Using amplicon deep sequencing to detect genetic signatures of Plasmodium vivax relapse

In recent years, there has been an increased appreciation that global malaria elimination efforts cannot succeed without a better understanding of Plasmodium vivax, the leading cause of malaria outside Africa [1–3]. In particular, P. vivax's ability to cause periodic relapse poses a major barrier to malaria elimination, because hypnozoites, the parasite stages in the liver that reactivate to cause relapse, are not killed by traditional blood-stage drugs [4, 5]. In Southeast Asia, P. vivax relapses are common and frequent: up to two-thirds of individuals not treated with antirelapse therapy suffer 1 or more relapses, approximately 3–4 weeks after plasma levels of antimalarials wane [6–11]. However, because individuals can also become reinfected, it is difficult to determine the true relapse rate and to distinguish when treatment failures are due to relapse. Molecular genotyping aimed at distinguishing relapses from reinfections has been confounded by the frequent finding of genetically different parasites at relapse, even in the setting of known relapse [12–15]. Thus, tools to assess interventions targeting P. vivax in clinical studies are missing. We and others have previously shown that P. vivax populations in Thailand and Cambodia exhibit great genetic diversity despite relatively low-level transmission: many alleles circulate on a population level, and individuals commonly harbor multiple genetic variants at once [16–18]. With this diversity in mind, we applied targeted deep sequencing to a malaria cohort in Cambodia in which one-third of individuals suffered recurrent P. vivax infections. We hypothesized that the within-host diversity unveiled by deep sequencing at a highly polymorphic molecular marker would expose genotypic patterns suggestive of relapse. We found that enhanced detection of minority variants revealed patterns of variant overlap between initial and recurrent parasite isolates within individuals. This finding, combined with population-based characterization of haplotypes, provide a statistical framework for determining the probability of reinfection and relapse. Our findings shed light on the nature of P. vivax hypnozoite activation and represent important steps toward identifying genotypic signatures of relapse.