Hub Genes Identification in a Murine Model of Allergic Rhinitis Based on Bioinformatics Analysis

Integration of bioinformatics analysis, molecular docking and animal experiments to study the therapeutic mechanisms of berberine against allergic rhinitis

Allergic rhinitis is a prevalent inflammatory condition that impacts individuals of all age groups. Despite reports indicating the potential of berberine in alleviating allergic rhinitis symptoms, the specific molecular mechanisms and therapeutic targets of berberine remain unclear. This research aims to explore the pharmacological mechanism of berberine in the treatment of allergic rhinitis through bioinformatic analyses and experimental validation. The research utilized public databases to identify potential targets of berberine. Furthermore, differentially expressed genes (DEGs) related to allergic rhinitis were pinpointed from the GSE52804 dataset. Through bioinformatics techniques, the primary targets were discovered and key KEGG and GO-BP pathways were established. To confirm the therapeutic mechanisms of berberine on allergic rhinitis, an OVA-induced allergic rhinitis model was developed using guinea pigs. We identified 32 key genes responsible for the effectiveness of berberine in treating allergic rhinitis. In addition, five central genes (Alb, Il6, Tlr4, Ptas2, and Il1b) were pinpointed. Further examination using KEGG and GO-BP pathways revealed that the main targets were primarily involved in pathways such as NF-kappa B, IL-17, TNF, and inflammatory response. Molecular docking analysis demonstrated that berberine exhibited strong affinity towards these five key targets. Furthermore, the expression levels of IL-6, TLR4, PTGS2, and IL-1β were significantly upregulated in the model group but downregulated following berberine treatment. This research has revealed the mechanism through which berberine combats allergic rhinitis and has identified its potential to regulate pathways linked to inflammation. These discoveries provide valuable insights for the development of novel medications for the treatment of allergic rhinitis.

The early-phase transcriptome and the clinical efficacy analysis in three modes of subcutaneous immunotherapy for allergic rhinitis

Background

Allergen immunotherapy is the only etiological treatment for allergic rhinitis.

Objective

To analyze the efficacy, safety, and mechanism of subcutaneous immunotherapy (SCIT).

Methods

The efficacy, safety, and serum immunological changes of 3 modes of subcutaneous immunotherapy were compared. Peripheral blood mononuclear cells (PBMC) transcriptome changes were obtained on the Illumina sequencing platforms. We confirmed differentially expressed genes (DEGs) by quantitative real-time polymerase chain reaction (PCR). The DEGs were analyzed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) networks. The correlation between the common DEGs and clinical indicators was analyzed by Origin 2022.

Results

The 3 SCITs were all effective after 1 year. The Combined Symptom and Medication Score (CSMS) and Visual Analog Score (VAS) in rush immunotherapy (RIT) are lowest after 24 and 48 weeks of treatment among the 3 groups. After treatment, the levels of sIgE, sIgE/tIgE, Th2 cytokines, Th17 cytokines, and percentage of peripheral eosinophils (EOS%) decreased significantly (P＜0.05), while the levels of Th1 type cytokines did not change significantly. Transcriptome analysis identified 24, 24, and 91 DEGs at W3 and 42, 52, 175 DEGs at W7 in conventional immunotherapy (CIT), cluster immunotherapy (CLIT), and RIT groups, respectively. The pathways and functions involved in SCIT include secretion of Th1/2 cytokines, immune cell differentiation. Unlike CIT and CLIT, DEGs are also involved in T cell tolerance induction, T cell anergy, and lymphocyte anergy in RIT. CXCR1, CXCR2, and IER3 had a specific effect on reflecting the improvement of symptoms in allergic rhinitis patients with SCIT.

Conclusion

The clinical efficacy of RIT appeared earlier than CIT and CLIT. Clinicians can use the highly conserved gene expression profile to evaluate responses to immunotherapy.

Multifaceted functions of RPS27a: An unconventional ribosomal protein

The ribosomal protein S27a (RPS27a) is cleaved from the fusion protein ubiquitin-RPS27a (Ub-RPS27a). Generally, Ub and RPS27a are coexpressed as a fusion protein but function independently after Ub is cleaved from RPS27a by a deubiquitinating enzyme. As an RP, RPS27a assembles into ribosomes, but it also functions independently of ribosomes. RPS27a is involved in the development and poor prognosis of various cancers, such as colorectal cancer, liver cancer, chronic myeloid leukemia, and renal carcinoma, and is associated with poor prognosis. Notably, the murine double minute 2/P53 axis is a major pathway through which RPS27a regulates cancer development. Moreover, RPS27a maintains sperm motility, regulates winged aphid indirect flight muscle degeneration, and facilitates plant growth. Additionally, RPS27a is a metalloprotein and mercury (Hg) biomarker. In the present review, we described the origin, structure, and biological functions of RPS27a.

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.

Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF. Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR). Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis. Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.