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Alterations of the Human Gut Microbiome in Chronic Kidney Disease
Gut microbiota make up the largest microecosystem in the human body and are closely related to chronic metabolic diseases. Herein, 520 fecal samples are collected from different regions of China, the gut microbiome in chronic kidney disease (CKD) is characterized, and CKD classifiers based on microb...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578882/ https://www.ncbi.nlm.nih.gov/pubmed/33101877 http://dx.doi.org/10.1002/advs.202001936 |
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author | Ren, Zhigang Fan, Yajuan Li, Ang Shen, Quanquan Wu, Jian Ren, Lingyan Lu, Haifeng Ding, Suying Ren, Hongyan Liu, Chao Liu, Wenli Gao, Dan Wu, Zhongwen Guo, Shiyuan Wu, Ge Liu, Zhangsuo Yu, Zujiang Li, Lanjuan |
author_facet | Ren, Zhigang Fan, Yajuan Li, Ang Shen, Quanquan Wu, Jian Ren, Lingyan Lu, Haifeng Ding, Suying Ren, Hongyan Liu, Chao Liu, Wenli Gao, Dan Wu, Zhongwen Guo, Shiyuan Wu, Ge Liu, Zhangsuo Yu, Zujiang Li, Lanjuan |
author_sort | Ren, Zhigang |
collection | PubMed |
description | Gut microbiota make up the largest microecosystem in the human body and are closely related to chronic metabolic diseases. Herein, 520 fecal samples are collected from different regions of China, the gut microbiome in chronic kidney disease (CKD) is characterized, and CKD classifiers based on microbial markers are constructed. Compared with healthy controls (HC, n = 210), gut microbial diversity is significantly decreased in CKD (n = 110), and the microbial community is remarkably distinguished from HC. Genera Klebsiella and Enterobacteriaceae are enriched, while Blautia and Roseburia are reduced in CKD. Fifty predicted microbial functions including tryptophan and phenylalanine metabolisms increase, while 36 functions including arginine and proline metabolisms decrease in CKD. Notably, five optimal microbial markers are identified using the random forest model. The area under the curve (AUC) reaches 0.9887 in the discovery cohort and 0.9512 in the validation cohort (49 CKD vs 63 HC). Importantly, the AUC reaches 0.8986 in the extra diagnosis cohort from Hangzhou. Moreover, Thalassospira and Akkermansia are increased with CKD progression. Thirteen operational taxonomy units are correlated with six clinical indicators of CKD. In conclusion, this study comprehensively characterizes gut microbiome in non‐dialysis CKD and demonstrates the potential of microbial markers as non‐invasive diagnostic tools for CKD in different regions of China. |
format | Online Article Text |
id | pubmed-7578882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75788822020-10-23 Alterations of the Human Gut Microbiome in Chronic Kidney Disease Ren, Zhigang Fan, Yajuan Li, Ang Shen, Quanquan Wu, Jian Ren, Lingyan Lu, Haifeng Ding, Suying Ren, Hongyan Liu, Chao Liu, Wenli Gao, Dan Wu, Zhongwen Guo, Shiyuan Wu, Ge Liu, Zhangsuo Yu, Zujiang Li, Lanjuan Adv Sci (Weinh) Full Papers Gut microbiota make up the largest microecosystem in the human body and are closely related to chronic metabolic diseases. Herein, 520 fecal samples are collected from different regions of China, the gut microbiome in chronic kidney disease (CKD) is characterized, and CKD classifiers based on microbial markers are constructed. Compared with healthy controls (HC, n = 210), gut microbial diversity is significantly decreased in CKD (n = 110), and the microbial community is remarkably distinguished from HC. Genera Klebsiella and Enterobacteriaceae are enriched, while Blautia and Roseburia are reduced in CKD. Fifty predicted microbial functions including tryptophan and phenylalanine metabolisms increase, while 36 functions including arginine and proline metabolisms decrease in CKD. Notably, five optimal microbial markers are identified using the random forest model. The area under the curve (AUC) reaches 0.9887 in the discovery cohort and 0.9512 in the validation cohort (49 CKD vs 63 HC). Importantly, the AUC reaches 0.8986 in the extra diagnosis cohort from Hangzhou. Moreover, Thalassospira and Akkermansia are increased with CKD progression. Thirteen operational taxonomy units are correlated with six clinical indicators of CKD. In conclusion, this study comprehensively characterizes gut microbiome in non‐dialysis CKD and demonstrates the potential of microbial markers as non‐invasive diagnostic tools for CKD in different regions of China. John Wiley and Sons Inc. 2020-09-02 /pmc/articles/PMC7578882/ /pubmed/33101877 http://dx.doi.org/10.1002/advs.202001936 Text en © 2020 The Authors. Published by Wiley‐VCH GmbH This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Full Papers Ren, Zhigang Fan, Yajuan Li, Ang Shen, Quanquan Wu, Jian Ren, Lingyan Lu, Haifeng Ding, Suying Ren, Hongyan Liu, Chao Liu, Wenli Gao, Dan Wu, Zhongwen Guo, Shiyuan Wu, Ge Liu, Zhangsuo Yu, Zujiang Li, Lanjuan Alterations of the Human Gut Microbiome in Chronic Kidney Disease |
title | Alterations of the Human Gut Microbiome in Chronic Kidney Disease |
title_full | Alterations of the Human Gut Microbiome in Chronic Kidney Disease |
title_fullStr | Alterations of the Human Gut Microbiome in Chronic Kidney Disease |
title_full_unstemmed | Alterations of the Human Gut Microbiome in Chronic Kidney Disease |
title_short | Alterations of the Human Gut Microbiome in Chronic Kidney Disease |
title_sort | alterations of the human gut microbiome in chronic kidney disease |
topic | Full Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578882/ https://www.ncbi.nlm.nih.gov/pubmed/33101877 http://dx.doi.org/10.1002/advs.202001936 |
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