Molecular markers as indicators of antimalarial drug failure rates

A comprehensive analysis of drug resistance molecular markers and Plasmodium falciparum genetic diversity in two malaria endemic sites in Mali

BACKGROUND

Drug resistance is one of the greatest challenges of malaria control programme in Mali. Recent advances in next-generation sequencing (NGS) technologies provide new and effective ways of tracking drug-resistant malaria parasites in Africa. The diversity and the prevalence of Plasmodium falciparum drug-resistance molecular markers were assessed in Dangassa and Nioro-du-Sahel in Mali, two sites with distinct malaria transmission patterns. Dangassa has an intense seasonal malaria transmission, whereas Nioro-du-Sahel has an unstable and short seasonal malaria transmission.

METHODS

Up to 270 dried blood spot samples (214 in Dangassa and 56 in Nioro-du-Sahel) were collected from P. falciparum positive patients in 2016. Samples were analysed on the Agena MassARRAY® iPLEX platform. Specific codons were targeted in Pfcrt, Pfmdr1, Pfdhfr, and Pfdhps, Pfarps10, Pfferredoxin, Pfexonuclease and Pfmdr2 genes. The Sanger's 101-SNPs-barcode method was used to assess the genetic diversity of P. falciparum and to determine the parasite species.

RESULTS

The Pfcrt_76T chloroquine-resistance genotype was found at a rate of 64.4% in Dangassa and 45.2% in Nioro-du-Sahel (p = 0.025). The Pfdhfr_51I-59R-108N pyrimethamine-resistance genotype was 14.1% and 19.6%, respectively in Dangassa and Nioro-du-Sahel. Mutations in the Pfdhps_S436-A437-K540-A581-613A sulfadoxine-resistance gene was significantly more prevalent in Dangassa as compared to Nioro-du-Sahel (p = 0.035). Up to 17.8% of the isolates from Dangassa vs 7% from Nioro-du-Sahel harboured at least two codon substitutions in this haplotype. The amodiaquine-resistance Pfmdr1_N86Y mutation was identified in only three samples (two in Dangassa and one in Nioro-du-Sahel). The lumefantrine-reduced susceptibility Pfmdr1_Y184F mutation was found in 39.9% and 48.2% of samples in Dangassa and Nioro-du-Sahel, respectively. One piperaquine-resistance Exo_E415G mutation was found in Dangassa, while no artemisinin resistance genetic-background were identified. A high P. falciparum diversity was observed, but no clear genetic aggregation was found at either study sites. Higher multiplicity of infection was observed in Dangassa with both COIL (p = 0.04) and Real McCOIL (p = 0.02) methods relative to Nioro-du-Sahel.

CONCLUSIONS

This study reveals high prevalence of chloroquine and pyrimethamine-resistance markers as well as high codon substitution rate in the sulfadoxine-resistance gene. High genetic diversity of P. falciparum was observed. These observations suggest that the use of artemisinins is relevant in both Dangassa and Nioro-du-Sahel.

A better resolution for integrating methods for monitoring Plasmodium falciparum resistance to antimalarial drugs

Effective chemotherapy is the mainstay of malaria control. However, resistance of falciparum malaria to antimalarial drugs compromised the efforts to eliminate the disease and led to the resurgence of malaria epidemics. Three main approaches are used to monitor antimalarial drug efficacy and drug resistance; namely, in vivo trials, in vitro/ex vivo assays and molecular markers of drug resistance. Each approach has its implications of use as well as its advantages and drawbacks. Therefore, there is a need to use an integrated approach that would give the utmost effect to detect resistance as early as its emergence and to track it once spread. Such integration becomes increasingly needed in the era of artemisinin-based combination therapy as a forward action to deter resistance. The existence of regional and global networks for the standardization of methodology, provision of high quality reagents for the assessment of antimalarial drug resistance and dissemination of open-access data would help in approaching an integrated resistance surveillance system on a global scale.

Development of a TaqMan Allelic Discrimination assay for detection of single nucleotides polymorphisms associated with anti-malarial drug resistance

Background

Anti-malarial drug resistance poses a threat to current global efforts towards control and elimination of malaria. Several methods are used in monitoring anti-malarial drug resistance. Molecular markers such as single nucleotide polymorphism (SNP) for example are increasingly being used to identify genetic mutations related to anti-malarial drug resistance. Several methods are currently being used in analysis of SNP associated with anti-malarial drug resistance and although each one of these methods has unique strengths and shortcoming, there is still need to improve and/or develop new methods that will close the gap found in the current methods.

Methods

TaqMan Allelic Discrimination assays for detection of SNPs associated with anti-malarial drug resistance were designed for analysis on Applied Biosystems PCR platform. These assays were designed by submitting SNP sequences associated with anti-malarial drug resistance to Applied Biosystems website. Eleven SNPs associated with resistance to anti-malarial drugs were selected and tested. The performance of each SNP assay was tested by creating plasmid DNAs carrying codons of interests and analysing them for analysis. To test the sensitivity and specificity of each SNP assay, 12 clinical samples were sequenced at codons of interest and used in the analysis. Plasmid DNAs were used to establish the Limit of Detection (LoD) for each assay.

Results

Data from genetic profiles of the Plasmodium falciparum laboratory strains and sequence data from 12 clinical samples was used as the reference method with which the performance of the SNP assays were compared to. The sensitivity and specificity of each SNP assay was establish at 100%. LoD for each assay was established at 2 GE, equivalent to less than 1 parasite/μL. SNP assays performed well in detecting mixed infection and analysis of clinical samples.

Conclusion

TaqMan Allelic Discrimination assay provides a good alternative tool in detection of SNPs associated with anti-malarial drug.

Plasmodium falciparum resistance to anti-malarial drugs in Papua New Guinea: evaluation of a community-based approach for the molecular monitoring of resistance

Background

Molecular monitoring of parasite resistance has become an important complementary tool in establishing rational anti-malarial drug policies. Community surveys provide a representative sample of the parasite population and can be carried out more rapidly than accrual of samples from clinical cases, but it is not known whether the frequencies of genetic resistance markers in clinical cases differ from those in the overall population, or whether such community surveys can provide good predictions of treatment failure rates.

Methods

Between 2003 and 2005, in vivo drug efficacy of amodiaquine or chloroquine plus sulphadoxine-pyrimethamine was determined at three sites in Papua New Guinea. The genetic drug resistance profile (i.e., 33 single nucleotide polymorphisms in Plasmodium falciparum crt, mdr1, dhfr, dhps, and ATPase6) was concurrently assessed in 639 community samples collected in the catchment areas of the respective health facilities by using a DNA microarray-based method. Mutant allele and haplotype frequencies were determined and their relationship with treatment failure rates at each site in each year was investigated.

Results

PCR-corrected in vivo treatment failure rates were between 12% and 28% and varied by site and year with variable longitudinal trends. In the community samples, the frequencies of mutations in pfcrt and pfmdr1 were high and did not show significant changes over time. Mutant allele frequencies in pfdhfr were moderate and those in pfdhps were low. No mutations were detected in pfATPase6. There was much more variation between sites than temporal, within-site, variation in allele and haplotype frequencies. This variation did not correlate well with treatment failure rates. Allele and haplotype frequencies were very similar in clinical and community samples from the same site.

Conclusions

The relationship between parasite genetics and in vivo treatment failure rate is not straightforward. The frequencies of genetic anti-malarial resistance markers appear to be very similar in community and clinical samples, but cannot be used to make precise predictions of clinical outcome. Thus, indicators based on molecular data have to be considered with caution and interpreted in the local context, especially with regard to prior drug usage and level of pre-existing immunity. Testing community samples for molecular drug resistance markers is a complementary tool that should help decision-making for the best treatment options and appropriate potential alternatives.