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. 2025 Feb 5;15(1):4375.
doi: 10.1038/s41598-025-88892-7.

Assessment of different genotyping markers and algorithms for distinguishing Plasmodium falciparum recrudescence from reinfection in Uganda

Alex Mwesigwa  1   2 , Monica Golumbeanu  3   4 , Sam Jones  5 , Sara L Cantoreggi  3   4 , Benson Musinguzi  6 , Joaniter I Nankabirwa  7   8 , Everd Maniple Bikaitwoha  9 , Joan N Kalyango  7 , Charles Karamagi  7 , Mateusz Plucinski  10 , Samuel L Nsobya  8 , Christian Nsanzabana  3   4 , Pauline Byakika-Kibwika  11
Affiliations

Assessment of different genotyping markers and algorithms for distinguishing Plasmodium falciparum recrudescence from reinfection in Uganda

Alex Mwesigwa et al. Sci Rep. .

Abstract

Antimalarial therapeutic efficacy studies are vital for monitoring drug efficacy in malaria-endemic regions. The WHO recommends genotyping polymorphic markers including msp-1, msp-2, and glurp for distinguishing recrudescences from reinfections. Recently, WHO proposed replacing glurp with microsatellites (Poly-α, PfPK2, TA1). However, suitable combinations with msp-1 and msp-2, as well as the performance of different algorithms for classifying recrudescence, have not been systematically assessed. This study investigated various microsatellites alongside msp-1 and msp-2 for molecular correction and compared different genotyping algorithms across three sites in Uganda. Microsatellites 313, Poly-α, and 383 exhibited the highest diversity, while PfPK2 and Poly-α revealed elevated multiplicity of infection (MOI) across all sites. The 3/3 match-counting algorithm classified significantly fewer recrudescences than both the ≥ 2/3 and Bayesian algorithms at probability cutoffs of ≥ 0.7 and ≥ 0.8 (P < 0.05). The msp-1/msp-2/2490 combination identified more recrudescences using the ≥ 2/3 and 3/3 algorithms in the artemether-lumefantrine (AL) treatment arm, while msp-1/msp-2/glurp combination classified more cases of recrudescence using the ≥ 2/3 in the dihydroartemisinin-piperaquine (DP) arm. Microsatellites PfPK2 and Poly-α, potentially sensitive to detecting minority clones, are promising replacements for glurp. Discrepancies in recrudescence classification between match-counting and Bayesian algorithms highlight the need for standardized PCR correction practices.

Keywords: Plasmodium falciparum; msp-1; msp-2; Antimalarial drug; Microsatellites; Recrudescence; Reinfection.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was approved by the Makerere University School of Medicine Research and Ethics Committee (Mak-SOMREC #2021 − 152) and the Uganda National Council for Science and Technology (UNCST #HS2744ES). All procedures were conducted in accordance with the ethical guidelines and regulations of both Mak-SOMREC and UNCST. The study utilized dried blood spot (DBS) filter papers collected from children aged 6 months to 10 years. Informed assent was obtained from the children, and parental consent was granted for the reuse of their samples in future molecular parasite studies. Parents were fully informed about the study and provided written consent for their child’s participation and the use of their samples. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Distribution of the P. falciparum MOI across the three study sites. Each violin plot shows, for a given site, the distribution of the observed MOIs in the samples collected at Day 0. The diamond from each violin plot represents the average MOI whose corresponding value is displayed above.
Fig. 2
Fig. 2
Distribution of the probability of recrudescence estimated with the Bayesian algorithm. Results are presented for the infections in all three study sites in the AL drug arm (A) and the DP drug arm (B). Each sub-panel displays, for each marker combination, the distribution of probabilities of recrudescence estimated using the algorithm. The heights of the bars correspond to the number of samples with the respective probability.
Fig. 3
Fig. 3
Comparison of the number of recrudescences identified by each algorithm and marker combination. Results are presented for the ≥ 2/3, 3/3, and Bayesian algorithm using cutoffs of 0.7 and 0.8 for the probability of recrudescence, across each marker combination (x-axis). The number of recrudescences identified by each algorithm (y-axis) is illustrated with the colored bars
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