Kinetics of anti-SARS-CoV-2 antibodies and hematological parameters in hospitalized pre-vaccination COVID-19 patients in Peru - Salyoc Tapia-Rojas; Alexis Germán Murillo Carrasco; Maria J. Pons; Manuel Ugarte-Gil; Ana Mayanga-Herrera (PeerJ)
Background The COVID-19 pandemic exposed vulnerabilities in health systems and revealed variations in immune responses across populations worldwide. This study examined the kinetics of IgG and IgM antibodies against S1 and receptor-binding domain (RBD) proteins in hospitalized Peruvian patients prior to vaccination. Method A total of 157 serological samples were collected from 44 hospitalized COVID-19 patients during Peru’s first wave (August–October 2020) and stored at −80 °C. Anti-SARS-CoV-2 IgG and IgM antibodies were quantified using an in-house ELISA with recombinant Spike S1 and RBD proteins. Statistical analyses—including linear regression, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves—were conducted to evaluate antibody kinetics, clinical correlations, and predictive accuracy. Results IgG levels stabilized between days 10 and 15 of hospitalization, while IgM levels declined after day 10, with greater variability observed in severe acute respiratory distress syndrome (ARDS) cases. A significant positive correlation was found between IgG levels and lymphocyte counts (R = 0.37, p < 0.001), and a negative correlation with neutrophil counts (R =  − 0.33, p < 0.01), particularly in severe ARDS non-ICU patients (R =  − 0.34, p < 0.01). Severe ARDS cases also exhibited elevated neutrophil-to-lymphocyte ratios and increased inflammatory biomarkers, such as C-reactive protein and D-dimer, indicating an exacerbated inflammatory response associated with poorer prognosis. Risk factors, including sex and obesity, were linked to higher mortality and increased need for mechanical ventilation. This study contributes to a better understanding of the immune response in COVID-19 and supports the development of predictive models based on immunological and hematological biomarkers.