朱 继, 卢 曼, 焦 倩, 孙 运, 刘 璐, 丁 红, 于 燕, 潘 磊. [Analysis of gut target microbiota and species difference in patients with obstructive sleep apnea based on 16S rRNA sequencing].
NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2024;
44:146-155. [PMID:
38293986 PMCID:
PMC10878889 DOI:
10.12122/j.issn.1673-4254.2024.01.17]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Indexed: 02/01/2024]
Abstract
OBJECTIVE
To explore the difference in gut microbiota composition between patients with obstructive sleep apnea (OSA) and healthy individuals and the role of gut microbiota in the pathogenesis of OSA.
METHODS
Thirty-nine patients with OSA admitted to our hospital between May and December, 2022 and 20 healthy individuals were enrolled in this study. Stool samples were collected from all the participants for analysis of microbiome composition using 16S rRNA high- throughput sequencing analysis. The alpha diversity, beta diversity, and species difference were determined between the two groups and marker species analysis and metabolic pathway function prediction analysis were performed.
RESULTS
The species diversity (Shannon and Simpson) indexes, richness (observed species) and evenness (Pielou) of gut microbiota were significantly lower in OSA patients than in the healthy individuals (P < 0.05). The OSA patients had also a significantly lowered community diversity (P < 0.05) with different gut microbial communities from those of the healthy individuals shown by increased relative abundance of potentially pathogenic bacteria such as Pseudomonas and Monocytogenes (P < 0.05). LEfSe analysis showed that the abundance of 23 species of gut microbiota differed significantly between the two groups and the OSA patients had significant increases in the abundance of Pseudomonas, Meganomonas, and Fusobacterium (P < 0.05). The differential marker flora affected host homeostasis. Random Forest and ROC curve analyses confirmed that Pseudomonas could be used as important biomarkers for a differential diagnosis. Metabolic pathway function prediction analysis showed that biosynthesis function had the greatest contribution to maintaining gut microbiota homeostasis, and Pseudomonas affected the occurrence and progression of OSA by participating in aromatic bioamine degradation and ketogluconic acid metabolic pathway.
CONCLUSION
OSA patients have obvious gut microbiota disturbances, and Pseudomonas may affect the development of OSA by participating in substance metabolism to serve as the potential target gut bacteria for OSA treatment.
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