International Rhinologic Society Rhinology 0300-0729 2026 03 17 Integrated omics-based analysis reveals distinct microbial-metabolite interaction networks in eosinophilic and non-eosinophilic chronic rhinosinusitis with nasal polyps in a Chinese population EN H. Zhang Department of Otolaryngology, The Second Qilu Hospital of Shandong University, Jinan, Shandong, China X. Zi Department of Otolaryngology, The Second Qilu Hospital of Shandong University, Jinan, Shandong, China X. Li Department of Allergy, The First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Shandong Institute of Respiratory Diseases, Jinan, China T. Gao Department of Allergy, The First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Shandong Institute of Respiratory Diseases, Jinan, China H. Zhang Department of Otolaryngology, The Second Qilu Hospital of Shandong University, Jinan, Shandong, China H. Zhang Department of Otolaryngology, The Second Qilu Hospital of Shandong University, Jinan, Shandong, China X. Liang Department of Otolaryngology, The Second Qilu Hospital of Shandong University, Jinan, Shandong, China L. Zhi Department of Allergy, The First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Shandong Institute of Respiratory Diseases, Jinan, China P. Jin Department of Otolaryngology, The Second Qilu Hospital of Shandong University, Jinan, Shandong, China Journal Article 3417 10.4193/Rhin25.166 Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a heterogeneous inflammatory condition often classified into eosinophilic (Eos) and non-eosinophilic (nonEos) subtypes. While microbial dysbiosis and metabolic disturbance are known contributors to CRSwNP, the interplay between sinonasal microbiota and local metabolic activity remains unclear. Methods: We conducted 16S rRNA gene sequencing and untargeted metabolomics on sinonasal swabs and tissue samples from patients with Eos-CRSwNP (n = 14), nonEos CRSwNP (n = 7), and healthy controls (n = 14). Microbial diversity, taxonomic differences, and metabolic alterations were analyzed. Spearman correlation and network modeling were used to explore phenotype-specific microbiota–metabolite interactions and pathway enrichment. Results: Eos CRSwNP was characterized by reduced microbial diversity and increased abundance of Staphylococcus and Corynebacterium, along with elevated levels of fumaric acid, linoleic acid, and arachidonic acid—metabolites linked to oxidative stress and lipid-mediated inflammation. In contrast, nonEos-CRSwNP exhibited greater microbial richness, with enrichment of Streptococcus, Anaerococcus, and Clostridium XlVa, and metabolic shifts in amino acid and nitrogen metabolism, including increased glutamine, taurine, and ethanolamine phosphate. Correlation analysis revealed phenotype-specific networks connecting core microbial genera and metabolites, suggesting distinct inflammatory microenvironments between subtypes. Conclusion: Our integrated multi-omics analysis highlights divergent microbial and metabolic signatures in Eos and nonEos CRSwNP. These findings offer mechanistic insights into subtype-specific disease processes and may guide the future development of targeted diagnostic and therapeutic strategies.