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Standing genetic variation and the evolution of drug resistance in HIV.

Pennings PS - PLoS Comput. Biol. (2012)

Bottom Line: We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters under the assumption that treatment failure is caused by the fixation of a single drug resistance mutation.We find that both the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-arameters which determine the probability that resistance evolves from standing genetic variation.Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.

View Article: PubMed Central - PubMed

Affiliation: Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America. pennings@fas.harvard.edu

ABSTRACT
Drug resistance remains a major problem for the treatment of HIV. Resistance can occur due to mutations that were present before treatment starts or due to mutations that occur during treatment. The relative importance of these two sources is unknown. Resistance can also be transmitted between patients, but this process is not considered in the current study. We study three different situations in which HIV drug resistance may evolve: starting triple-drug therapy, treatment with a single dose of nevirapine and interruption of treatment. For each of these three cases good data are available from literature, which allows us to estimate the probability that resistance evolves from standing genetic variation. Depending on the treatment we find probabilities of the evolution of drug resistance due to standing genetic variation between 0 and 39%. For patients who start triple-drug combination therapy, we find that drug resistance evolves from standing genetic variation in approximately 6% of the patients. We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters under the assumption that treatment failure is caused by the fixation of a single drug resistance mutation. We find that both the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-arameters which determine the probability that resistance evolves from standing genetic variation. Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.

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Related in: MedlinePlus

The probability that resistance mutations are detected in women treated for prevention of mother-to-child transmission.The probability that resistance mutations are detected 6 to 8 weeks after treatment with single dose nevirapine. Black crosses are data from single studies, grey bars with estimated standard error are percentages for all studies combined (the number of patients that were used to calculate this percentage is indicated at the top of the graph). Red circles with standard error are results from 1000 simulations and the black squares are analytical predictions. Parameter values as in table 2.
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pcbi-1002527-g003: The probability that resistance mutations are detected in women treated for prevention of mother-to-child transmission.The probability that resistance mutations are detected 6 to 8 weeks after treatment with single dose nevirapine. Black crosses are data from single studies, grey bars with estimated standard error are percentages for all studies combined (the number of patients that were used to calculate this percentage is indicated at the top of the graph). Red circles with standard error are results from 1000 simulations and the black squares are analytical predictions. Parameter values as in table 2.

Mentions: We identified 23 published studies that reported on NVP resistance 6 to 8 weeks after women were treated with sdNVP. Several of the studies directly compared two different treatment options. We found at least three studies for each of the four different treatment options. An overview of the studies can be found in table S2 in the supplementary text S2. For each study we recorded which of the four treatment options was used and in how many of the patients NVP resistance mutations were detected using simple Sanger (population) sequencing (we excluded studies that only recorded deep-sequencing or allele-specific PCR results, as there were too few of those to allow us to compare the treatment options). For each of the four treatment options, we also calculated the overall probability that resistance mutations were detected in a patient (simply by summing the number of patients with resistance and summing the total number of patients in the studies). We found that sdNVP leads to detectable resistance mutations in 39% of 952 patients, ZDV/sdNVP leads to detectable resistance mutations in 22% of 888 patients, adding two drugs during and after labor (sdNVP/PP) lead to detectable resistance mutations in 7.8% of 372 patients and ZDV/sdNVP/PP lead to detectable resistance mutations in none of 292 patients (see figure 3).


Standing genetic variation and the evolution of drug resistance in HIV.

Pennings PS - PLoS Comput. Biol. (2012)

The probability that resistance mutations are detected in women treated for prevention of mother-to-child transmission.The probability that resistance mutations are detected 6 to 8 weeks after treatment with single dose nevirapine. Black crosses are data from single studies, grey bars with estimated standard error are percentages for all studies combined (the number of patients that were used to calculate this percentage is indicated at the top of the graph). Red circles with standard error are results from 1000 simulations and the black squares are analytical predictions. Parameter values as in table 2.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3369920&req=5

pcbi-1002527-g003: The probability that resistance mutations are detected in women treated for prevention of mother-to-child transmission.The probability that resistance mutations are detected 6 to 8 weeks after treatment with single dose nevirapine. Black crosses are data from single studies, grey bars with estimated standard error are percentages for all studies combined (the number of patients that were used to calculate this percentage is indicated at the top of the graph). Red circles with standard error are results from 1000 simulations and the black squares are analytical predictions. Parameter values as in table 2.
Mentions: We identified 23 published studies that reported on NVP resistance 6 to 8 weeks after women were treated with sdNVP. Several of the studies directly compared two different treatment options. We found at least three studies for each of the four different treatment options. An overview of the studies can be found in table S2 in the supplementary text S2. For each study we recorded which of the four treatment options was used and in how many of the patients NVP resistance mutations were detected using simple Sanger (population) sequencing (we excluded studies that only recorded deep-sequencing or allele-specific PCR results, as there were too few of those to allow us to compare the treatment options). For each of the four treatment options, we also calculated the overall probability that resistance mutations were detected in a patient (simply by summing the number of patients with resistance and summing the total number of patients in the studies). We found that sdNVP leads to detectable resistance mutations in 39% of 952 patients, ZDV/sdNVP leads to detectable resistance mutations in 22% of 888 patients, adding two drugs during and after labor (sdNVP/PP) lead to detectable resistance mutations in 7.8% of 372 patients and ZDV/sdNVP/PP lead to detectable resistance mutations in none of 292 patients (see figure 3).

Bottom Line: We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters under the assumption that treatment failure is caused by the fixation of a single drug resistance mutation.We find that both the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-arameters which determine the probability that resistance evolves from standing genetic variation.Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.

View Article: PubMed Central - PubMed

Affiliation: Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America. pennings@fas.harvard.edu

ABSTRACT
Drug resistance remains a major problem for the treatment of HIV. Resistance can occur due to mutations that were present before treatment starts or due to mutations that occur during treatment. The relative importance of these two sources is unknown. Resistance can also be transmitted between patients, but this process is not considered in the current study. We study three different situations in which HIV drug resistance may evolve: starting triple-drug therapy, treatment with a single dose of nevirapine and interruption of treatment. For each of these three cases good data are available from literature, which allows us to estimate the probability that resistance evolves from standing genetic variation. Depending on the treatment we find probabilities of the evolution of drug resistance due to standing genetic variation between 0 and 39%. For patients who start triple-drug combination therapy, we find that drug resistance evolves from standing genetic variation in approximately 6% of the patients. We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters under the assumption that treatment failure is caused by the fixation of a single drug resistance mutation. We find that both the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-arameters which determine the probability that resistance evolves from standing genetic variation. Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.

Show MeSH
Related in: MedlinePlus