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. 2021 Jul;49(7):3000605211029521.
doi: 10.1177/03000605211029521.

Identification of key genes in allergic rhinitis by bioinformatics analysis

Yunfei Zhang  1 , Yue Huang  1 , Wen-Xia Chen  1 , Zheng-Min Xu  1
Affiliations

Identification of key genes in allergic rhinitis by bioinformatics analysis

Yunfei Zhang et al. J Int Med Res. 2021 Jul.

Abstract

Objective: This study aimed to explore the potential molecular mechanism of allergic rhinitis (AR) and identify gene signatures by analyzing microarray data using bioinformatics methods.

Methods: The 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.

Results: A 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.

Conclusions: Our findings suggest that hub genes play important roles in the development of AR.

Keywords: Allergic rhinitis; bioinformatics; differentially expressed genes; gene expression profile; gene ontology; hub gene.

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Conflict of interest statement

Declaration of conflicting interest: The authors declare that there is no conflict of interest.

Figures

Figure 1.
Figure 1.
Volcano plot for the distribution of gene expression between patients with AR and healthy controls from the GSE19187 dataset. Negative log10-transformed P values are plotted against log ratios (log2 fold change) in the two groups. Red and blue points represent down-regulated and up-regulated genes in patients with AR compared with healthy controls, respectively. Gray points represent non-differentially expressed genes. Critical genes are labeled. AR, allergic rhinitis.
Figure 2.
Figure 2.
Heatmap of DEG hierarchical clustering between patients with AR and healthy controls. Rows represent genes, while columns represent samples. The red bar represents patients with AR while the blue bar represents healthy controls. Values are gene expression levels. DEGs, differentially expressed genes; AR, allergic rhinitis.
Figure 3.
Figure 3.
Highest module selected from the DEG PPI between patients with AR and healthy controls. Pink rectangles represent up-regulated genes while blue ones represent down-regulated genes DEG, differentially expressed gene; PPI, protein–protein interaction; AR, allergic rhinitis.
Figure 4.
Figure 4.
Expression of validated hub genes in original and validation datasets. GSE19187 is the original dataset, while the merger of GSE44037 and GSE43523 was used as the validation dataset. *, P < 0.05
See this image and copyright information in PMC

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