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.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Adult
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Aged
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Animals
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COVID-19 / blood
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COVID-19 / diagnosis*
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COVID-19 / genetics*
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COVID-19 Testing / methods*
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Case-Control Studies
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Diagnosis, Differential
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Disease Models, Animal
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Female
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Ferrets
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Gene Expression
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Host Microbial Interactions / genetics
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Humans
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Influenza A Virus, H1N1 Subtype
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Longitudinal Studies
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Male
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MicroRNAs / blood
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MicroRNAs / genetics*
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Middle Aged
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Orthomyxoviridae Infections / diagnosis
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Orthomyxoviridae Infections / genetics
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Pandemics
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SARS-CoV-2*
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Supervised Machine Learning
Substances
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MIRN195 microRNA, human
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MIRN23a microRNA, human
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MIRN423 microRNA, human
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MicroRNAs
Grants and funding
This work was supported by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) (
www.csiro.au) (C.R.S., grant number N/A). We acknowledge funding from the Coalition for Epidemic Preparedness Innovations (CEPI) (
https://cepi.net/) (S.S.V., grant number N/A) for supporting ferret COVID-19 studies. S.S.V. is grateful for support from Australian Department of Finance (grant number N/A) and CSIRO Future Science Platforms (grant number N/A). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.