Identification of diagnostic signature, molecular subtypes, and potential drugs in allergic rhinitis based on an inflammatory response gene set
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ABSTRACT:
SUBMITTER: Dai J
PROVIDER: S-EPMC10926906 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:IntroductionPrevious studies have found that unique patterns of gut microbial colonization in infancy associated with the development of allergic diseases. However, there is no research on the gut microbiota characteristics of AR children in Chinese Mainland.ObjectiveTo investigate the changes of gut microbial of AR children in Chinese Mainland and evaluate the correlation between gut microbial and clinical indexes.MethodsIn this clinical study, fecal samples from 24 AR children and 25 healthy control children (HCs) were comparative via next generation sequencing of the V3-V4 regions of the 16S rRNA gene. Analyzed the relationship between clinical features and gut microbial using Spearman correlation.ResultsCompared to HCs, AR children showed significant decreases in Shannon index and significant increases in Simpson index at both the family and genera levels (all p < 0.05). In terms of bacterial composition, at the phylum level, AR children had higher abundance of Bacteroidetes than that in the HCs group (p < 0.05) and were significantly positively correlated with TNSS (p < 0.05). At the family level, AR children had higher abundance of Prevotellaceae and Enterobacteriaceae higher than that in the HCs group (all p < 0.05) and had a significantly positive correlation with TNSS, eosinophils (EOS) and total immunoglobulin E (tIgE) (all p < 0.05). At the genus level, reduced abundance of Agathobacter, Parasutterella, Roseburia and Subdoligranulum were also observed in the AR cohorts compared to HCs (all p < 0.05) and significantly negatively associated with TNSS, EOS, tIgE, QOL, and FeNO (all p < 0.05).ConclusionAR children in Chinese Mainland were characterized by reduced microbial diversity and distinguished microbial characteristics in comparison with HCs. The observations of this study offer proof that distinctive gut microbiota profiles were present in AR children and necessitate further investigation in the form of mechanistic studies.
| S-EPMC10408450 | biostudies-literature
Project description:ObjectiveThis study aimed to explore the potential molecular mechanism of allergic rhinitis (AR) and identify gene signatures by analyzing microarray data using bioinformatics methods.MethodsThe dataset GSE19187 was used to screen differentially expressed genes (DEGs) between samples from patients with AR and healthy controls. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied for the DEGs. Subsequently, a protein-protein interaction (PPI) network was constructed to identify hub genes. GSE44037 and GSE43523 datasets were screened to validate critical genes.ResultsA total of 156 DEGs were identified. GO analysis verified that the DEGs were enriched in antigen processing and presentation, the immune response, and antigen binding. KEGG analysis demonstrated that the DEGs were enriched in Staphylococcus aureus infection, rheumatoid arthritis, and allograft rejection. PPI network and module analysis predicted seven hub genes, of which six (CD44, HLA-DPA1, HLA-DRB1, HLA-DRB5, MUC5B, and CD274) were identified in the validation dataset.ConclusionsOur findings suggest that hub genes play important roles in the development of AR.
| S-EPMC8326637 | biostudies-literature
Project description:BackgroundStudies have shown that the lipid metabolism mediator leukotriene and prostaglandins are associated with the pathogenesis of allergic rhinitis (AR). The aim of this study was to identify key lipid metabolism-related genes (LMRGs) related to the diagnosis and treatment of AR.Materials and methodsAR-related expression datasets (GSE75011, GSE46171) were downloaded through the Gene Expression Omnibus (GEO) database. First, weighted gene co-expression network analysis (WGCNA) was used to get AR-related genes (ARRGs). Next, between control and AR groups in GSE75011, differentially expressed genes (DEGs) were screened, and DEGs were intersected with LMRGs to obtain lipid metabolism-related differentially expressed genes (LMR DEGs). Protein-protein interaction (PPI) networks were constructed for these LMR DEGs. Hub genes were then identified through stress, radiality, closeness and edge percolated component (EPC) analysis and intersected with the ARRGs to obtain candidate genes. Biomarkers with diagnostic value were screened via receiver operating characteristic (ROC) curves. Differential immune cells screened between control and AR groups were then assessed for correlation with the diagnostic genes, and clinical correlation analysis and enrichment analysis were performed. Finally, real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was made on blood samples from control and AR patients to validate these identified diagnostic genes.Results73 LMR DEGs were obtained, which were involved in biological processes such as metabolism of lipids and lipid biosynthetic processes. 66 ARRGs and 22 hub genes were intersected to obtain four candidate genes. Three diagnostic genes (LPCAT1, SGPP1, SMARCD3) with diagnostic value were screened according to the AUC > 0.7, with markedly variant between control and AR groups. In addition, two immune cells, regulatory T cells (Treg) and T follicular helper cells (TFH), were marked variations between control and AR groups, and SMARCD3 was significantly associated with TFH. Moreover, SMARCD3 was relevant to immune-related pathways, and correlated significantly with clinical characteristics (age and sex). Finally, RT-qPCR results indicated that changes in the expression of LPCAT1 and SMARCD3 between control and AR groups were consistent with the GSE75011 and GSE46171.ConclusionLPCAT1, SGPP1 and SMARCD3 might be used as biomarkers for AR.
| S-EPMC10362667 | biostudies-literature
Project description: Not available
| S-EPMC4324099 | biostudies-literature
Project description:IntroductionBasophil activation test (BAT) might be an alternative to nasal allergen challenge (NAC) to identify the allergic etiology in rhinitis patients. Here, we investigate the diagnostic performance of BAT for allergic phenotypes of rhinitis.MethodsRhinitis patients and healthy controls were subjected to NAC with Dermatophagoides pteronyssinus (DP), Alternaria alternata (AA), grass (GP) and olive (OP) pollens. Rhinitis subjects also underwent skin prick test (SPT) with relevant allergens. Patients were classified into allergic rhinitis (AR, positive NAC and SPT), local allergic rhinitis (LAR, positive NAC and negative SPT), dual allergic rhinitis (DAR, defined as AR for ≥1 allergen and LAR for ≥1 allergen), and non-allergic rhinitis (NAR, negative NAC and SPT) phenotypes. BAT with DP, AA, GP and OP was conducted in study individuals and compared with NAC results.ResultsA total of 47 AR, 31 DAR, 26 LAR, 12 NAR and 21 control subjects were recruited. The best positivity cut-offs of BAT for DP-, AA-, GP- and OP-driven allergy (all phenotypes) were a %CD63 cells of 8.650, 14.250, 26.200, and 12.780, respectively (AUC 0.851, 0.701, 0.887, and 0.921, respectively). Sensitivity, specificity, negative and positive predictive values of BAT (all phenotypes) ranged 43.5%(AA)-83.3%(OP), 88.9%(GP)-100%(AA), 87%(GP)-100%(AA), and 61.1%(DP)-80.0%(pollens), respectively. BAT identified 79%-100% of SPT-positive allergies (AR and DAR), and 25%-75% of SPT-negative allergies (LAR and DAR), while ≤10% of NAR/HC subjects tested positive. BAT positivity correlated with rhinitis severity in LAR patients (p = 0.018), and associated with conjunctivitis (p = 0.015) in allergic subjects.ConclusionBAT can replace NAC for AR confirmation, and limit the number of NAC required for LAR and DAR diagnosis. BAT can demonstrate sIgE in SPT-negative allergies.
| S-EPMC11891400 | biostudies-literature
Project description:Using an allergic rhinitis (AR) model, we evaluated the pharmacological effects of novel peptide drugs (P-ONE and P-TWO) at the small RNA (sRNA) level. Using high-throughput sequencing, we assessed the sRNA expression profile of the negative control, AR antagonist (positive control), P-ONE, and P-TWO groups. By functional clustering and Gene Ontology and KEGG pathway analyses, we found that sRNA target genes have a specific enrichment pattern and may contribute to the effects of the novel peptides. Small RNA sequencing confirmed the biological foundations of novel and traditional AR treatments and suggested unique pharmacological effects. Our findings will facilitate evaluation of the pathogenesis of AR and of the pharmacological mechanisms of novel peptide drugs.
| S-EPMC7517717 | biostudies-literature
Project description:PurposePrevious studies have shown the role of ten-eleven translocation 2 (TET2) in CD4+ T cells. However, its function in CD4+ T cells under allergic inflammation is unclear. We aimed to investigate the epigenomic distribution of DNA 5-hydroxymethylcytosine (5hmC) and the role of TET2 in CD4+ T cells of allergic rhinitis (AR).MethodsThe hMeDIP-seq was performed to identify sequences with 5hmC deposition in CD4+ T cells of AR patients. Tet2-deficient or wild type mice were stimulated with ovalbumin (OVA) to develop an AR mouse model. The histopathology in nasal mucosae, Th1/Th2/Treg/Th17 cell percentage, concentrations of Th-related cytokines, expression of Tets and differential hydroxymethylated genes (DhMG), and the global deposition of 5hmC in sorted CD4+ T cells were detected.ResultsEpigenome-wide 5hmC landscape and DhMG in the CD4+ T cells of AR patients were identified. Tet2 depletion did not led to spontaneous inflammation. However, under the stimulation of allergen, OVA, loss of Tet2 resulted in the exacerbation of allergic inflammation, which was characterized by severer allergic symptoms, more inflammatory cells infiltrating the nasal lamina propria, sharper imbalances between Th1/Th2 and Treg/Th17 cells, and excessive secretion of OVA-specific IgE and Th2-related cytokines. Moreover, altered mRNA production of several DhMG and sharp decrease in 5hmC deposition were also observed in Tet2-deficient OVA-exposed mice.ConclusionsTET2 may regulate DNA 5hmC, DhMG expressions, and CD4+ T cell balance in AR.
| S-EPMC8914607 | biostudies-literature
Project description:As an extremely prevalent disease worldwide, allergic rhinitis (AR) is a condition characterized by chronic inflammation of the nasal mucosa. To identify the finer molecular mechanisms associated with the AR susceptibility genes, differentially expressed genes (DEGs) in AR were investigated. The DEG expression and clinical data of the GSE19187 data set were used for weighted gene co-expression network analysis (WGCNA). After the modules related to AR had been screened, the genes in the module were extracted for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, whereby the genes enriched in the KEGG pathway were regarded as the pathway-genes. The DEGs in patients with AR were subsequently screened out from GSE19187, and the sensitive genes were identified in GSE18574 in connection with the allergen challenge. Two kinds of genes were compared with the pathway-genes in order to screen the AR susceptibility genes. Receiver operating characteristic (ROC) curve was plotted to evaluate the capability of the susceptibility genes to distinguish the AR state. Based on the WGCNA in the GSE19187 data set, 10 co-expression network modules were identified. The correlation analyses revealed that the yellow module was positively correlated with the disease state of AR. A total of 89 genes were found to be involved in the enrichment of the yellow module pathway. Four genes (CST1, SH2D1B, DPP4, and SLC5A5) were upregulated in AR and sensitive to allergen challenge, whose potentials were further confirmed by ROC curve. Taken together, CST1, SH2D1B, DPP4, and SLC5A5 are susceptibility genes to AR.
| S-EPMC6951973 | biostudies-literature
Project description:BackgroundAllergic rhinitis (AR) is an upper respiratory tract inflammation disease caused by IgE-mediated reactions against inhaled allergens. The incidence of AR is significantly increasing throughout the world. Hence, more specific, and sensitive gene biomarkers and understanding the underlying pathways are necessary to further explore the AR pathogenesis.ObjectiveTo identify gene biomarkers in nasal mucosa and in blood from AR patients which could be used in AR diagnosis.MethodsThe gene expression profiles of GSE43523 from nasal epithelial cells and GSE75011 from Th2-enriched CD4+ T cells in blood were downloaded from the Gene Expression Omnibus database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and protein-protein interaction (PPI) network analysis were conducted to investigate the functional changes of genes. The receiver operating characteristic (ROC) curves were used to assess the diagnostic values of the hub genes. Real-time quantitative PCR (RT-qPCR) was performed to validate the hub genes.ResultsSignificant differentially enriched gene signatures in AR patients were identified in nasal epithelial cells (n-DEGs) and in blood (t-DEGs). Signatures associated with axoneme, extracellular matrix, collagen fibril organization, cell motility, calcium ion binding, and so on were more enriched in n-DEGs, whereas signatures associated with TNF signaling pathway, detoxification of inorganic compound, and cellular response to corticotropin-releasing hormone stimulus were enriched in t-DEGs. In addition, we identified 8 hub genes and 14 hub genes from n-DEGs and t-DEGs, respectively. The combination of POSTN in nasal mucosa and PENK and CDC25A in blood was constructed with a good AR predicting performance. The area under the curve (AUC) of the ROC curve of 3 hub genes' combination was 0.98 for AR diagnosis.ConclusionThis study utilized gene expression profiles and RT-qPCR validation on nasal mucosa and blood from AR patients to investigate the potential biomarkers for AR diagnosis.
| S-EPMC8897927 | biostudies-literature
Project description:IntroductionAlthough recent studies have shown that the human microbiome is involved in the pathogenesis of allergic diseases, the impact of microbiota on allergic rhinitis (AR) and non-allergic rhinitis (nAR) has not been elucidated. The aim of this study was to investigate the differences in the composition of the nasal flora in patients with AR and nAR and their role in the pathogenesis.MethodFrom February to September 2022, 35 AR patients and 35 nAR patients admitted to Harbin Medical University's Second Affiliated Hospital, as well as 20 healthy subjects who underwent physical examination during the same period, were subjected to 16SrDNA and metagenomic sequencing of nasal flora.ResultsThe microbiota composition of the three groups of study subjects differs significantly. The relative abundance of Vibrio vulnificus and Acinetobacter baumanni in the nasal cavity of AR patients was significantly higher when compared to nAR patients, while the relative abundance of Lactobacillus murinus, Lactobacillus iners, Proteobacteria, Pseudomonadales, and Escherichia coli was lower. In addition, Lactobacillus murinus and Lacttobacillus kunkeei were also negatively correlated with IgE, while Lacttobacillus kunkeei was positively correlated with age. The relative distribution of Faecalibacterium was higher in moderate than in severe AR patients. According to KEGG functional enrichment annotation, ICMT(protein-S-isoprenylcysteine O-methyltransferase,ICMT) is an AR microbiota-specific enzyme that plays a role, while glycan biosynthesis and metabolism are more active in AR microbiota. For AR, the model containing Parabacteroides goldstemii, Sutterella-SP-6FBBBBH3, Pseudoalteromonas luteoviolacea, Lachnospiraceae bacterium-615, and Bacteroides coprocola had the highest the area under the curve (AUC), which was 0.9733(95%CI:0.926-1.000) in the constructed random forest prediction model. The largest AUC for nAR is 0.984(95%CI:0.949-1.000) for the model containing Pseudomonas-SP-LTJR-52, Lachnospiraceae bacterium-615, Prevotella corporis, Anaerococcus vaginalis, and Roseburia inulinivorans.ConclusionIn conclusion, patients with AR and nAR had significantly different microbiota profiles compared to healthy controls. The results suggest that the nasal microbiota may play a key role in the pathogenesis and symptoms of AR and nAR, providing us with new ideas for the treatment of AR and nAR.
| S-EPMC10166850 | biostudies-literature