Multiple linear regression model describes VIA breadth outcomes
REGRESSION
After determining how VIA breadth relates to other cellular responses to vaccination, we sought to build a model that could express VIA breadth as a function of these cellular responses. Understanding how these responses relate to inhibitory function may provide a deeper mechanistic understanding of what drives broad viral inhibition and, thus, inform which readouts are most critical to assess in vaccine development programs. Focusing on CD8+ T cell functionalities that showed correlations with VIA breadth as independent variables (Table S3), we constructed a multiple linear regression model to find significant predictors of VIA breadth. This included CD8+ T cell IFN-γ ELISpot responses to Env, Gag, and Pol peptide pools and the summed responses to these pools, as well as CD8+ T cell polyfunctionality scores to the Mos1 gag peptide pool. No significant regression equation was found (Multiple linear regression analysis, including transformed data of best-correlated outcomes to the VIA scoreThe estimate, standard error, and 