Altered microRNA expression in COVID-19 patients enables identification of SARS-CoV-2 infection

Author:

Farr Ryan J.ORCID,Rootes Christina L.ORCID,Rowntree Louise C.ORCID,Nguyen Thi H. O.ORCID,Hensen LucaORCID,Kedzierski Lukasz,Cheng Allen C.ORCID,Kedzierska Katherine,Au Gough G.,Marsh Glenn A.ORCID,Vasan Seshadri S.ORCID,Foo Chwan Hong,Cowled Christopher,Stewart Cameron R.ORCID

Abstract

The host response to SARS-CoV-2 infection provide insights into both viral pathogenesis and patient management. The host-encoded microRNA (miRNA) response to SARS-CoV-2 infection, however, remains poorly defined. Here we profiled circulating miRNAs from ten COVID-19 patients sampled longitudinally and ten age and gender matched healthy donors. We observed 55 miRNAs that were altered in COVID-19 patients during early-stage disease, with the inflammatory miR-31-5p the most strongly upregulated. Supervised machine learning analysis revealed that a three-miRNA signature (miR-423-5p, miR-23a-3p and miR-195-5p) independently classified COVID-19 cases with an accuracy of 99.9%. In a ferret COVID-19 model, the three-miRNA signature again detected SARS-CoV-2 infection with 99.7% accuracy, and distinguished SARS-CoV-2 infection from influenza A (H1N1) infection and healthy controls with 95% accuracy. Distinct miRNA profiles were also observed in COVID-19 patients requiring oxygenation. This study demonstrates that SARS-CoV-2 infection induces a robust host miRNA response that could improve COVID-19 detection and patient management.

Funder

Commonwealth Scientific and Industrial Research Organisation

Coalition for Epidemic Preparedness Innovations

australian department of finance

csiro future science platforms

Publisher

Public Library of Science (PLoS)

Subject

Virology,Genetics,Molecular Biology,Immunology,Microbiology,Parasitology

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