Introduction: Chronic obstructive pulmonary disease (COPD), an incurable chronic respiratory disease, has become a major public health problem. The relationship between the composition of intestinal microbiota and the important clinical factors affecting COPD remains unclear. This study aimed to identify specific intestinal microbiota with high clinical diagnostic value for COPD.
Methods: The fecal microbiota of patients with COPD and healthy individuals were analyzed by 16S rDNA sequencing. Random forest classification was performed to analyze the different intestinal microbiota. Spearman correlation was conducted to analyze the correlation between different intestinal microbiota and clinical characteristics. A microbiota-disease network diagram was constructed using the gut MDisorder database to identify the possible pathogenesis of intestinal microorganisms affecting COPD, screen for potential treatment, and guide future research.
Results: No significant difference in biodiversity was shown between the two groups but significant differences in microbial community structure. Fifteen genera of bacteria with large abundance differences were identified, including , and . Among them, the relative abundance of and was negatively related to the smoking index and positively related to lung function results. By contrast, the relative abundance of was positively correlated with the smoking index and negatively correlated with lung function findings. Random forest classification showed that was the genus most capable of distinguishing between patients with COPD and healthy individuals suggesting it may be a potential biomarker of COPD. A disease network diagram suggested that decreased in some diseases, such as asthma, diabetes mellitus, and coronavirus disease 2019 (COVID-19), and increased in other diseases, such as irritable bowel syndrome, hypertension, and bovine lichen.
Conclusion: The dominant intestinal microbiota with significant differences is related to the clinical characteristics of COPD, and the has the potential value to identify COPD.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11003469 | PMC |
http://dx.doi.org/10.2147/COPD.S436551 | DOI Listing |
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