Background: Dysregulation of the arachidonic acid metabolic pathway is the most widely known pathomechanism of AERD. We performed integrative analysis of transcriptomic and epigenomic profiling with network analysis to determine the novel pathogenic features of AERD. Methods: Ten patients with asthma including 5 patients with AERD and another 5 patients with aspirin tolerant asthma (ATA) were enrolled. Nasal epithelial scraping was performed and nasal mucosa was used in omics profiling. Peripheral eosinophil counts, sputum eosinophil counts, FeNO levels, and pulmonary function test results were evaluated. Differentially expressed genes (DEGs), differentially methylated probes (DMPs) and differentially correlated genes (DCGs) between patients with AERD and those with ATA were analyzed. Network analysis using Ingenuity Pathway Analysis (IPA) was performed to determine the gene connection network and signaling pathways. Results: In total, 1,736 DEGs and 1,401 DMPs were identified. Finally, 19 pairs for DCGs were selected. Among DCGs, genes related to vesicle transport (e.g. STX2 and RAB3B) and sphingolipid dysregulation (e.g. SMPD3) were found to be hypo-methylated and up-regulated in patients with AERD. A total number of 78 asthma-related DEGs were identified by the IPA knowledge base. Using the canonical pathway analysis of IPA, signaling pathways of T helper cell differentiation/activation and Fcε receptor I were generated. Up-regulation of RORγt and down-regulation of MHCII, TNFR, and TGF-β as well as up-regulation of FCER1A and JAK and down-regulation of VAV and cPLA2 were noted in patients with AERD. Conclusions: Distinct pathogenic features were identified by using integrative multi-omics data analysis in patients with AERD.