Journal of inflammation research · 2026
Nasal Secretion Multi-Omics Reveals Candidate Signatures for Noninvasive Endotyping of Chronic Rhinosinusitis with Nasal Polyps.
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Wang Yunfei, Cong Jianchao, Lv Hao, Xie Yulie, Guan Mengting, Lei Weiwei, Yu Mengcheng, Peng Hui, Sun Yibin, Liu Peiqiang, Xu Yu
Аннотация
BACKGROUND: Chronic rhinosinusitis with nasal polyps (CRSwNP) is biologically heterogeneous, yet practical noninvasive markers that distinguish eosinophilic CRSwNP (eCRSwNP) from non-eosinophilic CRSwNP (neCRSwNP) remain limited. We investigated nasal-secretion proteomic and metabolic features associated with tissue-defined endotypes in a small pilot cohort.
METHODS: Nasal secretions from controls (n = 5), eCRSwNP (n = 5), and neCRSwNP (n = 5) were analyzed by four-dimensional data-independent acquisition (4D-DIA) proteomics and untargeted metabolomics. An intersection-exclusion strategy was used to prioritize eCRSwNP-associated features across three pairwise comparisons. Candidate proteins were further ranked using apparent receiver operating characteristic (ROC) performance, effect size, exploratory multiple-testing support, and repeated leave-one-out cross-validation (LOOCV)-based penalized regression. Three proteins were measured by enzyme-linked immunosorbent assay (ELISA) in a separate same-center replication set (n = 9). Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO) was performed in nine matched eCRSwNP/neCRSwNP samples retained after metabolomic quality control.
RESULTS: Of 5874 proteins, 4609 passed filtering, and global principal component analysis showed limited separation among groups. The screening strategy prioritized 94 protein features and 28 putatively annotated metabolic features. A score based on tumor protein D52 (TPD52), eosinophil peroxidase (EPX), and transmembrane protein 263 (TMEM263) was higher in eCRSwNP than in neCRSwNP and controls, with concordant directional trends in the ELISA set. DIABLO retained these three proteins together with features putatively annotated as guanosine 3',5'-cyclic monophosphate and UDP-D-galactose. In the nine matched samples, the integrated model yielded an apparent area under the ROC curve (AUC) of 0.95 and a LOOCV error of 0.167; these estimates remain vulnerable to selection bias and overfitting.
CONCLUSION: In this small, single-center study, nasal-secretion multi-omics identified molecular features associated with tissue-defined eCRSwNP. These findings are preliminary and require confirmation in larger independent cohorts using targeted quantification and paired tissue-level biological validation.
METHODS: Nasal secretions from controls (n = 5), eCRSwNP (n = 5), and neCRSwNP (n = 5) were analyzed by four-dimensional data-independent acquisition (4D-DIA) proteomics and untargeted metabolomics. An intersection-exclusion strategy was used to prioritize eCRSwNP-associated features across three pairwise comparisons. Candidate proteins were further ranked using apparent receiver operating characteristic (ROC) performance, effect size, exploratory multiple-testing support, and repeated leave-one-out cross-validation (LOOCV)-based penalized regression. Three proteins were measured by enzyme-linked immunosorbent assay (ELISA) in a separate same-center replication set (n = 9). Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO) was performed in nine matched eCRSwNP/neCRSwNP samples retained after metabolomic quality control.
RESULTS: Of 5874 proteins, 4609 passed filtering, and global principal component analysis showed limited separation among groups. The screening strategy prioritized 94 protein features and 28 putatively annotated metabolic features. A score based on tumor protein D52 (TPD52), eosinophil peroxidase (EPX), and transmembrane protein 263 (TMEM263) was higher in eCRSwNP than in neCRSwNP and controls, with concordant directional trends in the ELISA set. DIABLO retained these three proteins together with features putatively annotated as guanosine 3',5'-cyclic monophosphate and UDP-D-galactose. In the nine matched samples, the integrated model yielded an apparent area under the ROC curve (AUC) of 0.95 and a LOOCV error of 0.167; these estimates remain vulnerable to selection bias and overfitting.
CONCLUSION: In this small, single-center study, nasal-secretion multi-omics identified molecular features associated with tissue-defined eCRSwNP. These findings are preliminary and require confirmation in larger independent cohorts using targeted quantification and paired tissue-level biological validation.