Multi-kingdom gut microbiota analyses define COVID-19 severity and post-acute COVID-19 syndrome
© 2022. The Author(s)..
Our knowledge of the role of the gut microbiome in acute coronavirus disease 2019 (COVID-19) and post-acute COVID-19 is rapidly increasing, whereas little is known regarding the contribution of multi-kingdom microbiota and host-microbial interactions to COVID-19 severity and consequences. Herein, we perform an integrated analysis using 296 fecal metagenomes, 79 fecal metabolomics, viral load in 1378 respiratory tract samples, and clinical features of 133 COVID-19 patients prospectively followed for up to 6 months. Metagenomic-based clustering identifies two robust ecological clusters (hereafter referred to as Clusters 1 and 2), of which Cluster 1 is significantly associated with severe COVID-19 and the development of post-acute COVID-19 syndrome. Significant differences between clusters could be explained by both multi-kingdom ecological drivers (bacteria, fungi, and viruses) and host factors with a good predictive value and an area under the curve (AUC) of 0.98. A model combining host and microbial factors could predict the duration of respiratory viral shedding with 82.1% accuracy (error ± 3 days). These results highlight the potential utility of host phenotype and multi-kingdom microbiota profiling as a prognostic tool for patients with COVID-19.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:13 |
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| Enthalten in: |
Nature communications - 13(2022), 1 vom: 10. Nov., Seite 6806 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liu, Qin [VerfasserIn] |
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| Links: |
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| Themen: |
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| Anmerkungen: |
Date Completed 14.11.2022 Date Revised 26.12.2022 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1038/s41467-022-34535-8 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM348709714 |
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| 520 | |a © 2022. The Author(s). | ||
| 520 | |a Our knowledge of the role of the gut microbiome in acute coronavirus disease 2019 (COVID-19) and post-acute COVID-19 is rapidly increasing, whereas little is known regarding the contribution of multi-kingdom microbiota and host-microbial interactions to COVID-19 severity and consequences. Herein, we perform an integrated analysis using 296 fecal metagenomes, 79 fecal metabolomics, viral load in 1378 respiratory tract samples, and clinical features of 133 COVID-19 patients prospectively followed for up to 6 months. Metagenomic-based clustering identifies two robust ecological clusters (hereafter referred to as Clusters 1 and 2), of which Cluster 1 is significantly associated with severe COVID-19 and the development of post-acute COVID-19 syndrome. Significant differences between clusters could be explained by both multi-kingdom ecological drivers (bacteria, fungi, and viruses) and host factors with a good predictive value and an area under the curve (AUC) of 0.98. A model combining host and microbial factors could predict the duration of respiratory viral shedding with 82.1% accuracy (error ± 3 days). These results highlight the potential utility of host phenotype and multi-kingdom microbiota profiling as a prognostic tool for patients with COVID-19 | ||
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| 700 | 1 | |a Zhang, Fen |e verfasserin |4 aut | |
| 700 | 1 | |a Tun, Hein M |e verfasserin |4 aut | |
| 700 | 1 | |a Mak, Joyce Wing Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Lui, Grace Chung-Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Ng, Susanna So Shan |e verfasserin |4 aut | |
| 700 | 1 | |a Ching, Jessica Y L |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Amy |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Wenqi |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Chenyu |e verfasserin |4 aut | |
| 700 | 1 | |a Cheung, Chun Pan |e verfasserin |4 aut | |
| 700 | 1 | |a Hui, David S C |e verfasserin |4 aut | |
| 700 | 1 | |a Chan, Paul K S |e verfasserin |4 aut | |
| 700 | 1 | |a Chan, Francis Ka Leung |e verfasserin |4 aut | |
| 700 | 1 | |a Ng, Siew C |e verfasserin |4 aut | |
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