ArticleThe Journal of international medical research2021
Identification of key genes in allergic rhinitis by bioinformatics analysis.
Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- Identification of allergic rhinitis-related genes and mediating immune cells based on cis-eQTL: A Mendelian randomization study.Medicine · 2026Article
- DNMT3A-mediated Methylation of IRF4 Alleviates Inflammatory Response in Allergic Rhinitis Mice.Applied biochemistry and biotechnology · 2026Article
- A Novel Machine Learning Approach to Assist Early Diagnosis of Diffuse Panbronchiolitis.Journal of Korean medical science · 2025Article
- [Progress of allergic rhinitis research based on transcriptome sequencing].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2024Review
- Gene-Smoking Interaction Analysis for the Identification of Novel Asthma-Associated Genetic Factors.International journal of molecular sciences · 2023Article
- Article
- A functional genomics pipeline to identify high-value asthma and allergy CpGs in the human methylome.The Journal of allergy and clinical immunology · 2023Article
- Gene Signatures and Associated Transcription Factors of Allergic Rhinitis:BioMed research international · 2023Article
- Genes related to allergen exposure in allergic rhinitis: a gene-chip-based study in a mouse model.BMC medical genomics · 2022Article
- Allergic Diseases: A Comprehensive Review on Risk Factors, Immunological Mechanisms, Link with COVID-19, Potential Treatments, and Role of Allergen Bioinformatics.International journal of environmental research and public health · 2021Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
conclusionsOur findings suggest that hub genes play important roles in the development of AR.
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Registered trials
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