Objective:To identify diagnostic markers related to oxidative stress in chronic rhinosinusitis with nasal polyps (CRSwNP) by analyzing transcriptome sequencing data, and to investigate their roles in CRSwNP.Methods:Utilizing four CRSwNP sequencing datasets, differentially expressed genes (DEGs) analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning methods for Hub gene selection were performed in this study. Subsequent validation was carried out using external datasets, as well as real-time quantitative polymerase chain reaction (Real-time qPCR), and immunofluorescence staining of clinical samples. Moreover, the diagnostic efficacy of the genes was assessed by receiver operating characteristic (ROC) curve, followed by functional and pathway enrichment analysis, immune-related analysis, and cell population localization. Additionally, a competing endogenous RNA (CeRNA) network was constructed to predict potential drug targets. Statistical analysis and plotting were conducted using SPSS 26.0 and Graphpad Prism9 software.Results:Through data analysis and clinical validation, CP, SERPINF1 and GSTO2 were identified among 4 138 DEGs as oxidative stress markers related to CRSwNP. Specifically, the expression of CP and SERPINF1 increased in CRSwNP, whereas that of GSTO2 decreased, with statistically significant differences ( P<0.05). Additionally, an area under the curve (AUC)>0.7 indicated their effectiveness as diagnostic indicators. Importantly, functional analysis indicated that these genes were mainly related to lipid metabolism, cell adhesion migration, and immunity. Single-cell data analysis revealed that SERPINF1 was mainly distributed in epithelial cells, stromal cells, and fibroblasts, while CP was primarily located in epithelial cells, and GSTO2 was minimally present in the epithelial cells and fibroblasts of nasal polyps. Consequently, a CeRNA regulatory network was constructed for the genes CP and GSTO2. This construction allowed for the prediction of potential drugs that could target CP. Conclusion:This study successfully identifies CP, SERPINF1 and GSTO2 as diagnostic and therapeutic markers related to oxidative stress in CRSwNP.

OBJECTIVETo investigate the relationship between the genetic polymorphisms of matrix metalloproteinase-2 (MMP-2) (-735) and matrix metalloproteinase-3 (MMP-3) (-1171) and the susceptibility to silicosis.

METHODSA case-control study was conducted in 113 patients diagnosed with stage I silicosis (case group) and 115 dust-exposed workers without silicosis (control group); the two groups had the same sex, ethnic group, and type of dust and similar age and cumulative exposure time. Polymerase chain reaction-restriction fragment length polymorphism was used to determine the genotypes of MMP-2 (-735) and MMP-3 (-1171).

RESULTSNo significant difference was observed in age, cumulative exposure time, or smoking rate between cases and controls (P > 0.05). The frequencies of genotypes C/C, C/T, and T/T at MMP-2 C-735T in the case group were 57.5% (65/113), 31.0% (35/113), and 11.5% (13/113), respectively, which were significantly different from those of the control group (69.6% (80/115), 26.9% (31/115), and 3.5% (4/115)), χ² = 6.542, P < 0.05). The frequencies of T allele in cases and controls were 27.0% and 17.0%, respectively, which were significantly different from each other χ² = 6.704, P < 0.05). Carriage of T allele at MMP-2 C-735T increased the risk of silicosis (OR = 1.811, 95% CI: 1.151-2.847). The frequencies of genotypes 6A/6A, 5A/6A, and 5A/5A at MMP-3 A-1171A were 67.2% (76/113), 24.8% (28/113), and 8.0% (9/113), respectively, in the case group, versus 59.1% (68/115), 37.4% (43/115), and 3.5% (4/115) in the control group (χ² = 5.519, P > 0.05).

CONCLUSIONGenetic polymorphism at MMP-2 C-735T is significantly associated with the development of silicosis. Carriage of T allele increases the risk of silicosis among workers exposed to dust. No significant association was found between MMP-3 A-1171A polymorphism and silicosis in this study.

Adult ; Aged ; Aged, 80 and over ; Case-Control Studies ; Genetic Predisposition to Disease ; Genotype ; Humans ; Matrix Metalloproteinase 2 ; genetics ; Matrix Metalloproteinase 3 ; genetics ; Middle Aged ; Polymorphism, Genetic ; Silicosis ; genetics