A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections

• Published in: Scientific reports Vol. 12; no. 1; p. 889
• Main Authors: Buturovic, Ljubomir, Zheng, Hong, Tang, Benjamin, Lai, Kevin, Kuan, Win Sen, Gillett, Mark, Santram, Rahul, Shojaei, Maryam, Almansa, Raquel, Nieto, Jose Ángel, Muñoz, Sonsoles, Herrero, Carmen, Antonakos, Nikolaos, Koufargyris, Panayiotis, Kontogiorgi, Marina, Damoraki, Georgia, Liesenfeld, Oliver, Wacker, James, Midic, Uros, Luethy, Roland, Rawling, David, Remmel, Melissa, Coyle, Sabrina, Liu, Yiran E., Rao, Aditya M., Dermadi, Denis, Toh, Jiaying, Jones, Lara Murphy, Donato, Michele, Khatri, Purvesh, Giamarellos-Bourboulis, Evangelos J., Sweeney, Timothy E.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 18.01.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1305; 631/114/2415; 631/250/255; 692/4017; 692/53/2422; 692/699/255/2514; Acute Disease; Blood; Coronaviruses; COVID-19; COVID-19 - blood; COVID-19 - mortality; Female; Gene expression; Gene Expression Regulation; Humanities and Social Sciences; Humans; Immune response; Infections; Influenza; Male; Middle Aged; Mortality; multidisciplinary; Patients; Predictive Value of Tests; Public health; Respiratory failure; Retrospective Studies; Risk assessment; RNA, Messenger - blood; SARS-CoV-2 - metabolism; Science; Science (multidisciplinary); Transcriptomics; Viral infections
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-04509-9

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-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 response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.