Cargando…
Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis
PURPOSE: To investigate the relationship between gut microbiota and liver fibrosis and establish a microbiota biomarker for detecting and staging liver fibrosis. METHODS: 131 Wistar rats were used in our study, and liver fibrosis was induced by carbon tetrachloride. Stool samples were collected with...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322594/ https://www.ncbi.nlm.nih.gov/pubmed/32685479 http://dx.doi.org/10.1155/2020/3905130 |
_version_ | 1783551673221775360 |
---|---|
author | Li, Zhiming Ni, Ming Yu, Haiyang Wang, Lili Zhou, Xiaoming Chen, Tao Liu, Guangzhen Gao, Yuanxiang |
author_facet | Li, Zhiming Ni, Ming Yu, Haiyang Wang, Lili Zhou, Xiaoming Chen, Tao Liu, Guangzhen Gao, Yuanxiang |
author_sort | Li, Zhiming |
collection | PubMed |
description | PURPOSE: To investigate the relationship between gut microbiota and liver fibrosis and establish a microbiota biomarker for detecting and staging liver fibrosis. METHODS: 131 Wistar rats were used in our study, and liver fibrosis was induced by carbon tetrachloride. Stool samples were collected within 72 hours after the last administration. The V4 regions of 16S rRNA gene were amplified. The sequencing data was processed using the Quantitative Insights Into Microbial Ecology (QIIME version 1.9). The diversity, principal coordinate analysis (PCoA), nonmetric multidimensional scaling (NMDS), and linear discriminant analysis (LDA) effect size (LEfSe) were performed. Random-Forest classification was performed for discriminating the samples from different groups. Microbial function was assessed using the PICRUST. RESULTS: The Simpson in the control group was lower than that in the liver fibrosis group (p = 0.048) and differed significantly among different fibrosis stages (p = 0.047). The Chao1 index in the control group was higher than that in the liver fibrosis group (p < 0.001). NMDS analysis showed a marked difference between the control and liver fibrosis groups (p < 0.001). PCoA analysis indicated the different community composition between the control and liver fibrosis groups with variances of PC1 13.76% and PC2 5.89% and between different liver fibrosis stages with variances of PC1 10.51% and PC2 7.78%. LEfSe analysis showed alteration of gut microbiota in the liver fibrosis group. Biomarkers obtained from Random-Forest classification showed excellent diagnostic accuracy in prediction of liver fibrosis with AUROCs of 0.99. The AUROCs were 0.77~0.84 in prediction of stage F4. There were six increased and 17 decreased metabolic functions in the liver fibrosis group and 6 metabolic functions significantly differed among four liver fibrosis stages. CONCLUSION: Gut microbiota is a potential biomarker for detecting and staging liver fibrosis with high diagnostic accuracies. |
format | Online Article Text |
id | pubmed-7322594 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-73225942020-07-17 Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis Li, Zhiming Ni, Ming Yu, Haiyang Wang, Lili Zhou, Xiaoming Chen, Tao Liu, Guangzhen Gao, Yuanxiang Biomed Res Int Research Article PURPOSE: To investigate the relationship between gut microbiota and liver fibrosis and establish a microbiota biomarker for detecting and staging liver fibrosis. METHODS: 131 Wistar rats were used in our study, and liver fibrosis was induced by carbon tetrachloride. Stool samples were collected within 72 hours after the last administration. The V4 regions of 16S rRNA gene were amplified. The sequencing data was processed using the Quantitative Insights Into Microbial Ecology (QIIME version 1.9). The diversity, principal coordinate analysis (PCoA), nonmetric multidimensional scaling (NMDS), and linear discriminant analysis (LDA) effect size (LEfSe) were performed. Random-Forest classification was performed for discriminating the samples from different groups. Microbial function was assessed using the PICRUST. RESULTS: The Simpson in the control group was lower than that in the liver fibrosis group (p = 0.048) and differed significantly among different fibrosis stages (p = 0.047). The Chao1 index in the control group was higher than that in the liver fibrosis group (p < 0.001). NMDS analysis showed a marked difference between the control and liver fibrosis groups (p < 0.001). PCoA analysis indicated the different community composition between the control and liver fibrosis groups with variances of PC1 13.76% and PC2 5.89% and between different liver fibrosis stages with variances of PC1 10.51% and PC2 7.78%. LEfSe analysis showed alteration of gut microbiota in the liver fibrosis group. Biomarkers obtained from Random-Forest classification showed excellent diagnostic accuracy in prediction of liver fibrosis with AUROCs of 0.99. The AUROCs were 0.77~0.84 in prediction of stage F4. There were six increased and 17 decreased metabolic functions in the liver fibrosis group and 6 metabolic functions significantly differed among four liver fibrosis stages. CONCLUSION: Gut microbiota is a potential biomarker for detecting and staging liver fibrosis with high diagnostic accuracies. Hindawi 2020-06-19 /pmc/articles/PMC7322594/ /pubmed/32685479 http://dx.doi.org/10.1155/2020/3905130 Text en Copyright © 2020 Zhiming Li et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Zhiming Ni, Ming Yu, Haiyang Wang, Lili Zhou, Xiaoming Chen, Tao Liu, Guangzhen Gao, Yuanxiang Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis |
title | Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis |
title_full | Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis |
title_fullStr | Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis |
title_full_unstemmed | Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis |
title_short | Gut Microbiota and Liver Fibrosis: One Potential Biomarker for Predicting Liver Fibrosis |
title_sort | gut microbiota and liver fibrosis: one potential biomarker for predicting liver fibrosis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322594/ https://www.ncbi.nlm.nih.gov/pubmed/32685479 http://dx.doi.org/10.1155/2020/3905130 |
work_keys_str_mv | AT lizhiming gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis AT niming gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis AT yuhaiyang gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis AT wanglili gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis AT zhouxiaoming gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis AT chentao gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis AT liuguangzhen gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis AT gaoyuanxiang gutmicrobiotaandliverfibrosisonepotentialbiomarkerforpredictingliverfibrosis |