Dataset Information

Molecular assays for antimalarial drug resistance surveillance: A target product profile.

ABSTRACT: Antimalarial drug resistance is a major constraint for malaria control and elimination efforts. Artemisinin-based combination therapy is now the mainstay for malaria treatment. However, delayed parasite clearance following treatment with artemisinin derivatives has now spread in the Greater Mekong Sub region and may emerge or spread to other malaria endemic regions. This spread is of great concern for malaria control programmes, as no alternatives to artemisinin-based combination therapies are expected to be available in the near future. There is a need to strengthen surveillance systems for early detection and response to the antimalarial drug resistance threat. Current surveillance is mainly done through therapeutic efficacy studies; however these studies are complex and both time- and resource-intensive. For multiple common antimalarials, parasite drug resistance has been correlated with specific genetic mutations, and the molecular markers associated with antimalarial drug resistance offer a simple and powerful tool to monitor the emergence and spread of resistant parasites. Different techniques to analyse molecular markers associated with antimalarial drug resistance are available, each with advantages and disadvantages. However, procedures are not adequately harmonized to facilitate comparisons between sites. Here we describe the target product profiles for tests to analyse molecular markers associated with antimalarial drug resistance, discuss how use of current techniques can be standardised, and identify the requirements for an ideal product that would allow malaria endemic countries to provide useful spatial and temporal information on the spread of resistance.

SUBMITTER: Nsanzabana C

PROVIDER: S-EPMC6147503 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular assays for antimalarial drug resistance surveillance: A target product profile.

Nsanzabana Christian C Ariey Frederic F Beck Hans-Peter HP Ding Xavier C XC Kamau Edwin E Krishna Sanjeev S Legrand Eric E Lucchi Naomi N Miotto Olivo O Nag Sidsel S Noedl Harald H Roper Cally C Rosenthal Philip J PJ Schallig Henk D F H HDFH Taylor Steve M SM Volkman Sarah K SK Gonzalez Iveth J IJ

PloS one 20180920 9

Antimalarial drug resistance is a major constraint for malaria control and elimination efforts. Artemisinin-based combination therapy is now the mainstay for malaria treatment. However, delayed parasite clearance following treatment with artemisinin derivatives has now spread in the Greater Mekong Sub region and may emerge or spread to other malaria endemic regions. This spread is of great concern for malaria control programmes, as no alternatives to artemisinin-based combination therapies are e ...[more]

PMID: 30235327

Similar Datasets

Project description:BackgroundMolecular markers for antimalarial drug resistance can be used to rapidly monitor the emergence and spatial distribution of resistance to artemisinin-based combination therapies (ACTs). Little has been done to analyse molecular surveillance efforts or to assess surveillance coverage. This study aimed to develop an evidence map to characterise the spatial-temporal distribution and sampling methodologies of drug resistance surveillance in sub-Saharan Africa, specifically focusing on markers associated with ACT partner drugs.MethodsBy use of a systematic search, we identified studies that reported data on the following mutations associated with ACT partner drug resistance: pfmdr1 Asn86Tyr, Tyr184Phe, Asp1246Tyr, and copy number variation and pfcrt Lys76Thr, with sample collection occurring in sub-Saharan Africa between Jan 1, 2004, and Dec 31, 2018, corresponding to the uptake of ACTs. For each identified study, we extracted information on its sampling and laboratory methods, author and publication affiliations, years of sampling and of publication, geographic coordinates of the study sites, and prevalence of the partner drug resistance-associated markers. We used linear models to test whether urbanicity, population density, and endemicity were predictors of drug resistance survey sites and linear regressions to identify associations between the number of resistance surveys within a given country and the at-risk malaria population in 2010, the per-capita GDP in 2010, and the mean amount of funding directed to malaria and to determine trends in marker prevalence over time. For country case studies with three or more datapoints, we assessed global spatial autocorrelation using Moran's I.FindingsOur search yielded 254 studies encompassing 492 year-specific and location-specific surveys from 35 malaria-endemic countries, the most complete set of molecular partner drug surveillance data to date. We observed a median time lag of 3·1 years (95% CI 1·0-7·7) from final sample acquisition to publication. 22 (49%) of the 44 countries in the study region conducted, on average, one or fewer studies every 3 years. The locations of surveillance sites were positively associated with urbanicity (p<0·0001), and the abundance of country-level data was associated with reported donor funding in 2004-18 (p=0·0011) and local government funding in 2004-09 (p=0·014). Nearly all molecular markers displayed significant regional trends over time and global spatial autocorrelation in space. For selected countries with more widespread coverage of surveillance data, some markers also displayed spatial heterogeneity.InterpretationIn most sub-Saharan countries, molecular data on antimalarial resistance might not be representative of the temporal and geographic heterogeneity of partner drug resistance, and likely do not represent the true spatially dependent distribution of partner drug resistance. Our results highlight several inefficiencies that can be improved upon to develop more accurate data landscapes, including the expansion of sentinel surveillance systems, syndemic usage of research samples, and increased participation in reporting published and unpublished data to centralised platforms.

Project description:BackgroundCurrent malaria control and elimination strategies rely mainly on efficacious antimalarial drugs. However, drug resistance is a major threat facing malaria control programs. Determination of drug resistance molecular markers is useful in the monitoring and surveillance of malaria drug efficacy. This study aimed to determine the mutations and haplotypes frequencies of different genes linked with antimalarial drug resistance in certain areas in Sudan.MethodsA total of 226 dried blood spots (DBS) of microscopically diagnosed P. falciparum isolates were collected from Khartoum and three other areas in Sudan during 2015-2017. Plasmodium falciparum confirmation and multiplicity of infection was assessed using the Sanger's 101 SNPs-barcode and speciation was confirmed using regions of the parasite mitochondria. Molecular genotyping of drug resistance genes (Pfcrt, Pfmdr1, Pfdhfr, Pfdhps, exonuclease, Pfk13, parasite genetic background (PGB) (Pfarps10, ferredoxin, Pfcrt, Pfmdr2)) was also performed. All genotypes were generated by selective regions amplicon sequencing of the parasite genome using the Illumina MiSeq platform at the Wellcome Sanger Institute, UK then genotypes were translated into drug resistance haplotypes and species determination.FindingsIn total 225 samples were confirmed to be P. falciparum. A higher proportion of multiplicity of infection was observed in Gezira (P<0.001) based on the Sanger 101 SNPs -barcode. The overall frequency of mutant haplotype Pfcrt 72-76 CVIET was 71.8%. For Pfmdr1, N86Y was detected in 53.6%, Y184F was observed in 88.1% and D1246Y was detected in 1.5% of the samples. The most frequently observed haplotype was YFD 47.4%. For Pfdhfr (codons 51, 59,108,164), the ICNI haplotype was the most frequent (80.7%) while for Pfdhps (codons 436, 437, 540, 581, 613) the (SGEAA) was most frequent haplotype (41%). The Quadruple mutation (dhfr N51I, S108N + dhps A437G, K540E) was the highest frequent combined mutation (33.9%). In Pfkelch13 gene, 18 non-synonymous mutations were detected, 7 of them were detected in other African countries. The most frequent Pfk13 mutation was E433D detected in four samples. All of the Pfk13 mutant alleles have not been reported to belong to mutations associated with delayed parasite clearance in Southeast Asia. PGB mutations were detected only in Pfcrt N326S\I (46.3%) and Pfcrt I356T (8.2%). The exonuclease mutation was not detected. There was no significant variation in mutant haplotypes between study areas.ConclusionsThere was high frequency of mutations in Pfcrt, Pfdhfr and Pfdhps in this study. These mutations are associated with chloroquine and sulfadoxine-pyrimethamine (SP) resistance. Many SNPs in Pfk13 not linked with delayed parasite clearance were observed. The exonuclease E415G mutation which is linked with piperaquine resistance was not reported.

Dataset Information

Molecular assays for antimalarial drug resistance surveillance: A target product profile.

Publications

Molecular assays for antimalarial drug resistance surveillance: A target product profile.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets