Exploring dysregulated immune response genes and endothelial dysfunction biomarkers as predictors of severe COVID-19.

Identifying individuals and factors associated with severe cases of COVID-19 is crucial as the pandemic continues to spread globally. Effective biomarkers for predicting severe cases are essential for optimizing clinical management, therapy, and preventing unfavorable outcomes. This exploratory observational study aimed to investigate the expression of dysregulated immune response genes (ARG1, NOS2, ITGA4, and SELPLG) in total leukocytes, plasmatic levels of P-selectin and PSGL-1, and their clinical associations in patients with mild and severe COVID-19. Data from 117 confirmed COVID-19 patients (severe = 58, mild = 59) were collected upon admission. Gene expression was measured using RT-qPCR, and plasma protein levels assessed with ELISA assay. The severe COVID-19 patient group had a higher median age of 62.0 (p = 0.0001), a higher proportion of black individuals (86.2%, p < 0.0001), and more males (65.5%, p = 0.007). The neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) were significantly higher in the severe COVID-19 patient group (p < 0.0001), indicating ongoing systemic inflammation. Severe COVID-19 patients also exhibited increased expression of ARG1 (p < 0.05) and SELPLG (p < 0.0001) genes, as well as higher concentrations of soluble P-selectin (p < 0.005) and PSGL-1 (p < 0.05) proteins. Multivariate analysis revealed that NLR, PLR, the expression of SELPLG and sPSGL-1 were independent predictors of COVID-19 severity. In conclusion, this study suggests that biomarkers of endothelial dysfunction and dysregulated leukocyte responses are associated with COVID-19 severity, serving as promising predictive tools for optimizing clinical management and patient monitoring.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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