Multi-kingdom gut microbiota analyses define COVID-19 severity and post-acute COVID-19 syndrome

Qin Liu, Qi Su, Fen Zhang, Hein M. Tun, Joyce Wing Yan Mak, Grace Chung-Yan Lui, Susanna So Shan Ng, Jessica Y.L. Ching, Amy Li, Wenqi Lu, Chenyu Liu, Chun Pan Cheung, David S.C. Hui, Paul K.S. Chan, Francis Ka Leung Chan, Siew C. Ng*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

29 Citations (Scopus)

Abstract

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.
Original languageEnglish
Article number6806
Number of pages11
JournalNature Communications
Volume13
DOIs
Publication statusPublished - 10 Nov 2022

Scopus Subject Areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

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