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Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD
OBJECTIVE: To investigate the distribution differences in the respiratory tract microbiota of AECOPD patients in different BMI groups and explore its guiding value for treatment. METHODS: Sputum samples of thirty-eight AECOPD patients were collected. The patients were divided into low, normal and hi...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10166817/ https://www.ncbi.nlm.nih.gov/pubmed/37180432 http://dx.doi.org/10.3389/fcimb.2023.1161203 |
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author | Cao, Yang Chen, Xiaolin Shu, Lei Shi, Lei Wu, Mingjing Wang, Xueli Deng, Kaili Wei, Jing Yan, Jiaxin Feng, Ganzhu |
author_facet | Cao, Yang Chen, Xiaolin Shu, Lei Shi, Lei Wu, Mingjing Wang, Xueli Deng, Kaili Wei, Jing Yan, Jiaxin Feng, Ganzhu |
author_sort | Cao, Yang |
collection | PubMed |
description | OBJECTIVE: To investigate the distribution differences in the respiratory tract microbiota of AECOPD patients in different BMI groups and explore its guiding value for treatment. METHODS: Sputum samples of thirty-eight AECOPD patients were collected. The patients were divided into low, normal and high BMI group. The sputum microbiota was sequenced by 16S rRNA detection technology, and the distribution of sputum microbiota was compared. Rarefaction curve, α-diversity, principal coordinate analysis (PCoA) and measurement of sputum microbiota abundance in each group were performed and analyzed by bioinformatics methods. RESULTS: 1. The rarefaction curve in each BMI group reached a plateau. No significant differences were observed in the OTU total number or α-diversity index of microbiota in each group. PCoA showed significant differences in the distance matrix of sputum microbiota between the three groups, which was calculated by the Binary Jaccard and the Bray Curtis algorithm. 2. At the phylum level, most of the microbiota were Proteobacteria, Bacteroidetes Firmicutes, Actinobacteria, and Fusobacteria. At the genus level, most were Streptococcus, Prevotella, Haemophilus, Neisseria and Bacteroides. 3. At the phylum level, the abundance of Proteobacteria in the low group was significantly higher than that in normal and high BMI groups, the abundances of Firmicutes in the low and normal groups were significantly lower than that in high BMI groups. At the genus level, the abundance of Haemophilus in the low group was significantly higher than that in high BMI group, and the abundances of Streptococcus in the low and normal BMI groups were significantly lower than that in the high BMI group. CONCLUSIONS: 1. The sputum microbiota of AECOPD patients in different BMI groups covered almost all microbiota, and BMI had no significant association with total number of respiratory tract microbiota or α-diversity in AECOPD patients. However, there was a significant difference in the PCoA between different BMI groups. 2. The microbiota structure of AECOPD patients differed in different BMI groups. Gram-negative bacteria (G(-)) in the respiratory tract of patients predominated in the low BMI group, while gram-positive bacteria (G(+)) predominated in the high BMI group. |
format | Online Article Text |
id | pubmed-10166817 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101668172023-05-10 Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD Cao, Yang Chen, Xiaolin Shu, Lei Shi, Lei Wu, Mingjing Wang, Xueli Deng, Kaili Wei, Jing Yan, Jiaxin Feng, Ganzhu Front Cell Infect Microbiol Cellular and Infection Microbiology OBJECTIVE: To investigate the distribution differences in the respiratory tract microbiota of AECOPD patients in different BMI groups and explore its guiding value for treatment. METHODS: Sputum samples of thirty-eight AECOPD patients were collected. The patients were divided into low, normal and high BMI group. The sputum microbiota was sequenced by 16S rRNA detection technology, and the distribution of sputum microbiota was compared. Rarefaction curve, α-diversity, principal coordinate analysis (PCoA) and measurement of sputum microbiota abundance in each group were performed and analyzed by bioinformatics methods. RESULTS: 1. The rarefaction curve in each BMI group reached a plateau. No significant differences were observed in the OTU total number or α-diversity index of microbiota in each group. PCoA showed significant differences in the distance matrix of sputum microbiota between the three groups, which was calculated by the Binary Jaccard and the Bray Curtis algorithm. 2. At the phylum level, most of the microbiota were Proteobacteria, Bacteroidetes Firmicutes, Actinobacteria, and Fusobacteria. At the genus level, most were Streptococcus, Prevotella, Haemophilus, Neisseria and Bacteroides. 3. At the phylum level, the abundance of Proteobacteria in the low group was significantly higher than that in normal and high BMI groups, the abundances of Firmicutes in the low and normal groups were significantly lower than that in high BMI groups. At the genus level, the abundance of Haemophilus in the low group was significantly higher than that in high BMI group, and the abundances of Streptococcus in the low and normal BMI groups were significantly lower than that in the high BMI group. CONCLUSIONS: 1. The sputum microbiota of AECOPD patients in different BMI groups covered almost all microbiota, and BMI had no significant association with total number of respiratory tract microbiota or α-diversity in AECOPD patients. However, there was a significant difference in the PCoA between different BMI groups. 2. The microbiota structure of AECOPD patients differed in different BMI groups. Gram-negative bacteria (G(-)) in the respiratory tract of patients predominated in the low BMI group, while gram-positive bacteria (G(+)) predominated in the high BMI group. Frontiers Media S.A. 2023-04-25 /pmc/articles/PMC10166817/ /pubmed/37180432 http://dx.doi.org/10.3389/fcimb.2023.1161203 Text en Copyright © 2023 Cao, Chen, Shu, Shi, Wu, Wang, Deng, Wei, Yan and Feng https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular and Infection Microbiology Cao, Yang Chen, Xiaolin Shu, Lei Shi, Lei Wu, Mingjing Wang, Xueli Deng, Kaili Wei, Jing Yan, Jiaxin Feng, Ganzhu Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD |
title | Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD |
title_full | Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD |
title_fullStr | Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD |
title_full_unstemmed | Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD |
title_short | Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD |
title_sort | analysis of the correlation between bmi and respiratory tract microbiota in acute exacerbation of copd |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10166817/ https://www.ncbi.nlm.nih.gov/pubmed/37180432 http://dx.doi.org/10.3389/fcimb.2023.1161203 |
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