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In Heliyon

SARS-CoV-2 infection causes a wide spectrum of disease severity. Identifying the immunological characteristics of severe disease and the risk factors for their development are important in the management of COVID-19. This study aimed to identify and rank clinical and immunological features associated with progression to severe COVID-19 in order to investigate an immunological signature of severe disease. One hundred and eight patients with positive SARS-CoV-2 PCR were recruited. Routine clinical and laboratory markers were measured, as well as myeloid and lymphoid whole-blood immunophenotyping and measurement of the pro-inflammatory cytokines IL-6 and soluble CD25. All analysis was carried out in a routine hospital diagnostic laboratory. Univariate analysis demonstrated that severe disease was most strongly associated with elevated CRP and IL-6, loss of DLA-DR expression on monocytes and CD10 expression on neutrophils. Unbiased machine learning demonstrated that these four features were strongly associated with severe disease, with an average prediction score for severe disease of 0.925. These results demonstrate that these four markers could be used to identify patients developing severe COVID-19 and allow timely delivery of therapeutics.

Townsend Liam, Dyer Adam H, Naughton Aifric, Imangaliyev Sultan, Dunne Jean, Kiersey Rachel, Holden Dean, Mooney Aoife, Leavy Deirdre, Ridge Katie, Sugrue Jamie, Aldoseri Mubarak, Kelliher Jo Hannah, Hennessy Martina, Byrne Declan, Browne Paul, Bacon Christopher L, Doyle Catriona, O’Riordan Ruth, McLaughlin Anne-Marie, Bannan Ciaran, Martin-Loeches Ignacio, White Arthur, McLoughlin Rachel M, Bergin Colm, Bourke Nollaig M, O’Farrelly Cliona, Conlon Niall, Cheallaigh Clíona Ní


Biomarkers, COVID-19, Immune phenotype, Machine learning, Neutrophil maturity