Assessment of different techniques and markers to distinguish recrudescence from new infection in an antimalarial therapeutic efficacy study conducted in Rwanda
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Introduction
Accurate estimation of antimalarial drug efficacy against P. falciparum requires PCR correction to distinguish recrudescence from new infection in recurrent infections. Genotyping length polymorphic or SNP-rich markers, and various decision algorithms based on match counting or probabilistic approaches may be used for this purpose. In this study, we compared several markers and decision algorithms using samples collected in a therapeutic efficacy study conducted in Rwanda to identify the most suitable and robust approaches for PCR correction.
Methods
We optimized nested PCR assays to genotype four microsatellites and assessed their sensitivity in detecting minority clones with laboratory parasite strain mixtures. We analyzed patient samples by capillary electrophoresis and amplicon deep sequencing and assessed the diversity and allelic frequency of msp1 , msp2 , glurp , microsatellites ( Poly-α, PfPK2, TA40, TA81 ), and SNP-rich markers ( ama1-D2, ama1-D3, cpmp, cpp, csp ). We then classified the samples into recrudescence or new infection based on different marker combinations ( msp1/msp2/glurp, msp1/msp2/ microsatellite, and SNP-rich markers) and three decision algorithms (WHO algorithm, 2/3 algorithm, and a Bayesian approach), and compared our results with previously published findings.
Results
Among microsatellites, TA40 and PfPK2 had the highest sensitivity in detecting minority clones; however, their intra-assay reproducibility was found to be limited. The 3D7 allelic family of the msp2 gene, glurp and SNP-rich markers had the highest genetic diversity. In distinguishing recrudescence from new infection, the WHO algorithm identified the fewest recrudescences across all marker combinations. Conversely, the 2/3 algorithm identified the highest number of recrudescences, and the algorithm based on Bayesian statistics yielded intermediate results. We observed the least variability in classification results among the different algorithms for the SNP-rich markers ama1-D2/ama1-D3/cpmp combination. In our study, replacing glurp with one of the four analyzed microsatellites or using SNP-rich markers did not significantly alter the final number of recrudescent infections.
Interpretation
Our findings emphasize the importance of using assays with high sensitivity in detecting minority clones, and markers with high diversity and low allelic frequency for accurate PCR correction. The SNP-rich markers method yielded the most consistent results in detecting recrudescences, regardless of the decision algorithm used. Therefore, it holds great potential for performing reliable PCR correction. Further evaluation of decision algorithms based on probabilistic approaches, compared to match-counting methods, is essential to ensure the accuracy and consistency of PCR-corrected drug efficacy estimations.
