[Investigation of the Relationship Between the Immune Responses due to COVID-19 Vaccine and Peripheral Bloodlymphocyte Subtypes of Healthcare Workers]. / Saglik Çalisanlarinda COVID-19 Asisina Bagli Bagisik Yanit ile Hemogram Parametreleri ve Periferik Kandaki Lenfosit Alt Tipleri Arasindaki Iliskinin Arastirilmasi.

ABSTRACT

Worldwide vaccination is the best strategy to limit the Coronavirus disease-2019 (COVID-19) pandemic. The aim of this study was to investigate the antibody levels and hemogram parameters and the prediction of T-helper, T-cytotoxic and B lymphocyte subtypes in the peripheral blood for the development of these antibodies in the selected group of healthcare workers who were vaccinated with CoronaVac® (Sinovac, China). In a previous study with the same researchers, blood samples were taken from healthcare workers one month after the second vaccination, and anti-RBD anti-severe acute respiratory syndrome coronavirus-2 (anti-SARS-CoV-2) IgG antibodies were measured by enzyme linked immunosorbent assay (ELISA) method. Test results were classified as binding antibody <25.6 BAU/mL unresponsive, 25.6-35.1 BAU/mL weak response, <35.2 BAU/mL strong response, according to the assay manufacturer's recommendations. According to these criteria, it was determined that 22 (8.3%) people had no response, 25 (9.5%) people had a moderate response, and 217 (82.2%) people had a strong response. According to these results, 30 people from each group were invited. The results of three individuals were excluded from the evaluation due to chronic illness. A total of 87 health workers were included in the study. Twenty-two of these people had no response, 25 had a moderate response, and 40 had a good response. Flow cytometry was used to examine the peripheral blood lymphocyte percentage distribution. Statistical analyzes were performed with SPSS 26 software. The conformity of the variables to the normal distribution was examined using analytical methods (Kolmogorov-Smirnov/ Shapiro-Wilk tests). Pearson's Chi-square test was used to compare categorical variables. The correlation between the antibody level and the measurement results of hemogram parameters and lymphocyte indicators was evaluated by Pearson's correlation analysis. The model was established by performing linear regression analysis with the variables correlated with the antibody level. Cases with a p value below 0.05 were considered statistically significant. The age range of the participants in the study was 22-69. The mean age was 45.5 ± 10.4 years. Antibodies against SARS-CoV-2 virus were detected by ELISA method in 65 (74.7%) of the healthcare professionals, while no antibodies were detected in 22 (25.3%) of them. Lymphocyte count (p= 0.002), CD3 count (p= 0.0004), CD4 count (p= 0.0001), CD3/CD19 ratio (p= 0.011), CD4 percentage (p= 0.004) in the antibody positive group was found to be significant. According to the level of correlation between antibody level and lymphocyte indicators, a statistically significant negative correlation was found in CD3, CD4, CD8 and CD19 positive lymphocytes, respectively, and the best correlation was observed in CD3 positive lymphocytes. The formula f (Antibody level)= y= 358002 -0.176 x CD3 + 0.469 x CD19 was created using the linear regression model. In the light of the data of this study, the central role of T and B cells in COVID-19 immunization emerges. The vaccine-related antibody level-related formula may be useful for healthcare professionals in patient follow-up. It is thought that conducting vaccine related immune response studies involving larger populations will contribute more to the literature.