Detection of drug-resistant malaria in resource-limited settings: efficient and high-throughput surveillance of artemisinin and partner drug resistance

J Antimicrob Chemother. 2024 Apr 25:dkae120. doi: 10.1093/jac/dkae120. Online ahead of print.

Abstract

Objectives: Artemisinin-resistant Plasmodium falciparum malaria is currently spreading globally, including in Africa. Artemisinin resistance also leads to resistance to partner drugs used in artemisinin-based combination therapies. Sequencing of kelch13, which is associated with artemisinin resistance, culture-based partner drug susceptibility tests, and ELISA-based growth measurement are conventionally used to monitor resistance; however, their application is challenging in resource-limited settings.

Methods: An experimental package for field studies with minimum human/material requirements was developed.

Results: First, qPCR-based SNP assay was applied in artemisinin resistance screening, which can detect mutations within 1 h and facilitate sample selection for subsequent processes. It had 100% sensitivity and specificity compared with DNA sequencing in the detection of the two common artemisinin resistance mutations in Uganda, C469Y and A675V. Moreover, in the partner drug susceptibility test, the cultured samples were dry-preserved on a 96-well filter paper plate and shipped to the central laboratory. Parasite growth was measured by ELISA using redissolved samples. It well reproduced the results of direct ELISA, reducing significant workload in the field (Pearson correlation coefficient: 0.984; 95% CI: 0.975-0.990).

Conclusions: Large-scale and sustainable monitoring is required urgently to track rapidly spreading drug-resistant malaria. In malaria-endemic areas, where research resources are often limited, simplicity and feasibility of the procedure is especially important. Our approach combines a qPCR-based rapid test, which is also applicable to point-of-care diagnosis of artemisinin resistance and centralized analysis of ex vivo culture. The approach could improve efficiency of field experiments and accelerate global drug resistance surveillance.