to improve diagnostic testing for severe asthma.

Clinical trial registration

ClinicalTrials.gov, identifier, NCT04671446.

A prognosis prediction chromatin regulator signature for patients with severe asthma

Severe asthma imposes a physical and economic burden on both patients and society. As chromatin regulators (CRs) influence the progression of multiple diseases through epigenetic mechanisms, we aimed to study the role of CRs in patients with severe asthma. Transcriptome data (GSE143303) from 47 patients with severe asthma and 13 healthy participants was downloaded from the Gene Expression Omnibus database. Enrichment analysis was performed to investigate the functions of differentially expressed CRs between the groups. We identified 80 differentially expressed CRs; they were mainly enriched in histone modification, chromatin organization, and lysine degradation. A protein-protein interaction network was then constructed. The analyzed immune scores were different between sick and healthy individuals. Thus, CRs with a high correlation in the immune analysis, SMARCC1, SETD2, KMT2B, and CHD8, were used to construct a nomogram model. Finally, using online prediction tools, we determined that lanatoside C, cefepime, and methapyrilene may be potentially effective drugs in the treatment of severe asthma. The nomogram constructed using the four CRs, SMARCC1, SETD2, KMT2B, and CHD8, may be a useful tool for predicting the prognosis of patients with severe asthma. This study provided new insights into the role of CRs in severe asthma.

ACDC: a general approach for detecting phenotype or exposure associated co-expression

Background

Existing module-based differential co-expression methods identify differences in gene-gene relationships across phenotype or exposure structures by testing for consistent changes in transcription abundance. Current methods only allow for assessment of co-expression variation across a singular, binary or categorical exposure or phenotype, limiting the information that can be obtained from these analyses.

Methods

Here, we propose a novel approach for detection of differential co-expression that simultaneously accommodates multiple phenotypes or exposures with binary, ordinal, or continuous data types.

Results

We report an application to two cohorts of asthmatic patients with varying levels of asthma control to identify associations between gene co-expression and asthma control test scores. Results suggest that both expression levels and covariances of ADORA3, ALOX15, and IDO1 are associated with asthma control.

Conclusion

ACDC is a flexible extension to existing methodology that can detect differential co-expression across varying external variables.

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).

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

BACKGROUND

Unsupervised clustering of biomarkers derived from noninvasive samples such as nasal fluid is less evaluated as a tool for describing asthma endotypes.

OBJECTIVE

We sought to evaluate whether protein expression in nasal fluid would identify distinct clusters of patients with asthma with specific lower airway molecular phenotypes.

METHODS

Unsupervised clustering of 168 nasal inflammatory and immune proteins and Shapley values was used to stratify 43 patients with severe asthma (endotype of noneosinophilic asthma) using a 2 "modeling blocks" machine learning approach. This algorithm was also applied to nasal brushings transcriptomics from U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes). Feature reduction and functional gene analysis were used to compare proteomic and transcriptomic clusters. Gene set variation analysis provided enrichment scores of the endotype of noneosinophilic asthma protein signature within U-BIOPRED sputum and blood.

RESULTS

The nasal protein machine learning model identified 2 severe asthma endotypes, which were replicated in U-BIOPRED nasal transcriptomics. Cluster 1 patients had significant airway obstruction, small airways disease, air trapping, decreased diffusing capacity, and increased oxidative stress, although only 4 of 18 were current smokers. Shapley identified 20 cluster-defining proteins. Forty-one proteins were significantly higher in cluster 1. Pathways associated with proteomic and transcriptomic clusters were linked to T_H1, T_H2, neutrophil, Janus kinase-signal transducer and activator of transcription, TLR, and infection activation. Gene set variation analysis of the nasal protein and gene signatures were enriched in subjects with sputum neutrophilic/mixed granulocytic asthma and in subjects with a molecular phenotype found in sputum neutrophil-high subjects.

CONCLUSIONS

Protein or gene analysis may indicate molecular phenotypes within the asthmatic lower airway and provide a simple, noninvasive test for non-type 2 immune response asthma that is currently unavailable.

Phenotype of Atopic Dermatitis With Food Allergy Predicts Development of Childhood Asthma via Gut Wnt Signaling

PURPOSE

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by a wide spectrum of clinical phenotype. However, specific description of phenotypes of AD depending on the comorbidities in early childhood is lacking. This study aimed to investigate whether the AD phenotype in early childhood is related to childhood asthma and to elucidate the mechanisms involved.

METHODS

Data on the first 3 years of life were collected prospectively from 1,699 children in the COhort for Childhood Origin of Asthma and allergic diseases (COCOA). We applied an unsupervised latent class analysis to the following five factors: food sensitization, inhalant sensitization, food allergy (FA), AD, and recurrent wheezing. The risks of developing FA, AD, allergic rhinitis (AR), and asthma in children aged 5-7 years were evaluated. Colonocyte transcriptome and ingenuity pathway analysis were performed.

RESULTS

Four phenotypes were identified; no allergic diseases (78.4%), AD without sensitization (16.4%), FA with AD (2.9%), and AD with sensitization (7.8%). The FA with AD had the highest risk for FA, AR, and asthma and the highest cord blood immunoglobulin E (IgE) levels. In AD without sensitization and with sensitization, scoring of AD (SCORAD) in early childhood was higher than in FA with AD. Canonical pathway analysis with the colonocyte transcriptome revealed that the key pathway in FA with AD was 'Wnt/β-catenin Signaling.' The relative abundance of Wnt6 mRNA was positively correlated with food-specific IgE levels at 1 and 3 years.

CONCLUSIONS

When FA is present in various phenotypes of AD at early life, regardless of severity of eczema, it may be associated with gut Wnt signaling and later development of asthma.

Identification of Hub Genes and Potential Biomarkers for Childhood Asthma by Utilizing an Established Bioinformatic Analysis Approach

Childhood asthma represents a heterogeneous disease resulting from the interaction between genetic factors and environmental exposures. Currently, finding reliable biomarkers is necessary for the clinical management of childhood asthma. However, only a few biomarkers are being used in clinical practice in the pediatric population. In the long run, new biomarkers for asthma in children are required and would help direct therapy approaches. This study aims to identify potential childhood asthma biomarkers using a genetic-driven biomarkers approach. Herein, childhood asthma-associated Single Nucleotide Polymorphisms (SNPs) were utilized from the GWAS database to drive and facilitate the biomarker of childhood asthma. We uncovered 466 childhood asthma-associated loci by extending to proximal SNPs based on r2 > 0.8 in Asian populations and utilizing HaploReg version 4.1 to determine 393 childhood asthma risk genes. Next, the functional roles of these genes were subsequently investigated using Gene Ontology (GO) term enrichment analysis, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and a protein−protein interaction (PPI) network. MCODE and CytoHubba are two Cytoscape plugins utilized to find biomarker genes from functional networks created using childhood asthma risk genes. Intriguingly, 10 hub genes (IL6, IL4, IL2, IL13, PTPRC, IL5, IL33, TBX21, IL2RA, and STAT6) were successfully identified and may have been identified to play a potential role in the pathogenesis of childhood asthma. Among 10 hub genes, we strongly suggest IL6 and IL4 as prospective childhood asthma biomarkers since both of these biomarkers achieved a high systemic score in Cytohubba’s MCC algorithm. In summary, this study offers a valuable genetic-driven biomarker approach to facilitate the potential biomarkers for asthma in children.

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.

See relatededitorial

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.

Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis

Severe asthma is the main reason for death and disability caused by asthma. However, effective biomarkers for severe asthma have not been identified. Here, we aimed to identify potential biomarkers in severe asthma. We identified 202 differentially expressed genes (DEGs) between severe asthma and mild-moderate asthma after integrating the results from GSE69683 and GSE27011 datasets. The enrichment analysis indicated that 202 DEGs were associated with metabolism- and immune-related processes. 10 hub genes were identified by Cytoscape and five of these genes’ AUC (area under the curve) values were greater than 0.6 in GSE69683. The AUC value reached to 0.701 when combined SEC61A1 and ALDH18A1 expression. The expression of the five hub genes was verified in an external dataset. The network analysis revealed that transcription factor (TF) WT1, ZEB1, RERE, FOSL1, and miR-20a may be involved in the development of asthma. In addition, we found cyclosporine and acetaminophen could interact with these hub genes and may be negatively associated with most of the five hub genes according to previous reports. Overall, key genes were identified between mild-moderate and severe asthmatics, which contributed to the understanding of the development of asthma.

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.