Increasing reports of resistance to a frontline malaria blood-stage treatment, chloroquine (CQ), raises concerns for the elimination of Plasmodium vivax. The absence of an effective molecular marker of CQ resistance in P. vivax greatly constrains surveillance of this emerging threat. A recent genetic cross between CQ sensitive (CQS) and CQ resistant (CQR) NIH-1993 strains of P. vivax linked a moderate CQR phenotype with two candidate markers in P. vivax CQ resistance transporter gene (pvcrt-o): MS334 and In9pvcrt. Longer TGAAGH motif lengths at MS334 were associated with CQ resistance, as were shorter motifs at the In9pvcrt locus. In this study, high-grade CQR clinical isolates of P. vivax from a low endemic setting in Malaysia were used to investigate the association between the MS334 and In9pvcrt variants and treatment efficacy. Among a total of 49 independent monoclonal P. vivax isolates assessed, high-quality MS334 and In9pvcrt sequences could be derived from 30 (61%) and 23 (47%), respectively. Five MS334 and six In9pvcrt alleles were observed, with allele frequencies ranging from 2 to 76% and 3 to 71%, respectively. None of the clinical isolates had the same variant as the NIH-1993 CQR strain, and none of the variants were associated with CQ treatment failure (all P > 0.05). Multi-locus genotypes (MLGs) at 9 neutral microsatellites revealed a predominant P. vivax strain (MLG6) accounting for 52% of Day 0 infections. The MLG6 strain comprised equal proportions of CQS and CQR infections. Our study reveals complexity in the genetic basis of CQ resistance in the Malaysian P. vivax pre-elimination setting and suggests that the proposed pvcrt-o MS334 and In9pvcrt markers are not reliable markers of CQ treatment efficacy in this setting. Further studies are needed in other endemic settings, applying hypothesis-free genome-wide approaches, and functional approaches to understand the biological impact of the TGAAGH repeats linked to CQ response in a cross are warranted to comprehend and track CQR P. vivax.
The Horn of Africa harbors the largest reservoir of Plasmodium vivax in the continent. Most of sub-Saharan Africa has remained relatively vivax-free due to a high prevalence of the human Duffy-negative trait, but the emergence of strains able to invade Duffy-negative reticulocytes poses a major public health threat. We undertook the first population genomic investigation of P. vivax from the region, comparing the genomes of 24 Ethiopian isolates against data from Southeast Asia to identify important local adaptions. The prevalence of the Duffy binding protein amplification in Ethiopia was 79%, potentially reflecting adaptation to Duffy negativity. There was also evidence of selection in a region upstream of the chloroquine resistance transporter, a putative chloroquine-resistance determinant. Strong signals of selection were observed in genes involved in immune evasion and regulation of gene expression, highlighting the need for a multifaceted intervention approach to combat P. vivax in the region.
This report describes the MalariaGEN Pv4 dataset, a new release of curated genome variation data on 1,895 samples of Plasmodium vivax collected at 88 worldwide locations between 2001 and 2017. It includes 1,370 new samples contributed by MalariaGEN and VivaxGEN partner studies in addition to previously published samples from these and other sources. We provide genotype calls at over 4.5 million variable positions including over 3 million single nucleotide polymorphisms (SNPs), as well as short indels and tandem duplications. This enlarged dataset highlights major compartments of parasite population structure, with clear differentiation between Africa, Latin America, Oceania, Western Asia and different parts of Southeast Asia. Each sample has been classified for drug resistance to sulfadoxine, pyrimethamine and mefloquine based on known markers at the dhfr, dhps and mdr1 loci. The prevalence of all of these resistance markers was much higher in Southeast Asia and Oceania than elsewhere. This open resource of analysis-ready genome variation data from the MalariaGEN and VivaxGEN networks is driven by our collective goal to advance research into the complex biology of P. vivax and to accelerate genomic surveillance for malaria control and elimination.