BMC Microbiology (Aug 2025)

Correlation between gut microbiota and metabolomics under intermittent hypoxic conditions

  • Tingyuan Zeng,
  • Jianqin Cheng,
  • Yu Pan,
  • Jiaxin Lu,
  • Cheng Niu,
  • Min Wu,
  • Wen Li,
  • Yaqin Liu,
  • Dan Zhao

DOI
https://doi.org/10.1186/s12866-025-04220-z
Journal volume & issue
Vol. 25, no. 1
pp. 1 – 19

Abstract

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Abstract Objective This study investigates the role of gut microbiota and metabolites as biomarkers in the diagnosis and assessment of Obstructive Sleep Apnea (OSA) by analyzing the correlation between microbiota and metabolomics in the host's gut under conditions of chronic intermittent hypoxia (CIH). Methods We analyzed the composition and function of gut microorganisms and metabolites in OSA and CIH mouse models using 16S rRNA sequencing combined with targeted metabolomics to evaluate the association between clinical indicators and severity of OSA and gut flora and metabolites. Results Compared with normal controls, we found: (1) The apnea hypoventilation index (AHI) and fasting blood glucose were higher in the moderate and severe OSA groups, the eosinophilia score (EP) and neutrophil percentage were significantly higher in the severe OSA group, and the percentage of lymphocytes in the blood count and platelet pressures were lower in the moderate group (P < 0.05).(2) The OSA and CIH groups showed an increase in the abundance of Firmicutes and Tenotrophomonas, and a decrease in the abundance of Bacteroidota and Ligilactobacillus (P < 0.05).(3) The OSA and CIH groups had elevated Nervonic acid and Erucic acid and decreased Arachidonic acid (P < 0.05). In addition, correlation analysis showed that: There was a negative correlation between Coprobacillus and percentage of lymphocytes, and Bacteroidota and EP and AHI;and a positive correlation between Lactococcus and Neutrophils, Arachidonic acid and width of erythrocyte distribution, and Erucic and Neuronic acids and AHI (P < 0.05). Conclusion The CIH condition can lead to microbial and metabolite alterations, which correlate with disease severity and clinical indicators, and is expected to be a new biomarker for the diagnosis and assessment of severity of OSA.

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