Abstract
RNA sequencing (transcriptomics) is used to study biological pathways. However, the yield of data depends on comparing well-characterized cohorts. We compared tissue eosinophilia versus nasal polyp (NP) status as the metric to characterize transcriptomic mechanisms at play in eosinophilic and non-eosinophilic chronic rhinosinusitis (CRS) versus controls. RNA sequencing was conducted on sinonasal tissue samples of CRS and controls. Analyses were conducted based on polyp status [with nasal polyps (CRSwNP) and without nasal polyps (CRSsNP)] as well as tissue eosinophil levels per high power field (eos/hpf)[non-eosinophilic (<10 eos/hpf, neCRS) or eosinophilic (≥10 eos/hpf, eCRS)]. The yield of differentially expressed genes (DEGs) and biological pathways through Ingenuity Pathway Analysis (IPA) were compared. CRS tissue differed from controls by 736 statistically significant DEGs. Both NP status and tissue eosinophilia were effective in differentiating CRS from controls and into two distinct subgroups. Statistically significant DEGs identified when comparing CRS by NP status were 60, whereas 110 DEGs were identified using eosinophil cutoff ≥10 and <10 eos/hpf. Additionally, heatmaps showed greater homogeneity within each CRS subgroup when analyzed by tissue eosinophilia versus NP status. On IPA, the IL-17 signaling pathway was significantly different only by tissue eosinophilia status, not NP status, being higher in CRS <10 eos/hpf. Tissue eosinophilia is superior to an analysis by NP status for the study of CRS transcriptome by RNA sequencing in identifying DEGs. Classification of CRS samples by eosinophil counts agnostic of NP status may offer advantageous insights into CRS pathogenetic mechanisms. 3 Laryngoscope, 133:2480-2489, 2023.
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