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Modeling the Effects of Morphine on Simian Immunodeficiency Virus Dynamics

View Article: PubMed Central - PubMed

ABSTRACT

Complications of HIV-1 infection in individuals who utilize drugs of abuse is a significant problem, because these drugs have been associated with higher virus replication and accelerated disease progression as well as severe neuropathogenesis. To gain further insight it is important to quantify the effects of drugs of abuse on HIV-1 infection dynamics. Here, we develop a mathematical model that incorporates experimentally observed effects of morphine on inducing HIV-1 co-receptor expression. For comparison we also considered viral dynamic models with cytolytic or noncytolytic effector cell responses. Based on the small sample size Akaike information criterion, these models were inferior to the new model based on changes in co-receptor expression. The model with morphine affecting co-receptor expression agrees well with the experimental data from simian immunodeficiency virus infections in morphine-addicted macaques. Our results show that morphine promotes a target cell subpopulation switch from a lower level of susceptibility to a state that is about 2-orders of magnitude higher in susceptibility to SIV infection. As a result, the proportion of target cells with higher susceptibility remains extremely high in morphine conditioning. Such a morphine-induced population switch not only has adverse effects on the replication rate, but also results in a higher steady state viral load and larger CD4 count drops. Moreover, morphine conditioning may pose extra obstacles to controlling viral load during antiretroviral therapy, such as pre-exposure prophylaxis and post infection treatments. This study provides, for the first time, a viral dynamics model, viral dynamics parameters, and related analytical and simulation results for SIV dynamics under drugs of abuse.

No MeSH data available.


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Dependence of the value of R0 on ε, efficacy of ART.Parameters given in Table 2 are used for computation of R0. The dashed-dot line represents the control group while the solid line represents the morphine group.
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pcbi.1005127.g005: Dependence of the value of R0 on ε, efficacy of ART.Parameters given in Table 2 are used for computation of R0. The dashed-dot line represents the control group while the solid line represents the morphine group.

Mentions: While morphine does not seem to play a role in determining whether infection is established or not as R0 > 1 in both groups, a significantly higher R0 value in the morphine group comes into play when some interventions, such as antiretroviral therapy as pre-exposure prophylaxis (PrEP), are considered. If ε is the efficacy of PrEP, then ε > 1 − 1/R0 is needed for successful control of infection (i.e., for bringing the R0 value to less than 1). Thus, we estimate that at least 52% effective PrEP can control infection in the control group, while at least 90% efficacy of PrEP is required in the morphine group. Fig 5 shows how R0 depends on PrEP efficacy. These results suggest that morphine can decrease the effectiveness of PrEP in people who abuse drugs.


Modeling the Effects of Morphine on Simian Immunodeficiency Virus Dynamics
Dependence of the value of R0 on ε, efficacy of ART.Parameters given in Table 2 are used for computation of R0. The dashed-dot line represents the control group while the solid line represents the morphine group.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036892&req=5

pcbi.1005127.g005: Dependence of the value of R0 on ε, efficacy of ART.Parameters given in Table 2 are used for computation of R0. The dashed-dot line represents the control group while the solid line represents the morphine group.
Mentions: While morphine does not seem to play a role in determining whether infection is established or not as R0 > 1 in both groups, a significantly higher R0 value in the morphine group comes into play when some interventions, such as antiretroviral therapy as pre-exposure prophylaxis (PrEP), are considered. If ε is the efficacy of PrEP, then ε > 1 − 1/R0 is needed for successful control of infection (i.e., for bringing the R0 value to less than 1). Thus, we estimate that at least 52% effective PrEP can control infection in the control group, while at least 90% efficacy of PrEP is required in the morphine group. Fig 5 shows how R0 depends on PrEP efficacy. These results suggest that morphine can decrease the effectiveness of PrEP in people who abuse drugs.

View Article: PubMed Central - PubMed

ABSTRACT

Complications of HIV-1 infection in individuals who utilize drugs of abuse is a significant problem, because these drugs have been associated with higher virus replication and accelerated disease progression as well as severe neuropathogenesis. To gain further insight it is important to quantify the effects of drugs of abuse on HIV-1 infection dynamics. Here, we develop a mathematical model that incorporates experimentally observed effects of morphine on inducing HIV-1 co-receptor expression. For comparison we also considered viral dynamic models with cytolytic or noncytolytic effector cell responses. Based on the small sample size Akaike information criterion, these models were inferior to the new model based on changes in co-receptor expression. The model with morphine affecting co-receptor expression agrees well with the experimental data from simian immunodeficiency virus infections in morphine-addicted macaques. Our results show that morphine promotes a target cell subpopulation switch from a lower level of susceptibility to a state that is about 2-orders of magnitude higher in susceptibility to SIV infection. As a result, the proportion of target cells with higher susceptibility remains extremely high in morphine conditioning. Such a morphine-induced population switch not only has adverse effects on the replication rate, but also results in a higher steady state viral load and larger CD4 count drops. Moreover, morphine conditioning may pose extra obstacles to controlling viral load during antiretroviral therapy, such as pre-exposure prophylaxis and post infection treatments. This study provides, for the first time, a viral dynamics model, viral dynamics parameters, and related analytical and simulation results for SIV dynamics under drugs of abuse.

No MeSH data available.


Related in: MedlinePlus