Multivariate analysis of the parameters of the immune response after immunization with inactivated influenza vaccines

Abstract

Influenza A and B viruses are widely spread respiratory pathogens of humans and cause both isolated cases and local outbreaks of the disease, as well as massive seasonal epidemics and pandemics. Vaccination is the main strategy for combating influenza, and an increase in the proportion of vaccinated people in the population determines the success of vaccination. To identify patterns of postvaccination immune response formation to different types of vaccines and assess the significance of its multiple parameters the appropriate statistical methods should by applied. These methods allow to operate with large datasets and reduce their dimension, while keeping the maximum of information about the differences between individual observations. The aim of our study was the analysis of parameters of humoral and cellular immunity and their dynamics after vaccination with different types of inactivated influenza vaccines (IIV) using statistical methods of complex data analysis. The study was conducted in the clinical department of the Smorodintsev Research Institute of Influenza, Ministry of Health of the Russian Federation, in the flu season 2018 – 2019. The multivariate analysis of the immune response parameters after immunization with IIV “Grippol plus”, “Sovigripp” “Ultrix” included data obtained for 39 volunteers before vaccination, on the 7th and 21st days after vaccination. To identify parameters with significant differences between groups, one-factor analysis of variance (ANOVA) was used separately for each parameter and time point. To visualize the differences in the parameters selected in the analysis of variance, the Principal component analysis (PCA) method was used. The conducted studies revealed the peculiarities of the formation of a post-vaccination immune response to various types of IIV. It was shown that the factors of antigen-specific CD4+ and CD8+ T-cell immune response introduced the major contribution to the formation of the differences between groups. The approach is a powerful tool in analyzing the parameters of the immune response in clinical trials of influenza vaccines and other preventive medicine.