1. A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections
- Author
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Ljubomir Buturovic, Hong Zheng, Benjamin Tang, Kevin Lai, Win Sen Kuan, Mark Gillett, Rahul Santram, Maryam Shojaei, Raquel Almansa, Jose Ángel Nieto, Sonsoles Muñoz, Carmen Herrero, Nikolaos Antonakos, Panayiotis Koufargyris, Marina Kontogiorgi, Georgia Damoraki, Oliver Liesenfeld, James Wacker, Uros Midic, Roland Luethy, David Rawling, Melissa Remmel, Sabrina Coyle, Yiran E. Liu, Aditya M. Rao, Denis Dermadi, Jiaying Toh, Lara Murphy Jones, Michele Donato, Purvesh Khatri, Evangelos J. Giamarellos-Bourboulis, and Timothy E. Sweeney
- Subjects
Male ,Multidisciplinary ,Molecular medicine ,Statistical methods ,SARS-CoV-2 ,Science ,COVID-19 ,Middle Aged ,Article ,Coronavirus ,Prognostic markers ,Gene Expression Regulation ,Viral infection ,Predictive Value of Tests ,Machine learning ,Acute Disease ,Medicine ,Infectious diseases ,Humans ,Female ,RNA, Messenger ,Retrospective Studies - Abstract
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.
- Published
- 2022