Comparison of techniques and markers to distinguish Plasmodium falciparum recrudescence from new infection in Rwanda

Accurate estimation of antimalarial drug efficacy against P. falciparum requires PCR correction to distinguish recrudescence from new infection in recurrent infections. Here, we compared two different genotyping techniques and different decision algorithms used for PCR correction using samples collected in a Therapeutic Efficacy Study (TES) conducted in Rwanda in 2018. We first optimized an assay to genotype four microsatellites by capillary electrophoresis and assessed its sensitivity in detecting minority clones with laboratory parasite strain mixtures. We then analyzed patient samples by capillary electrophoresis using msp1, msp2, glurp and microsatellites (length-polymorphic markers) and amplicon deep sequencing using cpmp, ama1, cpp and csp (SNP-rich markers), and assessed their diversity and allelic frequency. We classified the recurrent infections as recrudescence or new infection based on different marker combinations and decision algorithms (WHO, 2/3, Bayesian algorithm). Among microsatellites, TA40 and PfPK2 had the highest sensitivity in detecting minority clones. Msp2/3D7, glurp and SNP-rich markers had the highest genetic diversity and lowest allelic frequencies. The WHO algorithm identified the fewest recrudescences across all marker combinations, while the 2/3 identified the most. The Bayesian algorithm yielded intermediate results. Replacing glurp with any of the microsatellites or using SNP-rich markers did not significantly alter recrudescence estimates. Amplicon sequencing of SNP-rich markers provided the most consistent results regardless of the decision algorithm used and therefore holds great potential for reliable PCR correction. Additionally, probabilistic approaches may provide more robust results compared to match counting algorithms; however, they require rigorous validation with datasets from different transmission settings.