Oropharyngeal microbiome profiled at admission is predictive of the need for respiratory support among COVID-19 patients.
COVID-19
LPS biosynthesis
Prevotella
SARS-CoV-2
commensal organisms
oropharyngeal microbiome
random forest classification
Journal
Frontiers in microbiology
ISSN: 1664-302X
Titre abrégé: Front Microbiol
Pays: Switzerland
ID NLM: 101548977
Informations de publication
Date de publication:
2022
2022
Historique:
received:
01
08
2022
accepted:
12
09
2022
entrez:
17
10
2022
pubmed:
18
10
2022
medline:
18
10
2022
Statut:
epublish
Résumé
The oropharyngeal microbiome, the collective genomes of the community of microorganisms that colonizes the upper respiratory tract, is thought to influence the clinical course of infection by respiratory viruses, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Infectious Disease 2019 (COVID-19). In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 initially enrolled patients, 50 had positive molecular testing for COVID-19+ and had symptom duration of 14 days or less. These patients were analyzed further as progression of disease could most likely be attributed to acute COVID-19 and less likely a secondary process. Of these, 38 (76%) went on to require some form of supplemental oxygen support. To identify functional patterns associated with respiratory illness requiring respiratory support, we applied an interpretable random forest classification machine learning pipeline to shotgun metagenomic sequencing data and select clinical covariates. When combined with clinical factors, both species and metabolic pathways abundance-based models were found to be highly predictive of the need for respiratory support (F1-score 0.857 for microbes and 0.821 for functional pathways). To determine biologically meaningful and highly predictive signals in the microbiome, we applied the Stable and Interpretable RUle Set to the output of the models. This analysis revealed that low abundance of two commensal organisms,
Identifiants
pubmed: 36246273
doi: 10.3389/fmicb.2022.1009440
pmc: PMC9561819
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1009440Subventions
Organisme : NCI NIH HHS
ID : U01 CA261276
Pays : United States
Commentaires et corrections
Type : UpdateOf
Informations de copyright
Copyright © 2022 Bradley, Zeamer, Bucci, Cincotta, Salive, Dutta, Mutaawe, Anya, Tocci, Moormann, Ward, McCormick and Haran.
Déclaration de conflit d'intérêts
The 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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