| Title: |
Altered microRNA expression in COVID-19 patients enables identification of SARS-CoV-2 infection |
| Authors: |
Farr, RJ; Rootes, CL; Rowntree, LC; Nguyen, THO; Hensen, L; Kedzierski, L; Cheng, AC; Kedzierska, K; Au, GG; Marsh, GA; Vasan, SS; Foo, CH; Cowled, C; Stewart, CR |
| Contributors: |
Fouchier, RAM |
| Publisher Information: |
PUBLIC LIBRARY SCIENCE |
| Publication Year: |
2021 |
| Collection: |
The University of Melbourne: Digital Repository |
| Description: |
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. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| ISSN: |
1553-7366 |
| Relation: |
https://hdl.handle.net/11343/287536 |
| Availability: |
https://hdl.handle.net/11343/287536 |
| Rights: |
https://creativecommons.org/licenses/by/4.0 ; CC BY |
| Accession Number: |
edsbas.742402C |
| Database: |
BASE |