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

•Risk factors: male, age over 65, black ethnicity, pre-existing comorbidities were associated with COVID-19 severity.•Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) efficiently identified COVID-19 severity.•Upregulation of SELPLG and ARG1, elevated sPSGL-1 and sP-selectin significantly associated with severe COVID-19.•Upregulation of plasmatic PSGL, P-selectin, SELPLG, and ARG1 suggests a central role in severe COVID-19 pathogenesis.•Soluble PSGL-1 and SELPLG independently predict severe COVID-19, facilitating monitoring and tailoring interventions. 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