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Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo

Autoimmune diseases are increasingly linked to aberrant gut microbiome and relevant metabolites. However, the association between vitiligo and the gut microbiome remains to be elucidated. Thus, we conducted a case-control study through 16S rRNA sequencing and serum untargeted-metabolomic profiling b...

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Autores principales: Ni, Qingrong, Ye, Zhubiao, Wang, Yinghan, Chen, Jianru, Zhang, Weigang, Ma, Cuiling, Li, Kai, Liu, Yu, Liu, Ling, Han, Zheyi, Gao, Tianwen, Jian, Zhe, Li, Shuli, Li, Chunying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7768019/
https://www.ncbi.nlm.nih.gov/pubmed/33381090
http://dx.doi.org/10.3389/fmicb.2020.592248
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author Ni, Qingrong
Ye, Zhubiao
Wang, Yinghan
Chen, Jianru
Zhang, Weigang
Ma, Cuiling
Li, Kai
Liu, Yu
Liu, Ling
Han, Zheyi
Gao, Tianwen
Jian, Zhe
Li, Shuli
Li, Chunying
author_facet Ni, Qingrong
Ye, Zhubiao
Wang, Yinghan
Chen, Jianru
Zhang, Weigang
Ma, Cuiling
Li, Kai
Liu, Yu
Liu, Ling
Han, Zheyi
Gao, Tianwen
Jian, Zhe
Li, Shuli
Li, Chunying
author_sort Ni, Qingrong
collection PubMed
description Autoimmune diseases are increasingly linked to aberrant gut microbiome and relevant metabolites. However, the association between vitiligo and the gut microbiome remains to be elucidated. Thus, we conducted a case-control study through 16S rRNA sequencing and serum untargeted-metabolomic profiling based on 30 vitiligo patients and 30 matched healthy controls. In vitiligo patients, the microbial composition was distinct from that of healthy controls according to the analysis on α- and β-diversity (P < 0.05), with a characteristic decreased Bacteroidetes: Firmicutes ratio. Meanwhile, the levels of 23 serum metabolites (including taurochenodeoxycholate and L-NG-monomethyl-arginine) in the vitiligo patients were different from those in the healthy individuals and showed significant correlations with some microbial markers. We found that Corynebacterium 1, Ruminococcus 2, Jeotgalibaca and Psychrobacter were correlated significantly with disease duration and serum IL-1β level in vitiligo patients. And Psychrobacter was identified as the most predictive features for vitiligo by machine learning analysis (“importance” = 0.0236). Finally, combining multi-omics data and joint prediction models with accuracies up to 0.929 were established with dominant contribution of Corynebacterium 1 and Psychrobacter. Our findings replenished the previously unknown relationship between gut dysbiosis and vitiligo circulating metabolome and enrolled the gut-skin axis into the understanding of vitiligo pathogenesis.
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spelling pubmed-77680192020-12-29 Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo Ni, Qingrong Ye, Zhubiao Wang, Yinghan Chen, Jianru Zhang, Weigang Ma, Cuiling Li, Kai Liu, Yu Liu, Ling Han, Zheyi Gao, Tianwen Jian, Zhe Li, Shuli Li, Chunying Front Microbiol Microbiology Autoimmune diseases are increasingly linked to aberrant gut microbiome and relevant metabolites. However, the association between vitiligo and the gut microbiome remains to be elucidated. Thus, we conducted a case-control study through 16S rRNA sequencing and serum untargeted-metabolomic profiling based on 30 vitiligo patients and 30 matched healthy controls. In vitiligo patients, the microbial composition was distinct from that of healthy controls according to the analysis on α- and β-diversity (P < 0.05), with a characteristic decreased Bacteroidetes: Firmicutes ratio. Meanwhile, the levels of 23 serum metabolites (including taurochenodeoxycholate and L-NG-monomethyl-arginine) in the vitiligo patients were different from those in the healthy individuals and showed significant correlations with some microbial markers. We found that Corynebacterium 1, Ruminococcus 2, Jeotgalibaca and Psychrobacter were correlated significantly with disease duration and serum IL-1β level in vitiligo patients. And Psychrobacter was identified as the most predictive features for vitiligo by machine learning analysis (“importance” = 0.0236). Finally, combining multi-omics data and joint prediction models with accuracies up to 0.929 were established with dominant contribution of Corynebacterium 1 and Psychrobacter. Our findings replenished the previously unknown relationship between gut dysbiosis and vitiligo circulating metabolome and enrolled the gut-skin axis into the understanding of vitiligo pathogenesis. Frontiers Media S.A. 2020-12-14 /pmc/articles/PMC7768019/ /pubmed/33381090 http://dx.doi.org/10.3389/fmicb.2020.592248 Text en Copyright © 2020 Ni, Ye, Wang, Chen, Zhang, Ma, Li, Liu, Liu, Han, Gao, Jian, Li and Li. http://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 Microbiology
Ni, Qingrong
Ye, Zhubiao
Wang, Yinghan
Chen, Jianru
Zhang, Weigang
Ma, Cuiling
Li, Kai
Liu, Yu
Liu, Ling
Han, Zheyi
Gao, Tianwen
Jian, Zhe
Li, Shuli
Li, Chunying
Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo
title Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo
title_full Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo
title_fullStr Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo
title_full_unstemmed Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo
title_short Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo
title_sort gut microbial dysbiosis and plasma metabolic profile in individuals with vitiligo
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7768019/
https://www.ncbi.nlm.nih.gov/pubmed/33381090
http://dx.doi.org/10.3389/fmicb.2020.592248
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