S100a9 might act as a modulator of the Toll-like receptor 4 transduction pathway in chronic rhinosinusitis with nasal polyps.
Nasibeh KhayerMaryam JalessiMohammad FarhadiZahra AzadPublished in: Scientific reports (2024)
Chronic rhinosinusitis with nasal polyp (CRSwNP) is a highly prevalent disorder characterized by persistent nasal and sinus mucosa inflammation. Despite significant morbidity and decreased quality of life, there are limited effective treatment options for such a disease. Therefore, identifying causal genes and dysregulated pathways paves the way for novel therapeutic interventions. In the current study, a three-way interaction approach was used to detect dynamic co-expression interactions involved in CRSwNP. In this approach, the internal evolution of the co-expression relation between a pair of genes (X, Y) was captured under a change in the expression profile of a third gene (Z), named the switch gene. Subsequently, the biological relevancy of the statistically significant triplets was confirmed using both gene set enrichment analysis and gene regulatory network reconstruction. Finally, the importance of identified switch genes was confirmed using a random forest model. The results suggested four dysregulated pathways in CRSwNP, including "positive regulation of intracellular signal transduction", "arachidonic acid metabolic process", "spermatogenesis" and "negative regulation of cellular protein metabolic process". Additionally, the S100a9 as a switch gene together with the gene pair {Cd14, Tpd52l1} form a biologically relevant triplet. More specifically, we suggested that S100a9 might act as a potential upstream modulator in toll-like receptor 4 transduction pathway in the major CRSwNP pathologies.
Keyphrases
- chronic rhinosinusitis
- toll like receptor
- genome wide identification
- genome wide
- copy number
- inflammatory response
- genome wide analysis
- poor prognosis
- nuclear factor
- dna methylation
- immune response
- transcription factor
- oxidative stress
- small molecule
- physical activity
- gene expression
- binding protein
- risk assessment
- protein protein
- data analysis