There was no significant difference between the two groups in the postoperative air-bone gap and air-bone gap closure at 1, 2, 3, and 6 months.
ObjectiveRNA 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.MethodsRNA 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.ResultsCRS 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.ConclusionTissue 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.Level of Evidence3 Laryngoscope, 133:2480–2489, 2023
Background The role of microbes in chronic rhinosinusitis (CRS) is poorly understood. We hypothesize that analyzing prior microbial exposures via assessing microbial protein serological reactivity in CRS versus controls may offer insights for CRS etiopathogenesis. Methods We profiled IgG and IgA antibodies to individual microbial proteins in serum samples of CRS patients and controls using a novel high‐throughput microarray protein technology, Nucleic Acid Programmable Protein Array (NAPPA). The study was conducted on 118 subjects (39 CRS, 79 controls). A CRS‐focused NAPPA array, with 1557 potentially sero‐reactive microbial proteins elected from a pre‐screening of 6500 genes of interest was constructed. It included membrane‐associated proteins from 47 bacterial species and all proteins from 43 viral strains. Differences between CRS and controls were compared across individual antimicrobial antibodies and the species. Results Chronic rhinosinusitis patients had significantly elevated antimicrobial antibodies compared with controls. One bacterium (Staphylococcus aureus) and three viral strains (human metapneumovirus, human herpesvirus 5, and human herpesvirus 4) were identified as sources of the proteins that showed significantly elevated sero‐reactivity in CRS patients. Within CRS, patients with polyps had elevated antibodies against S. aureus, influenza A virus (H1N1, H3N2), and rhinovirus B14. CRS patients without polyps showed more antibodies against human herpesvirus 1 and vaccinia virus WR. Conclusions Compared with healthy controls, CRS patients’ serum samples showed significantly increased sero‐reactivity to both bacterial and viral proteins, reflecting recent or current infection or active colonization. Significantly higher antibodies against S. aureus, human metapneumovirus, human herpesvirus 5, and human herpesvirus 4 in CRS need further study.
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