Tracking Resilience to Infections by Mapping Disease Space

Infected hosts differ in their responses to pathogens; some hosts are resilient and recover their original health, whereas others follow a divergent path and die. To quantitate these differences, we propose mapping the routes infected individuals take through "disease space." We find that...

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Veröffentlicht in:PLoS biology 2016-04, Vol.14 (4), p.e1002436-e1002436
Hauptverfasser: Torres, Brenda Y, Oliveira, Jose Henrique M, Thomas Tate, Ann, Rath, Poonam, Cumnock, Katherine, Schneider, David S
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container_title PLoS biology
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creator Torres, Brenda Y
Oliveira, Jose Henrique M
Thomas Tate, Ann
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Schneider, David S
description Infected hosts differ in their responses to pathogens; some hosts are resilient and recover their original health, whereas others follow a divergent path and die. To quantitate these differences, we propose mapping the routes infected individuals take through "disease space." We find that when plotting physiological parameters against each other, many pairs have hysteretic relationships that identify the current location of the host and predict the future route of the infection. These maps can readily be constructed from experimental longitudinal data, and we provide two methods to generate the maps from the cross-sectional data that is commonly gathered in field trials. We hypothesize that resilient hosts tend to take small loops through disease space, whereas nonresilient individuals take large loops. We support this hypothesis with experimental data in mice infected with Plasmodium chabaudi, finding that dying mice trace a large arc in red blood cells (RBCs) by reticulocyte space as compared to surviving mice. We find that human malaria patients who are heterozygous for sickle cell hemoglobin occupy a small area of RBCs by reticulocyte space, suggesting this approach can be used to distinguish resilience in human populations. This technique should be broadly useful in describing the in-host dynamics of infections in both model hosts and patients at both population and individual levels.
doi_str_mv 10.1371/journal.pbio.1002436
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subjects Animals
Biology and Life Sciences
Blood
Computer and Information Sciences
Confidence intervals
Erythrocytes
Funding
Genetic engineering
Host-parasite relationships
Humans
Infections
Infections - physiopathology
Infectious diseases
Malaria
Malaria - blood
Malaria - physiopathology
Medicine and Health Sciences
Methods
Mice
Observations
Pathogenesis
Pathogens
Patients
Plasmodium chabaudi
Plasmodium chabaudi - pathogenicity
Research and Analysis Methods
Statistical analysis
Studies
title Tracking Resilience to Infections by Mapping Disease Space
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