Limits...
Drug coverage in treatment of malaria and the consequences for resistance evolution--evidence from the use of sulphadoxine/pyrimethamine.

Malisa AL, Pearce RJ, Abdulla S, Mshinda H, Kachur PS, Bloland P, Roper C - Malar. J. (2010)

Bottom Line: The influence of policy on the parasite reservoir was profound.The national policy change brought about a shift in treatment practice and the resulting increase in coverage had a substantial impact on drug pressure.The selection applied by first-line use is strong enough to overcome recombination pressure and create significant linkage disequilibrium between the unlinked genetic determinants of pyrimethamine and sulphadoxine resistance, showing that recombination is no barrier to the emergence of resistance to combination treatments when they are used as the first-line malaria therapy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Sciences, Faculty of Science, Sokoine University of Agriculture, SUA, PO Box 3038, Morogoro, Tanzania.

ABSTRACT

Background: It is argued that, the efficacy of anti-malarials could be prolonged through policy-mediated reductions in drug pressure, but gathering evidence of the relationship between policy, treatment practice, drug pressure and the evolution of resistance in the field is challenging. Mathematical models indicate that drug coverage is the primary determinant of drug pressure and the driving force behind the evolution of drug resistance. These models show that where the basis of resistance is multigenic, the effects of selection can be moderated by high recombination rates, which disrupt the associations between co-selected resistance genes.

Methods: To test these predictions, dhfr and dhps frequency changes were measured during 2000-2001 while SP was the second-line treatment and contrasted these with changes during 2001-2002 when SP was used for first-line therapy. Annual cross sectional community surveys carried out before, during and after the policy switch in 2001 were used to collect samples. Genetic analysis of SP resistance genes was carried out on 4,950 Plasmodium falciparum infections and the selection pressure under the two policies compared.

Results: The influence of policy on the parasite reservoir was profound. The frequency of dhfr and dhps resistance alleles did not change significantly while SP was the recommended second-line treatment, but highly significant changes occurred during the subsequent year after the switch to first line SP. The frequency of the triple mutant dhfr (N51I,C59R,S108N) allele (conferring pyrimethamine resistance) increased by 37% - 63% and the frequency of the double A437G, K540E mutant dhps allele (conferring sulphadoxine resistance) increased 200%-300%. A strong association between these unlinked alleles also emerged, confirming that they are co-selected by SP.

Conclusion: The national policy change brought about a shift in treatment practice and the resulting increase in coverage had a substantial impact on drug pressure. The selection applied by first-line use is strong enough to overcome recombination pressure and create significant linkage disequilibrium between the unlinked genetic determinants of pyrimethamine and sulphadoxine resistance, showing that recombination is no barrier to the emergence of resistance to combination treatments when they are used as the first-line malaria therapy.

Show MeSH

Related in: MedlinePlus

The minimum number of co-infecting genotypes (multiplicity of infection or MOI) was determined by measuring the number of alleles in every sample at 3 unlinked microsatellite loci (Poly A, Pfpk2 and TA109). Here the MOI in 178 samples from Kilombero/Ulanga 2002 (white) and 180 samples Rufiji 2002 (black) are compared.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2908640&req=5

Figure 5: The minimum number of co-infecting genotypes (multiplicity of infection or MOI) was determined by measuring the number of alleles in every sample at 3 unlinked microsatellite loci (Poly A, Pfpk2 and TA109). Here the MOI in 178 samples from Kilombero/Ulanga 2002 (white) and 180 samples Rufiji 2002 (black) are compared.

Mentions: To examine the extent of the underlying rate of mixture in infections and test the robustness of this frequency estimates, this study looked at three unlinked microsatellite markers (Poly A, Pfpk2 and TA109) in 178 and 180 samples from 2002 survey from Kilombero/Ulanga and Rufiji, respectively. The minimum number of co-infecting genotypes in each infection was determined as the greatest number of alleles at any of the three microsatellite loci. This number is often referred to as the "multiplicity of infection" or (MOI). In Figure 5 the distribution of MOI in the two districts is compared showing that they are similar. The presence/absence of dhps A437G and K540E among the same infections was used to test whether the distribution of the dhps double mutant alleles was consistent with expectation using a method devised by Schneider et al [34] (see Additional file 1). This uses maximum likelihood to predict the underlying frequency of resistance alleles based on measures of the multiplicity of infection and the presence/absence of resistance mutations in those infections. The analysis predicted an underlying frequency of the dhps double mutant of 0.276 in Rufiji (where the frequency among single and majority genotype infections was 0.274) and a frequency of 0.262 in Kilombero Ulanga (where the frequency among single and majority genotype infections was 0.245). The estimates using these two approaches are very consistent showing that no obvious bias is introduced into the estimation of frequencies by excluding mixed infections.


Drug coverage in treatment of malaria and the consequences for resistance evolution--evidence from the use of sulphadoxine/pyrimethamine.

Malisa AL, Pearce RJ, Abdulla S, Mshinda H, Kachur PS, Bloland P, Roper C - Malar. J. (2010)

The minimum number of co-infecting genotypes (multiplicity of infection or MOI) was determined by measuring the number of alleles in every sample at 3 unlinked microsatellite loci (Poly A, Pfpk2 and TA109). Here the MOI in 178 samples from Kilombero/Ulanga 2002 (white) and 180 samples Rufiji 2002 (black) are compared.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2908640&req=5

Figure 5: The minimum number of co-infecting genotypes (multiplicity of infection or MOI) was determined by measuring the number of alleles in every sample at 3 unlinked microsatellite loci (Poly A, Pfpk2 and TA109). Here the MOI in 178 samples from Kilombero/Ulanga 2002 (white) and 180 samples Rufiji 2002 (black) are compared.
Mentions: To examine the extent of the underlying rate of mixture in infections and test the robustness of this frequency estimates, this study looked at three unlinked microsatellite markers (Poly A, Pfpk2 and TA109) in 178 and 180 samples from 2002 survey from Kilombero/Ulanga and Rufiji, respectively. The minimum number of co-infecting genotypes in each infection was determined as the greatest number of alleles at any of the three microsatellite loci. This number is often referred to as the "multiplicity of infection" or (MOI). In Figure 5 the distribution of MOI in the two districts is compared showing that they are similar. The presence/absence of dhps A437G and K540E among the same infections was used to test whether the distribution of the dhps double mutant alleles was consistent with expectation using a method devised by Schneider et al [34] (see Additional file 1). This uses maximum likelihood to predict the underlying frequency of resistance alleles based on measures of the multiplicity of infection and the presence/absence of resistance mutations in those infections. The analysis predicted an underlying frequency of the dhps double mutant of 0.276 in Rufiji (where the frequency among single and majority genotype infections was 0.274) and a frequency of 0.262 in Kilombero Ulanga (where the frequency among single and majority genotype infections was 0.245). The estimates using these two approaches are very consistent showing that no obvious bias is introduced into the estimation of frequencies by excluding mixed infections.

Bottom Line: The influence of policy on the parasite reservoir was profound.The national policy change brought about a shift in treatment practice and the resulting increase in coverage had a substantial impact on drug pressure.The selection applied by first-line use is strong enough to overcome recombination pressure and create significant linkage disequilibrium between the unlinked genetic determinants of pyrimethamine and sulphadoxine resistance, showing that recombination is no barrier to the emergence of resistance to combination treatments when they are used as the first-line malaria therapy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Sciences, Faculty of Science, Sokoine University of Agriculture, SUA, PO Box 3038, Morogoro, Tanzania.

ABSTRACT

Background: It is argued that, the efficacy of anti-malarials could be prolonged through policy-mediated reductions in drug pressure, but gathering evidence of the relationship between policy, treatment practice, drug pressure and the evolution of resistance in the field is challenging. Mathematical models indicate that drug coverage is the primary determinant of drug pressure and the driving force behind the evolution of drug resistance. These models show that where the basis of resistance is multigenic, the effects of selection can be moderated by high recombination rates, which disrupt the associations between co-selected resistance genes.

Methods: To test these predictions, dhfr and dhps frequency changes were measured during 2000-2001 while SP was the second-line treatment and contrasted these with changes during 2001-2002 when SP was used for first-line therapy. Annual cross sectional community surveys carried out before, during and after the policy switch in 2001 were used to collect samples. Genetic analysis of SP resistance genes was carried out on 4,950 Plasmodium falciparum infections and the selection pressure under the two policies compared.

Results: The influence of policy on the parasite reservoir was profound. The frequency of dhfr and dhps resistance alleles did not change significantly while SP was the recommended second-line treatment, but highly significant changes occurred during the subsequent year after the switch to first line SP. The frequency of the triple mutant dhfr (N51I,C59R,S108N) allele (conferring pyrimethamine resistance) increased by 37% - 63% and the frequency of the double A437G, K540E mutant dhps allele (conferring sulphadoxine resistance) increased 200%-300%. A strong association between these unlinked alleles also emerged, confirming that they are co-selected by SP.

Conclusion: The national policy change brought about a shift in treatment practice and the resulting increase in coverage had a substantial impact on drug pressure. The selection applied by first-line use is strong enough to overcome recombination pressure and create significant linkage disequilibrium between the unlinked genetic determinants of pyrimethamine and sulphadoxine resistance, showing that recombination is no barrier to the emergence of resistance to combination treatments when they are used as the first-line malaria therapy.

Show MeSH
Related in: MedlinePlus