Tuberculosis (TB) is currently the deadliest infectious disease globally. Despite this, the only widely accepted vaccine for TB (BCG) has variable efficacy and its mechanisms are not fully understood. We sought to understand the immune response to TB under various doses of BCG vaccination using a dose-challenge study in macaques. In this system, we fit a partial correlation network learning protective relationships within a rich panel of immunological features, including serology, immune cell quantities, and cytokine levels. Using this framework, we applied in silico knockouts and identified features involved in vaccine-mediated protection from TB. While classically known features such as interferon-gamma level and CD4 cell quantity were highlighted, our analysis also revealed that antibody titer and phagocytic activity for LAM (a TB antigen involved in immune evasion) are especially important for vaccine-mediated protection. To characterize the role of complete pathways in vaccine-mediated protection we used pathway paired subscore (PPS) revealing the most important pathways controlling the relationship between vaccine dose and measures of both early and late stages of TB infection. We then validated these pathways in unseen single-cell RNA sequencing data collected from the same macaques, confirming the presence of individual interactions in an independently fit cell-cell communication network. Our analysis sheds light on differences between early and overall protection from TB, as well as novel features and paths critical for vaccine-mediated protection. These results are promising for guiding future vaccine development and hypothesis-driven discovery of disease mechanisms.

Co-authors: Shu Wang, Douglas Lauffenburger