Author
Listed:
- Joshua Rosenheim
(University College London)
- Rishi K. Gupta
(University College London
University College London)
- Clare Thakker
(University College London)
- Tiffeney Mann
(University College London)
- Lucy C. K. Bell
(University College London)
- Claire M. Broderick
(Imperial College London)
- Kieran Madon
(Imperial College London)
- Loukas Papargyris
(Imperial College London)
- Pete Dayananda
(Imperial College London)
- Andrew J. Kwok
(University of Oxford
The Chinese University of Hong Kong)
- James Greenan-Barrett
(University College London)
- Helen R. Wagstaffe
(Imperial College London)
- Emily Conibear
(Imperial College London)
- Joe Fenn
(Imperial College London)
- Seran Hakki
(Imperial College London)
- Rik G. H. Lindeboom
(Wellcome Genome Campus)
- Lisa M. Dratva
(University of Cambridge
University of Cambridge)
- Briac Lemetais
(University College London)
- Caroline M. Weight
(University College London)
- Cristina Venturini
(University College London)
- Myrsini Kaforou
(Imperial College London)
- Michael Levin
(Imperial College London)
- Mariya Kalinova
(hVIVO Services Ltd)
- Alex J. Mann
(hVIVO Services Ltd)
- Andrew Catchpole
(hVIVO Services Ltd)
- Julian C. Knight
(University of Oxford)
- Marko Z. Nikolić
(University College London
University College London Hospitals NHS Foundation Trust)
- Sarah A. Teichmann
(University of Cambridge
University of Cambridge)
- Ben Killingley
(University College London Hospital NHS Foundation Trust)
- Wendy Barclay
(Imperial College London)
- Benjamin M. Chain
(University College London)
- Ajit Lalvani
(Imperial College London)
- Robert S. Heyderman
(University College London)
- Christopher Chiu
(Imperial College London)
- Mahdad Noursadeghi
(University College London)
Abstract
Blood transcriptional biomarkers of acute viral infections typically reflect type 1 interferon (IFN) signalling, but it is not known whether there are biological differences in their regulation that can be leveraged for distinct translational applications. We use high frequency sampling in the SARS-CoV-2 human challenge model to show induction of IFN-stimulated gene (ISG) expression with different temporal and cellular profiles. MX1 gene expression correlates with a rapid and transient wave of ISG expression across all cell types, which may precede PCR detection of replicative infection. Another ISG, IFI27, shows a delayed but sustained response restricted to myeloid cells, attributable to gene and cell-specific epigenetic regulation. These findings are reproducible in experimental and naturally acquired infections with influenza, respiratory syncytial virus and rhinovirus. Blood MX1 expression is superior to IFI27 expression for diagnosis of early infection, as a correlate of viral load and for discrimination of virus culture positivity. Therefore, MX1 expression offers potential to stratify patients for antiviral therapy or infection control interventions. Blood IFI27 expression is superior to MX1 expression for diagnostic accuracy across the time course of symptomatic infection and thereby, offers higher diagnostic yield for respiratory virus infections that incur a delay between transmission and testing.
Suggested Citation
Joshua Rosenheim & Rishi K. Gupta & Clare Thakker & Tiffeney Mann & Lucy C. K. Bell & Claire M. Broderick & Kieran Madon & Loukas Papargyris & Pete Dayananda & Andrew J. Kwok & James Greenan-Barrett &, 2024.
"SARS-CoV-2 human challenge reveals biomarkers that discriminate early and late phases of respiratory viral infections,"
Nature Communications, Nature, vol. 15(1), pages 1-13, December.
Handle:
RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-54764-3
DOI: 10.1038/s41467-024-54764-3
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