Development and validation of blood-based prognostic biomarkers for severity of COVID disease outcome using EpiSwitch 3D genomic regulatory immuno-genetic profiling.

Hunter, E.; Koutsothanasi, C.; Wilson, A.; Santos, F. C.; Salter, M.; Westra, J.; Powell, R.; Dring, A.; Brajer, P.; Egan, B.; Matthew, P.; Catriona, W.; Aemilia, K.; Thomas, L.; Ramadass, A.; Messner, W.; Brunton, A.; Lyski, Z.; Robbins, P.; Mellor, J.; Vancheeswaran, R.; Barlow, A.; Pchejetski, D.; Akoulitchev, A.

The COVID-19 pandemic has raised several global public health challenges to which the international medical community have responded. Diagnostic testing and the development of vaccines against the SARS-CoV-2 virus have made remarkable progress to date. As the population is now faced with the complex lifestyle and medical decisions that come with living in a pandemic, a forward-looking understanding of how a COVID-19 diagnosis may affect the health of an individual represents a pressing need. Previously we used whole genome microarray to identify 200 3D genomic marker leads that could predict mild or severe COVID-19 disease outcomes from blood samples in a multinational cohort of COVID-19 patients. Here, we focus on the development and validation of a qPCR assay to accurately predict severe COVID-19 disease requiring intensive care unit (ICU) support and/or mechanical ventilation. From 200 original biomarker leads we established a classification model containing six markers. The markers were qualified and validated on 38 COVID-19 patients from an independent cohort. Overall, the six-marker model obtained a positive predictive value of 93% and balanced accuracy of 88% across 116 patients for the prognosis of COVID-19 severity requiring ICU care/ventilation support. The six-marker signature identifies individuals at the highest risk of developing severe complications in COVID-19 with high predictive accuracy and can assist in patient prognosis and clinical management decisions.