Changes in malaria parasite drug resistance in an endemic population over a 25-year period with resulting genomic evidence of selection.

Davis C Nwakanma; Craig W Duffy; Alfred Amambua-Ngwa ORCID logo; Eniyou C Oriero ORCID logo; Kalifa A Bojang ORCID logo; Margaret Pinder; Chris J Drakeley ORCID logo; Colin J Sutherland ORCID logo; Paul J Milligan ORCID logo; Bronwyn Macinnis; +4 more... Dominic P Kwiatkowski; Taane G Clark ORCID logo; Brian M Greenwood ORCID logo; David J Conway ORCID logo; (2013) Changes in malaria parasite drug resistance in an endemic population over a 25-year period with resulting genomic evidence of selection. The Journal of infectious diseases, 209 (7). pp. 1126-1135. ISSN 0022-1899 DOI: 10.1093/infdis/jit618
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BACKGROUND:  Analysis of genome-wide polymorphism in many organisms has potential to identify genes under recent selection. However, data on historical allele frequency changes are rarely available for direct confirmation. METHODS:  We genotyped single nucleotide polymorphisms (SNPs) in 4 Plasmodium falciparum drug resistance genes in 668 archived parasite-positive blood samples of a Gambian population between 1984 and 2008. This covered a period before antimalarial resistance was detected locally, through subsequent failure of multiple drugs until introduction of artemisinin combination therapy. We separately performed genome-wide sequence analysis of 52 clinical isolates from 2008 to prospect for loci under recent directional selection. RESULTS:  Resistance alleles increased from very low frequencies, peaking in 2000 for chloroquine resistance-associated crt and mdr1 genes and at the end of the survey period for dhfr and dhps genes respectively associated with pyrimethamine and sulfadoxine resistance. Temporal changes fit a model incorporating likely selection coefficients over the period. Three of the drug resistance loci were in the top 4 regions under strong selection implicated by the genome-wide analysis. CONCLUSIONS:  Genome-wide polymorphism analysis of an endemic population sample robustly identifies loci with detailed documentation of recent selection, demonstrating power to prospectively detect emerging drug resistance genes.


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