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Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome

AIM: To analyze the bacterial community structure and distribution of intestinal microflora in people with and without metabolic syndrome and combined these data with clinical indicators to determine relationships between selected bacteria and metabolic diseases. METHODS: Faecal samples were collect...

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Autores principales: Lin, Lang, Wen, Zai-Bo, Lin, Dong-Jiao, Dong, Jiang-Ting, Jin, Jie, Meng, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902506/
https://www.ncbi.nlm.nih.gov/pubmed/29670890
http://dx.doi.org/10.12998/wjcc.v6.i4.54
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author Lin, Lang
Wen, Zai-Bo
Lin, Dong-Jiao
Dong, Jiang-Ting
Jin, Jie
Meng, Fei
author_facet Lin, Lang
Wen, Zai-Bo
Lin, Dong-Jiao
Dong, Jiang-Ting
Jin, Jie
Meng, Fei
author_sort Lin, Lang
collection PubMed
description AIM: To analyze the bacterial community structure and distribution of intestinal microflora in people with and without metabolic syndrome and combined these data with clinical indicators to determine relationships between selected bacteria and metabolic diseases. METHODS: Faecal samples were collected from 20 patients with metabolic syndrome and 16 controls at Cangnan People’s Hospital, Zhejiang Province, China. DNA was extracted and the V3-V4 regions of the 16S rRNA genes were amplified for high throughput sequencing. Clear reads were clustered at the 97% sequence similarity level. α and β diversity were used to describe the bacterial community structure and distribution in patients. Combined with the clinical indicators, further analysis was performed. RESULTS: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, Fusobacteria were the dominant phyla, and Prevotella, Bacteroides and Faecalibacterium was the top three genera in faecal samples. α diversity analysis showed that the species richness of metabolic syndrome samples (group D) was significantly higher than the control (group C) (P < 0.05), and the microbial diversity of group C was greater than that of group D. According to the principal co-ordinates analysis, the samples of group C clustered more tightly, indicating that the distribution of bacteria in healthy patients was similar. The correlation analysis showed that alkaline phosphatase was negatively correlated with the abundance of Prevotella (P < 0.05). There was a negative correlation between low-density lipoprotein and the abundance of Ruminococcus (P < 0.05) and a positive correlation between the high-density lipoprotein and the abundance of Ruminococcus (P < 0.05). The total protein and the alanine aminotransferase was positively correlated with the abundance of Peptostreptococcus (P < 0.05). CONCLUSION: The changes microbial communities can be used as an indicator of metabolic syndrome, and Prevotella may be a target microorganism in patients with metabolic syndrome.
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spelling pubmed-59025062018-04-18 Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome Lin, Lang Wen, Zai-Bo Lin, Dong-Jiao Dong, Jiang-Ting Jin, Jie Meng, Fei World J Clin Cases Observational Study AIM: To analyze the bacterial community structure and distribution of intestinal microflora in people with and without metabolic syndrome and combined these data with clinical indicators to determine relationships between selected bacteria and metabolic diseases. METHODS: Faecal samples were collected from 20 patients with metabolic syndrome and 16 controls at Cangnan People’s Hospital, Zhejiang Province, China. DNA was extracted and the V3-V4 regions of the 16S rRNA genes were amplified for high throughput sequencing. Clear reads were clustered at the 97% sequence similarity level. α and β diversity were used to describe the bacterial community structure and distribution in patients. Combined with the clinical indicators, further analysis was performed. RESULTS: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, Fusobacteria were the dominant phyla, and Prevotella, Bacteroides and Faecalibacterium was the top three genera in faecal samples. α diversity analysis showed that the species richness of metabolic syndrome samples (group D) was significantly higher than the control (group C) (P < 0.05), and the microbial diversity of group C was greater than that of group D. According to the principal co-ordinates analysis, the samples of group C clustered more tightly, indicating that the distribution of bacteria in healthy patients was similar. The correlation analysis showed that alkaline phosphatase was negatively correlated with the abundance of Prevotella (P < 0.05). There was a negative correlation between low-density lipoprotein and the abundance of Ruminococcus (P < 0.05) and a positive correlation between the high-density lipoprotein and the abundance of Ruminococcus (P < 0.05). The total protein and the alanine aminotransferase was positively correlated with the abundance of Peptostreptococcus (P < 0.05). CONCLUSION: The changes microbial communities can be used as an indicator of metabolic syndrome, and Prevotella may be a target microorganism in patients with metabolic syndrome. Baishideng Publishing Group Inc 2018-04-16 2018-04-16 /pmc/articles/PMC5902506/ /pubmed/29670890 http://dx.doi.org/10.12998/wjcc.v6.i4.54 Text en ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
spellingShingle Observational Study
Lin, Lang
Wen, Zai-Bo
Lin, Dong-Jiao
Dong, Jiang-Ting
Jin, Jie
Meng, Fei
Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome
title Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome
title_full Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome
title_fullStr Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome
title_full_unstemmed Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome
title_short Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome
title_sort correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome
topic Observational Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902506/
https://www.ncbi.nlm.nih.gov/pubmed/29670890
http://dx.doi.org/10.12998/wjcc.v6.i4.54
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