{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["17(4)"],"submitter":["Farr RJ"],"pubmed_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."],"journal":["PloS one"],"pagination":["e0265670"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8982876"],"repository":["biostudies-literature"],"pubmed_title":["Detection of SARS-CoV-2 infection by microRNA profiling of the upper respiratory tract."],"pmcid":["PMC8982876"],"pubmed_authors":["Stewart CR","Cowled C","Farr RJ","Stenos J","Foo CH","Rootes CL"],"additional_accession":[]},"is_claimable":false,"name":"Detection of SARS-CoV-2 infection by microRNA profiling of the upper respiratory tract.","description":"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.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2026-04-08T17:46:39.357Z","creation":"2025-02-19T01:55:02.598Z"},"accession":"S-EPMC8982876","cross_references":{"pubmed":["35381016"],"doi":["10.1371/journal.pone.0265670"]}}