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Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis

Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospita...

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Autores principales: Guo, Mingquan, Wu, Guojun, Tan, Yun, Li, Yan, Jin, Xin, Qi, Weiqiang, Guo, Xiaokui, Zhang, Chenhong, Zhu, Zhaoqin, Zhao, Liping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9973266/
https://www.ncbi.nlm.nih.gov/pubmed/36744910
http://dx.doi.org/10.1128/mbio.03519-22
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author Guo, Mingquan
Wu, Guojun
Tan, Yun
Li, Yan
Jin, Xin
Qi, Weiqiang
Guo, Xiaokui
Zhang, Chenhong
Zhu, Zhaoqin
Zhao, Liping
author_facet Guo, Mingquan
Wu, Guojun
Tan, Yun
Li, Yan
Jin, Xin
Qi, Weiqiang
Guo, Xiaokui
Zhang, Chenhong
Zhu, Zhaoqin
Zhao, Liping
author_sort Guo, Mingquan
collection PubMed
description Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman’s correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission.
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spelling pubmed-99732662023-03-01 Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis Guo, Mingquan Wu, Guojun Tan, Yun Li, Yan Jin, Xin Qi, Weiqiang Guo, Xiaokui Zhang, Chenhong Zhu, Zhaoqin Zhao, Liping mBio Research Article Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman’s correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. American Society for Microbiology 2023-02-06 /pmc/articles/PMC9973266/ /pubmed/36744910 http://dx.doi.org/10.1128/mbio.03519-22 Text en Copyright © 2023 Guo et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Guo, Mingquan
Wu, Guojun
Tan, Yun
Li, Yan
Jin, Xin
Qi, Weiqiang
Guo, Xiaokui
Zhang, Chenhong
Zhu, Zhaoqin
Zhao, Liping
Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis
title Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis
title_full Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis
title_fullStr Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis
title_full_unstemmed Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis
title_short Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis
title_sort guild-level microbiome signature associated with covid-19 severity and prognosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9973266/
https://www.ncbi.nlm.nih.gov/pubmed/36744910
http://dx.doi.org/10.1128/mbio.03519-22
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