Introduction: While there is evidence that Ebola virus (EBOV) antagonizes the antiviral type I interferon (IFN-I) response, the role of IFN-I for EBOV disease remains controversial, as initially protective responses may contribute to disease pathogenesis later. Methods: We analyzed patient data from the 2014-2016 West Africa epidemic with a combination of machine learning and mathematical modeling to identify predictive immune mediators and reconstruct their temporal dynamics in survivors and non-survivors. Results: Our results suggest that IFN-I response in survivors occurs before symptom onset, while non-survivors mount IFN-I responses 3-4 days later, although with a similar strength. This delayed IFN-I response overlaps in time with IL-12 signals in non-survivors. As optimal T cell activation requires a particular temporal sequence in cytokine signals, this impairs the development of T cell-based cellular immunity. Discussion: The presented patient data analysis helps reconcile the seemingly contradictory role of IFN-I in EBOV disease from a cytokine dynamics perspective and supports the theory of sequential T cell activation, according to which a dysregulated temporal sequence of cytokine signals keeps T cells unresponsive to the pathogen.
Zhao et al. (Thu,) studied this question.