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 man-agement, therapy, and preventing unfavorable outcomes. This exploratory observational study aimed to inves-tigate 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.