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BACKGROUND: The recent identification of a novel coronavirus, also known as SARS-CoV-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 three core elements – pathogens, the microbiome, and host responses – were interrogated. 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 potential for diagnosing COVID-19 (AUC of 0.75-0.89) and indicating disease severity. CONCLUSIONS: Compared to 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.
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document_parses/pdf_json/59cc297c007e31b70d6c68d9a11563f704fb792e.json
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Metatranscriptomic Characterization of COVID-19 Identified A Host Transcriptional Classifier Associated With Immune Signaling
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