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Abstract
SARS-CoV2 infection results in a range of disease severities, but the underlying differential pathogenesis is still not completely understood. At presentation it remains difficult to estimate and predict severity, in particular, identify individuals at greatest risk of progression towards the most severe disease-states. Here we used advanced models with circulating serum analytes as variables in combination with daily assessment of disease severity using the SCODA-score, not only at single time points but also during the course of disease, to correlate analyte levels and disease severity. We identified a remarkably strong pro-inflammatory cytokine/chemokine profile with high levels for sCD163, CCL20, HGF, CHintinase3like1 and Pentraxin3 in serum which correlated with COVID-19 disease severity and overall outcome. Although precise analyte levels differed, resulting biomarker profiles were highly similar at early and late disease stages, and even during convalescence similar biomarkers were elevated and further included CXCL3, CXCL6 and Osteopontin. Taken together, strong pro-inflammatory marker profiles were identified in patients with COVID-19 disease which correlated with overall outcome and disease severity.
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Details
1 Leiden University Medical Center, Department of Infectious Diseases, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
2 Leiden University Medical Center, Department of Biomedical Data Sciences, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
3 Leiden University Medical Center, Department of Intensive Care Medicine, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
4 Leiden University Medical Center, Department of Clinical Epidemiology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
5 Leiden University Medical Center, Department of Internal Medicine, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
6 Leiden University Medical Center, Department of Clinical Chemistry, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
7 Leiden University Medical Center, Department of Pulmonology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
8 Leiden University Medical Center, Department of Immunology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
9 Leiden University Medical Center, Department of Medical Microbiology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
10 Leiden University Medical Center, Center for Proteomics and Metabolomics, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
11 Leiden University, Division of Systems Biomedicine and Pharmacology, Leiden Academic Center for Drug Research, Leiden, The Netherlands (GRID:grid.5132.5) (ISNI:0000 0001 2312 1970)
12 Leiden University Medical Center, Department of Hematology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
13 Leiden University Medical Center, Department of Parasitology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
14 Leiden University Medical Center, Department of Intensive Care, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
15 Leiden University Medical Center, Department of Infectious Diseases, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978); Leiden University Medical Center, Department of Parasitology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)
16 Leiden University Medical Center, Department of Clinical Epidemiology, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978); Leiden University Medical Center, Department of Intensive Care, Leiden, The Netherlands (GRID:grid.10419.3d) (ISNI:0000 0000 8945 2978)