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Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV 2 infection (preprint)
medrxiv; 2021.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2021.01.18.21250044
ABSTRACT
We hypothesised that host-response biomarkers of viral infections may contribute to early identification of SARS-CoV-2 infected individuals, critical to breaking chains of transmission. We identified 20 candidate blood transcriptomic signatures of viral infection by systematic review and evaluated their ability to detect SARS-CoV-2 infection, compared to the gold-standard of virus PCR tests, among a prospective cohort of 400 hospital staff subjected to weekly testing when fit to attend work. The transcriptional signatures had limited overlap, but were mostly co-correlated as components of type 1 interferon responses. We reconstructed each signature score in blood RNA sequencing data from 41 individuals over sequential weeks spanning a first positive SARS-CoV-2 PCR, and after 6-month convalescence. A single blood transcript for IFI27 provided the highest accuracy for discriminating individuals at the time of their first positive viral PCR result from uninfected controls, with area under the receiver operating characteristic curve (AUROC) of 0.95 (95% confidence interval 0.91-0.99), sensitivity 0.84 (0.7-0.93) and specificity 0.95 (0.85-0.98) at a predefined test threshold. The test performed equally well in individuals with and without symptoms, correlated with viral load, and identified incident infections one week before the first positive viral PCR with sensitivity 0.4 (0.17-0.69) and specificity 0.95 (0.85-0.98). Our findings strongly support further urgent evaluation and development of blood IFI27 transcripts as a biomarker for early phase SARS-CoV-2 infection, for screening individuals such as contacts of index cases, in order to facilitate early case isolation and early antiviral treatments as they emerge.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
COVID-19
Language:
English
Year:
2021
Document Type:
Preprint
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