Analysis of blood and nasal epithelial transcriptomes to identify mechanisms associated with control of SARS

Background: The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load. Methods: COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time. Results: Eighty-two subjects (50% female, median age 54 years (range 3-73)) with COVID-19 were recruited. Paired URT viral load samples were available for 16 blood transcriptome samples, and 17 respiratory epithelial transcriptome samples. Natural Killer (NK) cells were the only blood cell type significantly correlated with URT viral load z-scores (r = -0.62, P = 0.010). Twenty-four blood gene expression modules were significantly correlated with URT viral load z-score, the most significant being a module of genes connected around IFNA14 (Interferon Alpha-14) expression (r = -0.60, P = 1e-10). In fixed repertoire analysis, prostanoid-related gene expression was significantly associated with higher viral load. In nasal epithelium, only GNLY (granulysin) gene expression showed significant negative correlation with viral load. Conclusions: Correlations between the transcriptional host response and inter-individual variations in SARS-CoV-2 URT viral load, revealed many molecular mechanisms plausibly favouring or constraining viral load. Existing evidence corroborates many of these mechanisms, including likely roles for NK cells, granulysin, prostanoids and interferon alpha-14. Inhibition of prostanoid production, and administration of interferon alpha-14 may be attractive transmission-blocking interventions.

The authors have declared no competing interest.

This work was supported by UKRI (MRC) and the DHSC (NIHR) (Grant Ref: MR/V027409/1). This study also received support from Instituto de Salud Carlos III ([ISCIII] TRINEO: PI22/00162; DIAVIR: DTS19/00049; Resvi-Omics: PI19/01039 [AS]; ReSVinext: PI16/01569 [F.M.-T.]; Enterogen: PI19/01090 [F.M.-T.]; OMI-COVI-VAC (PI22/00406 [F.M.-T.] cofinanciados FEDER), GAIN: Grupos con Potencial de Crecimiento (IN607B 2020/08, [A.S.]); ACIS: BI-BACVIR (PRIS-3, [A.S.]), and CovidPhy (SA 304 C, [A.S.]); and consorcio Centro de Investigacion Biomedica en Red de Enfermedades Respiratorias (CB21/06/00103; F.M.-T.); GEN-COVID (IN845D 2020/23, F.M.-T.) and Grupos de Referencia Competitiva (IIN607A2021/05, F.M.-T.). The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. M.M.M. is supported in part by the NIHR Biomedical Research Centre of Imperial College NHS Trust. JD.C. and L.C.O. acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 programme supported by the European Union. F.L. is supported by an MRC clinical training fellowship [award MR/W000970/1]. F.L. and R.T. are supported by the UK Coronavirus Immunology Consortium (UKCIC). H.R.J. received support from the Wellcome Trust (4-year PhD programme, grant number 215214/Z/19/Z). M.K. acknowledges support from the Wellcome Trust and the Medical Research Foundation Grants (206508/Z/17/Z and MRF-160-0008-ELP-KAFO-C0801). L.C.O. declares grant funding from Merck Group on an unrelated project.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The GEN-COVID and PERFORM (Personalised Risk assessment in Febrile illness to Optimise Real-life Management across the European Union; perform2020.org/) studies were conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Galicia (EL COMITE ETICO DE INVESTIGACION CLINICA (CEIC) Galicia, ref 2020/178, 18/03/2020) and St Mary's Research Ethics Committee (16/LO/1684, 25/02/2013), respectively.

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Raw RNA-Seq data and corresponding metadata are available on ArrayExpress under the accession E-MTAB-12791. NanoString nCounter data and corresponding metadata are available at https://github.com/MahdiMoradiMarjaneh/COVID19_viral_load.