Tracking Resilience to Infections by Mapping Disease Space

Area of Science:

• Pathogen-host interactions
• Disease dynamics modeling
• Physiological systems biology

Background:

• Infected hosts exhibit varied responses, ranging from resilience and recovery to mortality.
• Quantifying these divergent host responses to pathogens is crucial for understanding disease progression.

Purpose of the Study:

• To propose and validate a novel method for quantifying host resilience during infection by mapping disease progression in a multi-dimensional "disease space."
• To differentiate between resilient and non-resilient host trajectories using physiological data.

Main Methods:

• Developing a "disease space" by plotting physiological parameters against each other to visualize host trajectories.
• Utilizing longitudinal experimental data and proposing two methods for generating disease space maps from cross-sectional field trial data.
• Analyzing red blood cell (RBC) and reticulocyte dynamics in mice infected with Plasmodium chabaudi and in human malaria patients.

Main Results:

• Hysteretic relationships between physiological parameters were identified, serving as indicators of host location and predicting infection routes.
• Dying mice infected with Plasmodium chabaudi exhibited larger trajectories in RBC-reticulocyte space compared to surviving mice.
• Human malaria patients heterozygous for sickle cell hemoglobin showed smaller occupied areas in RBC-reticulocyte space, indicating resilience.

Conclusions:

• Mapping host trajectories in "disease space" provides a quantitative measure of in-host infection dynamics and host resilience.
• This approach can distinguish between resilient and non-resilient individuals and populations, with potential applications in both model organisms and human clinical settings.