Use cases for genetic epidemiology in malaria elimination

Dalmat, Ronit R.; Naughton, Brienna; Kwan-Gett, Tao; Slyker, Jennifer A.; Stuckey, Erin M.

doi:10.1186/s12936-019-2784-0

Cited by 70 publications

(70 citation statements)

References 34 publications

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“…84 To be of practical value for national malaria control programmes, genetic data must address well-defined use cases and be readily accessible. 85 Amplicon sequencing technologies provide a powerful new tool for targeted genotyping that could feasibly be implemented locally in malaria-endemic countries 86,87 , but there remains a need for the international malaria control community to generate and share whole genome sequencing data, e.g. to monitor for newly emerging forms of drug resistance and to understand regional patterns of parasite migration.…”

Section: Discussionmentioning

confidence: 99%

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples

Pearson

Amato

Kwiatkowski

2019

Preprint

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MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed. Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination. MethodsAll samples in this study were derived from blood samples obtained from patients with P. falciparum malaria, collected with informed consent from the patient or a parent or guardian. At each location, sample collection was approved by the appropriate local and institutional ethics committees. The following local and institutional committees gave ethical approval for the partner studies:Standard laboratory protocols were used to determine DNA quantity and proportion of human DNA in each sample as previously described 7,56 .

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Section: Discussionmentioning

confidence: 99%

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples

Pearson

Amato

Kwiatkowski

2019

Preprint

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“…Patterns of genetic similarity between pathogen populations help us understand how the disease spreads. Patterns of relatedness (a measure of genetic similarity) between malaria parasites in different human populations, for instance, help characterise the connectivity between them, thus guide the design of targeted public health interventions [1].…”

Section: Introductionmentioning

confidence: 99%

Identity-by-descent relatedness estimates with uncertainty characterise departure from isolation-by-distance betweenPlasmodium falciparumpopulations on the Colombian-Pacific coast

Taylor

Echeverry

Anderson

et al. 2020

Preprint

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18Characterising connectivity between geographically separated biological populations is a common goal in 19 many fields. Recent approaches to understanding connectivity between malaria parasite populations, with 20 implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). 21 However, uncertainty around estimated relatedness has not been accounted for to date. IBD-based relat-22 edness estimates with uncertainty were computed for pairs of monoclonal Plasmodium falciparum samples 23 collected from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum 24 is frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically 25 but connected by frequent marine traffic. The fraction of highly-related sample pairs (whose classification 26 accounts for uncertainty) was greater within cities versus between. However, based on both the fraction 27 of highly-related sample pairs and on a threshold-free approach (Wasserstein distances between parasite 28 populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura- 29Tumaco connectivity was consistent with three separate transmission events involving parasites from five 30 different clonal components (groups of statistically indistinguishable parasites identified under a graph theo-31 retic framework). To conclude, P. falciparum population connectivity on the Colombian-Pacific coast abides 32 by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with 33 opportunities for targeted intervention. Further investigations are required to test this and alternative hy-34 potheses. For the first time in malaria epidemiology, we account for uncertainty around estimated relatedness 35 (an important consideration for future studies that plan to use genotype versus whole genome sequence data 36 to estimate IBD-based relatedness); we also use a threshold-free approach to compare parasite populations, 37 and identify clonal components in a statistically principled manner. The approaches we employ could be 38 adapted to other recombining organisms with mixed mating systems, thus have broad relevance. 39 1 In many research fields genetic data are used to help characterise connectivity between geographically dis-41 parate biological populations, with numerous applications in conservation, agriculture, and public health. 42Patterns of genetic similarity between pathogen populations help us understand how the disease spreads. 43 Patterns of relatedness (a measure of genetic similarity) between malaria parasites in different human pop-44 ulations, for instance, help characterise the connectivity between them, thus guide the design of targeted 45 public health interventions [1]. 46 Several methods are employed to measure genetic similarity and thus characterise connectivity. Phylo-47 genetic methods, in which genetic distances between individuals are measured in unit...

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“…Expanding MIPs to explore these trends in other high transmission settings in Africa is an efficient way to establish contemporary genetic trends, and can provide ongoing surveillance of circulating parasite populations. Such characterization would provide control programs with baseline and ongoing parasite surveillance data to evaluate public health interventions in high-transmission areas of sub-Saharan Africa that are pivoting to elimination efforts (19,20) .…”

Section: Introductionmentioning

confidence: 99%

Describing the current status ofPlasmodium falciparumpopulation structure and drug resistance within mainland Tanzania using molecular inversion probes

Moser

Madebe

Aydemir

et al. 2020

Preprint

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Word Count : 246 Main Text Word Count: 3,649ABSTRACT High-throughput Plasmodium genomic data is increasingly useful in assessing prevalence of clinically important mutations and malaria transmission patterns. Understanding parasite diversity is important for identification of specific human or parasite populations that can be targeted by control programs, and to monitor the spread of mutations associated with drug resistance. An up-to-date understanding of regional parasite population dynamics is also critical to monitor the impact of control efforts. However, this data is largely absent from high-burden nations in Africa, and to date, no such analysis has been conducted for malaria parasites in Tanzania country-wide. To this end, over 1,000 P. falciparum clinical isolates were collected in 2017 from 13 sites in seven administrative regions across Tanzania, and parasites were genotyped at 1,800 variable positions genome-wide using molecular inversion probes. Population structure was detectable among Tanzanian P. falciparum parasites, roughly separating parasites from the northern and southern districts and identifying genetically admixed populations in the north. Isolates from geographically close districts were more likely to be genetically related compared to parasites sampled from more distant districts. Known drug resistance mutations were seen at increased frequency in northern districts, and additional variants with undetermined significance for antimalarial resistance also varied by geography. Malaria Indicator Survey (2017) data corresponded with genetic findings, including average region-level complexity-of-infection and malaria prevalence estimates. The parasite populations identified here provide important information on extant spatial patterns of genetic diversity of Tanzanian parasites, to which future surveys of genetic relatedness can be compared. 4 SIGNIFICANCE: Documenting dynamics of malaria parasite genomics in high-transmission settings at scale in sub-Saharan Africa is critical for policy and decision making to support ongoing malaria elimination initiatives.Using molecular inversion probes, we genotyped over 1,000 Tanzanian Plasmodium falciparum samples collected country-wide in 2017 at hundreds of variable polymorphic positions across the genome. Frequencies of known drug resistance mutations were higher in northern districts of the country compared to the south.Results also showed a distinct isolation-by-distance pattern (whereby increasing geographic distance was correlated with decreasing genetic relatedness), as well as signals of higher genetic sharing between several southern districts. These results provide, for the first time, a picture of current within-country diversity of Tanzanian P. falciparum populations.

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Use cases for genetic epidemiology in malaria elimination

Cited by 70 publications

References 34 publications

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples

Identity-by-descent relatedness estimates with uncertainty characterise departure from isolation-by-distance betweenPlasmodium falciparumpopulations on the Colombian-Pacific coast

Describing the current status ofPlasmodium falciparumpopulation structure and drug resistance within mainland Tanzania using molecular inversion probes

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