Detection of SARS-CoV-2 infection by microRNA profiling of the upper respiratory tract.
PLoS One
; 17(4): e0265670, 2022.
Article
in English
| MEDLINE | ID: covidwho-1775445
ABSTRACT
Host biomarkers are increasingly being considered as tools for improved COVID-19 detection and prognosis. We recently profiled circulating host-encoded microRNA (miRNAs) during SARS-CoV-2 infection, revealing a signature that classified COVID-19 cases with 99.9% accuracy. Here we sought to develop a signature suited for clinical application by analyzing specimens collected using minimally invasive procedures. Eight miRNAs displayed altered expression in anterior nasal tissues from COVID-19 patients, with miR-142-3p, a negative regulator of interleukin-6 (IL-6) production, the most strongly upregulated. Supervised machine learning analysis revealed that a three-miRNA signature (miR-30c-2-3p, miR-628-3p and miR-93-5p) independently classifies COVID-19 cases with 100% accuracy. This study further defines the host miRNA response to SARS-CoV-2 infection and identifies candidate biomarkers for improved COVID-19 detection.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
MicroRNAs
/
COVID-19
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
PLoS One
Journal subject:
Science
/
Medicine
Year:
2022
Document Type:
Article
Affiliation country:
Journal.pone.0265670
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