Emergence Of Artemisinin Resistance Research Articles

Ensemble machine learning modeling for the prediction of artemisinin resistance in malaria.

Resistance in malaria is a growing concern affecting many areas of Sub-Saharan Africa and Southeast Asia. Since the emergence of artemisinin resistance in the late 2000s in Cambodia, research into the underlying mechanisms has been underway. The 2019 Malaria Challenge posited the task of developing computational models that address important problems in advancing the fight against malaria. The first goal was to accurately predict artemisinin drug resistance levels of Plasmodium falciparum isolates, as quantified by the IC 50. The second goal was to predict the parasite clearance rate of malaria parasite isolates based on in vitro transcriptional profiles. In this work, we develop machine learning models using novel methods for transforming isolate data and handling the tens of thousands of variables that result from these data transformation exercises. This is demonstrated by using massively parallel processing of the data vectorization for use in scalable machine learning. In addition, we show the utility of ensemble machine learning modeling for highly effective predictions of both goals of this challenge. This is demonstrated by the use of multiple machine learning algorithms combined with various scaling and normalization preprocessing steps. Then, using a voting ensemble, multiple models are combined to generate a final model prediction.

Ensemble machine learning modeling for the prediction of artemisinin resistance in malaria.

Resistance in malaria is a growing concern affecting many areas of Sub-Saharan Africa and Southeast Asia. Since the emergence of artemisinin resistance in the late 2000s in Cambodia, research into the underlying mechanisms has been underway. The 2019 Malaria Challenge posited the task of developing computational models that address important problems in advancing the fight against malaria. The first goal was to accurately predict artemisinin drug resistance levels of Plasmodium falciparum isolates, as quantified by the IC 50. The second goal was to predict the parasite clearance rate of malaria parasite isolates based on in vitro transcriptional profiles. In this work, we develop machine learning models using novel methods for transforming isolate data and handling the tens of thousands of variables that result from these data transformation exercises. This is demonstrated by using massively parallel processing of the data vectorization for use in scalable machine learning. In addition, we show the utility of ensemble machine learning modeling for highly effective predictions of both goals of this challenge. This is demonstrated by the use of multiple machine learning algorithms combined with various scaling and normalization preprocessing steps. Then, using a voting ensemble, multiple models are combined to generate a final model prediction.

Antimalarial Trioxolanes with Superior Drug-Like Properties and In Vivo Efficacy.

The emergence of artemisinin resistance, combined with certain suboptimal properties of ozonide agents arterolane and artefenomel, has necessitated the search for new drug candidates in the endoperoxide class. Our group has focused on trioxolane analogues with substitution patterns not previously explored. Here, we describe the enantioselective synthesis of analogues bearing a trans-3″ carbamate side chain and find these to be superior, both in vitro and in vivo, to the previously reported amides. We identified multiple analogues that surpass the oral efficacy of arterolane in the Plasmodium berghei model while exhibiting drug-like properties (logD, solubility, metabolic stability) similar or superior to next-generation clinical candidates like E209 and OZ609. While the preclinical assessment of new analogues is still underway, current data suggest the potential of this chemotype as a likely source of future drug candidates from the endoperoxide class.

Ensemble machine learning modeling for the prediction of artemisinin resistance in malaria

Resistance in malaria is a growing concern affecting many areas of Sub-Saharan Africa and Southeast Asia. Since the emergence of artemisinin resistance in the late 2000s in Cambodia, research into the underlying mechanisms has been underway. The 2019 Malaria Challenge posited the task of developing computational models that address important problems in advancing the fight against malaria. The first goal was to accurately predict artemisinin drug resistance levels of Plasmodium falciparum isolates, as quantified by the IC50. The second goal was to predict the parasite clearance rate of malaria parasite isolates based on in vitro transcriptional profiles. In this work, we develop machine learning models using novel methods for transforming isolate data and handling the tens of thousands of variables that result from these data transformation exercises. This is demonstrated by using massively parallel processing of the data vectorization for use in scalable machine learning. In addition, we show the utility of ensemble machine learning modeling for highly effective predictions of both goals of this challenge. This is demonstrated by the use of multiple machine learning algorithms combined with various scaling and normalization preprocessing steps. Then, using a voting ensemble, multiple models are combined to generate a final model prediction.

Plasmodium falciparum DDX55 is a nucleocytoplasmic protein and a 3'-5' direction-specific DNA helicase.

Malaria is one of the major causes of mortality as well as morbidity in many tropical and subtropical countries around the world. Although artemisinin combination therapies (ACTs) are contributing to substantial decline in the worldwide malaria burden, it is becoming vulnerable by the emergence of artemisinin resistance in Plasmodium falciparum leading to clinical failure of ACTs in Southeast Asia. Helicases play important role in nucleic acid metabolic processes and have been also identified as therapeutic drug target for different diseases. Previously, it has been reported that P. falciparum contains a group of DEAD-box family of helicases which are homologous to Has1 family of yeast. Here, we present the characterization of a member of Has1 family (PlasmoDB number PF3D7_1419100) named as PfDDX55. The biochemical characterization of PfDDX55C revealed that it contains both DNA- and RNA-dependent ATPase activity. PfDDX55C unwinds partially duplex DNA in 3' to 5' direction and utilizes mainly ATP or dATP for its activity. The immunofluorescence assay and q-RT PCR analysis show that PfDDX55 is a nucleocytoplasmic protein expressed in all the intraerythrocytic development of P. falciparum 3D7 strain with maximum expression level in trophozoite stage. The LC-MS/MS experiment results and STRING analysis show that PfDDX55 interacts with AAA-ATPase which has been shown to be involved in ribosomal biogenesis.

Ensemble machine learning modeling for the prediction of artemisinin resistance in malaria

Resistance in malaria is a growing concern affecting many areas of Sub-Saharan Africa and Southeast Asia. Since the emergence of artemisinin resistance in the late 2000s in Cambodia, research into the underlying mechanisms has been underway. The 2019 Malaria Challenge posited the task of developing computational models that address important problems in advancing the fight against malaria. The first goal was to accurately predict artemisinin drug resistance levels of Plasmodium falciparum isolates, as quantified by the IC 50. The second goal was to predict the parasite clearance rate of malaria parasite isolates based on in vitro transcriptional profiles. In this work, we develop machine learning models using novel methods for transforming isolate data and handling the tens of thousands of variables that result from these data transformation exercises. This is demonstrated by using massively parallel processing of the data vectorization for use in scalable machine learning. In addition, we show the utility of ensemble machine learning modeling for highly effective predictions of both goals of this challenge. This is demonstrated by the use of multiple machine learning algorithms combined with various scaling and normalization preprocessing steps. Then, using a voting ensemble, multiple models are combined to generate a final model prediction.

Ensemble machine learning modeling for the prediction of artemisinin resistance in malaria

Resistance in malaria is a growing concern affecting many areas of Sub-Saharan Africa and Southeast Asia. Since the emergence of artemisinin resistance in the late 2000s in Cambodia, research into the underlying mechanisms has been underway. The 2019 Malaria Challenge posited the task of developing computational models that address important problems in advancing the fight against malaria. The first goal was to accurately predict artemisinin drug resistance levels of Plasmodium falciparum isolates, as quantified by the IC50. The second goal was to predict the parasite clearance rate of malaria parasite isolates based on in vitro transcriptional profiles. In this work, we develop machine learning models using novel methods for transforming isolate data and handling the tens of thousands of variables that result from these data transformation exercises. This is demonstrated by using massively parallel processing of the data vectorization for use in scalable machine learning. In addition, we show the utility of ensemble machine learning modeling for highly effective predictions of both goals of this challenge. This is demonstrated by the use of multiple machine learning algorithms combined with various scaling and normalization preprocessing steps. Then, using a voting ensemble, multiple models are combined to generate a final model prediction.

Forest work and its implications for malaria elimination: a qualitative study

BackgroundOver the last 20 years, malaria incidence has decreased across the Greater Mekong Sub-region (GMS) and the emergence of artemisinin resistance has stimulated efforts to accelerate regional elimination. In the GMS, the malaria transmission is focused increasingly in forested zones. This article describes forest-going activities and examines forest workers’ attitudes to and experiences of malaria prevention and control in north-eastern Cambodia.MethodsIn Stung Treng Province, Cambodia, 19 in-depth interviews were conducted in villages with participants recently diagnosed with uncomplicated falciparum malaria who reported working in forests. Two focus group discussions with respondents’ forest-working peers were held. Interviews and focus groups were audio-recorded transcribed, and translated for thematic analysis.ResultsForest work is an essential source of income for respondents. Many combine it with farming, which influences the timing and duration of forest visits. Forest activities include logging and collecting other forest products, particularly malva nuts. Men log year-round, whereas gathering forest products is seasonal and can involve entire families. Forest workers sleep chiefly in unimpregnated hammock nets in make-shift encampments. Respondents are concerned about symptomatic malaria, but unfamiliar with the concept of asymptomatic infection. They view the forest as an area of potential malaria infection and seek to protect themselves from mosquito bites through wearing long-sleeved clothes, using repellents, and lighting fires. Forest workers express a willingness to self-test and self-administer anti-malarials.ConclusionsForest workers’ behaviour and perceptions of risk indicate that improvements are needed to current control measures. There is potential to: better target distribution of impregnated hammock nets; offer curative or presumptive treatment while in forests; and expand access to screening. Establishing the efficacy and feasibility of prophylaxis for forest workers in the GMS is a priority.

Development of Chemical Entities Endowed with Potent Fast-Killing Properties against Plasmodium falciparum Malaria Parasites.

One of the attractive properties of artemisinins is their extremely fast-killing capability, quickly relieving malaria symptoms. Nevertheless, the unique benefits of these medicines are now compromised by the prolonged parasite clearance times and the increasing frequency of treatment failures, attributed to the increased tolerance of Plasmodium falciparum to artemisinin. This emerging artemisinin resistance threatens to undermine the effectiveness of antimalarial combination therapies. Herein, we describe the medicinal chemistry efforts focused on a cGMP-dependent protein kinase (PKG) inhibitor scaffold, leading to the identification of novel chemical entities with very potent, similar to artemisinins, fast-killing potency against asexual blood stages that cause disease, and activity against gametocyte activation that is required for transmission. Furthermore, we confirm that selective PKG inhibitors have a slow speed of kill, while chemoproteomic analysis suggests for the first time serine/arginine protein kinase 2 (SRPK2) targeting as a novel strategy for developing antimalarial compounds with extremely fast-killing properties.

Pairwise growth competitions identify relative fitness relationships among artemisinin resistant Plasmodium falciparum field isolates

BackgroundCompetitive outcomes between co-infecting malaria parasite lines can reveal fitness disparities in blood stage growth. Blood stage fitness costs often accompany the evolution of drug resistance, with the expectation that relatively fitter parasites will be more likely to spread in populations. With the recent emergence of artemisinin resistance, it is important to understand the relative competitive fitness of the metabolically active asexual blood stage parasites. Genetically distinct drug resistant parasite clones with independently evolved sets of mutations are likely to vary in asexual proliferation rate, contributing to their chance of transmission to the mosquito vector.MethodsAn optimized in vitro 96-well plate-based protocol was used to quantitatively measure-head-to-head competitive fitness during blood stage development between seven genetically distinct field isolates from a hotspot of emerging artemisinin resistance and the laboratory strain, NF54. These field isolates were isolated from patients in Southeast Asia carrying different alleles of kelch13 and included both artemisinin-sensitive and artemisinin-resistant isolates. Fluorescent labeled microsatellite markers were used to track the relative densities of each parasite throughout the co-growth period of 14–60 days. All-on-all competitions were conducted for the panel of eight parasite lines (28 pairwise competitions) to determine their quantitative competitive fitness relationships.ResultsTwenty-eight pairwise competitive growth outcomes allowed for an unambiguous ranking among a set of seven genetically distinct parasite lines isolated from patients in Southeast Asia displaying a range of both kelch13 alleles and clinical clearance times and a laboratory strain, NF54. This comprehensive series of assays established the growth relationships among the eight parasite lines. Interestingly, a clinically artemisinin resistant parasite line that carries the wild-type form of kelch13 outcompeted all other parasites in this study. Furthermore, a kelch13 mutant line (E252Q) was competitively more fit without drug than lines with other resistance-associated kelch13 alleles, including the C580Y allele that has expanded to high frequencies under drug pressure in Southeast Asian resistant populations.ConclusionsThis optimized competitive growth assay can be employed for assessment of relative growth as an index of fitness during the asexual blood stage growth between natural lines carrying different genetic variants associated with artemisinin resistance. Improved understanding of the fitness costs of different parasites proliferating in human blood and the role different resistance mutations play in the context of specific genetic backgrounds will contribute to an understanding of the potential for specific mutations to spread in populations, with the potential to inform targeted strategies for malaria therapy.

Dispensing practices for anti-malarials in the La Nkwantanang-Madina municipality, Greater Accra, Ghana: a cross-sectional study

BackgroundDespite recent strides made towards reducing the emergence of artemisinin resistance, inappropriate dispensing practices for anti-malarials in both private and public sectors affect treatment outcomes negatively. In Ghana, private retail pharmacies are the most accessible health facilities for managing diseases of common occurrence. However, there is growing concern about the number of patients harmed by dispensing errors in the management of malaria in retail pharmacies. Although considerable work has been done in this area, several questions regarding dispensing practices remain unanswered. This study, therefore, sought to investigate the predictors of appropriate dispensing practices for anti-malarials in community pharmacies in the La Nkwantanang-Madina municipality of Greater Accra, Ghana.MethodsA cross-sectional analytic study was conducted in sixty-one randomly selected community pharmacies in the La Nkwantanang-Madina. Data from 230 clients and 106 dispensers were analysed. It was checked for internal consistency and completeness then entered and analysed using STATA I/C version 14.0. Frequencies, Chi square tests, and logistic regression analyses were conducted, accounting for clustering.Results and discussionOf the 106 dispensers interviewed, 71.4% were medicine counter assistants. The mean age of dispensers was 30.4 years (SD 8.8). Over 88.0% of clients were advised to complete the full course of their anti-malarials. However, the 8-h loading dose principle for artemether-lumefantrine was not explained to 88.3% of the clients. More than half of the clients (52.2%) were given appropriate dispensing information on anti-malarial use. Most clients (66.1%), were dispensed anti-malarials without malaria tests. Dispensers with more than a 10-years experience were less likely to dispense artemisinin-based combinations appropriately relative to dispensers with less than 2 years experience (AOR = 0.04, 95% CI 0.002–0.802 p-value = 0.036) while pharmacy interns were about 19 times more likely (AOR = 18.5, 95% CI 1.40–245.6 p-value = 0.03) to dispense artemisinin-based combinations appropriately compared to pharmacists.ConclusionDispensing practices for anti-malarials is unsatisfactory. There is a need to enforce existing legislation with educational programmes directed towards dispensers especially those with more than 10 years experience. Specific adherence to the World Health Organization Test, Treat and Track initiative should be encouraged to ensure effective use of anti-malarials.

Artemisinin-Based Antimalarial Drug Therapy: Molecular Pharmacology and Evolving Resistance.

The molecular pharmacology of artemisinin (ART)-based antimalarial drugs is incompletely understood. Clinically, these drugs are used in combination with longer lasting partner drugs in several different artemisinin combination therapies (ACTs). ACTs are currently the standard of care against Plasmodium falciparum malaria across much of the world. A harbinger of emerging artemisinin resistance (ARTR), known as the delayed clearance phenotype (DCP), has been well documented in South East Asia (SEA) and is beginning to affect the efficacy of some ACTs. Though several genetic mutations have been associated with ARTR/DCP, a molecular mechanism remains elusive. This paper summarizes our current understanding of ART molecular pharmacology and hypotheses for ARTR/DCP.

Dihydroartemisinin-Ferriprotoporphyrin IX Adduct Abundance in Plasmodium falciparum Malarial Parasites and the Relationship to Emerging Artemisinin Resistance.

Previously (Heller, L. E., and Roepe, P. D. Quantification of Free Ferriprotoporphyrin IX Heme and Hemozoin for Artemisinin Sensitive versus Delayed Clearance Phenotype Plasmodium falciparum Malarial Parasites. Biochemistry, DOI: 10.1021/acs.biochem.8b00959, preceding paper in this issue), we quantified free ferriprotoporphyrin IX (FPIX) heme abundance for control versus delayed clearance phenotype (DCP) intraerythrocytic Plasmodium falciparum malarial parasites. Because artemisinin drugs are activated by free FPIX, these data predict that the abundance of long-hypothesized toxic artemisinin drug-FPIX covalent adducts might differ for control versus DCP parasites. If so, this would have important repercussions for understanding the mechanism of the DCP, also known as emerging artemisinin resistance. To test these predictions, we studied in vitro formation of FPIX-dihydroartemisinin (DHA) adducts and then for the first time quantified the abundance of FPIX-DHA adducts formed within live P. falciparum versus the stage of intraerythrocytic development. Using matched isogenic parasite strains, we quantified the adduct for DCP versus control parasite strains and found that mutant PfK13 mediates lower adduct abundance for DCP parasites. The results suggest improved models for the molecular pharmacology of artemisinin-based antimalarial drugs and the molecular mechanism of the DCP.

Overexpression of plasmepsin II and plasmepsin III does not directly cause reduction in Plasmodium falciparum sensitivity to artesunate, chloroquine and piperaquine

Artemisinin derivatives and their partner drugs in artemisinin combination therapies (ACTs) have played a pivotal role in global malaria mortality reduction during the last two decades. The loss of artemisinin efficacy due to evolving drug-resistant parasites could become a serious global health threat. Dihydroartemisinin-piperaquine is a well tolerated and generally highly effective ACT. The implementation of a partner drug in ACTs is critical in the control of emerging artemisinin resistance. Even though artemisinin is highly effective in parasite clearance, it is labile in the human body. A partner drug is necessary for killing the remaining parasites when the pulses of artemisinin have ceased. A population of Plasmodium falciparum parasites in Cambodia and adjacent countries has become resistant to piperaquine. Increased copy number of the genes encoding the haemoglobinases Plasmepsin II and Plasmepsin III has been linked with piperaquine resistance by genome-wide association studies and in clinical trials, leading to the use of increased plasmepsin II/plasmepsin III copy number as a molecular marker for piperaquine resistance. Here we demonstrate that overexpression of plasmepsin II and plasmepsin III in the 3D7 genetic background failed to change the susceptibility of P. falciparum to artemisinin, chloroquine and piperaquine by both a standard dose-response analysis and a piperaquine survival assay. Whilst plasmepsin copy number polymorphism is currently implemented as a molecular surveillance resistance marker, further studies to discover the molecular basis of piperaquine resistance and potential epistatic interactions are needed.

K13-propeller gene polymorphisms in Plasmodium falciparum parasite population: a systematic review protocol of burden and associated factors

BackgroundMalaria control and prevention efforts continue to rely heavily on the use of medicines especially artemisinin agents. However, currently, the emergence of artemisinin resistance threatens this effort globally. The K13-gene polymorphisms associated with artemisinin resistance have been detected in Southeast Asia. In countries outside Southeast Asia, artemisinin resistance has not yet been confirmed.Methods/designThe articles will be obtained from the search of MEDLINE via PubMed, Scopus, EMBASE, and LILACS/VHL databases. Mesh terms will be used in the article search. Boolean operators (“AND”, “OR”) will be used in the article search. Article search will be done independently by two librarians (RS and AK). The articles will be screened for inclusion using set criteria and following the PRISMA guidelines. Data extraction will be done by two independent reviewers (NL and BB), Kappa statistic will be calculated, and any discrepancies resolved by discussion. Heterogeneity in the articles will be established using I2 statistic.DiscussionThis review will focus on establishing the K13-gene polymorphisms among Plasmodium falciparum parasites reported from previous studies in malaria-affected countries. Artemisinin resistance has not been widely reported among parasites in Africa and other malaria-endemic countries outside Southeast Asia. However, several studies on artemisinin resistance have reported different K13-gene polymorphisms from the validated mutations found in Southeast Asia. This study will collate evidence from previous studies on the commonly reported K13 -gene polymorphisms among P. falciparum parasites in malaria-affected countries.Systematic review registrationPROSPERO CRD 42018084624

Efficacy of artemether-lumefantrine for the treatment of uncomplicated Plasmodium falciparum malaria in Nepal

BackgroundThe national treatment guidelines of Nepal have adopted Artemisinin Combination Therapies (ACTs) for the treatment of uncomplicated falciparum malaria since 2004. Emergence of Artemisinin resistance in the Greater Mekong Sub-region (GMS) and beyond may become a threat for Nepal as well. The main objective of this study was to assess the therapeutic efficacy of antimalarial drug artemether-lumefantrine in uncomplicated P. falciparum infected patients at health centers/hospitals treated over the period of 2 years (2013–2014).MethodsGiemsa stained thick and thin smears, prepared from uncomplicated falciparum malaria patients who visited the selected sentinel sites in Nepal during 2013 to 2014 and met the inclusion criteria that included parasitemia (1000–10,000 /μL of blood), were evaluated until 28 days after ACTs treatment, following a World Health Organization (WHO) therapeutic efficacy protocol. Based on the re-occurrence of fever and resurge in parasitemia, the study patients were classified as resistant or susceptible. Blood specimens on filter papers were further analyzed by Polymerase Chain Reaction (PCR), specifically for the K13 propeller gene mutation (a recently identified molecular marker for ACT resistance).ResultsA total of 56,013 suspected malaria cases were screened for this study. Of which, 120 (0.21%) were infected with falciparum malaria. Out of 120, 28 cases of P. falciparum (28/120; 23.33%) were enrolled in the study, of which 24 cases completed the post-treatment follow up for 28 days. Only one case out of 24 (4%) was identified as a late treatment failure (LTF). K13 mutation, a proxy indicator for ACT resistance in parasites, was not detected on the day 1, which indicates resistance had not yet reached the molecular level.ConclusionOnly one case of late treatment failure was identified in this study. ACT combination using artemether-lumefantrine was still effective for the treatment of uncomplicated falciparum malaria in Nepal. A close monitoring and supervision for ACT resistance is essential for future malaria treatment in Nepal.

Effectiveness and safety of 3 and 5\xa0day courses of artemether\u2013lumefantrine for the treatment of uncomplicated falciparum malaria in an area of emerging artemisinin resistance in Myanmar

BackgroundArtemisinin resistance in Plasmodium falciparum has emerged and spread in Southeast Asia. In areas where resistance is established longer courses of artemisinin-based combination therapy have improved cure rates.MethodsThe standard 3-day course of artemether–lumefantrine (AL) was compared with an extended 5-day regimen for the treatment of uncomplicated falciparum malaria in Kayin state in South-East Myanmar, an area of emerging artemisinin resistance. Late parasite clearance dynamics were described by microscopy and quantitative ultra-sensitive PCR. Patients were followed up for 42 days.ResultsOf 154 patients recruited (105 adults and 49 children < 14 years) 78 were randomized to 3 days and 76 to 5 days AL. Mutations in the P. falciparum kelch13 propeller gene (k13) were found in 46% (70/152) of infections, with F446I the most prevalent propeller mutation (29%; 20/70). Both regimens were well-tolerated. Parasite clearance profiles were biphasic with a slower submicroscopic phase which was similar in k13 wild-type and mutant infections. The cure rates were 100% (70/70) and 97% (68/70) in the 3- and 5-day arms respectively. Genotyping of the two recurrences was unsuccessful.ConclusionDespite a high prevalence of k13 mutations, the current first-line treatment, AL, was still highly effective in this area of South-East Myanmar. The extended 5 day regimen was very well tolerated, and would be an option to prolong the useful therapeutic life of AL.Trial registration NCT02020330. Registered 24 December 2013, https://clinicaltrials.gov/NCT02020330

How to combat emerging artemisinin resistance: Lessons from "The Three Little Pigs".

It is rare to come across an Aesop’s fable in respectable journals. It might catch scientists outside the malaria field by surprise to learn that the famous story of “The Boy Who Cried Wolf” has been repeatedly compared to the threat from artemisinin-resistant malaria parasites, including the two latest reports on the rise of a specific haplotype in Cambodia and Thailand, sensationally dubbed “Super Malaria” by the media [1, 2]. The comparison to a children’s tale should not negate the fact that malaria drug resistance is one of the most pressing threats to the global public health community. Here, the findings leading to this contentious discourse will be delineated in order to provide a perspective. Possible solutions will be presented to stimulate further research and discussion to solve one of the greatest public health challenges of our lifetime.

Declining Transmission and Immunity to Malaria and Emerging Artemisinin Resistance in Thailand: A Longitudinal Study.

Reductions in malaria transmission decrease naturally acquired immunity, which may influence the emergence of Plasmodium falciparum artemisinin-resistant phenotypes and genotypes over time. Antibodies specific for P. falciparum antigens were determined in uncomplicated hyperparasitemic malaria patients over a 10-year period of declining malaria transmission and emerging artemisinin resistance in northwestern Thailand. We investigated the association between antibody levels and both parasite clearance time (PCt½) and artemisinin resistance-associated kelch13 genotypes over time. Immunity to P. falciparum declined prior to 2004, preceding the emergence of artemisinin resistance-associated genotypes and phenotypes (maximum mean change in antibody level per year: anti-MSP142 = -0.17; 95% confidence interval [CI] = -.31 to -.04; P = .01). In this period of declining immunity, and in the absence of kelch13 mutations, PCt½ increased. Between 2007 and 2011, levels of antibodies fluctuated, and higher antibody levels were associated with faster PCt½ (maximum yearly change in PCt½, in hours: EBA140rII = -0.39; 95% CI = -.61 to -.17; P < .001). Understanding the impact of changing transmission and immunity on the emergence of artemisinin resistance is important particularly as increased malaria control and elimination activities may enhance immunological conditions for the expansion of artemisinin-resistant P. falciparum.

Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance

BackgroundArtemisinin-based combination therapies are the first line of treatment for Plasmodium falciparum infections worldwide, but artemisinin resistance has risen rapidly in Southeast Asia over the past decade. Mutations in the kelch13 gene have been implicated in this resistance. We used longitudinal genomic surveillance to detect signals in kelch13 and other loci that contribute to artemisinin or partner drug resistance. We retrospectively sequenced the genomes of 194 P. falciparum isolates from five sites in Northwest Thailand, over the period of a rapid increase in the emergence of artemisinin resistance (2001–2014).ResultsWe evaluate statistical metrics for temporal change in the frequency of individual SNPs, assuming that SNPs associated with resistance increase in frequency over this period. After Kelch13-C580Y, the strongest temporal change is seen at a SNP in phosphatidylinositol 4-kinase, which is involved in a pathway recently implicated in artemisinin resistance. Furthermore, other loci exhibit strong temporal signatures which warrant further investigation for involvement in artemisinin resistance evolution. Through genome-wide association analysis we identify a variant in a kelch domain-containing gene on chromosome 10 that may epistatically modulate artemisinin resistance.ConclusionsThis analysis demonstrates the potential of a longitudinal genomic surveillance approach to detect resistance-associated gene loci to improve our mechanistic understanding of how resistance develops. Evidence for additional genomic regions outside of the kelch13 locus associated with artemisinin-resistant parasites may yield new molecular markers for resistance surveillance, which may be useful in efforts to reduce the emergence or spread of artemisinin resistance in African parasite populations.