Dissecting malaria biology and epidemiology using population genetics and genomics

Auburn, Sarah; Barry, Alyssa E.

doi:10.1016/j.ijpara.2016.08.006

Cited by 66 publications

(85 citation statements)

References 107 publications

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“…All data are published [50,51,29,30,52,8]. They were obtained either from sparse genome-wide panels of select markers, called barcodes, or from dense whole genome sequencing (WGS) data sets (reviewed in [53]); full details of sample collection and data generation can be found via the citations above and references therein. Additional steps we took to process the data are as follows.…”

Section: Plasmodium Datamentioning

confidence: 99%

Estimating relatedness between malaria parasites

Taylor

Jacob

Neafsey

et al. 2019

Preprint

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Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites, Plasmodium falciparum and Plasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-bystate are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

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Section: Plasmodium Datamentioning

confidence: 99%

Estimating relatedness between malaria parasites

Taylor

Jacob

Neafsey

et al. 2019

Preprint

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“…To complement traditional approaches to surveillance, genotyping of P. falciparum has become a popular approach to understanding the underlying malaria transmission dynamics [8][9][10]. As transmission declines, recombination between genetically distinct clones likely reduces, leading to decreases in genetic diversity, effective population size and fragmented populations [11].…”

Section: Introductionmentioning

confidence: 99%

“…As transmission declines, recombination between genetically distinct clones likely reduces, leading to decreases in genetic diversity, effective population size and fragmented populations [11]. This relationship has been proposed to be potentially useful as a "genomic thermometer" to gauge changes in malaria transmission resulting from intensified malaria control and elimination efforts [8,12,13]. This "genomic thermometer" framework has been based on numerous studies that have shown that P. falciparum parasite populations generally have higher population and within-host diversity (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…This "genomic thermometer" framework has been based on numerous studies that have shown that P. falciparum parasite populations generally have higher population and within-host diversity (i.e. higher multiplicity of infection or MOI) in high transmission settings of sub-Saharan Africa than in lower transmission settings such as Southeast Asia and Latin America [8,11,[14][15][16][17][18][19][20][21][22]. However, studies of P. falciparum parasite diversity in low transmission settings of sub-Saharan Africa are limited, and in these settings, importation of malaria from neighboring, high transmission countries may complicate the relationship between transmission intensity and genetic diversity.…”

Section: Introductionmentioning

confidence: 99%

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High genetic diversity of Plasmodium falciparum in the low transmission setting of the Kingdom of Eswatini

Roh

Tessema

Murphy

et al. 2019

Preprint

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“…Whilst measures of parasite prevalence or incidence are helpful to gauge transmission intensity, these methods can underestimate the burden of malaria, particularly of P. vivax , where infections are often sub-patent and/or asymptomatic [16]. Genetic analysis of the parasite is a complementary approach to strengthen local estimates of transmission intensity and stability through characterization of parasite diversity and relatedness, as well as offering an approach to gauge parasite gene flow between different populations, and the associated risks of drug resistance spread [17, 18]. …”

Section: Introductionmentioning

confidence: 99%

Chloroquine efficacy for Plasmodium vivax in Myanmar in populations with high genetic diversity and moderate parasite gene flow

Htun

Mon

Aye

et al. 2017

Malar J

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Background Plasmodium vivax malaria remains a major public health burden in Myanmar. Resistance to chloroquine (CQ), the first-line treatment for P. vivax, has been reported in the country and has potential to undermine local control efforts.MethodsPatients over 6 years of age with uncomplicated P. vivax mono-infection were enrolled into clinical efficacy studies in Myawaddy in 2014 and Kawthoung in 2012. Study participants received a standard dose of CQ (25 mg/kg over 3 days) followed by weekly review until day 28. Pvmdr1 copy number (CN) and microsatellite diversity were assessed on samples from the patients enrolled in the clinical study and additional cross-sectional surveys undertaken in Myawaddy and Shwegyin in 2012.ResultsA total of 85 patients were enrolled in the CQ clinical studies, 25 in Myawaddy and 60 in Kawthoung. One patient in Myawaddy (1.2%) had an early treatment failure and two patients (2.3%) in Kawthoung presented with late treatment failures on day 28. The day 28 efficacy was 92.0% (95% CI 71.6–97.9) in Myawaddy and 98.3% (95% CI 88.7–99.8) in Kawthoung. By day 2, 92.2% (23/25) in Myawaddy and 85.0% (51/60) in Kawthoung were aparasitaemic. Genotyping and pvmdr1 CN assessment was undertaken on 43, 52 and 46 clinical isolates from Myawaddy, Kawthoung and Shwegyin respectively. Pvmdr1 amplification was observed in 3.2% (1/31) of isolates in Myawaddy, 0% (0/49) in Kawthoung and 2.5% (1/40) in Shwegyin. Diversity was high in all sites (H E 0.855–0.876), with low inter-population differentiation (F ST 0.016–0.026, P < 0.05).ConclusionsTreatment failures after chloroquine were observed following chloroquine monotherapy, with pvmdr1 amplification present in both Myawaddy and Shwegyin. The results emphasize the importance of ongoing P. vivax drug resistance surveillance in Myanmar, particularly given the potential connectivity between parasite population at different sites.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-017-1912-y) contains supplementary material, which is available to authorized users.

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Dissecting malaria biology and epidemiology using population genetics and genomics

Cited by 66 publications

References 107 publications

Estimating relatedness between malaria parasites

Estimating relatedness between malaria parasites

High genetic diversity of Plasmodium falciparum in the low transmission setting of the Kingdom of Eswatini

Chloroquine efficacy for Plasmodium vivax in Myanmar in populations with high genetic diversity and moderate parasite gene flow

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