Nasal Transcriptome and Epigenome Analysis Identifies the Pathogenic Features of Aspirin-Exacerbated Respiratory Disease

Abstract

Dysregulation of the arachidonic acid metabolic pathway is the most widely known pathomechanism of aspirin-exacerbated respiratory disease (AERD). This study aimed to perform integrative analysis of transcriptomic and epigenomic profiling with network analysis to determine the novel pathogenic features of AERD. Ten patients with asthma including 5 patients with AERD and another 5 patients with aspirin tolerant asthma (ATA) were enrolled. Nasal scraping was performed and nasal mucosa was used in omics profiling. Peripheral eosinophil counts, sputum eosinophil counts, fractional exhaled nitric oxide 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. In total, 1,736 DEGs, 1,401 DMPs, and 19 pairs for DCGs were identified. Among DCGs, genes related to vesicle transport (e.g., RAB3B and STX2) and sphingolipid dysregulation (e.g., SMPD3) were found to be hypo-methylated and up-regulated in AERD. Using the canonical pathway analysis of IPA with 78 asthma-related DEGs, signaling pathways of T helper cell differentiation/activation and Fcε receptor I were generated. Up-regulation of RORγt and FcER1A were noted in AERD. Gene expression levels of RAB3B, SYNE1, STX2, SMPD3 and RORγt were significantly associated with sputum eosinophil counts. Quantitative real-time polymerase chain reaction was performed and mRNA expression levels of STX2, SMPD3, RORγt, and FcER1A were significantly higher in AERD compared to ATA. Distinct pathogenic features were identified by using integrative multi-omics data analysis in patients with AERD.