Metatranscriptomic Characterization of Coronavirus Disease 2019 Identified a Host Transcriptional Classifier Associated With Immune Signaling

Abstract

Abstract Background The recent identification of a novel coronavirus, also known as severe acute respiratory syndrome coronavirus 2, has caused a global outbreak of respiratory illnesses. The rapidly developing pandemic has posed great challenges to diagnosis of this novel infection. However, little is known about the metatranscriptomic characteristics of patients with coronavirus disease 2019 (COVID-19). Methods We analyzed metatranscriptomics in 187 patients (62 cases with COVID-19 and 125 with non–COVID-19 pneumonia). Transcriptional aspects of 3 core elements, pathogens, the microbiome, and host responses, were evaluated. Based on the host transcriptional signature, we built a host gene classifier and examined its potential for diagnosing COVID-19 and indicating disease severity. Results The airway microbiome in COVID-19 patients had reduced alpha diversity, with 18 taxa of differential abundance. Potentially pathogenic microbes were also detected in 47% of the COVID-19 cases, 58% of which were respiratory viruses. Host gene analysis revealed a transcriptional signature of 36 differentially expressed genes significantly associated with immune pathways, such as cytokine signaling. The host gene classifier built on such a signature exhibited the potential for diagnosing COVID-19 (area under the curve of 0.75–0.89) and indicating disease severity. Conclusions Compared with those with non–COVID-19 pneumonias, COVID-19 patients appeared to have a more disrupted airway microbiome with frequent potential concurrent infections and a special trigger host immune response in certain pathways, such as interferon-gamma signaling. The immune-associated host transcriptional signatures of COVID-19 hold promise as a tool for improving COVID-19 diagnosis and indicating disease severity.