COVID-19 severity is associated with population-level gut microbiome variations.

COVID-19 gut microbiome population health probiotics topological data analysis

Journal

Frontiers in cellular and infection microbiology
ISSN: 2235-2988
Titre abrégé: Front Cell Infect Microbiol
Pays: Switzerland
ID NLM: 101585359

Informations de publication

Date de publication:
2022
Historique:
received: 07 06 2022
accepted: 03 08 2022
entrez: 9 9 2022
pubmed: 10 9 2022
medline: 14 9 2022
Statut: epublish

Résumé

The human gut microbiome interacts with many diseases, with recent small studies suggesting a link with COVID-19 severity. Exploring this association at the population-level may provide novel insights and help to explain differences in COVID-19 severity between countries. We explore whether there is an association between the gut microbiome of people within different countries and the severity of COVID-19, measured as hospitalisation rate. We use data from the large (n = 3,055) open-access gut microbiome repository curatedMetagenomicData, as well as demographic and country-level metadata. Twelve countries were placed into two groups (high/low) according to COVID-19 hospitalisation rate before December 2020 (ourworldindata.com). We use an unsupervised machine learning method, Topological Data Analysis (TDA). This method analyses both the local geometry and global topology of a high-dimensional dataset, making it particularly suitable for population-level microbiome data. We report an association of distinct baseline population-level gut microbiome signatures with COVID-19 severity. This was found both with a PERMANOVA, as well as with TDA. Specifically, it suggests an association of anti-inflammatory bacteria, including

Identifiants

pubmed: 36081770
doi: 10.3389/fcimb.2022.963338
pmc: PMC9445151
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

963338

Subventions

Organisme : Wellcome Trust
ID : 566701
Pays : United Kingdom

Informations de copyright

Copyright © 2022 Lymberopoulos, Gentili, Budhdeo and Sharma.

Déclaration de conflit d'intérêts

Author NS is CEO and founder of BioCorteX Ltd. Author SB owns equity in Owkin Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Eva Lymberopoulos (E)

The Sharma Lab, Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, England.
Centre for Doctoral Training in AI-London enabled Healthcare Systems, Institute of Health Informatics, University College London, London, England.

Giorgia Isabella Gentili (GI)

The Sharma Lab, Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, England.

Sanjay Budhdeo (S)

The Sharma Lab, Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, England.
National Hospital for Neurology and Neurosurgery, Queen Square, London, England.
School of Biomedical Engineering & Imaging Sciences, Faculty of Life Sciences & Medicine, King's College London, London, England.

Nikhil Sharma (N)

The Sharma Lab, Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, England.

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