Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways

Wang, Mingming; Gong, L.; Luo, Yang; He, Shaojuan; Zhang, Xianxing; Xie, Xinyu; Li, Xuezhong; Feng, Xin

doi:10.3389/fimmu.2023.1048195

Cited by 18 publications

(10 citation statements)

References 68 publications

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“…AR‐disease signature genes reported in the current study are consistent with genes known to be involved in allergic inflammation across multiple tissue types. Genes highly upregulated in both the off‐season AR versus healthy individuals and the in‐season AR versus healthy individuals include those encoding for the cysteine proteases CST1 and CST2 and the cysteine protease inhibitor FETUB, which have been previously associated with AR and inflammatory airway disease 45 . CPA3 ‐encoding mast‐cell carboxypeptidase A is similarly associated with allergic inflammation and type 2–high asthma 46,47 .…”

Section: Discussionmentioning

confidence: 99%

Differential modulation of allergic rhinitis nasal transcriptome by dupilumab and allergy immunotherapy

Wipperman,

Gayvert,

Atanasio

et al. 2024

Allergy

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BackgroundNasal epithelial cells are important regulators of barrier function and immune signaling; however, in allergic rhinitis (AR) these functions can be disrupted by inflammatory mediators. We aimed to better discern AR disease mechanisms using transcriptome data from nasal brushing samples from individuals with and without AR.MethodsData were drawn from a feasibility study of individuals with and without AR to Timothy grass and from a clinical trial evaluating 16 weeks of treatment with the following: dupilumab, a monoclonal antibody that binds interleukin (IL)‐4Rα and inhibits type 2 inflammation by blocking signaling of both IL‐4/IL‐13; subcutaneous immunotherapy with Timothy grass (SCIT), which inhibits allergic responses through pleiotropic effects; SCIT + dupilumab; or placebo. Using nasal brushing samples from these studies, we defined distinct gene signatures in nasal tissue of AR disease and after nasal allergen challenge (NAC) and assessed how these signatures were modulated by study drug(s).ResultsTreatment with dupilumab (normalized enrichment score [NES] = −1.73, p = .002) or SCIT + dupilumab (NES = −2.55, p < .001), but not SCIT alone (NES = +1.16, p = .107), significantly repressed the AR disease signature. Dupilumab (NES = −2.55, p < .001), SCIT (NES = −2.99, p < .001), and SCIT + dupilumab (NES = −3.15, p < .001) all repressed the NAC gene signature.ConclusionThese results demonstrate type 2 inflammation is an important contributor to the pathophysiology of AR disease and that inhibition of the type 2 pathway with dupilumab may normalize nasal tissue gene expression.

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Section: Discussionmentioning

confidence: 99%

Differential modulation of allergic rhinitis nasal transcriptome by dupilumab and allergy immunotherapy

Wipperman,

Gayvert,

Atanasio

et al. 2024

Allergy

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“…As per the concept of the “unified airway”, the upper and lower respiratory tracts share common barrier and immune characteristics, making them a morphologically and functionally unified entity ( Bachert et al, 2023 ; Wang et al, 2023 ), which can explain that allergy is not a disease of a specific organ, but a disorder of the whole respiratory tract ( Compalati et al, 2010 ). This coincides with the concept of the allergic constitution, which is considered as the background and foundation for the development of allergic diseases by the theory of traditional Chinese medicine constitution ( Wang et al, 2023 ).…”

Section: Discussionmentioning

confidence: 99%

Methylation-driven mechanisms of allergic rhinitis during pollen and non-pollen seasons using integrated bioinformatics analysis

Sun,

Wang,

Liu

et al. 2024

Front. Genet.

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Background:Allergic rhinitis (AR) is a widespread allergic airway disease that results from a complex interplay between genetic and environmental factors and affects approximately 10%–40% of the global population. Pollen is a common allergen, and exposure to pollen can cause epigenetic changes. However, the mechanism underlying pollen-induced DNA methylation changes and their potential effects on the allergic march are still unclear. The purpose of this study was to explore the methylation-driven mechanisms of AR during the pollen and non-pollen seasons using bioinformatics analysis and to investigate their relationship with asthma.Methods:We downloaded DNA methylation and gene expression data from the GEO database (GSE50387: GSE50222, GSE50101) and identified differentially methylated positions (DMPs) and differentially expressed genes (DEGs) during the pollen and non-pollen seasons using the CHAMP and limma packages. Through correlation analysis, we identified methylation-driven genes and performed pathway enrichment analysis to annotate their functions. We incorporated external data on AR combined with asthma (GSE101720) for analysis to identify key CpGs that promote the transformation of AR to asthma. We also utilized external data on olive pollen allergy (GSE54522) for analysis to validate the methylation-driven genes. Weighted correlation network analysis (WGCNA) was employed to identify gene modules significantly correlated with pollen allergy. We extracted genes related to the key methylation-driven gene ZNF667-AS1 from the significant module and performed pathway intelligent clustering using KOBAS-i. We also utilized gene set enrichment analysis to explore the potential function of ZNF667-AS1.Results:We identified 20 and 24 CpG-Gene pairings during the pollen and non-pollen seasons. After incorporating external data from GSE101720, we found that ZNF667-AS1 is a key gene that may facilitate the transformation of AR into asthma during the pollen season. This finding was further validated in another external dataset, GSE54522, which is associated with pollen allergy. WGCNA identified 17 modules, among which the blue module showed significant correlation with allergies. ZNF667-AS1 was located in the blue module. We performed pathway analysis on the genes correlated with ZNF667-AS1 extracted from the blue module and identified a prominent cluster of pathways in the KOBAS-i results, including Toll-like receptor (TLR) family, MyD88, MAPK, and oxidative stress. Gene set enrichment analysis around cg05508084 (paired with ZNF667-AS1) also indicated its potential involvement in initiating and modulating allergic inflammation from the perspective of TLR and MAPK signaling.Conclusion:We identified methylation-driven genes and their related pathways during the pollen and non-pollen seasons in patients with AR and identified key CpGs that promote the transformation of AR into asthma due to pollen exposure. This study provides new insights into the underlying molecular mechanisms of the transformation of AR to asthma.

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“…Moreover, CIBERSORT (http://cibersort.stanford.edu), an immune cell composition analysis tool, aids in understanding immune in ltration in complex tissues 11 . Despite their applications in studying related diseases 12,13 , their use in exploring both HF and pan-cancer has remained limited.…”

Section: The Spatiotemporal Exhaustion Of Cytotoxic Cd8 + T-cells Wit...mentioning

confidence: 99%

Exploring the link between heart failure and cancer: insights into immune mechanisms and therapeutic targets for CD8 + T-cells

Zhou,

Pan,

et al. 2024

Preprint

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Background Heart failure (HF) is a terminal condition of multiple cardiovascular disorders. Cancer is a highly prevalent and deadly disease worldwide. However, the relationship between HF and cancer remains poorly understood. Therefore, there is a critical need to explore the potential mechanisms and therapeutic targets shared between HF and cancer. Method The Gene Expression Omnibus (GEO) database was used to download the RNA sequencing (RNA-seq) data of 356 patients, including individuals with HF and those without HF, to establish a co-expression network using the weighted correlation network analysis (WGCNA) algorithm, to calculate the compositions of immune infiltrating cells in the CIBERSORT algorithm, and to identify candidate hub genes within the modules of individuals with HF. Pearson Correlation Analysis was employed to identify the correlation between hub genes and CD8+T-cells in HF, as well as between hub genes and both tumor mutation burden (TMB) and microsatellite instability (MSI) across cancers. Molecular biology experiments were conducted to confirm the correlation between the hub genes and HF. Finally, the NetworkAnalyst database and the CellMiner database were utilized to predict the transcription factors (TFs) and potential therapeutic drugs of hub genes, respectively. Results HF was significantly linked to immune response pathway by the analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The brown and blue modules, identified by WGCNA, were the primary modules related to CD8+T-cells. Concomitantly, we observed a positive correlation between the expression levels of the four hub genes and the infiltration of CD8+T-cells in pan-cancer. Additionally, western blotting and real-time polymerase chain reaction (RT-PCR) validated the high expression of three hub genes (GZMM, NKG7, and ZAP70) in both mice and patients with HF compared to those in the control group. Finally, the hub gene-associated TF-gene networks and 11 agents targeting the hub genes were successfully predicted. Conclusion Our study highlights the shared pathogenesis of HF and cancer and provides valuable insights for developing novel therapeutic strategies that target shared pathways, offering new opportunities for improving the management and treatment outcomes of both HF and cancer.

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Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways

Cited by 18 publications

References 68 publications

Differential modulation of allergic rhinitis nasal transcriptome by dupilumab and allergy immunotherapy

Differential modulation of allergic rhinitis nasal transcriptome by dupilumab and allergy immunotherapy

Methylation-driven mechanisms of allergic rhinitis during pollen and non-pollen seasons using integrated bioinformatics analysis

Exploring the link between heart failure and cancer: insights into immune mechanisms and therapeutic targets for CD8 + T-cells

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