Thursday, December 22, 2011

Collected Plasmodium faliciparum GWAS and resistance to antimalarial drugs

Plasmodium falciparum parasite spreads rapidly and widely, if it is out of control. The major prevention is antimalarial drugs. However, drug resistance in parasites has evolved and spread rapidly. In consequence, it’s necessary to launch genome-wide association studies of parasite traits. Previous studies show that mutations in MAL7P1.27 (also known as pfcrt, the gene encoding the P. falciparum CQ resistance transporter) and in the genes encoding P. falciparum dihydrofolate reductase (pfdhfr) and P. falciparum dihydrofolate reductase (pfdhps) have been shown to confer resistance to CQ and SP. Moreover, copy number and/or point mutations at pfmdr1 on chromosome 5 linked to the parasite response to MQ, QN, ART and other antimalarial drugs. Additionally, it has been shown that using 342 genome-wide microsatellite markers and 92 parasite isolates collected from different parts of the world is a more efficient and less-time-consuming way to identify the chromosome segment carrying the pfcrt locus. In the present study, with increase of the number of isolated parasites, it reports the first genome-wide P. falciparum using sensitive method and GWAS of resistance of multiple antimalarial drugs.

In general, the authors isolated 189 culture-adapted P. falciparum parasites in vitro culture, from Asia, Africa, America and paua New Guina. In paralle, they use sensitive method to genotype those parasites. And then, they analyze the population structure, variation in recombination rate and loci under recent positive. In the end, they explore parasite half-maximum inhibitory concentrations for 7 antimalarial drugs and find out the responsible genes.

In the first step, they want to find out whether genetic heterogeneity due to geography. It is found that parasites could be clustered into continental populations with one exception. There is a group of Cambodian parasites separated from those from Thailand and the majority of the parasites from Cambodia. There are two possibilities for this observation. One is the presence of recent population admixture. The other one is that SNPS could distinguish parasites with different phenotypes. .

According to genome-wide SNP dataset, population recombination maps for all 14 chromosomes were generated to detect the recombination frequency. They indeed found hot several loci with high levels of activity including a locus at the end of chromosome 1 and segment on chromosome 7 containing pfcrt.

In order to map chromosomal loci potentially under positive selection, three techniques were utilized, namely, REHH, iHS, and XP-EHH. REHH detected multiple loci including those on chromosome 7 containing pfcrt, on chromosome 11 having the gene encoding pfama-1 and chromosome 13 containing PF13_0271. All the regions mentioned above may be associated with immune or drug selection pressure. Additionally, iHS confirms the results of REHH, meanwhile, it detects other high signal localized in chromosome 1 and 14. Using XP-EHH on one hand detected selective sweep driving some alleles to fixation in one population but polymorphic in the others. On the other hand, it shows the comparison of different population. In a word, using 3 methods detected 11 genes in total.

In the last part, they use IC50 to explore the response of selected parasites to antimalarial drug. After that, they conducted multiple GWAS for loci that are responsible for the different response. Multivariate analyses showed a strong positive correlation between IC 50 values of MQ and DHA suggesting either co-selection by the drugs and/ or a common resistance mechanism to the two drugs. On the contrary, it shows slight negative relationships between DHA and AMQ, MQ and AMA, CQ and MQ, and CQ and DHA both among all the parasites and among those from the Thai-Cambodian population. In particular, separated parasites from Thai-Cambodian population show higher resistance.

In my opinion, this paper is very useful to explore the new direction of treatment to the malaria. The design of this paper is based on the previous foundation showing the mutations in genes related to the resistance and immune target of the antimalarial drug. Under positive selection, they identified the candidate genes and the locations in their collected parasites from different continents. Furthermore, they compared the response of parasites to drugs and tried to find out the responsible genes. Even though they indeed found out some candidate genes, only 3 genes are really related. Among these genes, two of them were reported before. In fact, the real association needs investigating and requiring. In a word, the conclusion is still elusive. I suppose that increasing the number of parasites and decreasing the possibility of imbalanced collection should be taken into consideration in future experiment. Last but not least, this paper provided evidence that high throughput MIP array; estimates of genome-wide recombination events and recent positive selection maps are import tools and information for GWAS to identify genes.

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