Identifying high risk malaria infections using improved estimates of total body parasite load and new metrics for infection dynamics

Malaria remains a significant public health concern and is responsible for more than 400,000 deaths annually, most of which occur in African children under the age of five. The majority of malaria infections remain asymptomatic; only a small percentage progress to clinical symptoms and an even smaller proportion of these progress to a life-threatening disease. The host and parasite factors leading to this clinical heterogeneity are not well described or well understood. The study’s hypothesis is that the speed with which a malaria infection develops and the total number of parasites present in the body are important determinants of disease severity. Variables related to parasite dynamics cannot currently be measured in the human host and ex vivo measurements do not reflect in vivo reality.  Total body parasite load (TBPL): researchers will use tissue samples from children who died of cerebral malaria to quantify parasites in the most heavily parasitized organs and then extrapolate to the parasite load present in the entire body. This will create a new estimate of TBPL grounded in actual histological parasite counts. Parasite multiplication rate (PMR): Current estimates of PMR rely on removing the parasites from the host and testing their replication in culture, inevitably introducing culture-related artifact. This study propose to use a novel method based on parasite-produced proteins with different half-lives to calculate PMR in vivo. The researchers will then use clinical samples from well-characterized individuals at both extremes of the infection spectrum, asymptomatic parasitemia and cerebral malaria, in order to build a model to test the hypothesis that PMR and TBPL are important determinants of disease severity. If the hypothesis is correct and these parameters are related to disease severity, prognostic tests based on these metrics could lead to the real-time in vivo detection of high-risk malaria infections. Improved prognosis would lead, in turn, to earlier triage, and ultimately, a decrease in malaria morbidity and mortality. In addition, these measures of parasite dynamics would represent pathogenic processes that could be used to identify druggable targets. Should this hypothesis not hold true, the study will still have generated novel, robust measures of in vivo parasite activity, which will be useful in characterizing the interactions of parasites with the host immune system as well as defining inter-clone competition within a host.

NIH - Project details

Basic Science

May 2018 — Apr 2021

$349,351

United States