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The dynamics of naturally acquired immunity to Plasmodium falciparum infection.

Pinkevych M, Petravic J, Chelimo K, Kazura JW, Moormann AM, Davenport MP - PLoS Comput. Biol. (2012)

Bottom Line: Here we analyse the dynamics of Plasmodium falciparum malaria infection after treatment in a cohort of 197 healthy study participants of different ages in order to model naturally acquired immunity.We find that both delayed time-to-infection and reductions in asymptomatic parasitaemias in older age groups can be explained by immunity that reduces the growth of blood stage as opposed to liver stage parasites.We found that this mechanism would require at least two components - a rapidly acting strain-specific component, as well as a slowly acquired cross-reactive or general immunity to all strains.

View Article: PubMed Central - PubMed

Affiliation: Centre for Vascular Research, University of New South Wales, Sydney, New South Wales, Australia.

ABSTRACT
Severe malaria occurs predominantly in young children and immunity to clinical disease is associated with cumulative exposure in holoendemic settings. The relative contribution of immunity against various stages of the parasite life cycle that results in controlling infection and limiting disease is not well understood. Here we analyse the dynamics of Plasmodium falciparum malaria infection after treatment in a cohort of 197 healthy study participants of different ages in order to model naturally acquired immunity. We find that both delayed time-to-infection and reductions in asymptomatic parasitaemias in older age groups can be explained by immunity that reduces the growth of blood stage as opposed to liver stage parasites. We found that this mechanism would require at least two components - a rapidly acting strain-specific component, as well as a slowly acquired cross-reactive or general immunity to all strains. Analysis and modelling of malaria infection dynamics and naturally acquired immunity with age provides important insights into what mechanisms of immune control may be harnessed by malaria vaccine strategists.

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Related in: MedlinePlus

A distribution in growth rates explains differences in reinfection curves.Panel A. Optimal fit of a model allowing variation only in mean parasite multiplication rate (PMR) between groups. Panel B. The mean PMR for each group and the distributions. The shaded area at left indicates where PMR <1, and the parasite population does not grow, Panel C. Given the distribution in PMR, we can also calculate the distribution of delay as a distribution of a function of a random variable. Blue triangle and blue line- C1, green diamond and green line - C2, orange square and orange line - C3, red circle and red line - A.
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pcbi-1002729-g003: A distribution in growth rates explains differences in reinfection curves.Panel A. Optimal fit of a model allowing variation only in mean parasite multiplication rate (PMR) between groups. Panel B. The mean PMR for each group and the distributions. The shaded area at left indicates where PMR <1, and the parasite population does not grow, Panel C. Given the distribution in PMR, we can also calculate the distribution of delay as a distribution of a function of a random variable. Blue triangle and blue line- C1, green diamond and green line - C2, orange square and orange line - C3, red circle and red line - A.

Mentions: Remarkably, allowing only the average PMR to vary between age groups captures the main features of the natural infection profiles. We see both the increasing delay with age, as well as the early rapid increase in infection rates followed by an apparent slowing down of the rate of infection (Fig. 3A). With this model of a distribution in PMRs, we can now understand the unusual shape of the adult infection curve: The early slow shoulder of the curve represents the small fraction of infections that grow rapidly, and are detected early (the right hand side of the distribution in Fig. 3B). The rapid phase of infection is around the mean of the PMR curve, and the apparent slowing represents the very slowly growing infections, which are not detected during the 11 weeks of analysis. Because of the distribution of growth rates, there is a proportion of infections where the PMR <1 (shaded in Fig. 3B), implying the number of parasites decreases at each round of infection (each currently infected RBC infects less than one RBC in next round). In children, with mean PMR of ≈3.8, only a small proportion of infections have PMR <1. However, for the adults, with mean PMR ≈1.35, a large proportion of bites (≈24%) have PMR <1, which is why we see an apparent slowing of the infection rate later in the study. We note that by contrast simply allowing a distribution of the level of liver stage immunity alone does not improve the fit of the liver stage model (see [Text S3] for a detailed description of the model ).


The dynamics of naturally acquired immunity to Plasmodium falciparum infection.

Pinkevych M, Petravic J, Chelimo K, Kazura JW, Moormann AM, Davenport MP - PLoS Comput. Biol. (2012)

A distribution in growth rates explains differences in reinfection curves.Panel A. Optimal fit of a model allowing variation only in mean parasite multiplication rate (PMR) between groups. Panel B. The mean PMR for each group and the distributions. The shaded area at left indicates where PMR <1, and the parasite population does not grow, Panel C. Given the distribution in PMR, we can also calculate the distribution of delay as a distribution of a function of a random variable. Blue triangle and blue line- C1, green diamond and green line - C2, orange square and orange line - C3, red circle and red line - A.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3475668&req=5

pcbi-1002729-g003: A distribution in growth rates explains differences in reinfection curves.Panel A. Optimal fit of a model allowing variation only in mean parasite multiplication rate (PMR) between groups. Panel B. The mean PMR for each group and the distributions. The shaded area at left indicates where PMR <1, and the parasite population does not grow, Panel C. Given the distribution in PMR, we can also calculate the distribution of delay as a distribution of a function of a random variable. Blue triangle and blue line- C1, green diamond and green line - C2, orange square and orange line - C3, red circle and red line - A.
Mentions: Remarkably, allowing only the average PMR to vary between age groups captures the main features of the natural infection profiles. We see both the increasing delay with age, as well as the early rapid increase in infection rates followed by an apparent slowing down of the rate of infection (Fig. 3A). With this model of a distribution in PMRs, we can now understand the unusual shape of the adult infection curve: The early slow shoulder of the curve represents the small fraction of infections that grow rapidly, and are detected early (the right hand side of the distribution in Fig. 3B). The rapid phase of infection is around the mean of the PMR curve, and the apparent slowing represents the very slowly growing infections, which are not detected during the 11 weeks of analysis. Because of the distribution of growth rates, there is a proportion of infections where the PMR <1 (shaded in Fig. 3B), implying the number of parasites decreases at each round of infection (each currently infected RBC infects less than one RBC in next round). In children, with mean PMR of ≈3.8, only a small proportion of infections have PMR <1. However, for the adults, with mean PMR ≈1.35, a large proportion of bites (≈24%) have PMR <1, which is why we see an apparent slowing of the infection rate later in the study. We note that by contrast simply allowing a distribution of the level of liver stage immunity alone does not improve the fit of the liver stage model (see [Text S3] for a detailed description of the model ).

Bottom Line: Here we analyse the dynamics of Plasmodium falciparum malaria infection after treatment in a cohort of 197 healthy study participants of different ages in order to model naturally acquired immunity.We find that both delayed time-to-infection and reductions in asymptomatic parasitaemias in older age groups can be explained by immunity that reduces the growth of blood stage as opposed to liver stage parasites.We found that this mechanism would require at least two components - a rapidly acting strain-specific component, as well as a slowly acquired cross-reactive or general immunity to all strains.

View Article: PubMed Central - PubMed

Affiliation: Centre for Vascular Research, University of New South Wales, Sydney, New South Wales, Australia.

ABSTRACT
Severe malaria occurs predominantly in young children and immunity to clinical disease is associated with cumulative exposure in holoendemic settings. The relative contribution of immunity against various stages of the parasite life cycle that results in controlling infection and limiting disease is not well understood. Here we analyse the dynamics of Plasmodium falciparum malaria infection after treatment in a cohort of 197 healthy study participants of different ages in order to model naturally acquired immunity. We find that both delayed time-to-infection and reductions in asymptomatic parasitaemias in older age groups can be explained by immunity that reduces the growth of blood stage as opposed to liver stage parasites. We found that this mechanism would require at least two components - a rapidly acting strain-specific component, as well as a slowly acquired cross-reactive or general immunity to all strains. Analysis and modelling of malaria infection dynamics and naturally acquired immunity with age provides important insights into what mechanisms of immune control may be harnessed by malaria vaccine strategists.

Show MeSH
Related in: MedlinePlus