Characterisation of the blood RNA host response underpinning severity in COVID-19 patients

Abstract

Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups. Increasing COVID-19 severity was characterised by an abundance of inflammatory immune response genes and pathways, including many related to neutrophils and macrophages, in addition to an upregulation of immunoglobulin genes. In this study, for the first time, we show how immunomodulatory treatments commonly administered to COVID-19 patients greatly alter the transcriptome. Our insights into COVID-19 severity reveal the role of immune dysregulation in the progression to severe disease and highlight the need for further research exploring the interplay between SARS-CoV-2 and the inflammatory immune response.

Figure 1

A schematic summarising the number of patients analysed, the main analysis steps, and the key findings. The numbers in brackets following mild, moderate, and severe are the WHO severity scores that make up these classifications. Figure made with BioRender (https://biorender.com/).

Figure 2

Cross plots showing the log₂ fold change (LFC) values of genes for pairwise comparisons between three severity groups (A: moderate vs. mild; B: severe vs. mild; C: severe vs. moderate). The plots show how LFC values differ according to whether immune cell proportions (x-axis) or immunomodulatory treatments (y-axis) were included in the models. Red points are genes that were SDE in both models, whilst orange and green points are genes SDE in the cell correction and treatment correction models, respectively. NS not significant.

Figure 3

Heatmaps showing log-transformed expression values for (A) the 55 genes SDE with severity as an additive variable with absolute LFC values greater than 2 and B-H p-values < 0.0001 (B) the 10 genes SDE in all three pairwise severity comparisons in addition to the additive severity model with absolute LFC values greater than 2 and B-H p-values < 0.0001. Samples are ordered according to severity group. Age and sex were included as covariates in all differential expression analysis models.