PLoS ONE (Jan 2015)
Genetic Diversity of Plasmodium falciparum in Haiti: Insights from Microsatellite Markers.
Abstract
Hispaniola, comprising Haiti and the Dominican Republic, has been identified as a candidate for malaria elimination. However, incomplete surveillance data in Haiti hamper efforts to assess the impact of ongoing malaria control interventions. Characteristics of the genetic diversity of Plasmodium falciparum populations can be used to assess parasite transmission, which is information vital to evaluating malaria elimination efforts. Here we characterize the genetic diversity of P. falciparum samples collected from patients at seven sites in Haiti using 12 microsatellite markers previously employed in population genetic analyses of global P. falciparum populations. We measured multiplicity of infections, level of genetic diversity, degree of population geographic substructure, and linkage disequilibrium (defined as non-random association of alleles from different loci). For low transmission populations like Haiti, we expect to see few multiple infections, low levels of genetic diversity, high degree of population structure, and high linkage disequilibrium. In Haiti, we found low levels of multiple infections (12.9%), moderate to high levels of genetic diversity (mean number of alleles per locus = 4.9, heterozygosity = 0.61), low levels of population structure (highest pairwise Fst = 0.09 and no clustering in principal components analysis), and moderate linkage disequilibrium (ISA = 0.05, P<0.0001). In addition, population bottleneck analysis revealed no evidence for a reduction in the P. falciparum population size in Haiti. We conclude that the high level of genetic diversity and lack of evidence for a population bottleneck may suggest that Haiti's P. falciparum population has been stable and discuss the implications of our results for understanding the impact of malaria control interventions. We also discuss the relevance of parasite population history and other host and vector factors when assessing transmission intensity from genetic diversity data.