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Antimalarial therapeutic efficacy studies are routinely conducted in malaria-endemic countries to assess the effectiveness of antimalarial treatment strategies. Targeted amplicon deep sequencing (TADS) uniquely identifies and quantifies genetically distinct parasites within an infection. In this study, TADS Plasmodium falciparum apical membrane antigen 1 (ama1), and multidrug resistance gene 1 (mdr1), were used to characterize the complexity of infection (COI) and drug-resistance genotypes, respectively. P. falciparum positive samples were obtained from a triple artemisinin combination therapy clinical trial conducted in 30 children under 13 years of age between 2018 and 2019 in Kilifi, Kenya. Of the 30 participants, 9 presented with recurrent parasitemia from day 26 (624h) onwards. The ama1 and mdr1 genes were amplified and sequenced, while msp1, msp2 and glurp data were obtained from the original clinical study. The COI was comparable between ama1 and msp1, msp2 and glurp, however, overall ama1 detected more haplotypes. Based on ama1, a stable number of haplotypes were detected throughout treatment up until day 3. Additionally, a recrudescent infection was identified with an ama1 haplotype initially observed at 30h and later in an unscheduled follow-up visit. Using the relative frequencies of ama1 haplotypes and parasitaemia, we identified a fast (<1h) and slow (>5h) clearing haplotype. As expected, only two mdr1 haplotypes (NF and NY) were identified based on the combination of amino acid polymorphisms at codons 86 and 184. This study highlights TADS as a sensitive tool for tracking parasite haplotypes throughout treatment and can detect variation in haplotype clearance estimates. TADS can also identify slow clearing haplotypes, a potential early sign of selection during treatment. Consequently, TADS has the capability of improving the discriminatory power to accurately distinguish recrudescences from reinfections.

Original publication

DOI

10.12688/wellcomeopenres.17736.1

Type

Journal article

Journal

Wellcome Open Research

Publisher

F1000 Research Ltd

Publication Date

16/03/2022

Volume

7

Pages

95 - 95