Detection of SARS-CoV-2 infection by microRNA profiling of the upper respiratory tract

被引：20
作者：
Farr, Ryan J. [1 ]
Rootes, Christina L. [1 ]
Stenos, John [2 ]
Foo, Chwan Hong [3 ]
Cowled, Christopher [1 ]
Stewart, Cameron R. [1 ]
机构：
[1] Australian Ctr Dis Preparedness, CSIRO Hlth & Biosecur, Geelong, Vic, Australia
[2] Univ Hosp Geelong, Australian Rickettsial Reference Lab, Geelong, Vic, Australia
[3] Exios Bio LLC, Conshohocken, PA USA
来源：
PLOS ONE | 2022年 / 17卷 / 04期
关键词：
D O I：
10.1371/journal.pone.0265670
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
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.
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页数：10
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