Deciphering infection-related epigenetic dynamics to explain the variability of human susceptibility to infection with COVID-19 and tuberculosis

Background:

The two major pandemics of our time, tuberculosis (TB) and COVID-19, have highly variable infection susceptibility patterns resulting in inefficient disease management. This variation cannot be explained by genetics or systemic immunity, but we have found that both infections leave epigenetic marks in immune cells. However, how these epigenetic marks arise and how epigenetic predisposition contributes to susceptibility or disease severity remain unknown.

Neither is it known what consequences the infection-triggered epigenetic changes have for the risk of developing sequelae, such as long-COVID-19 syndrome, or whether the changes can propagate across generations. Objectives:

Our interdisciplinary team suggests the following hypotheses: 1) During infections not efficiently limited by herd immunity, such as TB and COVID-19, a tailored, dynamic epigenetic change contributes to infection control. 2) Exosomes convey information from infected cells to the body tissues and across generations to direct epigenetic reprogramming resulting in protection. 3) An aberrant epigenetic landscape, either existing before infection or triggered by the same, can explain susceptibility to infection or infection-induced sequelae.

Work plan:

To test these hypotheses, we create a platform for data-driven, machine learning-assisted exploration of epigenomic data from unique clinical materials and experimental assays. The objectives include 1) mapping the epigenetic dynamics during infection in healthy subjects, 2) dissecting the mechanisms behind transmission of infection-triggered epigenetic changes, and 3) exploring the contribution of the epigenetic dynamics to infection severity and sequelae.

Significance:

By describing the relationship between epigenetic predisposition and infection susceptibility, this project provides a steppingstone toward precision medicine tools to manage infections in the future. In addition, we will for the first time deliver data on infection-induced transgenerational epigenetic changes in humans.