Limits...
A model of HIV drug resistance driven by heterogeneities in host immunity and adherence patterns.

Bershteyn A, Eckhoff PA - BMC Syst Biol (2013)

Bottom Line: Population transmission models of antiretroviral therapy (ART) and pre-exposure prophylaxis (PrEP) use simplistic assumptions--typically constant, homogeneous rates--to represent the short-term risk and long-term effects of drug resistance.In the case of accidental PrEP use during infection, rapid transitions between adherence states and/or weak immunity fortifies the "memory" of previous PrEP exposure, increasing the risk of future drug resistance.This model framework provides a means for analyzing individual-level risks of drug resistance and implementing heterogeneities among hosts, thereby achieving a crucial prerequisite for improving population-level models of drug resistance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Epidemiological Modeling Group, Intellectual Ventures Laboratory, Washington, USA. abershteyn@intven.com

ABSTRACT

Background: Population transmission models of antiretroviral therapy (ART) and pre-exposure prophylaxis (PrEP) use simplistic assumptions--typically constant, homogeneous rates--to represent the short-term risk and long-term effects of drug resistance. In contrast, within-host models of drug resistance allow for more detailed dynamics of host immunity, latent reservoirs of virus, and drug PK/PD. Bridging these two levels of modeling detail requires an understanding of the "levers"--model parameters or combinations thereof--that change only one independent observable at a time. Using the example of accidental tenofovir-based pre-exposure prophyaxis (PrEP) use during HIV infection, we will explore methods of implementing host heterogeneities and their long-term effects on drug resistance.

Results: We combined and extended existing models of virus dynamics by incorporating pharmacokinetics, pharmacodynamics, and adherence behavior. We identified two "levers" associated with the host immune pressure against the virus, which can be used to independently modify the setpoint viral load and the shape of the acute phase viral load peak. We propose parameter relationships that can explain differences in acute and setpoint viral load among hosts, and demonstrate their influence on the rates of emergence and reversion of drug resistance. The importance of these dynamics is illustrated by modeling long-lived latent reservoirs of virus, through which past intervals of drug resistance can lead to failure of suppressive drug regimens. Finally, we analyze assumptions about temporal patterns of drug adherence and their impact on resistance dynamics, finding that with the same overall level of adherence, the dwell times in drug-adherent versus not-adherent states can alter the levels of drug-resistant virus incorporated into latent reservoirs.

Conclusions: We have shown how a diverse range of observable viral load trajectories can be produced from a basic model of virus dynamics using immunity-related "levers". Immune pressure, in turn, influences the dynamics of drug resistance, with increased immune activity delaying drug resistance and driving more rapid return to dominance of drug-susceptible virus after drug cessation. Both immune pressure and patterns of drug adherence influence the long-term risk of drug resistance. In the case of accidental PrEP use during infection, rapid transitions between adherence states and/or weak immunity fortifies the "memory" of previous PrEP exposure, increasing the risk of future drug resistance. This model framework provides a means for analyzing individual-level risks of drug resistance and implementing heterogeneities among hosts, thereby achieving a crucial prerequisite for improving population-level models of drug resistance.

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Long-lived latently infected cells “remember” drug resistance. Experiments begin with a variable duration of daily TDF monotherapy applied with perfect adherence (pink regions), followed by a decade without treatment (yellow region), and finally, five years of suppressive therapy (1000-fold reduction in viral replication, blue region). (a) In the model without latency, counts of free virus (v, solid line for WT and dashed line for mutant) and cells with incorporated viral DNA (y, dotted line for mutant) are shown for a 15-year period beginning with 90 days of daily TDF monotherapy. The system returns to equilibrium shortly after monotherapy cessation. When a latently infected compartment w is added, the number of cells with latently incorporated mutant virus grows throughout a monotherapy exposure of 30 days (b), 90 days (c), or 365 days (d). For the decade following monotherapy exposure, the reservoir declines while being replaced with WT latently infected cells. When suppressive therapy is applied for the final five years, the latent reservoir provides the dominant source of virus. In (b), the level of mutant virus plateaus approximately 7 years after monotherapy cessation because the latent reservoir becomes a smaller source of mutants than back-mutation of replicating virus. (e) Longer monotherapy exposure produces more mutant virus in the latent reservoir after two years of suppressive therapy. The fraction of mutant free virions, though also increased by long monotherapy, is lower than the fraction in the latent compartment due to the reduced replicative capacity of the mutant. (f) For a 90-day interval of monotherapy, increasing immune pressure reduces the fraction of drug-resistant free virus and latently infected cells, but loses any incremental effect at p>10-5. This is because, similarly to (b), back-mutation of replicating WT virus becomes a larger source of latently incorporated mutants during the untreated (yellow) interval.
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Figure 4: Long-lived latently infected cells “remember” drug resistance. Experiments begin with a variable duration of daily TDF monotherapy applied with perfect adherence (pink regions), followed by a decade without treatment (yellow region), and finally, five years of suppressive therapy (1000-fold reduction in viral replication, blue region). (a) In the model without latency, counts of free virus (v, solid line for WT and dashed line for mutant) and cells with incorporated viral DNA (y, dotted line for mutant) are shown for a 15-year period beginning with 90 days of daily TDF monotherapy. The system returns to equilibrium shortly after monotherapy cessation. When a latently infected compartment w is added, the number of cells with latently incorporated mutant virus grows throughout a monotherapy exposure of 30 days (b), 90 days (c), or 365 days (d). For the decade following monotherapy exposure, the reservoir declines while being replaced with WT latently infected cells. When suppressive therapy is applied for the final five years, the latent reservoir provides the dominant source of virus. In (b), the level of mutant virus plateaus approximately 7 years after monotherapy cessation because the latent reservoir becomes a smaller source of mutants than back-mutation of replicating virus. (e) Longer monotherapy exposure produces more mutant virus in the latent reservoir after two years of suppressive therapy. The fraction of mutant free virions, though also increased by long monotherapy, is lower than the fraction in the latent compartment due to the reduced replicative capacity of the mutant. (f) For a 90-day interval of monotherapy, increasing immune pressure reduces the fraction of drug-resistant free virus and latently infected cells, but loses any incremental effect at p>10-5. This is because, similarly to (b), back-mutation of replicating WT virus becomes a larger source of latently incorporated mutants during the untreated (yellow) interval.

Mentions: To test this hypothesis about the dynamics of the latency-embellished model, we simulated an interval of monotherapy, followed by one decade of untreated infection and, finally, an interval of prolonged suppressive therapy. The delay of one decade allows the very long-term effects of past drug resistance to be evaluated. Suppressive therapy is assumed to be a regimen against which the single mutations that exist in all infected individuals do not confer resistance, such as triple-drug highly active antirectroviral therapy (HAART). (Any given single-position mutant is almost guaranteed to exist in an infected individual due to the high error rate of reverse transcriptase, but the pre-existance of a mutant resistant to all components of HAART is unlikely [32]). Rather than modeling the pharmacokinetics of all three drugs in detail, we used a simple caricature for suppressive therapy in which we reduced the burst size of the virus by 1000-fold. As shown in Figure 4a, this rapidly drove the free virus and the activated, productively infected cell populations toward extinction. When the long-lived latent compartment w was added, as in Figure 4b-d, the latent reservoir maintained a very low-level viremia, representing the source of potential re-activation of virus that is observed after treatment cessation or failure.


A model of HIV drug resistance driven by heterogeneities in host immunity and adherence patterns.

Bershteyn A, Eckhoff PA - BMC Syst Biol (2013)

Long-lived latently infected cells “remember” drug resistance. Experiments begin with a variable duration of daily TDF monotherapy applied with perfect adherence (pink regions), followed by a decade without treatment (yellow region), and finally, five years of suppressive therapy (1000-fold reduction in viral replication, blue region). (a) In the model without latency, counts of free virus (v, solid line for WT and dashed line for mutant) and cells with incorporated viral DNA (y, dotted line for mutant) are shown for a 15-year period beginning with 90 days of daily TDF monotherapy. The system returns to equilibrium shortly after monotherapy cessation. When a latently infected compartment w is added, the number of cells with latently incorporated mutant virus grows throughout a monotherapy exposure of 30 days (b), 90 days (c), or 365 days (d). For the decade following monotherapy exposure, the reservoir declines while being replaced with WT latently infected cells. When suppressive therapy is applied for the final five years, the latent reservoir provides the dominant source of virus. In (b), the level of mutant virus plateaus approximately 7 years after monotherapy cessation because the latent reservoir becomes a smaller source of mutants than back-mutation of replicating virus. (e) Longer monotherapy exposure produces more mutant virus in the latent reservoir after two years of suppressive therapy. The fraction of mutant free virions, though also increased by long monotherapy, is lower than the fraction in the latent compartment due to the reduced replicative capacity of the mutant. (f) For a 90-day interval of monotherapy, increasing immune pressure reduces the fraction of drug-resistant free virus and latently infected cells, but loses any incremental effect at p>10-5. This is because, similarly to (b), back-mutation of replicating WT virus becomes a larger source of latently incorporated mutants during the untreated (yellow) interval.
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3643872&req=5

Figure 4: Long-lived latently infected cells “remember” drug resistance. Experiments begin with a variable duration of daily TDF monotherapy applied with perfect adherence (pink regions), followed by a decade without treatment (yellow region), and finally, five years of suppressive therapy (1000-fold reduction in viral replication, blue region). (a) In the model without latency, counts of free virus (v, solid line for WT and dashed line for mutant) and cells with incorporated viral DNA (y, dotted line for mutant) are shown for a 15-year period beginning with 90 days of daily TDF monotherapy. The system returns to equilibrium shortly after monotherapy cessation. When a latently infected compartment w is added, the number of cells with latently incorporated mutant virus grows throughout a monotherapy exposure of 30 days (b), 90 days (c), or 365 days (d). For the decade following monotherapy exposure, the reservoir declines while being replaced with WT latently infected cells. When suppressive therapy is applied for the final five years, the latent reservoir provides the dominant source of virus. In (b), the level of mutant virus plateaus approximately 7 years after monotherapy cessation because the latent reservoir becomes a smaller source of mutants than back-mutation of replicating virus. (e) Longer monotherapy exposure produces more mutant virus in the latent reservoir after two years of suppressive therapy. The fraction of mutant free virions, though also increased by long monotherapy, is lower than the fraction in the latent compartment due to the reduced replicative capacity of the mutant. (f) For a 90-day interval of monotherapy, increasing immune pressure reduces the fraction of drug-resistant free virus and latently infected cells, but loses any incremental effect at p>10-5. This is because, similarly to (b), back-mutation of replicating WT virus becomes a larger source of latently incorporated mutants during the untreated (yellow) interval.
Mentions: To test this hypothesis about the dynamics of the latency-embellished model, we simulated an interval of monotherapy, followed by one decade of untreated infection and, finally, an interval of prolonged suppressive therapy. The delay of one decade allows the very long-term effects of past drug resistance to be evaluated. Suppressive therapy is assumed to be a regimen against which the single mutations that exist in all infected individuals do not confer resistance, such as triple-drug highly active antirectroviral therapy (HAART). (Any given single-position mutant is almost guaranteed to exist in an infected individual due to the high error rate of reverse transcriptase, but the pre-existance of a mutant resistant to all components of HAART is unlikely [32]). Rather than modeling the pharmacokinetics of all three drugs in detail, we used a simple caricature for suppressive therapy in which we reduced the burst size of the virus by 1000-fold. As shown in Figure 4a, this rapidly drove the free virus and the activated, productively infected cell populations toward extinction. When the long-lived latent compartment w was added, as in Figure 4b-d, the latent reservoir maintained a very low-level viremia, representing the source of potential re-activation of virus that is observed after treatment cessation or failure.

Bottom Line: Population transmission models of antiretroviral therapy (ART) and pre-exposure prophylaxis (PrEP) use simplistic assumptions--typically constant, homogeneous rates--to represent the short-term risk and long-term effects of drug resistance.In the case of accidental PrEP use during infection, rapid transitions between adherence states and/or weak immunity fortifies the "memory" of previous PrEP exposure, increasing the risk of future drug resistance.This model framework provides a means for analyzing individual-level risks of drug resistance and implementing heterogeneities among hosts, thereby achieving a crucial prerequisite for improving population-level models of drug resistance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Epidemiological Modeling Group, Intellectual Ventures Laboratory, Washington, USA. abershteyn@intven.com

ABSTRACT

Background: Population transmission models of antiretroviral therapy (ART) and pre-exposure prophylaxis (PrEP) use simplistic assumptions--typically constant, homogeneous rates--to represent the short-term risk and long-term effects of drug resistance. In contrast, within-host models of drug resistance allow for more detailed dynamics of host immunity, latent reservoirs of virus, and drug PK/PD. Bridging these two levels of modeling detail requires an understanding of the "levers"--model parameters or combinations thereof--that change only one independent observable at a time. Using the example of accidental tenofovir-based pre-exposure prophyaxis (PrEP) use during HIV infection, we will explore methods of implementing host heterogeneities and their long-term effects on drug resistance.

Results: We combined and extended existing models of virus dynamics by incorporating pharmacokinetics, pharmacodynamics, and adherence behavior. We identified two "levers" associated with the host immune pressure against the virus, which can be used to independently modify the setpoint viral load and the shape of the acute phase viral load peak. We propose parameter relationships that can explain differences in acute and setpoint viral load among hosts, and demonstrate their influence on the rates of emergence and reversion of drug resistance. The importance of these dynamics is illustrated by modeling long-lived latent reservoirs of virus, through which past intervals of drug resistance can lead to failure of suppressive drug regimens. Finally, we analyze assumptions about temporal patterns of drug adherence and their impact on resistance dynamics, finding that with the same overall level of adherence, the dwell times in drug-adherent versus not-adherent states can alter the levels of drug-resistant virus incorporated into latent reservoirs.

Conclusions: We have shown how a diverse range of observable viral load trajectories can be produced from a basic model of virus dynamics using immunity-related "levers". Immune pressure, in turn, influences the dynamics of drug resistance, with increased immune activity delaying drug resistance and driving more rapid return to dominance of drug-susceptible virus after drug cessation. Both immune pressure and patterns of drug adherence influence the long-term risk of drug resistance. In the case of accidental PrEP use during infection, rapid transitions between adherence states and/or weak immunity fortifies the "memory" of previous PrEP exposure, increasing the risk of future drug resistance. This model framework provides a means for analyzing individual-level risks of drug resistance and implementing heterogeneities among hosts, thereby achieving a crucial prerequisite for improving population-level models of drug resistance.

Show MeSH
Related in: MedlinePlus