Identification of key genes in allergic rhinitis by bioinformatics analysis

Decoding the genetic landscape of allergic rhinitis: a comprehensive network analysis revealing key genes and potential therapeutic targets

BACKGROUND

Allergic Rhinitis (AR), an inflammatory affliction impacting the upper respiratory tract, has been registering a substantial surge in incidence across the globe.

METHODS

We embarked on examination of differentially expressed genes (DEGs) and the Weighted Gene Co-Expression Network Analysis (WGCNA). With this armory of genes identified, we engaged the tools of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Our study continued with the establishment of a protein-protein interaction (PPI) network and the application of LASSO regression. Finally, we leveraged a docking model to elucidate potential drug-gene interactions involving these key genes.

RESULTS

Through WGCNA and different express genes screening, PPI network was performed, identifying top 20 key genes, including CD44, CD69, CD274. LASSO regression identified three independent factors, STARD5, CST1, and CHAC1, that were significantly associated with AR. A predictive model was developed with an AUC value over 0.75. Also, 105 potential therapeutic agents were discovered, including Fluorouracil, Cyclophosphamide, Doxorubicin, and Hydrocortisone, offering promising therapeutic strategies for AR.

CONCLUSION

By fuzing DEGs with key genes derived from WGCNA, this study has illuminated a comprehensive network of gene interactions involved in the pathogenesis of AR, paving the way for future biomarker and therapeutic target discovery in AR.

[Progress of allergic rhinitis research based on transcriptome sequencing]

Traditional studies on allergic rhinitis（AR） have mainly adopted animal models and biomolecular approaches. In addition, the advent of transcriptome sequencing technology is promoting the development of AR at the genetic level. Recently, many scholars have focused on the role of common RNA in the pathogenesis of AR, suggesting that breakthroughs have been made in the field of AR bioinformatics analysis. This review aims to summarize the research advances in AR, the development of transcriptome sequencing technology, and the application of transcriptome sequencing in AR, in order to explore potential drug targets for AR treatment and provide new insights into precision medicine.

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

BACKGROUND

Nasal 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.

METHODS

Data 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).

RESULTS

Treatment 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.

CONCLUSION

These 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.

Gene-Smoking Interaction Analysis for the Identification of Novel Asthma-Associated Genetic Factors

Asthma is a complex heterogeneous disease caused by gene-environment interactions. Although numerous genome-wide association studies have been conducted, these interactions have not been systemically investigated. We sought to identify genetic factors associated with the asthma phenotype in 66,857 subjects from the Health Examination Study, Cardiovascular Disease Association Study, and Korea Association Resource Study cohorts. We investigated asthma-associated gene-environment (smoking status) interactions at the level of single nucleotide polymorphisms, genes, and gene sets. We identified two potentially novel (SETDB1 and ZNF8) and five previously reported (DM4C, DOCK8, MMP20, MYL7, and ADCY9) genes associated with increased asthma risk. Numerous gene ontology processes, including regulation of T cell differentiation in the thymus (GO:0033081), were significantly enriched for asthma risk. Functional annotation analysis confirmed the causal relationship between five genes (two potentially novel and three previously reported genes) and asthma through genome-wide functional prediction scores (combined annotation-dependent depletion, deleterious annotation of genetic variants using neural networks, and RegulomeDB). Our findings elucidate the genetic architecture of asthma and improve the understanding of its biological mechanisms. However, further studies are necessary for developing preventive treatments based on environmental factors and understanding the immune system mechanisms that contribute to the etiology of asthma.

A functional genomics pipeline to identify high-value asthma and allergy CpGs in the human methylome

BACKGROUND

DNA methylation of cytosines at cytosine-phosphate-guanine (CpG) dinucleotides (CpGs) is a widespread epigenetic mark, but genome-wide variation has been relatively unexplored due to the limited representation of variable CpGs on commercial high-throughput arrays.

OBJECTIVES

To explore this hidden portion of the epigenome, this study combined whole-genome bisulfite sequencing with in silico evidence of gene regulatory regions to design a custom array of high-value CpGs. This study focused on airway epithelial cells from children with and without allergic asthma because these cells mediate the effects of inhaled microbes, pollution, and allergens on asthma and allergic disease risk.

METHODS

This study identified differentially methylated regions from whole-genome bisulfite sequencing in nasal epithelial cell DNA from a total of 39 children with and without allergic asthma of both European and African ancestries. This study selected CpGs from differentially methylated regions, previous allergy or asthma epigenome-wide association studies (EWAS), or genome-wide association study loci, and overlapped them with functional annotations for inclusion on a custom Asthma&Allergy array. This study used both the custom and EPIC arrays to perform EWAS of allergic sensitization (AS) in nasal epithelial cell DNA from children in the URECA (Urban Environment and Childhood Asthma) birth cohort and using the custom array in the INSPIRE [Infant Susceptibility to Pulmonary Infections and Asthma Following RSV Exposure] birth cohort. Each CpG on the arrays was assigned to its nearest gene and its promotor capture Hi-C interacting gene and performed expression quantitative trait methylation (eQTM) studies for both sets of genes.

RESULTS

Custom array CpGs were enriched for intermediate methylation levels compared to EPIC CpGs. Intermediate methylation CpGs were further enriched among those associated with AS and for eQTMs on both arrays.

CONCLUSIONS

This study revealed signature features of high-value CpGs and evidence for epigenetic regulation of genes at AS EWAS loci that are robust to race/ethnicity, ascertainment, age, and geography.

Analysis of urine differential proteins in patients with allergic rhinitis

Background

Allergic rhinitis (AR) is one of the most common clinical allergic diseases. Early diagnosis and medical intervention will benefit patients with allergic rhinitis. In this study, we focused on changes in urine proteomics in AR patients to investigate their potential clinical utility in AR diagnosis and evaluation.

Material and methods

TMT-labeled mass spectrometry-based proteomics was carried out to identify differentially expressed proteins (DEPs) in urine between allergic rhinitis patients and normal control groups. The molecular biological role of DEPs was investigated by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-protein interaction (PPI) network analysis.

Results

Enrichment analysis showed that the differentially expressed proteins were mainly related to cell-cell adhesion, complement and coagulation cascades, peptidase activity regulation, MAP kinase activity, etc. Compared with the NC group, HLA-DRB1, WFDC12, and DEFA4, among the top ten up-regulated proteins in the urine of the AR group, were related to the biological process of the humoral immune response. Among the top 10 down-regulated proteins, GUSB, SQSTM1, and KIT are related to protein domain-specific binding in terms of molecular function.

Conclusions

We found differential protein changes between AR patients and normal subjects may be related to the pathophysiological changes of AR, which provides the possibility for further exploration of urinary proteomics biomarkers in the future.

Gene Signatures and Associated Transcription Factors of Allergic Rhinitis: KLF4 Expression Is Associated with Immune Response

This study is aimed at investigating the potential molecular features of allergic rhinitis (AR) and identifying gene signatures and related transcription factors using transcriptome analysis and in silico datasets. Transcriptome profiles were obtained using three independent cohorts (GSE101720, GSE19190, and GSE46171) comprising healthy controls (HC) and patients with AR. The pooled dataset (n = 82) was used to identify the critical signatures of AR compared with HC. Subsequently, key transcription factors were identified by a combined analysis using transcriptome and in silico datasets. Gene ontology: bioprocess (GO: BP) analysis using differentially expressed genes (DEGs) revealed that immune response-related genes were significantly enriched in AR compared with HC. Among them, IL1RL1, CD274, and CD44 were significantly higher in AR patients. We also identified key transcription factors between HC and AR using the in silico dataset and found that AR samples frequently express KLF transcription factor 4 (KLF4), which regulates immune response-related genes including IL1RL1, CD274, and CD44 in human nasal epithelial cells. Our integrative analysis of transcriptomic regulation provides new insights into AR, which may help in developing precision management for patients with AR.

Genes related to allergen exposure in allergic rhinitis: a gene-chip-based study in a mouse model

BACKGROUND

The typical clinical symptoms of allergic rhinitis (AR) are known to be associated with allergen exposure; however, the underlying mechanisms are not fully understood. We wanted to gain a comprehensive view of the molecular mechanisms related to allergen exposure in a well-controlled mouse model of AR.

METHODS

An OVA-induced AR model was developed. Two hours and 4 weeks after the last OVA challenge, AR symptoms and local immune responses were assessed. At the same time, differentially expressed genes (DEG) in nasal mucosa were identified by gene expression microarray and further analyzed by bioinformatics methods. Verification of DEG was done by quantitative RT-PCR and immunohistochemistry.

RESULTS

The number of nasal rubbings and sneezes, serum OVA-specific IgE concentrations, and the number of neutrophils and eosinophils in the nasal mucosa were significantly increased at 2 h and decreased at 4 weeks after the last allergen challenge compared to controls. A total of 2119 DEG were identified, and their expression dynamics were clustered into 8 profiles. Enriched functions in Profile 5, which had a similar trend to clinical features, were mainly related to inflammatory and immune response to environmental factors, eosinophils and neutrophils chemotaxis, and cell migration. Gene co-expression Network for genes from profile 5 identified BCL3, NFKB2, SOCS3, and CD53 having a higher degree. Profile 6 showed persistence of inflammatory and immune response at 4 weeks after the last allergen challenge. Olfactory and coagulation functions were enriched mainly in profiles with downward trends.

CONCLUSIONS

A wide range of genes with sequential cooperative action were identified to be associated with allergen exposure in AR. BCL3 may be the most vital in symptoms manifestation. Moreover, some inflammatory responses persisted for a period after allergen exposure, supporting a new treatment strategy of targeting inflammation out of season. This study may contribute to a better understanding of AR pathogenesis and provide potential therapeutic targets for AR patients.

A comprehensive gene expression profile of allergic rhinitis-derived nasal fibroblasts and the potential mechanism for its phenotype

BACKGROUND

Allergic rhinitis (AR) is a common immunoglobulin E-mediated immune response involved various cell types, while the role of nasal fibroblasts (NFs) in the pathogenesis of AR is less understood.

PURPOSE

The study aimed to uncover the gene expression profile of AR-derived NFs and the potential mechanism for the changed phenotype of AR-NFs.

RESEARCH DESIGN

The primary NFs were isolated from 3 AR patients (AR-NFs) and 3 controls (Ctrl-NFs), and the proliferation, migration and interleukins production abilities of NFs were detected respectively. RNA-sequence was used to identify differentially expressed genes (DEGs) in AR-NFs. Transcription factor (TF) regulatory network and bioinformatic analyses were both conducted to clarify the biological roles of DEGs including the TFs. The DEG with the highest validated |fold change (FC)| value, detected by qPCR, was selected for further confirmation.

RESULTS

AR-NFs showed a higher proliferation and migration abilities as well as released higher levels of IL-33 and IL-6, compared to Ctrl-NFs. A total of 729 DEGs were screened out in AR-NFs. TF regulatory network indicated that BARX homeobox 1 (BARX1) and forkhead box L1 were the major node TFs. Bioinformatic analyses showed that a large number of DEGs including several target genes of BARX1 were both enriched cytokine-related GO terms, and immune- or inflammation-related pathways. BARX1 had the highest |FC| value, and silencing BARX1 in AR-NFs resulted in the significant downregulation of proliferation and migration abilities, and the production of interleukins.

CONCLUSIONS

Our study for the first time provided the gene expression profile of AR-derived NFs, and BARX1 could be developed as a potent target to alleviate the pathogenesis of AR.

Allergic Diseases: A Comprehensive Review on Risk Factors, Immunological Mechanisms, Link with COVID-19, Potential Treatments, and Role of Allergen Bioinformatics

The prevalence of allergic diseases is regarded as one of the key challenges in health worldwide. Although the precise mechanisms underlying this rapid increase in prevalence are unknown, emerging evidence suggests that genetic and environmental factors play a significant role. The immune system, microbiota, viruses, and bacteria have all been linked to the onset of allergy disorders in recent years. Avoiding allergen exposure is the best treatment option; however, steroids, antihistamines, and other symptom-relieving drugs are also used. Allergen bioinformatics encompasses both computational tools/methods and allergen-related data resources for managing, archiving, and analyzing allergological data. This study highlights allergy-promoting mechanisms, algorithms, and concepts in allergen bioinformatics, as well as major areas for future research in the field of allergology.