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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
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.
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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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