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Tracking Resilience to Infections by Mapping Disease Space.

Torres BY, Oliveira JH, Thomas Tate A, Rath P, Cumnock K, Schneider DS - PLoS Biol. (2016)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Program in Immunology, Stanford University, Stanford, California, United States of America.

ABSTRACT
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.

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Related in: MedlinePlus

The relationship between time and angle in a disease map.(A) Disease map of live mice (n = 3) through Nkg7 by RBC space. (B) Linear correlation between angle and days post infection from day 11 to day 20 (r2 = 0.942). Only points colored red were included in the regression analysis. Data provided in S2 Data.
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pbio.1002436.g006: The relationship between time and angle in a disease map.(A) Disease map of live mice (n = 3) through Nkg7 by RBC space. (B) Linear correlation between angle and days post infection from day 11 to day 20 (r2 = 0.942). Only points colored red were included in the regression analysis. Data provided in S2 Data.

Mentions: We reasoned that it might be possible to discover the order of events in an infection using a looping disease curve because each point has a unique position along the loop. This would allow us to compare individuals at similar segments of the infection rather than consider the entire course of infection. The path mice take through RBCs by NKG7 space is a useful space to use to describe this process, as the disease curve traced by mice in this space is nearly circular (Fig 6A). Instead of recording these data points in terms of their (x,y) position in space, we transformed them to polar coordinates. This reports each point in terms of the distance from the center of the loop and their angle from an arbitrary origin that we positioned at the start of the infection; the angle provides a measure of how far the host has progressed along the infection path. If we plot angle versus time, we find a linear correlation (r2 > 0.96) over much of the curve (Fig 6B), demonstrating that we can recover the order of events from cross-sectional data using this polar transformation approach; thus, looping disease curves can serve as clocks that report the time-independent order of events in a disease.


Tracking Resilience to Infections by Mapping Disease Space.

Torres BY, Oliveira JH, Thomas Tate A, Rath P, Cumnock K, Schneider DS - PLoS Biol. (2016)

The relationship between time and angle in a disease map.(A) Disease map of live mice (n = 3) through Nkg7 by RBC space. (B) Linear correlation between angle and days post infection from day 11 to day 20 (r2 = 0.942). Only points colored red were included in the regression analysis. Data provided in S2 Data.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835107&req=5

pbio.1002436.g006: The relationship between time and angle in a disease map.(A) Disease map of live mice (n = 3) through Nkg7 by RBC space. (B) Linear correlation between angle and days post infection from day 11 to day 20 (r2 = 0.942). Only points colored red were included in the regression analysis. Data provided in S2 Data.
Mentions: We reasoned that it might be possible to discover the order of events in an infection using a looping disease curve because each point has a unique position along the loop. This would allow us to compare individuals at similar segments of the infection rather than consider the entire course of infection. The path mice take through RBCs by NKG7 space is a useful space to use to describe this process, as the disease curve traced by mice in this space is nearly circular (Fig 6A). Instead of recording these data points in terms of their (x,y) position in space, we transformed them to polar coordinates. This reports each point in terms of the distance from the center of the loop and their angle from an arbitrary origin that we positioned at the start of the infection; the angle provides a measure of how far the host has progressed along the infection path. If we plot angle versus time, we find a linear correlation (r2 > 0.96) over much of the curve (Fig 6B), demonstrating that we can recover the order of events from cross-sectional data using this polar transformation approach; thus, looping disease curves can serve as clocks that report the time-independent order of events in a disease.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Program in Immunology, Stanford University, Stanford, California, United States of America.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus