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Microbiome profiling of nasal extracellular vesicles in patients with allergic rhinitis.
Chiang, Tsai-Yeh; Yang, Yu-Ru; Zhuo, Ming-Ying; Yang, Feng; Zhang, Ying-Fei; Fu, Chia-Hsiang; Lee, Ta-Jen; Chung, Wen-Hung; Chen, Liang; Chang, Chih-Jung.
Afiliação
  • Chiang TY; Department of Otorhinolaryngology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
  • Yang YR; Xiamen Chang Gung Allergology Consortium, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
  • Zhuo MY; Department of Otorhinolaryngology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
  • Yang F; Department of Otorhinolaryngology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
  • Zhang YF; Department of Otorhinolaryngology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
  • Fu CH; Department of Otorhinolaryngology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
  • Lee TJ; Department of Otolaryngology-Head and Neck Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan City, Taiwan.
  • Chung WH; Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan City, Taiwan.
  • Chen L; Department of Otorhinolaryngology, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
  • Chang CJ; Department of Otolaryngology-Head and Neck Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan City, Taiwan.
World Allergy Organ J ; 15(8): 100674, 2022 Aug.
Article em En | MEDLINE | ID: mdl-36017065
ABSTRACT

Background:

Nasal microbiota is crucial for the pathogenesis of allergic rhinitis (AR), which has been reported to be different from that of healthy individuals. However, no study has investigated the microbiota in nasal extracellular vesicles (EVs). We aimed to compare the microbiome composition and diversity in EVs between AR patients and healthy controls (HCs) and reveal the potential metabolic mechanisms in AR.

Methods:

Eosinophil counts and serum immunoglobulin E (IgE) levels were measured in patients with AR (n = 20) and HCs (n = 19). Nasal EVs were identified using transmission electron microscopy and flow cytometry. 16S rRNA sequencing was used to profile the microbial communities. Alpha and beta diversities were analyzed to determine microbial diversity. Taxonomic abundance was analyzed based on the linear discriminant analysis effect size (LEfSe). Microbial metabolic pathways were characterized using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUst2) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses.

Results:

Eosinophils, total serum IgE, and IgE specific to Dermatophagoides were increased in patients with AR. Alpha diversity in nasal EVs from patients with AR was lower than that in HCs. Beta diversity showed microbiome differences between the AR and HCs groups. The microbial abundance was distinct between AR and HCs at different taxonomic levels. Significantly higher levels of the genera Acetobacter, Mycoplasma, Escherichia, and Halomonas were observed in AR patients than in HCs. Conversely, Zoogloea, Streptococcus, Burkholderia, and Pseudomonas were more abundant in the HCs group than in the AR group. Moreover, 35 microbial metabolic pathways recognized in AR patients and HCs, and 25 pathways were more abundant in the AR group.

Conclusion:

Patients with AR had distinct microbiota characteristics in nasal EVs compared to that in HCs. The metabolic mechanisms of the microbiota that regulate AR development were also different. These findings show that nasal fluid may reflect the specific pattern of microbiome EVs in patients with AR.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article