Genetic surveillance in the Greater Mekong subregion and South Asia to support malaria control and elimination

Abstract

Background: National Malaria Control Programmes (NMCPs) currently make limited use of parasite genetic data. We have developed GenRe-Mekong, a platform for genetic surveillance of malaria in the Greater Mekong Subregion (GMS) that enables NMCPs to implement large-scale surveillance projects by integrating simple sample collection procedures in routine public health procedures.

Methods: Samples from symptomatic patients are processed by SpotMalaria, a high-throughput system that produces a comprehensive set of genotypes comprising several drug resistance markers, species markers and a genomic barcode. GenRe-Mekong delivers Genetic Report Cards, a compendium of genotypes and phenotype predictions used to map prevalence of resistance to multiple drugs.

Results: GenRe-Mekong has worked with NMCPs and research projects in eight countries, processing 9623 samples from clinical cases. Monitoring resistance markers has been valuable for tracking the rapid spread of parasites resistant to the dihydroartemisinin-piperaquine combination therapy. In Vietnam and Laos, GenRe-Mekong data have provided novel knowledge about the spread of these resistant strains into previously unaffected provinces, informing decision-making by NMCPs.

Conclusions: GenRe-Mekong provides detailed knowledge about drug resistance at a local level, and facilitates data sharing at a regional level, enabling cross-border resistance monitoring and providing the public health community with valuable insights. The project provides a rich open data resource to benefit the entire malaria community.

Funding: The GenRe-Mekong project is funded by the Bill and Melinda Gates Foundation (OPP11188166, OPP1204268). Genotyping and sequencing were funded by the Wellcome Trust (098051, 206194, 203141, 090770, 204911, 106698/B/14/Z) and Medical Research Council (G0600718). A proportion of samples were collected with the support of the UK Department for International Development (201900, M006212), and Intramural Research Program of the National Institute of Allergy and Infectious Diseases.

Keywords: asia; drug resistance; epidemiology; genetic surveillance; global health; infectious disease; malaria; microbiology.

Figure 1.. Map of GenRe-Mekong sample collection sites in Asia.

Sites markers are colored by country. One site in Kinshasa (DR Congo) not shown.

Figure 1—figure supplement 1.. Number of samples collected prospectively by month in each country.

Figure 1—figure supplement 2.. Trends in sample collections over time.

Numbers of samples collected prospectively each year by surveillance projects (blue) and research studies (orange) are compared. Sample counts submitted retrospectively by research projects (green) are also shown.

Figure 2.. Neighbor-joining tree using barcode data to show genetic differentiation between parasites in the Thai-Myanmar and Thai-Cambodian border regions.

The tree was derived from a matrix distance matrix, computed by comparing the genetic barcodes of samples. The branch length separating each pair of parasites represents the amount of genetic differentiation between them: individuals separated by shorter branches are more similar to each other. Samples from provinces/states of Myanmar, Thailand, and Cambodia near to the borders were included. Each circular marker represents a sample, colored by the province/state of origin.

Figure 3.. Map of the spread of (A) artemisinin resistance (ART-R) and (B) dihydroartemisinin-piperaquine resistance (DHA-PPQ-R) in Asian countries.

Marker text and color indicate the proportion of sample classified as resistant in each province/state/division surveyed. A total of 6762 samples were included in (A) and 3395 samples in (B), after excluding samples with undetermined phenotype prediction. The results are summarized in Table 3.

Figure 3—figure supplement 1.. kelch13 allele diversity in Asian countries.

We show a pie chart for each province/state/division surveyed, indicating the relative proportion of different nonsynonymous mutations found in the resistance domains of kelch13. A total of 6758 samples were included in this analysis, after excluding samples where the kelch13 genotype could not be called, and those with undetermined ART-R phenotype prediction. For display clarity, mutations that we only found in singleton samples are also excluded (n=18).

Figure 3—figure supplement 2.. Map of Piperaquine Resistance (PPQ-R) in Asian countries.

Marker text and color indicate the proportion of sample classified as resistant in each province/state/division surveyed. A total of 3552 samples were included in this analysis, after excluding samples where plasmepsin 2/3 copy number could not be determined. The results are summarized in Table 3.

Figure 3—figure supplement 3.. Map of Chloroquine Resistance (CQ-R) in Asian countries.

Marker text and color indicate the proportion of sample classified as resistant in each province/state/division surveyed. A total of 6458 samples were included in this analysis, after excluding samples where the crt core haplotype could not predict a phenotype. The results are summarized in Table 3.

Figure 3—figure supplement 4.. Map of Pyrimethamine Resistance (PYR-R) in Asian countries.

Marker text and color indicate the proportion of sample classified as resistant in each province/state/division surveyed. A total of 7208 samples were included in this analysis, after excluding samples where the dhfr core haplotype could not predict a phenotype. The results are summarized in Table 3.

Figure 3—figure supplement 5.. Map of Sulfadoxine Resistance (SD-R) in Asian countries.

Marker text and color indicate the proportion of sample classified as resistant in each province/state/division surveyed. A total of 7095 samples were included in this analysis, after excluding samples where the dhps core haplotype could not predict a phenotype.

Figure 4.. Longitudinal sample counts and proportions of DHA-PPQ-R parasites in three provinces of Central Vietnam.

The same geographical area (Gia Lai, Dak Lak, and Dak Nong provinces) is shown for two malaria seasons: 2017/18 (12 months from May 2017, n=523) and 2018/2019 (the following 12 months, n=455). Districts are represented by markers whose size is proportional to the number of samples, and whose color indicates the frequency of samples carrying both the kelch13 C580Y mutation and the plasmepsin2/3 amplification, and thus predicted to be DHA-PPQ-R. Marker labels show district name, resistant parasite frequency, and sample count.

Figure 4—figure supplement 1.. Frequencies of ART-R and PPQ-R parasites in Vietnam.

The three maps show frequencies of predicted resistance to artemisinin (A, n=1543), piperaquine (B, n=1380), and DHA-piperaquine (C, n=1372). Samples are aggregated by district, represented by a marker; estimates are shown only for districts with more than 10 collected samples. Marker text and color indicate the proportion of sample classified as resistant in each district. Labels show the names of the seven provinces where samples were collected.

Figure 4—figure supplement 2.. Distribution of kelch13 alleles in seven provinces of Vietnam.

Each pie chart shows the proportions of kelch13 alleles in samples collected in each province. Numbers by each pie slice indicate the actual number of samples carrying that allele. Samples with heterozygous kelch13 calls were disregarded. A total of 1567 samples with kelch13 genotypes were analyzed.

Figure 5.. Proportions of ART-R and KEL1/PLA1 parasites in southern Laos districts.

Districts in five provinces of southern Laos are represented by markers whose color and label indicates the frequency of samples classified as ART-R (A) and as DHA-PPQ-R, i.e. possessing markers of resistance to both artemisinin and piperaquine (B). Only districts with more than 10 samples with valid genotypes are shown. In panel (B), a dashed line denotes a hypothetical demarcation line between a Lower Zone, where DHA-PPQ-R strains have spread, and an Upper Zone, where they are absent and ART-R parasites belong to different strains.

Figure 5—figure supplement 1.. Frequencies Distribution of kelch13 alleles in five provinces of Laos.

Each pie chart shows the proportions of kelch13 alleles in samples collected in each province. Numbers by each pie slice indicate the actual number of samples carrying that allele. Samples with heterozygous kelch13 calls were disregarded. A total of 1303 samples with kelch13 genotypes were analyzed.

Figure 5—figure supplement 2.. Neighbour-joining tree using barcode data to show genetic differentiation between groups of parasites collected in Southern Laos.

The tree was derived from a genetic distance matrix, computed by comparing the genetic barcodes of samples collected in the Lao PDR (n=1332). Each marker represents a parasite sample, coloured by province. The branch length separating each pair of parasites represents the amount of genetic differentiation between them: individuals separated by shorter branches are more similar to each other. Thicker marker borders indicate parasites carrying thekelch13C580Y mutation, while square markers indicate samples withplasmepsin2/3amplification. Orange circular callouts show notable features of this tree. (A) Shows a large cluster of parasites from the Lower Zone (Attapeu and Champasak provinces) carrying both C580Y andplasmepsin2/3amplification (DHA-PPQ-R). (B) Indicates that C580Y mutants from the Upper Zone (Savannakhet and Salavan provinces) are genetically distinct from the DHA-PPQ-R strains, but also from Upper Zone wild-type parasites.