Definition of erythroid cell-positive blood transcriptome phenotypes associated with severe respiratory syncytial virus infection.

Abstract

Biomarkers to assess the risk of developing severe 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). We identified eight prevalent blood transcriptome phenotypes, of which three Ery+ phenotypes comprised higher proportions of patients requiring intensive care. This finding confirms on a larger scale data from one of our earlier reports describing an association between an erythrocyte signature and RSV disease severity. Further contextual interpretation made it possible to associate this signature with immunosuppressive states (late stage cancer, pharmacological immunosuppression), and with a population of fetal glycophorin A+ erythroid precursors. Furthermore, we posit that this erythrocyte cell signature may be linked to a population of immunosuppressive erythroid cells previously described in the literature, and that overabundance of this cell population in RSV patients may underlie progression to severe disease. These findings outline potential priority areas for biomarker development and investigations into the immune biology of RSV infection. The approach that we developed and employed here should also permit to delineate prevalent blood transcriptome phenotypes in other settings.

• Authors: Darawan Rinchai, Matthew C Altman, Oceane Konza, Signe Hässler, Federica Martina, Mohammed Toufiq, Mathieu Garand, Basirudeen Syed Ahamed Kabeer, Karolina Palucka, Asuncion Mejias, Octavio Ramilo, Davide Bedognetti, Encarnita Mariotti-Ferrandiz, David Klatzmann, Damien Chaussabel
• Journal: Clinical and translational medicine (Clin Transl Med) Vol. 10 Issue 8 Pg. e244 (Dec 2020) ISSN: 2001-1326 [Print] United States
• PMID: 33377660 (Publication Type: Journal Article)
• Copyright: © 2020 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.