Cytokine, chemokine, and acute-phase protein profiles in plasma as correlative biomarkers of clinical outcomes for patients with COVID-19

Coronavirus disease identified in 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus-2, had a global impact on human health and the economy. The aim of this study was to quantify cytokines, chemokines, and acute phase proteins in the plasma of patients with COVID-19 to elucidate potential biomarkers to inform prognostic and treatment decisions. Clustering analysis using the K-prototypes method identified underlying biological patterns in patients with COVID-19. The penalized multinomial logistic regression analysis identified two comorbidities (hypertension, congestive heart failure) and thirteen analytes as potential risk factors for COVID-19 progression with 88.2% accuracy. Based on a patient's age, high concentrations of interleukin (IL)-6, monocyte chemoattractant protein-1, and pentraxin 3 were important biomarkers for lethal COVID-19. Decreased concentrations of interferon gamma-induced protein-10, IL-10, and soluble tumor necrosis factor receptor I were found to be associated with mild COVID-19, while increasing concentrations of these analytes could be used to predict COVID-19 severity.

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Publication Details

Journal
Scientific Reports
Published
2025-05-02
DOI
https://doi.org/10.1038/s41598-025-99248-6
Citations
4
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
5.58

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article

Cytokine, chemokine, and acute-phase protein profiles in plasma as correlative biomarkers of clinical outcomes for patients with COVID-19

Maysa Niazy, Byram W. Bridle, Kevin J. Stinson, Ashley A. Stegelmeier et al.
4 citations
Scientific Reports
COVID-19 Clinical Research Studies
5.58
article

Cytokine, chemokine, and acute-phase protein profiles in plasma as correlative biomarkers of clinical outcomes for patients with COVID-19

Maysa Niazy, Byram W. Bridle, Kevin J. Stinson, Ashley A. Stegelmeier, Sierra Vanderkamp, Nicole Ricker
article en
4 citations

Abstract

Coronavirus disease identified in 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus-2, had a global impact on human health and the economy. The aim of this study was to quantify cytokines, chemokines, and acute phase proteins in the plasma of patients with COVID-19 to elucidate potential biomarkers to inform prognostic and treatment decisions. Clustering analysis using the K-prototypes method identified underlying biological patterns in patients with COVID-19. The penalized multinomial logistic regression analysis identified two comorbidities (hypertension, congestive heart failure) and thirteen analytes as potential risk factors for COVID-19 progression with 88.2% accuracy. Based on a patient's age, high concentrations of interleukin (IL)-6, monocyte chemoattractant protein-1, and pentraxin 3 were important biomarkers for lethal COVID-19. Decreased concentrations of interferon gamma-induced protein-10, IL-10, and soluble tumor necrosis factor receptor I were found to be associated with mild COVID-19, while increasing concentrations of these analytes could be used to predict COVID-19 severity.

Scientific ReportsVol. 15(1)
University of Guelph (CA)
University of Guelph, Canada First Research Excellence Fund
Openalex Percentile: Top 4%
COVID-19 Clinical Research Studies
5.58
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