Immune selection suppresses the emergence of drug resistance in malaria parasites but facilitates its spread

Role of seasonal importation and genetic drift on selection for drug-resistant genotypes of Plasmodium falciparum in high-transmission settings

Historically Plasmodium falciparum has followed a pattern of drug resistance first appearing in low-transmission settings before spreading to high-transmission settings. Several features of low-transmission regions are hypothesized as explanations: higher chance of symptoms and treatment seeking, better treatment access, less within-host competition among clones and lower rates of recombination. Here, we test whether importation of drug-resistant parasites is more likely to lead to successful emergence and establishment in low-transmission or high-transmission periods of the same epidemiological setting, using a spatial, individual-based stochastic model of malaria and drug-resistance evolution calibrated for Burkina Faso. Upon controlling for the timing of importation of drug-resistant genotypes and examination of key model variables, we found that drug-resistant genotypes imported during the low-transmission season were (i) more susceptible to stochastic extinction due to the action of genetic drift, and (ii) more likely to lead to establishment of drug resistance when parasites are able to survive early stochastic loss due to drift. This implies that rare importation events are more likely to lead to establishment if they occur during a high-transmission season, but that constant importation (e.g. neighbouring countries with high levels of resistance) may produce a greater risk during low-transmission periods.

Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of antimalarial drug resistance

The establishment and spread of antimalarial drug resistance vary drastically across different biogeographic regions. Though most infections occur in sub-Saharan Africa, resistant strains often emerge in low-transmission regions. Existing models on resistance evolution lack consensus on the relationship between transmission intensity and drug resistance, possibly due to overlooking the feedback between antigenic diversity, host immunity, and selection for resistance. To address this, we developed a novel compartmental model that tracks sensitive and resistant parasite strains, as well as the host dynamics of generalized and antigen-specific immunity. Our results show a negative correlation between parasite prevalence and resistance frequency, regardless of resistance cost or efficacy. Validation using chloroquine-resistant marker data supports this trend. Post discontinuation of drugs, resistance remains high in low-diversity, low-transmission regions, while it steadily decreases in high-diversity, high-transmission regions. Our study underscores the critical role of malaria strain diversity in the biogeographic patterns of resistance evolution.

Assessing emergence risk of double-resistant and triple-resistant genotypes of Plasmodium falciparum

Delaying and slowing antimalarial drug resistance evolution is a priority for malaria-endemic countries. Until novel therapies become available, the mainstay of antimalarial treatment will continue to be artemisinin-based combination therapy (ACT). Deployment of different ACTs can be optimized to minimize evolutionary pressure for drug resistance by deploying them as a set of co-equal multiple first-line therapies (MFT) rather than rotating therapies in and out of use. Here, we consider one potential detriment of MFT policies, namely, that the simultaneous deployment of multiple ACTs could drive the evolution of different resistance alleles concurrently and that these resistance alleles could then be brought together by recombination into double-resistant or triple-resistant parasites. Using an individual-based model, we compare MFT and cycling policies in malaria transmission settings ranging from 0.1% to 50% prevalence. We define a total risk measure for multi-drug resistance (MDR) by summing the area under the genotype-frequency curves (AUC) of double- and triple-resistant genotypes. When prevalence ≥ 1%, total MDR risk ranges from statistically similar to 80% lower under MFT policies than under cycling policies, irrespective of whether resistance is imported or emerges de novo. At 0.1% prevalence, there is little statistical difference in MDR risk between MFT and cycling.

Evolutionary modelling indicates that mosquito metabolism shapes the life-history strategies of Plasmodium parasites

Within-host survival and between-host transmission are key life-history traits of single-celled malaria parasites. Understanding the evolutionary forces that shape these traits is crucial to predict malaria epidemiology, drug resistance, and virulence. However, very little is known about how Plasmodium parasites adapt to their mosquito vectors. Here, we examine the evolution of the time Plasmodium parasites require to develop within the vector (extrinsic incubation period) with an individual-based model of malaria transmission that includes mosquito metabolism. Specifically, we model the metabolic cascade of resource allocation induced by blood-feeding, as well as the influence of multiple blood meals on parasite development. Our model predicts that successful vector-to-human transmission events are rare, and are caused by long-lived mosquitoes. Importantly, our results show that the life-history strategies of malaria parasites depend on the mosquito's metabolic status. In our model, additional resources provided by multiple blood meals lead to selection for parasites with slow or intermediate developmental time. These results challenge the current assumption that evolution favors fast developing parasites to maximize their chances to complete their within-mosquito life cycle. We propose that the long sporogonic cycle observed for Plasmodium is not a constraint but rather an adaptation to increase transmission potential.

Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of anti-malarial drug resistance

The establishment and spread of anti-malarial drug resistance vary drastically across different biogeographic regions. Though most infections occur in Sub-Saharan Africa, resistant strains often emerge in low-transmission regions. Existing models on resistance evolution lack consensus on the relationship between transmission intensity and drug resistance, possibly due to overlooking the feedback between antigenic diversity, host immunity, and selection for resistance. To address this, we developed a novel compartmental model that tracks sensitive and resistant parasite strains, as well as the host dynamics of generalized and antigen-specific immunity. Our results show a negative correlation between parasite prevalence and resistance frequency, regardless of resistance cost or efficacy. Validation using chloroquine-resistant marker data supports this trend. Post discontinuation of drugs, resistance remains high in low-diversity, low-transmission regions, while it steadily decreases in high-diversity, high-transmission regions. Our study underscores the critical role of malaria strain diversity in the biogeographic patterns of resistance evolution.

Examining the Early Distribution of the Artemisinin-Resistant Plasmodium falciparum kelch13 R561H Mutation in Areas of Higher Transmission in Rwanda

Background

Artemisinin resistance mutations in Plasmodium falciparum kelch13 (Pfk13) have begun to emerge in Africa, with Pfk13-R561H being the first reported in Rwanda in 2014, but limited sampling left questions about its early distribution and origin.

Methods

We genotyped P. falciparum positive dried blood spot (DBS) samples from a nationally representative 2014-2015 Rwanda Demographic Health Surveys (DHS) HIV study. DBS were subsampled from DHS sampling clusters with >15% P. falciparum prevalence, as determined by rapid testing or microscopy done during the DHS study (n clusters = 67, n samples = 1873).

Results

We detected 476 parasitemias among 1873 residual blood spots from a 2014-2015 Rwanda Demographic Health Survey. We sequenced 351 samples: 341/351 were wild-type (97.03% weighted), and 4 samples (1.34% weighted) harbored R561H that were significantly spatially clustered. Other nonsynonymous mutations found were V555A (3), C532W (1), and G533A (1).

Conclusions

Our study better defines the early distribution of R561H in Rwanda. Previous studies only observed the mutation in Masaka as of 2014, but our study indicates its presence in higher-transmission regions in the southeast of the country at that time.

Artemisinin resistance and malaria elimination: Where are we now?

The emergence of artemisinin resistance is a major obstacle to the global malaria eradication/elimination programs. Artemisinin is a very fast-acting antimalarial drug and is the most important drug in the treatment of severe and uncomplicated malaria. For the treatment of acute uncomplicated falciparum malaria, artemisinin derivatives are combined with long half-life partner drugs and widely used as artemisinin-based combination therapies (ACTs). Some ACTs have shown decreased efficacy in the Southeast Asian region. Fortunately, artemisinin has an excellent safety profile and resistant infections can still be treated successfully by modifying the ACT. This review describes the pharmacological properties of ACTs, mechanisms of artemisinin resistance and the potential changes needed in the treatment regimens to overcome resistance. The suggested ACT modifications are extension of the duration of the ACT course, alternating use of different ACT regimens, and addition of another antimalarial drug to the standard ACTs (Triple-ACT). Furthermore, a malaria vaccine (e.g., RTS,S vaccine) could be added to mass drug administration (MDA) campaigns to enhance the treatment efficacy and to prevent further artemisinin resistance development. This review concludes that artemisinin remains the most important antimalarial drug, despite the development of drug-resistant falciparum malaria.

Genomic epidemiological models describe pathogen evolution across fitness valleys

Genomics is fundamentally changing epidemiological research. However, systematically exploring hypotheses in pathogen evolution requires new modeling tools. Models intertwining pathogen epidemiology and genomic evolution can help understand processes such as the emergence of novel pathogen genotypes with higher transmissibility or resistance to treatment. In this work, we present Opqua, a flexible simulation framework that explicitly links epidemiology to sequence evolution and selection. We use Opqua to study determinants of evolution across fitness valleys. We confirm that competition can limit evolution in high-transmission environments and find that low transmission, host mobility, and complex pathogen life cycles facilitate reaching new adaptive peaks through population bottlenecks and decoupling of selective pressures. The results show the potential of genomic epidemiological modeling as a tool in infectious disease research.

The influence of biological, epidemiological, and treatment factors on the establishment and spread of drug-resistant Plasmodium falciparum

The effectiveness of artemisinin-based combination therapies (ACTs) to treat Plasmodium falciparum malaria is threatened by resistance. The complex interplay between sources of selective pressure-treatment properties, biological factors, transmission intensity, and access to treatment-obscures understanding how, when, and why resistance establishes and spreads across different locations. We developed a disease modelling approach with emulator-based global sensitivity analysis to systematically quantify which of these factors drive establishment and spread of drug resistance. Drug resistance was more likely to evolve in low transmission settings due to the lower levels of (i) immunity and (ii) within-host competition between genotypes. Spread of parasites resistant to artemisinin partner drugs depended on the period of low drug concentration (known as the selection window). Spread of partial artemisinin resistance was slowed with prolonged parasite exposure to artemisinin derivatives and accelerated when the parasite was also resistant to the partner drug. Thus, to slow the spread of partial artemisinin resistance, molecular surveillance should be supported to detect resistance to partner drugs and to change ACTs accordingly. Furthermore, implementing more sustainable artemisinin-based therapies will require extending parasite exposure to artemisinin derivatives, and mitigating the selection windows of partner drugs, which could be achieved by including an additional long-acting drug.

Xeno-monitoring of molecular drivers of artemisinin and partner drug resistance in P. falciparum populations in malaria vectors across Cameroon

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High Plasmodium infection rate in the major Anopheles vectors across Cameroon.

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Emerging signal of the R575I polymorphism in the k13 propeller domain backbone.

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Dominance of the N⁸⁶F¹⁸⁴mdr1 variants in natural P. falciparum populations.

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Low k13 and mdr1 genetic diversity in P. falciparum-infected mosquitoes.

Background

Monitoring of drug resistance in Plasmodium populations is crucial for malaria control. This has primarily been performed in humans and rarely in mosquitoes where parasites genetic recombination occurs. Here, we characterized the Plasmodium spp populations in wild Anopheles vectors by analyzing the genetic diversity of the P. falciparum kelch13 and mdr1 gene fragments implicated in artemisinin and partner drug resistance across Cameroon in three major malaria vectors.

Methods

Anopheles mosquitoes were collected across nine localities in Cameroon and dissected into the head/thorax (H/T) and abdomen (Abd) after species identification. A TaqMan assay was performed to detect Plasmodium infection. Fragments of the Kelch 13 and mdr1 genes were amplified in P. falciparum positive samples and directly sequenced to assess their drug resistance polymorphisms and genetic diversity profile.

Results

The study revealed a high Plasmodium infection rate in the major Anopheles vectors across Cameroon. Notably, An. funestus vector recorded the highest sporozoite (8.0%) and oocyst (14.4%) infection rates. A high P. falciparum sporozoite rate (80.08%) alongside epidemiological signatures of significant P. malariae (15.9%) circulation were recorded in these vectors. Low genetic diversity with six (A578S, R575I, G450R, L663L, G453D, N458D) and eight (H53H, V62L, V77E, N86Y, G102G, L132I, H143H, Y184F) point mutations were observed in the k13 and mdr1 backbones respectively. Remarkably, the R575I (4.4%) k13 and Y184F (64.2%) mdr1 mutations were the predominant variants in the P. falciparum populations.

Conclusion

The emerging signal of the R575I polymorphism in the Pfk13 propeller backbone entails the regular surveillance of molecular markers to inform evidence-based policy decisions. Moreover, the high frequency of the ⁸⁶N¹⁸⁴F allele highlights concerns on the plausible decline in efficacy of artemisinin-combination therapies (ACTs); further implying that parasite genotyping from mosquitoes can provide a more relevant scale for quantifying resistance epidemiology in the field.

Time to scale up molecular surveillance for anti-malarial drug resistance in sub-saharan Africa

Artemisinin resistance has emerged and spread in the Greater Mekong Sub-region (GMS), followed by artemisinin-based combination therapy failure, due to both artemisinin and partner drug resistance. More worrying, artemisinin resistance has been recently reported and confirmed in Rwanda. Therefore, there is an urgent need to strengthen surveillance systems beyond the GMS to track the emergence or spread of artemisinin and partner drug resistance in other endemic settings. Currently, anti-malarial drug efficacy is monitored primarily through therapeutic efficacy studies (TES). Even though essential for anti-malarial drug policy change, these studies are difficult to conduct, expensive, and may not detect the early emergence of resistance. Additionally, results from TES may take years to be available to the stakeholders, jeopardizing their usefulness. Molecular markers are additional and useful tools to monitor anti-malarial drug resistance, as samples collected on dried blood spots are sufficient to monitor known and validated molecular markers of resistance, and could help detecting and monitoring the early emergence of resistance. However, molecular markers are not monitored systematically by national malaria control programmes, and are often assessed in research studies, but not in routine surveillance. The implementation of molecular markers as a routine tool for anti-malarial drug resistance surveillance could greatly improve surveillance of anti-malarial drug efficacy, making it possible to detect resistance before it translates to treatment failures. When possible, ex vivo assays should be included as their data could be useful complementary, especially when no molecular markers are validated.