Multiplex 5' nuclease quantitative real-time PCR for clinical diagnosis of malaria and species-level identification and epidemiologic evaluation of malaria-causing parasites, including Plasmodium knowlesi.
Molecular diagnosis of malaria offers many potential advantages over microscopy, including identification of malaria to the species level in an era with few experienced microscopists. We developed high-throughput multiplex 5' nuclease quantitative PCR (qPCR) assays, with the potential to support large studies, to specifically identify Plasmodium falciparum, P. vivax, P. ovale, P. malariae, and P. knowlesi. We compared qPCR to microscopy and confirmed discordant results with an alternative target PCR assay. The assays specifically detected 1 to 6 parasites/μl of blood. The clinical sensitivities (95% confidence intervals [CIs]) of the 4-plex assay to detect microscopically confirmed malaria were 95.8% (88.3 to 99.1%) for P. falciparum, 89.5% (75.2 to 97.1%) for P. vivax, 94.1% (71.3 to 99.9%) for P. ovale, and 100% (66.4 to 100%) for P. malariae. The specificities (95% CIs) were 98.6% (92.4 to 100%) for P. falciparum, 99% (84.8 to 100%) for P. vivax, 98.4% (94.4 to 99.8%) for P. ovale, and 99.3% (95.9 to 100%) for P. malariae. The clinical specificity for samples without malaria was 100%. The clinical sensitivity of the 5-plex assay for confirmed P. knowlesi malaria was 100% (95% CI, 69.2 to 100%), and the clinical specificity was 100% (95% CI, 87.2 to 100%). Coded retesting and testing with an alternative target PCR assay showed improved sensitivity and specificity of multiplex qPCR versus microscopy. Additionally, 91.7% (11/12) of the samples with uncertain species by microscopy were identified to the species level identically by both our multiplex qPCR assay and the alternative target PCR assay, including 9 P. falciparum infections. Multiplex qPCR can rapidly and simultaneously identify all 5 Plasmodium species known to cause malaria in humans, and it offers an alternative or adjunct to microscopy for clinical diagnosis as well as a needed high-throughput tool for research.
Reller, ME; Chen, WH; Dalton, J; Lichay, MA; Dumler, JS
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