Objectives: Allergic rhinitis (AR) patients infected with rhinovirus (RV) exhibit severer condition and more airway inflammation. However, the mechanisms of airway inflammation exacerbated by RV are still largely unknown. Methods: Bioinformatic tools were used to identify the differentially expressed genes (DEGs) specific in AR nasal epithelium responding to dsRNA based on the GSE51392 dataset retrieved from the Gene Expression Omnibus (GEO) database. DEGs were enriched by Gene ontology (GO) and the Kyoto encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. In addition, protein-protein interaction (PPI) network was constructed to find the key genes and modules specific in AR. Results: From GSE51392 dataset, we identified 545 up-regulated and 400 down-regulated AR-specific genes in nasal epithelium responding to dsRNA, including up-regulated PPBP/CXCL7 and down-regulated IL20, BLNK, CEBPD, LY96. After GO and KEGG analyses, we found different functions and signaling pathways in nasal epithelium of AR compared to HC. In addition, the PPI network of DEGs was constructed, which was composed of 791 nodes and 603 edges. 16 genes with high degrees, including PPBP/CXCL7, were identified as hub genes, and five important modules were selected from PPI network using MCODE. Conclusion: Our data suggested that up-regulated PPBP/CXCL7 and down-regulated IL20, BLNK, CEBPD, LY96 may be important contributors to RV induced AR exacerbation. We also found different functions and signaling pathways in nasal epithelium of AR compared to HC. These results may help to understand the underlying mechanisms linking RV infection to AR exacerbation.