The global pandemic caused by SARS-CoV-2 has claimed millions of lives and had a profound effect on global life. Understanding the pathogenicity of the virus and the body’s response to infection is crucial in improving patient management, prognosis, and therapeutic strategies. Whole blood RNA-seq was used to identify molecular differences between a well characterised cohort of patients hospitalised with COVID-19 or influenza virus to better understand the generic and specific effects of SARS-CoV-2 infection. These patients went on to survive or die of COVID-19. The analyses revealed contrasting innate and adaptive immune programmes, with transcripts and cell subsets associated with the adaptive immune response elevated in patients with COVID-19, and those involved in the innate immune response elevated in patients with influenza. An efficient adaptive immune response was associated with patient survival, while an inflammatory response predicted a negative outcome in patients with COVID-19. Machine learning and topological analysis identified gene expression signatures that differentiated patients with COVID-19 from patients with influenza, including insulin resistance, mitochondrial oxidative stress and interferon signalling, possible mechanistic drivers of worse disease prognoses in COVID. The results identified distinct differences in immune response between SARS-CoV-2 and influenza infection, prognostic of disease progression and indicative of different targeted therapies.
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