The Journal of allergy and clinical immunology · 2023
Alterations of nasal microbiome in eosinophilic chronic rhinosinusitis.
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Liang Yibo, Xie Runxiang, Xiong Xin, Hu Zhanjun, Mao Xiang, Wang Xiaoyu, Zhang Jinmei, Sun Peiyong, Yue Zhenzhong, Wang Wei, Zhang Guimin
Аннотация
BACKGROUND: Exposure to microbes may be important in the development of chronic rhinosinusitis (CRS). Dysbiosis of the nasal microbiome is considered to be related to CRS with nasal polyps (CRSwNP). The link between the nasal microbiota and eosinophilic CRSwNP (eCRSwNP) has rarely been studied.
OBJECTIVE: The aim of this study was to rigorously characterize nasal dysbiosis in a cohort of patients with eCRSwNP and compare the nasal microbiomes of these patients with those of healthy controls (HCs).
METHODS: We performed a cross-sectional study of 34 patients with eCRSwNP, 10 patients without CRSwNP, and 44 HCs by using 16S rRNA gene sequencing. An independent cohort of 14 patients with eCRSwNP, 9 patients without CRSwNP, and 11 HCs was used to validate the results.
RESULTS: Compared with the nasal microbiome of healthy controls, the nasal microbiome of patients with eCRSwNP was characterized by higher α-diversity (Shannon and Chao1 index) and a distinct composition of microbes. Notably, the distinct differences in microbial composition between patients with eCRSwNP and HCs were significantly correlated with eCRSwNP disease status. Furthermore, in a diagnostic model generated by using these differences, a combination of 15 genera could be used to distinguish patients with eCRSwNP from HCs, with an area under the curve of approximately 0.8 in both the exploration and validation cohorts.
CONCLUSION: Our study establishes the compositional alterations in the nasal microbiome in eCRSwNP and suggests the potential for using the nasal microbiota as a noninvasive predictive classifier for the diagnosis of eCRSwNP.
OBJECTIVE: The aim of this study was to rigorously characterize nasal dysbiosis in a cohort of patients with eCRSwNP and compare the nasal microbiomes of these patients with those of healthy controls (HCs).
METHODS: We performed a cross-sectional study of 34 patients with eCRSwNP, 10 patients without CRSwNP, and 44 HCs by using 16S rRNA gene sequencing. An independent cohort of 14 patients with eCRSwNP, 9 patients without CRSwNP, and 11 HCs was used to validate the results.
RESULTS: Compared with the nasal microbiome of healthy controls, the nasal microbiome of patients with eCRSwNP was characterized by higher α-diversity (Shannon and Chao1 index) and a distinct composition of microbes. Notably, the distinct differences in microbial composition between patients with eCRSwNP and HCs were significantly correlated with eCRSwNP disease status. Furthermore, in a diagnostic model generated by using these differences, a combination of 15 genera could be used to distinguish patients with eCRSwNP from HCs, with an area under the curve of approximately 0.8 in both the exploration and validation cohorts.
CONCLUSION: Our study establishes the compositional alterations in the nasal microbiome in eCRSwNP and suggests the potential for using the nasal microbiota as a noninvasive predictive classifier for the diagnosis of eCRSwNP.