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Identification of erythroid cell positive blood transcriptome phenotypes associated with severe respiratory syncytial virus infection

Authors :
Oceane Konza
Federica Martina
Mathieu Garand
David Klatzmann
Octavio Ramilo
Damien Chaussabel
Matthew B Altman
Mohammed Toufiq
Asuncion Mejias
Basirudeen Syed Ahamed Kabeer
Karolina Palucka
Encarnita Mariotti-Ferrandiz
Davide Bedognetti
Signe Hässler
Darawan Rinchai
Publication Year :
2019
Publisher :
Cold Spring Harbor Laboratory, 2019.

Abstract

Biomarkers to assess the severity of acute respiratory syncytial virus (RSV) infection are needed. We conducted a meta-analysis of 490 unique profiles from six public RSV blood transcriptome datasets. A repertoire of 382 well-characterized transcriptional modules was used to define dominant host responses to RSV infection. The consolidated RSV cohort was stratified according to four traits: “interferon response” (IFN), “neutrophil-driven inflammation” (Infl), “cell cycle” (CC), and “erythrocytes” (Ery). Eight prevalent blood transcriptome phenotypes were thus identified. Among those three Ery+ phenotypes comprised higher proportions of patients requiring intensive care. We posit that the erythrocyte module is linked to an overabundance of immunosuppressive erythroid cells that might underlie progression to severe RSV infection. These findings outline potential priority areas for biomarker development and investigations into the immune biology of RSV infection. The approach that was employed here will also permit to delineate prevalent blood transcriptome phenotypes in other settings.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........8b11ea6e9e9f2f9da27286b89e25a74b
Full Text :
https://doi.org/10.1101/527812