Multiomic analysis identifies natural intrapatient temporal variability and changes in response to systemic corticosteroid therapy in chronic rhinosinusitis.
2020
INTRODUCTION The pathophysiology and temporal dynamics of affected tissues in chronic rhinosinusitis (CRS) remain poorly understood. Here, we present a multiomics-based time-series assessment of nasal polyp biopsies from three patients with CRS, assessing natural variability over time and local response to systemic corticosteroid therapy. METHODS Polyp tissue biopsies were collected at three time points over two consecutive weeks. Patients were prescribed prednisone (30 mg daily) for 1 week between Collections 2 and 3. Polyp transcriptome, proteome, and microbiota were assessed via RNAseq, SWATH mass spectrometry, and 16S ribosomal RNA and ITS2 amplicon sequencing. Baseline interpatient variability, natural intrapatient variability over time, and local response to systemic corticosteroids, were investigated. RESULTS Overall, the highly abundant transcripts and proteins were associated with pathways involved in inflammation, FAS, cadherin, integrin, Wnt, apoptosis, and cytoskeletal signaling, as well as coagulation and B- and T-cell activation. Transcripts and proteins that naturally varied over time included those involved with inflammation- and epithelial-mesenchymal transition-related pathways, and a number of common candidate target biomarkers of CRS. Ten transcripts responded significantly to corticosteroid therapy, including downregulation of TNF, CCL20, and GSDMA, and upregulation of OVGP1, and PCDHGB1. Members of the bacterial genus Streptococcus positively correlated with immunoglobulin proteins IGKC and IGHG1. CONCLUSIONS Understanding natural dynamics of CRS-associated tissues is essential to provide baseline context for all studies on putative biomarkers, mechanisms, and subtypes of CRS. These data further our understanding of the natural dynamics within nasal polypoid tissue, as well as local changes in response to systemic corticosteroid therapy.
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