A 6-mRNA host response whole-blood classifier trained using patients with non-COVID-19 viral infections accurately predicts severity of COVID-19 (preprint)

BackgroundWhile major progress has been made to establish diagnostic tools for the identification of SARS-CoV-2 infection, determining the severity of COVID-19 remains an unmet medical need. There is a limited availability of hospital resources in this or any pandemic, and appropriately gauging severity would allow for some patients to safely recover in home quarantine, while ensuring that sicker patients get needed care. MethodsWe here developed a blood-based generalizable host-gene-expression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N=705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune mRNAs. ResultsWe selected 6 host mRNAs and trained a logistic regression classifier with a training cross-validation AUROC of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1,417 samples across 21 independent retrospective validation cohorts the locked 6-mRNA classifier had an AUROC of 0.91 for discriminating patients with severe vs. non-severe infection. Next, in an independent cohort of prospectively enrolled patients with confirmed COVID-19 (N=97) in Athens, Greece, the 6-mRNA locked classifier had an AUROC of 0.89 for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed an isothermal qRT-LAMP (loop-mediated isothermal gene expression) assay for the 6-mRNA panel to facilitate implementation as a rapid assay. ConclusionsWith further study, the classifier could assist in the risk assessment of patients with confirmed SARS-CoV-2 infection and COVID-19 to determine severity and level of care, thereby improving patient management and healthcare burden.

Transcriptomic Similarities and Differences in Host Response between SARS-CoV-2 and Other Viral Infections (preprint)

COVID-19 is a pandemic that shares certain clinical characteristics with other acute viral infections. Here, we studied the whole-blood transcriptomic host response to SARS-CoV-2 and compared it with other viral infections to understand similarities and differences in host response. Using RNAseq we profiled peripheral blood from 24 healthy controls and 62 prospectively enrolled patients with community-acquired lower respiratory tract infection by SARS-Cov-2 within the first 24 hours of hospital admission. We also compiled and curated 23 independent studies that profiled 1,855 blood samples from patients with one of six viruses (influenza, RSV, HRV, ebola, Dengue, and SARS-CoV-1). We show gene expression changes in peripheral blood in patients with COVID-19 versus healthy controls are highly correlated with changes in response to other viral infections (r=0.74, p<0.001). However, two genes, ACO1 and ATL3, show significantly opposite changes between conditions. Pathway analysis in patients with COVID-19 or other viral infections versus healthy controls identified similar pathways including neutrophil activation, innate immune response, immune response to viral infection, and cytokine production for over-expressed genes. Conversely, for under-expressed genes, pathways indicated repression of lymphocyte differentiation and T cell activation. When comparing transcriptome profiles of patients with COVID-19 directly with those with other viral infections, we found 114 and 302 genes were over- or under-expressed, respectively, during COVID-19. Pathways analysis did not identify any significant pathways in these genes, suggesting novel responses to further study. Statistical deconvolution using immunoStates found that M1 macrophages, plasmacytoid dendritic cells, CD14+ monocytes, CD4+ T cells, and total B cells showed change consistently in the same direction across all viral infections including COVID-19. Those that increased in COVID-19 but decreased in non-COVID-19 viral infections were CD56bright NK cells, M2 macrophages, and total NK cells. The concordant and discordant responses mapped out here provide a window to explore the pathophysiology of COVID-19 versus other viral infections and show clear differences in signaling pathways and cellularity as part of the host response to SARS-CoV-2.