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HEIndividual fellowship2023–2025

PvRecur · Using Plasmodium vivax genetic data to estimate the cause of recurrent vivax malaria

Horizon Europe — Marie Skłodowska-Curie Actions

Duration
2023-11-07 → 2025-11-06
EU contribution
€211,755
Participants
1
Scheme
HORIZON-TMA-MSCA-PF-EF

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Results in brief

Using Plasmodium vivax genetic data to estimate the cause of recurrent vivax malaria

Malaria is a major global health challenge. It is caused by Plasmodium parasites transmitted from human-to-human by female Anopheles mosquitoes. The parasite species Plasmodium vivax is one of the two most important causes of malaria and also the most difficult to eliminate because of its ability to relapse: cause recurrent blood-stage infection (recurrence) following the activation of dormant liver-stage parasites. Blood-stage treatment failure (recrudescence) and new infectious mosquito bites (reinfection) also cause recurrence. Distinguishing among these three causes of recurrence is important in both epidemiological and clinical studies, especially those that aim to estimate the clinical efficacy of antimalarial treatment. However, there are no definitive biomarkers of relapse, recrudescence and reinfection (the 3Rs). Genetic data on P. vivax parasites sampled from two or more blood-stage infections in the same person can be used to infer the cause of recurrence. Previously, we developed a statistical model capable of computing posterior 3R probabilities using data on fewer than 10 microsatellite markers. This was a breakthrough, showing that statistical genetic inference of P. vivax recurrence is feasible, but the prototypic model has two major drawbacks. Firstly, it is encoded in study specific scripts that are not easily accessible. Secondly, it does not scale to hundreds of markers typical of amplicon sequencing (AmpSeq) data, which many malaria studies are now generating. PvRecur aims to transform P. vivax recurrence state inference by providing a open-source tool that all P. vivax researchers (epidemiologists and clinical trial analysts) can use to compute 3R probabilities from P. vivax AmpSeq data (objective 1); and by demonstrating the utility of that tool through its application to AmpSeq datasets on samples collected in the Solomon Islands, Peru, and Ethiopia (objective 2). By clarifying the causes of recurrence, PvRecur will improve our epidemiological understanding of P. vivax and enable more accurate treatment efficacy estimation, guiding the optimization of new treatment regimens. Given that nearly 2.5 billion people live at risk of P. vivax infection, efforts to improve P. vivax control and elimination have a substantial potential impact on global health.

Data: CORDIS, © European Union

Project objective

Malaria infects hundreds of millions of people year on year. The WHO is committed to a world ultimately free of malaria. Of the two most important causes of malaria, Plasmodium vivax is the most difficult to eliminate largely because it has the capacity to relapse: causing recurrent malaria via the activation of latent liver-stage parasites. Recurrent malaria can also be caused by the failure to treat a previous blood-stage infection (recrudescence) and, in endemic settings, new infectious mosquito bites (reinfection). Knowing the cause of recurrent malaria is key to understanding malaria epidemiology and to providing efficacious treatment. For example, to evaluate the efficacy of a drug designed to kill P. vivax liver-stage parasites in an endemic setting, reinfections and recrudescence must be separated from relapses. However, there are no direct ways to diagnose the cause of recurrent malaria. To address this problem, I aim to build a tool (Pv3R) that uses Plasmodium vivax genetic data to estimate the probability of Relapse, Recrudescence and Reinfection, and use Pv3R to estimate the burden of relapse and its contribution to transmission, thereby validating Pv3R’s utility. I will achieve my objectives by merging my existing expertise in statistical malaria genetics with the expertise of Dr Michael White and his lab, its ties with field-based P. vivax epidemiology and its capacity to generate P. vivax genetic data. Working with Dr White, I will develop a state-of-the-art statistical inference method to tackle the challenging unsolved problem of differentiating between the causes of recurrent P. vivax. This will generate knowledge that directly improves our understanding of P. vivax epidemiology and, most long-lastingly, a public health resource (Pv3R) that can be used sustainably by the malaria community to generate more epidemiological knowledge and to guide the design of more effective treatment regimens needed for P. vivax control and elimination.

Original text from CORDIS.

Participants

  • INSTITUT PASTEUR · ParisCoordinatorFrance

Links

Data: CORDIS, © European Union