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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

Disease space analysis of malaria-infected children.(A) The mean radius for individuals with the sickle cell trait (AS, red) is below the average random distribution for a group size of 47 patients. (B) Marking individuals with Hemoglobin A (AA, blue, triangle), Hemoglobin C (AC, green, square), and Hemoglobin S (AS, red, circle) in RBC by reticulocyte (Fech) space. Individuals with Hemoglobin S form a smaller cluster than the other two hemoglobins, suggesting a smaller route through disease space. See also S2 Fig. Data provided in S4 Data.
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pbio.1002436.g008: Disease space analysis of malaria-infected children.(A) The mean radius for individuals with the sickle cell trait (AS, red) is below the average random distribution for a group size of 47 patients. (B) Marking individuals with Hemoglobin A (AA, blue, triangle), Hemoglobin C (AC, green, square), and Hemoglobin S (AS, red, circle) in RBC by reticulocyte (Fech) space. Individuals with Hemoglobin S form a smaller cluster than the other two hemoglobins, suggesting a smaller route through disease space. See also S2 Fig. Data provided in S4 Data.

Mentions: These experiments suggest that if we select a disease space in which sick individuals trace a loop, and that loop is a good indicator of disease, then the most resilient individuals in a population will trace the tightest loops. To test this idea, we examined published genetic variation and transcriptome data from malaria-infected children to determine whether polymorphisms known to limit the severity of malaria restricted patients to a narrow window of disease space [12]. To provide a statistical analysis of these data, we determined the probability that a randomly selected group of data points in this set would produce a cluster of a particular sized radius (Figs 8A and S3). To measure the distribution of small groups of varying sizes, we performed a bootstrap analysis, recording the calculated radii of 1,000 randomly chosen clusters from this dataset, ranging from two to 100 members. This gives us a sense of the distribution the radii would have for given group sizes if the members were chosen randomly. The resulting curve demonstrated that small groups have a relatively high radii variance and that mean radii variance plateaus once group sizes pass approximately 20 members. The dataset used here does not provide enough power to perform a genome-wide association study (GWAS) screen to identify SNPs from the whole genome, but it is powerful enough to let us ask hypothesis-based questions about individual polymorphisms.


Tracking Resilience to Infections by Mapping Disease Space.

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

Disease space analysis of malaria-infected children.(A) The mean radius for individuals with the sickle cell trait (AS, red) is below the average random distribution for a group size of 47 patients. (B) Marking individuals with Hemoglobin A (AA, blue, triangle), Hemoglobin C (AC, green, square), and Hemoglobin S (AS, red, circle) in RBC by reticulocyte (Fech) space. Individuals with Hemoglobin S form a smaller cluster than the other two hemoglobins, suggesting a smaller route through disease space. See also S2 Fig. Data provided in S4 Data.
© Copyright Policy
Related In: Results  -  Collection

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

pbio.1002436.g008: Disease space analysis of malaria-infected children.(A) The mean radius for individuals with the sickle cell trait (AS, red) is below the average random distribution for a group size of 47 patients. (B) Marking individuals with Hemoglobin A (AA, blue, triangle), Hemoglobin C (AC, green, square), and Hemoglobin S (AS, red, circle) in RBC by reticulocyte (Fech) space. Individuals with Hemoglobin S form a smaller cluster than the other two hemoglobins, suggesting a smaller route through disease space. See also S2 Fig. Data provided in S4 Data.
Mentions: These experiments suggest that if we select a disease space in which sick individuals trace a loop, and that loop is a good indicator of disease, then the most resilient individuals in a population will trace the tightest loops. To test this idea, we examined published genetic variation and transcriptome data from malaria-infected children to determine whether polymorphisms known to limit the severity of malaria restricted patients to a narrow window of disease space [12]. To provide a statistical analysis of these data, we determined the probability that a randomly selected group of data points in this set would produce a cluster of a particular sized radius (Figs 8A and S3). To measure the distribution of small groups of varying sizes, we performed a bootstrap analysis, recording the calculated radii of 1,000 randomly chosen clusters from this dataset, ranging from two to 100 members. This gives us a sense of the distribution the radii would have for given group sizes if the members were chosen randomly. The resulting curve demonstrated that small groups have a relatively high radii variance and that mean radii variance plateaus once group sizes pass approximately 20 members. The dataset used here does not provide enough power to perform a genome-wide association study (GWAS) screen to identify SNPs from the whole genome, but it is powerful enough to let us ask hypothesis-based questions about individual polymorphisms.

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