Age-dependent antibody profiles to plasmodium antigens are differentially associated with two artemisinin combination therapy outcomes in high transmission setting

The impact of pre-existing immunity on the efficacy of artemisinin combination therapy is largely unknown. We performed in-depth profiling of serological responses in a therapeutic efficacy study [comparing artesunate-mefloquine (ASMQ) and artemether-lumefantrine (AL)] using a proteomic microarray. Responses to over 200 Plasmodium antigens were significantly associated with ASMQ treatment outcome but not AL. We used machine learning to develop predictive models of treatment outcome based on the immunoprofile data. The models predict treatment outcome for ASMQ with high (72–85%) accuracy, but could not predict treatment outcome for AL. This divergent treatment outcome suggests that humoral immunity may synergize with the longer mefloquine half-life to provide a prophylactic effect at 28–42 days post-treatment, which was further supported by simulated pharmacokinetic profiling. Our computational approach and modeling revealed the synergistic effect of pre-existing immunity in patients with drug combination that has an extended efficacy on providing long term treatment efficacy of ASMQ.

Selective sweeps and genetic lineages of Plasmodium falciparum multi-drug resistance (pfmdr1) gene in Kenya

BACKGROUND

There are concerns that resistance to artemisinin-based combination therapy might emerge in Kenya and sub-Saharan Africa (SSA) in the same pattern as was with chloroquine and sulfadoxine-pyrimethamine. Single nucleotide polymorphisms (SNPs) in critical alleles of pfmdr1 gene have been associated with resistance to artemisinin and its partner drugs. Microsatellite analysis of loci flanking genes associated with anti-malarial drug resistance has been used in defining the geographic origins, dissemination of resistant parasites and identifying regions in the genome that have been under selection.

METHODS

This study set out to investigate evidence of selective sweep and genetic lineages in pfmdr1 genotypes associated with the use of artemether-lumefantrine (AL), as the first-line treatment in Kenya. Parasites (n = 252) from different regions in Kenya were assayed for SNPs at codons 86, 184 and 1246 and typed for 7 neutral microsatellites and 13 microsatellites loci flanking (± 99 kb) pfmdr1 in Plasmodium falciparum infections.

RESULTS

The data showed differential site and region specific prevalence of SNPs associated with drug resistance in the pfmdr1 gene. The prevalence of pfmdr1 N86, 184F, and D1246 in western Kenya (Kisumu, Kericho and Kisii) compared to the coast of Kenya (Malindi) was 92.9% vs. 66.7%, 53.5% vs. to 24.2% and 96% vs. to 87.9%, respectively. The NFD haplotype which is consistent with AL selection was at 51% in western Kenya compared to 25% in coastal Kenya.

CONCLUSION

Selection pressures were observed to be different in different regions of Kenya, especially the western region compared to the coastal region. The data showed independent genetic lineages for all the pfmdr1 alleles. The evidence of soft sweeps in pfmdr1 observed varied in direction from one region to another. This is challenging for malaria control programs in SSA which clearly indicate effective malaria control policies should be based on the region and not at a country wide level.

Polymorphisms in the K13 Gene in Plasmodium falciparum from Different Malaria Transmission Areas of Kenya

The development of artemisinin (ART)-resistant parasites in Southeast Asia (SEA) threatens malaria control globally. Mutations in the Kelch 13 (K13)-propeller domain have been useful in identifying ART resistance in SEA. ART combination therapy (ACT) remains highly efficacious in the treatment of uncomplicated malaria in Sub-Saharan Africa (SSA). However, it is crucial that the efficacy of ACT is closely monitored. Toward this effort, this study profiled the prevalence of K13 nonsynonymous mutations in different malaria ecological zones of Kenya and in different time periods, before (pre) and after (post) the introduction of ACT as the first-line treatment of malaria. Nineteen nonsynonymous mutations were present in the pre-ACT samples (N = 64) compared with 22 in the post-ACT samples (N = 251). Eight of these mutations were present in both pre- and post-ACT parasites. Interestingly, seven of the shared single-nucleotide polymorphisms were at higher frequencies in the pre-ACT than the post-ACT parasites. The A578S mutation reported in SSA and the V568G mutation reported in SEA were found in both pre- and post-ACT parasites, with their frequencies declining post-ACT. D584Y and R539K mutations were found only in post-ACT parasites; changes in these codons have also been reported in SEA with different amino acids. The N585K mutation described for the first time in this study was present only in post-ACT parasites, and it was the most prevalent mutation at a frequency of 5.2%. This study showed the type, prevalence, and frequency of K13 mutations that varied based on the malaria ecological zones and also between the pre- and post-ACT time periods.

Genetic variability and population structure of Plasmodium falciparum parasite populations from different malaria ecological regions of Kenya

Transmission intensity, movement of human and vector hosts, biogeographical features, and malaria control measures are some of the important factors that determine Plasmodium falciparum parasite genetic variability and population structure. Kenya has different malaria ecologies which might require different disease intervention methods. Refined parasite population genetic studies are critical for informing malaria control and elimination strategies. This study describes the genetic diversity and population structure of P. falciparum parasites from the different malaria ecological zones in Kenya. Twelve multi-locus microsatellite (MS) loci previously described were genotyped in 225 P. falciparum isolates collected between 2012 and 2013 from five sites; three in lowland endemic regions (Kisumu, Kombewa, and Malindi) and two in highland, epidemic regions (Kisii and Kericho). Parasites from the lowland endemic and highland epidemic regions of western Kenya had high genetic diversity compared to coastal lowland endemic region of Kenya [Malindi]. The Kenyan parasites had a mean genetic differentiation index (FST) of 0.072 (p=0.011). The multi-locus genetic analysis of the 12 MS revealed all the parasites had unique haplotypes. Significant linkage disequilibrium (LD) was observed in all the five parasite populations. Kisumu had the most significant index of association values (0.16; p<0.0001) whereas Kisii had the least significant index of association values (0.03; p<0.0001). Our data suggest high genetic diversity in Kenyan parasite population with the exception of parasite from Malindi where malaria has been on the decline. The presence of significant LD suggests that there is occurrence of inbreeding in the parasite population. Parasite populations from Kisii showed the strongest evidence for epidemic population structure whereas the rest of the regions showed panmixia. Defining the genetic diversity of the parasites in different ecological regions of Kenya after introduction of the artemether-lumefantrine is important in refining the spread of drug resistant strains and malaria transmission for more effective control and eventual elimination of malaria in Kenya.

Temporal trends in prevalence of Plasmodium falciparum molecular markers selected for by artemether-lumefantrine treatment in pre-ACT and post-ACT parasites in western Kenya

Artemether–lumefantrine (AL) became the first-line treatment for uncomplicated malaria in Kenya in 2006. Studies have shown AL selects for SNPs in pfcrt and pfmdr1 genes in recurring parasites compared to the baseline infections. The genotypes associated with AL selection are K76 in pfcrt and N86, 184F and D1246 in pfmdr1. To assess the temporal change of these genotypes in western Kenya, 47 parasite isolates collected before (pre-ACT; 1995–2003) and 745 after (post-ACT; 2008–2014) introduction of AL were analyzed. In addition, the associations of parasite haplotype against the IC₅₀ of artemether and lumefantrine, and clearance rates were determined. Parasite genomic DNA collected between 1995 and 2014 was analyzed by sequencing or PCR-based single-base extension on Sequenom MassARRAY. IC₅₀s were determined for a subset of the samples. One hundred eighteen samples from 2013 to 2014 were from an efficacy trial of which 68 had clearance half-lives. Data revealed there were significant differences between pre-ACT and post-ACT genotypes at the four codons (chi-square analysis; p < 0.0001). The prevalence of pfcrt K76 and N86 increased from 6.4% in 1995–1996 to 93.2% in 2014 and 0.0% in 2002–2003 to 92.4% in 2014 respectively. Analysis of parasites carrying pure alleles of K + NFD or T + YYY haplotypes revealed that 100.0% of the pre-ACT parasites carried T + YYY and 99.3% of post-ACT parasites carried K + NFD. There was significant correlation (p = 0.04) between lumefantrine IC₅₀ and polymorphism at pfmdr1 codon 184. There was no difference in parasite clearance half-lives based on genetic haplotype profiles. This study shows there is a significant change in parasite genotype, with key molecular determinants of AL selection almost reaching saturation. The implications of these findings are not clear since AL remains highly efficacious. However, there is need to closely monitor parasite genotypic, phenotypic and clinical dynamics in response to continued use of AL in western Kenya.

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The prevalence of pfcrt K76 increased from 6.4% in 1995 to 93.2% in 2014 and pfmdr1 N86 from 0% in 2002 to 92.4% in 2014.

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100% of pre-ACTs parasites carried T+YYY haplotype whereas 99.3% post-ACTs parasites carried K+NFD haplotype.

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There is resurgence of chloroquine sensitive parasite in western Kenya.

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AL is still highly efficacious but there are drastic genetic changes taking place in the parasite population.