Rate of HIV-1 decline following antiretroviral therapy is related to viral load at baseline and drug regimen

Quantifying the Dynamics of HIV Decline in Perinatally Infected Neonates on Antiretroviral Therapy

BACKGROUND

Mathematical modeling has provided important insights into HIV infection dynamics in adults undergoing antiretroviral treatment (ART). However, much less is known about the corresponding dynamics in perinatally infected neonates initiating early ART.

SETTING

From 2014 to 2017, HIV viral load (VL) was monitored in 122 perinatally infected infants identified at birth and initiating ART within a median of 2 days. Pretreatment infant and maternal covariates, including CD4 T cell counts and percentages, were also measured.

METHODS

From the initial cohort, 53 infants demonstrated consistent decline and suppressed VL below the detection threshold (20 copies mL) within 1 year. For 43 of these infants with sufficient VL data, we fit a mathematical model describing the loss of short-lived and long-lived infected cells during ART. We then estimated the lifespans of infected cells and the time to viral suppression, and tested for correlations with pretreatment covariates.

RESULTS

Most parameters governing the kinetics of VL decline were consistent with those obtained previously from adults and other infants. However, our estimates of the lifespan of short-lived infected cells were longer than published values. This difference may reflect sparse sampling during the early stages of VL decline, when the loss of short-lived cells is most apparent. In addition, infants with higher pretreatment CD4 percentage or lower pretreatment VL trended toward more rapid viral suppression.

CONCLUSIONS

HIV dynamics in perinatally infected neonates initiating early ART are broadly similar to those observed in other age groups. Accelerated viral suppression is also associated with higher CD4 percentage and lower VL.

Interactive Fuzzy Fractional Differential Equation: Application on HIV Dynamics

This work presents an application of interactive fuzzy fractional differential equation, with Caputo derivative, to an HIV model for seropositive individuals under antiretroviral treatment. The initial condition of the model is given by a fuzzy number and the differentiability is given by a fuzzy interactive derivative. A discussion about the model considering these notions are presented. Finally, a numerical solution to the problem is provided, in order to illustrate the results.

HIV Dynamics Under Antiretroviral Treatment with Interactivity

This manuscript presents a model for HIV dynamics of seropositive individuals under antiretroviral treatment described from fuzzy set theory by two different approaches considering interactivity: differential equation with interactive derivative and differential equation with Fréchet derivative. It also establishes an identity between interactive derivative and fuzzy Fréchet derivative. With this identity, we establish when the solutions of the two differential equations coincide. Lastly, we present biological interpretations for both cases.

Virologic failure is uncommon after treatment initiation during acute HIV infection

OBJECTIVE

In chronic HIV infection, initiation of antiretroviral therapy (ART) typically induces swift HIV RNA declines and virologic suppression within 24 weeks. The objective of this study was to investigate viral dynamics and common criteria for treatment success after ART initiation during acute HIV infection (AHI).

METHODS

Participants were prospectively enrolled and offered ART during AHI from May 2009-June 2015 in Bangkok, Thailand. Regimens included tenofovir, lamivudine or emtricitabine, and efavirenz with or without raltegravir and maraviroc. Participants were monitored for several HIV RNA end points: one-log reduction at week 2; two-log reduction at week 4; less than 1000 copies/ml at week 24; and less than 200 copies/ml at week 24. Factors associated with each end point, time to suppression, and virologic blips were explored.

RESULTS

Two hundred and sixty-four Thai participants initiated ART during AHI. Their median age was 27 years and 96% were men. At 2 weeks, 6.5% had not achieved a one-log reduction in HIV RNA. At 4 weeks, 11.0% had not achieved a two-log reduction. At 24 weeks, 1.1% had not achieved HIV RNA less than 1000 copies/ml and 1.5% had not achieved HIV RNA less than 200 copies/ml. Participants who initiated ART during Fiebig I demonstrated a shorter median time to virologic suppression than did all other stages combined, [4 (interquartile range 2-8) vs. 8 (interquartile range 4-12) weeks, P < 0.001] and 7.3% had subsequent blips (16.1% in other stages, P = 0.23).

CONCLUSION

Virologic failure is uncommon in individuals who initiate ART during AHI. ART initiation during AHI is efficacious and clinicians can monitor for virologic failure after 24 weeks of therapy.

Predicting virological decay in patients starting combination antiretroviral therapy

OBJECTIVE

Model trajectories of viral load measurements from time of starting combination antiretroviral therapy (cART), and use the model to predict whether patients will achieve suppressed viral load (≤200 copies/ml) within 6-months of starting cART.

DESIGN

Prospective cohort study including HIV-positive adults (UK Collaborative HIV Cohort Study).

METHODS

Eligible patients were antiretroviral naive and started cART after 1997. Random effects models were used to estimate viral load trends. Patients were randomly selected to form a validation dataset with those remaining used to fit the model. We evaluated predictions of suppression using indices of diagnostic test performance.

RESULTS

Of 9562 eligible patients 6435 were used to fit the model and 3127 for validation. Mean log10 viral load trajectories declined rapidly during the first 2 weeks post-cART, moderately between 2 weeks and 3 months, and more slowly thereafter. Higher pretreatment viral load predicted steeper declines, whereas older age, white ethnicity, and boosted protease inhibitor/non-nucleoside reverse transcriptase inhibitors based cART-regimen predicted a steeper decline from 3 months onwards. Specificity of predictions and the diagnostic odds ratio substantially improved when predictions were based on viral load measurements up to the 4-month visit compared with the 2 or 3-month visits. Diagnostic performance improved when suppression was defined by two consecutive suppressed viral loads compared with one.

CONCLUSIONS

Viral load measurements can be used to predict if a patient will be suppressed by 6-month post-cART. Graphical presentations of this information could help clinicians decide the optimum time to switch treatment regimen during the first months of cART.

Molecular clock of HIV-1 envelope genes under early immune selection

Background

The molecular clock hypothesis that genes or proteins evolve at a constant rate is a key tool to reveal phylogenetic relationships among species. Using the molecular clock, we can trace an infection back to transmission using HIV-1 sequences from a single time point. Whether or not a strict molecular clock applies to HIV-1’s early evolution in the presence of immune selection has not yet been fully examined.

Results

We identified molecular clock signatures from 1587 previously published HIV-1 full envelope gene sequences obtained since acute infection in 15 subjects. Each subject’s sequence diversity linearly increased during the first 150 days post infection, with rates ranging from \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1.54 \times 10^{ - 5}$$\end{document}1.54×10-5 to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3.91 \times 10^{ - 5}$$\end{document}3.91×10-5 with a mean of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2.69 \times 10^{ - 5}$$\end{document}2.69×10-5 per base per day. The rate of diversification for 12 out of the 15 subjects was comparable to the neutral evolution rate. While temporal diversification was consistent with evolution patterns in the absence of selection, mutations from the founder virus were highly clustered on statistically identified selection sites, which diversified more than 65 times faster than non-selection sites. By mathematically quantifying deviations from the molecular clock under various selection scenarios, we demonstrate that the deviation from a constant clock becomes negligible as multiple escape lineages emerge. The most recent common ancestor of a virus pair from distinct escape lineages is most likely the transmitted founder virus, indicating that HIV-1 molecular dating is feasible even after the founder viruses are no longer detectable.

Conclusions

The ability of HIV-1 to escape from immune surveillance in many different directions is the driving force of molecular clock persistence. This finding advances our understanding of the robustness of HIV-1’s molecular clock under immune selection, implying the potential for molecular dating.

Electronic supplementary material

The online version of this article (doi:10.1186/s12977-016-0269-6) contains supplementary material, which is available to authorized users.

Efficacy of generic highly active antiretroviral therapy in HIV-1 infected individuals in Nigeria

CD4 T lymphocyte and plasma HIV RNA parameters have been used to monitor disease progression, and predict clinical course in HIV infection. Initial evaluation of these parameters was conducted in the western countries where accessible ARVs, circulating HIV subtypes and mode of transmission are different from the situation in Nigeria. This study appraised these parameters, and efficacy of generic ARVs. Consenting 106 HIV infected ARV naïve patients were enrolled. CD4 T lymphocyte and plasma HIV RNA levels were determined at interval for 24 months. Ninety eight (92.5%) of the patients who completed the follow up in strict adherence to therapy guideline were included in the analysis. Baseline median CD4 T lymphocyte increased from 114 (Range: 6-330) to highest 357 (Range: 15-1036) cells/ μ L at 18 months of therapy, while baseline median plasma viral RNA declined from 4.6 (Range: 2.6-6.0) Log10 copies/mL to undetectable level within three months of therapy. Significant CD4 T-cell restoration and plasma viral RNA decline in the study population demonstrate efficacy of the generic HAART. The importance of combined use of both parameters for evaluation of immunologic and virologic responses to ART was confirmed.

Early HIV RNA decay during raltegravir-containing regimens exhibits two distinct subphases (1a and 1b)

BACKGROUND

We analyzed the early kinetics with integrase inhibitor treatment to gain new insights into viral dynamics.

METHODOLOGY

We analyzed data from 39 HIV-1 infected, treatment-naive, participants: 28 treated with raltegravir (RAL; multiple doses) monotherapy for 9 days, and 11 with RAL 400 mg twice daily and emtricitabine (200 mg daily)/tenofovir disoproxil fumarate (300 mg daily). Plasma HIV-1 RNA was measured frequently; the data was fitted using a mathematical model of viral dynamics distinguishing between infected cells with unintegrated HIV DNA and productively infected cells. Parameters were estimated using mixed-effect models.

RESULTS

RAL treatment led to a biphasic viral decline with a rapid first phase (1a) lasting approximately 5 days followed by a slower phase (1b). Phase 1a is attributed to the rapid elimination of productively infected cells. Phase 1b reflects the loss of infected cells with nonintegrated provirus due to cell loss and integration of HIV DNA. The half-lives of productively infected cells and of infected cells that had completed reverse transcription but had not yet integrated HIV DNA were approximately 19 h and between 3.6 and 5.8 days, respectively. The effectiveness of RAL in preventing proviral integration was 94% and 99.7%, for the combination therapy and monotherapy groups, respectively.

CONCLUSION

We found that the first phase of viral decay with RAL therapy was composed of two subphases corresponding to the half-lives of infected cells with integrated proviruses and with unintegrated HIV-DNA.

Mathematical modeling of multi-drugs therapy: a challenge for determining the optimal combinations of antiviral drugs

In the current era of antiviral drug therapy, combining multiple drugs is a primary approach for improving antiviral effects, reducing the doses of individual drugs, relieving the side effects of strong antiviral drugs, and preventing the emergence of drug-resistant viruses. Although a variety of new drugs have been developed for HIV, HCV and influenza virus, the optimal combinations of multiple drugs are incompletely understood. To optimize the benefits of multi-drugs combinations, we must investigate the interactions between the combined drugs and their target viruses. Mathematical models of viral infection dynamics provide an ideal tool for this purpose. Additionally, whether drug combinations computed by these models are synergistic can be assessed by two prominent drug combination theories, Loewe additivity and Bliss independence. By combining the mathematical modeling of virus dynamics with drug combination theories, we could show the principles by which drug combinations yield a synergistic effect. Here, we describe the theoretical aspects of multi-drugs therapy and discuss their application to antiviral research.

Mixed-Effects Models with Skewed Distributions for Time-Varying Decay Rate in HIV Dynamics

After initiation of treatment, HIV viral load has multiphasic changes, which indicates that the viral decay rate is a time-varying process. Mixed-effects models with different time-varying decay rate functions have been proposed in literature. However, there are two unresolved critical issues: (i) it is not clear which model is more appropriate for practical use, and (ii) the model random errors are commonly assumed to follow a normal distribution, which may be unrealistic and can obscure important features of within- and among-subject variations. Because asymmetry of HIV viral load data is still noticeable even after transformation, it is important to use a more general distribution family that enables the unrealistic normal assumption to be relaxed. We developed skew-elliptical (SE) Bayesian mixed-effects models by considering the model random errors to have an SE distribution. We compared the performance among five SE models that have different time-varying decay rate functions. For each model, we also contrasted the performance under different model random error assumption such as normal, Student-t, skew-normal or skew-t distribution. Two AIDS clinical trial data sets were used to illustrate the proposed models and methods. The results indicate that the model with a time-varying viral decay rate that has two exponential components is preferred. Among the four distribution assumptions, the skew-t and skew-normal models provided better fitting to the data than normal or Student-t model, suggesting that it is important to assume a model with a skewed distribution in order to achieve reasonable results when the data exhibit skewness.

Parameter Estimation for Differential Equation Models Using a Framework of Measurement Error in Regression Models

Differential equation (DE) models are widely used in many scientific fields that include engineering, physics and biomedical sciences. The so-called "forward problem", the problem of simulations and predictions of state variables for given parameter values in the DE models, has been extensively studied by mathematicians, physicists, engineers and other scientists. However, the "inverse problem", the problem of parameter estimation based on the measurements of output variables, has not been well explored using modern statistical methods, although some least squares-based approaches have been proposed and studied. In this paper, we propose parameter estimation methods for ordinary differential equation models (ODE) based on the local smoothing approach and a pseudo-least squares (PsLS) principle under a framework of measurement error in regression models. The asymptotic properties of the proposed PsLS estimator are established. We also compare the PsLS method to the corresponding SIMEX method and evaluate their finite sample performances via simulation studies. We illustrate the proposed approach using an application example from an HIV dynamic study.

Influence of HIV infection on cytomegalovirus-specific immunity: T-cell responses to pp65 and IE1 before and after HAART may reflect altered cytomegalovirus biology

BACKGROUND

Data are inconclusive whether treatment with HAART induces functional recovery of HIV-specific T-cells. Since the introduction of HAART, a marked decrease of cytomegalovirus (CMV) disease - for which untreated HIV-infected individuals are at increased risk - is observed, suggesting that this treatment influences CMV-specific T-cell immunity.

METHODS

To study potential functional recovery of HIV- and CMV-specific T-cells, CD4(+) and CD8(+) T-cell responses were measured longitudinally after in vitro expansion using gag, pp65 and IE1 peptide pools, during HIV infection and after long-term HAART.

RESULTS

HIV-specific T-cell function, measured by interferon (IFN)-γ production, was low after initiation of HAART. Interestingly, the cytotoxic function - measured by CD107a expression - of these T-cells temporarily increased after start of treatment, suggesting some functional recovery. The pp65-specific CD8(+) T-cell responses tended to decrease during HIV infection, whereas pp65-specific CD4(+) T-cell responses decreased upon treatment with HAART. Both pp65-specific CD4(+) and CD8(+) T-cell responses were low after initiation of HAART compared to healthy controls. By contrast, IE1-specific CD4(+) T-cell responses increased during the course of HIV infection. After initiation of HAART, IE1-specific T-cell responses decreased, but IE1-specific CD8(+) T-cells seemed increased compared to healthy controls.

CONCLUSIONS

This study suggests that HIV-infection leads to an altered CMV biology, affecting pp65- and IE1-specific T-cell responses in a different way, which is not restored by treatment with long-term HAART.

Hierarchical Bayesian inference for HIV dynamic differential equation models incorporating multiple treatment factors

Studies on HIV dynamics in AIDS research are very important in understanding the pathogenesis of HIV-1 infection and also in assessing the effectiveness of antiretroviral (ARV) treatment. Viral dynamic models can be formulated through a system of nonlinear ordinary differential equations (ODE), but there has been only limited development of statistical methodologies for inference. This article, motivated by an AIDS clinical study, discusses a hierarchical Bayesian nonlinear mixed-effects modeling approach to dynamic ODE models without a closed-form solution. In this model, we fully integrate viral load, medication adherence, drug resistance, pharmacokinetics, baseline covariates and time-dependent drug efficacy into the data analysis for characterizing long-term virologic responses. Our method is implemented by a data set from an AIDS clinical study. The results suggest that modeling HIV dynamics and virologic responses with consideration of time-varying clinical factors as well as baseline characteristics may be important for HIV/AIDS studies in providing quantitative guidance to better understand the virologic responses to ARV treatment and to help the evaluation of clinical trial design in response to existing therapies.

Cumulative viral load and virologic decay patterns after antiretroviral therapy in HIV-infected subjects influence CD4 recovery and AIDS

BACKGROUND

The impact of viral load (VL) decay and cumulative VL on CD4 recovery and AIDS after highly-active antiretroviral therapy (HAART) is unknown.

METHODS AND FINDINGS

Three virologic kinetic parameters (first year and overall exponential VL decay constants, and first year VL slope) and cumulative VL during HAART were estimated for 2,278 patients who initiated HAART in the U.S. Military HIV Natural History Study. CD4 and VL trajectories were computed using linear and nonlinear Generalized Estimating Equations models. Multivariate Poisson and linear regression models were used to determine associations of VL parameters with CD4 recovery, adjusted for factors known to correlate with immune recovery. Cumulative VL higher than the sample median was independently associated with an increased risk of AIDS (relative risk 2.38, 95% confidence interval 1.56-3.62, p<0.001). Among patients with VL suppression, first year VL decay and slope were independent predictors of early CD4 recovery (p = 0.001) and overall gain (p<0.05). Despite VL suppression, those with slow decay during the first year of HAART as well as during the entire therapy period (overall), in general, gained less CD4 cells compared to the other subjects (133 vs. 195.4 cells/µL; p = 0.001) even after adjusting for potential confounders.

CONCLUSIONS

In a cohort with free access to healthcare, independent of established predictors of AIDS and CD4 recovery during HAART, cumulative VL and virologic decay patterns were associated with AIDS and distinct aspects of CD4 reconstitution.

A DYNAMIC BAYESIAN NONLINEAR MIXED-EFFECTS MODEL OF HIV RESPONSE INCORPORATING MEDICATION ADHERENCE, DRUG RESISTANCE AND COVARIATES()

HIV dynamic studies have contributed significantly to the understanding of HIV pathogenesis and antiviral treatment strategies for AIDS patients. Establishing the relationship of virologic responses with clinical factors and covariates during long-term antiretroviral (ARV) therapy is important to the development of effective treatments. Medication adherence is an important predictor of the effectiveness of ARV treatment, but an appropriate determinant of adherence rate based on medication event monitoring system (MEMS) data is critical to predict virologic outcomes. The primary objective of this paper is to investigate the effects of a number of summary determinants of MEMS adherence rates on virologic response measured repeatedly over time in HIV-infected patients. We developed a mechanism-based differential equation model with consideration of drug adherence, interacted by virus susceptibility to drug and baseline characteristics, to characterize the long-term virologic responses after initiation of therapy. This model fully integrates viral load, MEMS adherence, drug resistance and baseline covariates into the data analysis. In this study we employed the proposed model and associated Bayesian nonlinear mixed-effects modeling approach to assess how to efficiently use the MEMS adherence data for prediction of virologic response, and to evaluate the predicting power of each summary metric of the MEMS adherence rates. In particular, we intend to address the questions: (i) how to summarize the MEMS adherence data for efficient prediction of virologic response after accounting for potential confounding factors such as drug resistance and covariates, and (ii) how to evaluate treatment effect of baseline characteristics interacted with adherence and other clinical factors. The approach is applied to an AIDS clinical trial involving 31 patients who had available data as required for the proposed model. Results demonstrate that the appropriate determinants of MEMS adherence rates are important in order to more efficiently predict virologic response, and investigations of adherence to ARV treatment would benefit from measuring not only adherence rate but also its summary metric assessment. Our study also shows that the mechanism-based dynamic model is powerful and effective to establish a relationship of virologic responses with medication adherence, virus resistance to drug and baseline covariates.

CD8+ lymphocytes control viral replication in SIVmac239-infected rhesus macaques without decreasing the lifespan of productively infected cells

While CD8+ T cells are clearly important in controlling virus replication during HIV and SIV infections, the mechanisms underlying this antiviral effect remain poorly understood. In this study, we assessed the in vivo effect of CD8+ lymphocyte depletion on the lifespan of productively infected cells during chronic SIVmac239 infection of rhesus macaques. We treated two groups of animals that were either CD8+ lymphocyte-depleted or controls with antiretroviral therapy, and used mathematical modeling to assess the lifespan of infected cells either in the presence or absence of CD8+ lymphocytes. We found that, in both early (day 57 post-SIV) and late (day 177 post-SIV) chronic SIV infection, depletion of CD8+ lymphocytes did not result in a measurable increase in the lifespan of either short- or long-lived productively infected cells in vivo. This result indicates that the presence of CD8+ lymphocytes does not result in a noticeably shorter lifespan of productively SIV-infected cells, and thus that direct cell killing is unlikely to be the main mechanism underlying the antiviral effect of CD8+ T cells in SIV-infected macaques with high virus replication.

Despite overwhelming evidence that CD8+ T cells are important in controlling virus replication during HIV and simian immunodeficiency virus (SIV) infections, the mechanisms responsible for this antiviral effect in vivo remain poorly understood. This lack of knowledge represents a key obstacle to our efforts to develop a CD8+ T cell-based AIDS vaccine. In this study, we implemented a new experimental system in which we determined the lifespan of productively SIV-infected cells in vivo, either in the presence or absence of CD8+ lymphocytes. The lifespan of productively infected cells was calculated based on the slope of the decline of SIV plasma viremia after initiation of ART using a widely accepted mathematical model. Using this novel approach, we determined that CD8+ lymphocytes control virus replication without noticeably decreasing the lifespan of productively infected cells, thus suggesting that the major mechanism of antiviral activity by CD8+ lymphocytes during pathogenic SIV infection may not be direct cell killing of productively SIV-infected cells.

Modelling of viral dynamics in hepatitis B and hepatitis C clinical trials

In the recent years, studies of hepatitis B (HBV) and hepatitis C virus (HCV) dynamics have drawn great attention as they provide insight into the process of virus elimination/production and of infected cells decay during antiviral treatment. Estimates of viral dynamic parameters may be used to determine the lifetime of HCV/HBV virions and of infected cells, to estimate how long patients need to be treated and to evaluate antiviral therapies. The implementation of viral dynamics studies is difficult because they involve an intensive blood-sampling schedule and subsequent viral load quantification. In the majority of these studies, a model proposed by Neumann et al. (Science 1998; 282:103-107) is used under various assumptions, such as ignoring the delay in initial viral load decay, assuming time-constant treatment efficacy in reducing virion production and/or complete blocking of new infections, etc. However, only recently the effect of some of these assumptions on the estimated parameters has been evaluated. In this paper we provide a detailed review of the model, its underlying assumptions as well as the assumptions usually made by researchers during the design and analysis of viral dynamics studies. Then, we investigate the effect of these assumptions on the estimated parameters using simulations and draw useful conclusions concerning the analysis of these studies. Real data examples from a clinical trial on hepatitis B are provided as illustrations.

Constraints on the dominant mechanism for HIV viral dynamics in patients on raltegravir

Background

Raltegravir is the first publicly released HIV integrase inhibitor. In clinical trials, patients on a raltegravir-based highly active antiretroviral therapy (HAART) regimen were observed to have 70% less viraemia in the second-phase decay of viraemia than patients on an efavirenz- based HAART regimen. Because of this accelerated decay of viraemia, raltegravir has been speculated to have greater antiretroviral activity than efavirenz. Alternative explanations for this phenomenon are also possible. For example, the stage in the viral life cycle at which raltegravir acts might explain the distinct viral dynamics produced by this drug.

Methods

In this report, we use a mathematical model of HIV viral dynamics to explore several hypotheses for why raltegravir causes different viral dynamics than efavirenz. Using the experimentally observed viral dynamics of raltegravir, we calculated constraints on the mechanisms possibly responsible for the unique viral dynamics produced by raltegravir.

Results

We predicted that the dominant mechanism for the 70% reduction in the second-phase viraemia is not antiviral efficacy but the stage of the HIV viral life cycle at which raltegravir acts. Furthermore, we found that the kinetic constraints placed on the identity of the virus-producing cells of the second phase were most consistent with monocytes/macrophages.

Conclusions

Our model predictions have important implications for the motivation behind the use of raltegravir and our understanding of the virus-producing cells of the second-phase viraemia. Our results also highlight that the viral dynamics produced by different antiretroviral drugs should not be directly compared with each other.

Estimating drug efficacy and viral dynamic parameters: HIV and HCV

Mathematical models have proven valuable in understanding the in vivo dynamics of human immunodeficiency virus type 1 (HIV-1), the virus that causes AIDS, and hepatitis C virus (HCV), the virus that causes hepatitis C infection. By comparing mathematical models with the data obtained from patients being treated with antiviral drugs, it has been possible to determine many quantitative features of these infections. The most dramatic finding has been that even though AIDS and hepatitis C are diseases that occur on a timescale of one or more decades, there are very rapid dynamical processes that occur on timescales of hours to days, as well as slower processes that occur on timescales of weeks to months. We show how dynamical modeling and parameter estimation techniques have uncovered these important features of HIV and HCV infection and subsequently impacted the way in which patients are treated with potent antiviral drugs. Published in 2007 by John Wiley & Sons, Ltd.

TAT-conjugated nanoparticles for the CNS delivery of anti-HIV drugs

We have shown that nanoparticles (NPs) conjugated to trans-activating transcriptor (TAT) peptide bypass the efflux action of P-glycoprotein and increase the transport of the encapsulated ritonavir, a protease inhibitor (PI), across the blood-brain-barrier (BBB) to the central nervous system (CNS). A steady increase in the drug parenchyma/capillary ratio over time without disrupting the BBB integrity suggests that TAT-conjugated NPs are first immobilized in the brain vasculature prior to their transport into parenchyma. Localization of NPs in the brain parenchyma was further confirmed with histological analysis of the brain sections. The brain drug level with conjugated NPs was 800-fold higher than that with drug in solution at two weeks. Drug clearance was seen within four weeks. In conclusion, TAT-conjugated NPs enhanced the CNS bioavailability of the encapsulated PI and maintained therapeutic drug levels in the brain for a sustained period that could be effective in reducing the viral load in the CNS, which acts as a reservoir for the replicating HIV-1 virus.

Optimal timing and duration of induction therapy for HIV-1 infection

The tradeoff between the need to suppress drug-resistant viruses and the problem of treatment toxicity has led to the development of various drug-sparing HIV-1 treatment strategies. Here we use a stochastic simulation model for viral dynamics to investigate how the timing and duration of the induction phase of induction–maintenance therapies might be optimized. Our model suggests that under a variety of biologically plausible conditions, 6–10 mo of induction therapy are needed to achieve durable suppression and maximize the probability of eradicating viruses resistant to the maintenance regimen. For induction regimens of more limited duration, a delayed-induction or -intensification period initiated sometime after the start of maintenance therapy appears to be optimal. The optimal delay length depends on the fitness of resistant viruses and the rate at which target-cell populations recover after therapy is initiated. These observations have implications for both the timing and the kinds of drugs selected for induction–maintenance and therapy-intensification strategies.

Clinicians treating HIV infection must balance the need to suppress viral replication against the harmful side effects and significant cost of antiretroviral therapy. Inadequate therapy often results in the emergence of resistant viruses and treatment failure. These difficulties are especially acute in resource-poor settings, where antiretroviral agents are limited. This has prompted an interest in induction–maintenance (IM) treatment strategies, in which brief intensive therapy is used to reduce host viral levels. Induction is followed by a simplified and more easily tolerated maintenance regimen. IM approaches remain an unproven concept in HIV therapy. We have developed a mathematical model to simulate clinical responses to antiretroviral drug therapy. We account for latent infection, partial drug efficacy, cross-resistance, viral recombination, and other factors. This model accurately reflects expected outcomes under single, double, and standard three-drug antiretroviral therapy. When applied to IM therapy, we find that (1) IM is expected to be successful beyond 3 y under a variety of conditions; (2) short-term induction therapy is optimally started several days to weeks after the start of maintenance; and (3) IM therapy may eradicate some preexisting drug-resistant viral strains from the host. Our simulations may help develop new treatment strategies and optimize future clinical trials.

Treatment response in acute/early infection versus advanced AIDS: equivalent first and second phases of HIV RNA decline

OBJECTIVE

Compare the initial phases of virologic decay when acute/early and advanced HIV-infected adults are administered the same treatment regimen.

DESIGN

Mathematical modeling of a previously completed prospective treatment pilot study involving treatment-naive patients with early and advanced immunosuppression.

METHODS

We analyzed data from a treatment protocol in which 18 individuals with acute or recent HIV-1 seroconversion and six patients with advanced AIDS were administered the same four-drug antiretroviral regimen. Initial treatment responses were compared by fitting a mathematical model to frequent viral load measurements in order to calculate the first and second phase kinetics of viral clearance, and also by comparing viral load suppression over 24 weeks. Patients were also comprehensively compared in terms of protease inhibitor drug levels, HIV-specific immune responses at baseline, and the presence of drug resistance-conferring mutations.

RESULTS

There was no statistically meaningful difference in first phase clearance of comparable high-level viremia in the two groups, whether protease inhibitor levels were inserted into the model or 100% antiviral drug effectiveness was assumed. In contrast, acute/early patients had inferior sustained responses than advanced patients, reflecting erratic adherence.

CONCLUSIONS

Despite many years of intervening immune destruction, the initial virologic decay on therapy appears to be the same at the extremes of the HIV disease spectrum.

Differential antiviral effect of PEG-interferon-alpha-2b on HIV and HCV in the treatment of HIV/HCV co-infected patients

OBJECTIVE

The major antiviral effect of interferon (IFN)-alpha on hepatitis C virus (HCV) is blocking of virion production from infected cells. We now investigate the previously unknown mechanism of action of IFN-alpha against HIV.

METHODS

HIV kinetics in parallel to HCV kinetics and IFN pharmacokinetics during pegylated-IFN-alpha-2b (1.5 microg/Kg q.w., PEG-IFN) and ribavirin (1-1.2 g daily) treatment in nine HIV patients co-infected with HCV genotype 1 were analyzed. In vivo modeling predictions of suppression of HIV replication by PEG-IFN in CD8-depleted peripheral blood mononuclear cells were verified by in vitro experiments.

RESULTS

HCV and HIV show different viral decline patterns after administration of PEG-IFN. Unlike the bi-phasic decline shown by HCV, HIV shows a slow continuous decline during the first week, with no rebound when PEG-IFN levels decline. Fitting of HIV kinetics with known half-lives of free virus and infected cells indicates that the major effect of IFN on HIV is to block de novo infection rather than to block virion production. The magnitude of the antiviral effect is similar (mean 1.1 log10 decline at 7 days) to those of direct anti-HIV drugs, but shows an inverse correlation with baseline viremia. In vitro studies show that preincubation with IFN renders a suppression of HIV replication superior to that of treatment postinfection, thus corroborating the mathematical analysis in vivo.

CONCLUSION

The complimentary antiviral properties of IFN-alpha and antiretroviral therapy suggest a role for pharmacokinetically improved formulations of IFN as part of salvage therapy for HIV-infected individuals.

Segmental modeling of changing viral load to assess drug resistance in HIV infection

Studies of viral dynamics are important to our understanding of the pathogenesis of HIV-1 infection and in assessment of the potency of antiretroviral therapies. Although many different viral dynamic models and methods for estimating viral dynamic parameters have been proposed and used in various studies, none has been entirely satisfactory. We propose here a segmental model to describe the viral load, and estimate the dynamic parameters by using a mixed-effects model. We address the relation between the baseline viral load and the decay rate of the first phase of viral load decay, and divide patients into three categories on the basis of their changing viral load patterns.

Analysis of relation between virologic responses and immunologic responses, patient's factors in AIDS clinical trials using a semiparametric mixed-effects model

In this article we propose to use a semiparametric mixed-effects model based on an exploratory analysis of clinical trial data for a study of the relation between virologic responses and immunologic markers such as CD4+ and CD8 counts, and host-specific factors in AIDS clinical trials. The regression spline technique, used for inference for parameters in the model, reduces the unknown nonparametric components to parametric functions. It is simple and straightforward to implement the procedures using readily available software, and parameter inference can be developed from standard parametric models. We apply the model and the proposed method to an AIDS clinical study. Our findings indicate that viral load level is positively related to baseline viral load level, negatively related to CD4+ cell counts, but unrelated to CD8 cell counts and patient's age neither.

Using mathematical modeling and control to develop structured treatment interruption strategies for HIV infection

The goal of this article is to suggest that mathematical models describing biological processes taking place within a patient over time can be used to design adaptive treatment strategies. We demonstrate using the key example of treatment strategies for human immunodeficiency virus type-1 (HIV) infection. Although there has been considerable progress in management of HIV infection using highly active antiretroviral therapies, continuous treatment with these agents involves significant cost and burden, toxicities, development of drug resistance, and problems with adherence; these latter complications are of particular concern in substance-abusing individuals. This has inspired interest in structured or supervised treatment interruption (STI) strategies, which involve cycles of treatment withdrawal and re-initiation. We argue that the most promising STI strategies are adaptive treatment strategies. We then describe how biological mechanisms governing the interaction over time between HIV and a patient's immune system may be represented by mathematical models and how control methods applied to these models can be used to design adaptive STI strategies seeking to maintain long-term suppression of the virus. We advocate that, when such mathematical representations of processes underlying a disease or disorder are available, they can be an important tool for suggesting adaptive treatment strategies for clinical study.

Multiple polyexponentials and quasipolynomials as empirical nonlinear regression models: a case study with HIV viral load data

Measurements of HIV1-RNA plasma concentrations are an important method of assessing patient response to anti-HIV1 treatment, and in most clinical trials of such treatments HIV1-RNA levels are assessed at regular intervals of time. HIV1-RNA levels in successfully treated patients tend to follow a standard pattern of biphasic decline-a rapid early decline in viral load, followed by a period of slower decline or a steady level. Fitting nonlinear regression models to these patterns of declining HIV1-RNA levels can be of value in comparing different treatment regimes and in predicting treatment outcome. Simple exponential-decline models can give an adequate fit to the typical pattern of HIV1-RNA decline, but we have explored the extent to which curve-fitting can be improved by using two novel nonlinear model forms. Specifically, we describe the fitting of multiple polyexponential and quasipolynomial forms to longitudinal HIV1-RNA plasma data collected in two recent trials of the novel anti-HIV1 treatment Fuzeon. We comment on the practicalities of fitting these nonlinear models, and compare the fit using various criteria.

A pharmacokinetic-pharmacodynamic model to optimize the phase IIa development program of maraviroc

OBJECTIVES

To use a viral dynamics model to compare the effectiveness of in vivo viral inhibition of several doses of maraviroc (MVC;UK-427,857) and to use a modeling approach to support design decisions for a monotherapy study using various dosing regimens of maraviroc given with and without food.

DESIGN

The pharmacokinetic-pharmacodynamic model was developed using clinical data from a first monotherapy study (study A4001007). This was a randomized, double-blind, placebo-controlled, multicenter study of maraviroc in 44 asymptomatic HIV-1-infected patients. Patients received maraviroc under food restrictions at 25 mg once daily or 50, 100, or 300 mg twice daily, or placebo for 10 days.

METHODS

Antiviral responses were assessed by measuring plasma HIV-1 RNA levels during screening, during randomization, at baseline, and daily during the 10 days of treatment and at days 11 to 15, 19, 22, 25, and 40. An integrated pharmacokinetic-pharmacodynamic model was developed using the mixed effects modeling approach with patients' pharmacokinetic profiles on the last day of treatment, HIV-1 RNA levels over time, and the individual viral susceptibility. The parameters derived from the viral dynamic model were used to calculate average viral inhibition fraction, decay rate of actively infected cells, and basic reproductive ratio for each treatment group. Monte Carlo simulation was then used to determine the distribution of viral load change across simulated patients over time for each regimen to be studied in another monotherapy study, A4001015.

RESULTS

The decline rate in the 300 mg twice daily group was comparable to that induced by potent protease inhibitor monotherapy, but was significantly slower than that in patients receiving combination therapy including both protease inhibitor and reverse transcriptase inhibitors. The efficacy of inhibition in vivo was estimated to range from 0.15 to 0.38 for the 25 mg once daily dose group and from 0.88 to 0.96 for the 300 mg twice daily dose group.

CONCLUSIONS

The model has aided the analysis and interpretation of the clinical data. The use of a model-based approach for selecting doses can accelerate drug development by replacing some arms or trials with simulations.

Density-dependent decay in HIV-1 dynamics

The decay of HIV-1-infected cell populations after treatment with antiretroviral therapy has been measured using simple exponential decay models. These models are unlikely to be realistic over periods longer than a few months, however, because the population dynamics of HIV are complex. We considered an alternate model developed by Perelson and colleagues that extends the standard model for biphasic viral load decline and allows for nonlinear log decay of infected cell populations. Using data from 6 children on highly active antiretroviral therapy (HAART) and a single parameter in the new model, the assumption of log linear decay of infected cell populations is tested. Our analysis indicates that the short-lived and long-lived infected cell populations do not decay according to a simple exponential model. Furthermore, the resulting estimates of time to eradication of infected cell compartments are dramatically longer than those previously reported (eg, decades vs. years for long-lived infected cell populations and years vs. weeks for short-lived infected cell populations). Furthermore, estimates of the second-phase decay rates are significantly different than 0 for most children when obtained using the Perelson biphasic decay model. In contrast, this rate is not significantly different than 0 when the density-dependent decay model is used for parameter estimation and inference. Thus, the density-dependent decay model but not the simple exponential decay model is consistent with recent data showing that even under consistent HAART-mediated suppression of viral replication, decay rates of infected cell reservoirs decay little over several years. This suggests that conclusions about long-term viral dynamics of HIV infection based on simple exponential decay models should be carefully re-evaluated.

Modeling long-term HIV dynamics and antiretroviral response: effects of drug potency, pharmacokinetics, adherence, and drug resistance

We propose a long-term HIV-1 dynamic model by considering drug potency, drug exposure, and drug susceptibility. Using a Bayesian approach, HIV-1 dynamic parameters were estimated by fitting the model to viral load data from a phase 1/2 randomized clinical study of 2 indinavir (IDV)/ritonavir (RTV)-containing highly active antiretroviral (ARV) therapy regimens in HIV-infected subjects who had previously failed protease inhibitor-containing ARV therapies. A large between-subject variation in estimated viral dynamic parameters was observed, even after accounting for variations in drug exposure and drug susceptibility, suggesting that characteristics of HIV-1 dynamics are host dependent. Significant correlations of baseline factors such as HIV-1 RNA levels and CD4 cell counts with viral dynamic parameters were found. These correlations coincide with biologic interaction mechanisms between HIV and the host immune system and also provide an explanation for the correlations between the baseline viral load and phase 1 viral decay rate, for which inconsistent results have been reported in the literature. The relations between viral dynamic parameters and virologic response were established, and these results suggest that viral dynamic parameters may play an important role in determining treatment success or failure. In particular, we estimated a drug efficacy threshold for each patient that can be used to assess whether an ARV regimen is potent enough to suppress HIV viruses in the individual patient. Our findings indicate that it is necessary to individualize the ARV regimen to treat HIV-1-infected patients. The proposed mathematic models and statistical techniques may provide a framework to simulate and predict antiviral response for individual patients.

Kinetics of hepatitis B viral load during 48 weeks of treatment with 600 mg vs 100 mg of lamivudine daily

Oral therapy for chronic hepatitis B remains suboptimal. Mathematical modelling of viral decay kinetics to rapidly assess potential antiviral regimens has proved valuable for human immunodeficiency virus and cytomegalovirus. We defined the kinetics of viral replication in 10 chronic hepatitis B patients randomized to lamivudine 100 mg vs 600 mg for 48 weeks. Viral decay kinetics conformed to a biphasic pattern in nine of 10 subjects. Persons receiving 600 mg daily of lamivudine exhibited a 1.6-fold faster decay rate in the infected cell compartment (0.028/day vs 0.017/day, P = 0.06) and a greater overall change in serum viral load when compared with those receiving 100 mg (4.06 vs 1.52 log(10) copies/mL, P = 0.08). More potent therapy appeared to result in more rapid decrease in the infected cell population. Studies using mathematical modelling of viral decay may be a useful method to evaluate single or combination therapy for HBV infection in vivo.

Viral and cellular dynamics in HIV disease

The control mechanisms that maintain a steady state viral load during chronic HIV-1 infection are critical to understanding the pathophysiology of HIV disease. The conceptual features of the two alternative models of viral control, referred to in this article as target cell limitation and immune control, are compared to the data regarding the viral and cellular dynamics of HIV-1 infection and the pattern of changes induced by effective antiretroviral drug therapy. The available data support the model that an antigen-driven immune response is the primary mechanism that limits viral growth in vivo.

Two phases of HIV RNA decay in CSF during initial days of multidrug therapy

BACKGROUND

Defining cellular and tissue sources of HIV-1 in CSF is important for understanding disease pathogenesis and optimal therapies for HIV infection in the brain.

OBJECTIVE

To identify the time of maximal viral decay in CSF during the initial days of antiretroviral therapy.

METHODS

Serial CSF and plasma data were available from four adults who underwent ultraintensive CSF sampling for 48 hours at baseline and again beginning 72 hours after starting antiretroviral therapy. Regression lines were generated using HIV-1 RNA data from 17 on-treatment serial CSF samples obtained at 3-hour intervals. Viral RNA was quantified by Nuclisens and Amplicor HIV-1 Monitor assays.

RESULTS

Extrapolation of regression lines intersected baseline below actual baseline CSF HIV-1 RNA concentrations, indicating that virus decayed most rapidly on days 1 through 3 with half-lives of no more than 0.9 to 2.8 days. Half-lives on days 4 and 5 ranged from 1.3 to 4.9 days. Plasma data also showed early rapid decay.

CONCLUSIONS

Multiple phases of viral decay suggest that virus in CSF originates from at least two sources during untreated, asymptomatic HIV-1 infection. The short half-life indicates that the primary source is CD4+ T cells. Sampling during days 1 through 3 and different stages of disease will better define sources of virus.

Glancing behind virus load variation in HIV-1 infection

Although the steady-state virus load during HIV-1 infection is remarkably stable within a patient, it displays variation over several orders of magnitude between patients. Despite intensive research, the host and virus factors that are responsible for the observed variation remain poorly understood. Comparison of model predictions with clinical data suggests that most of the variation in steady-state virus load between patients reflects variation of the net rate at which activated CD4 cells are produced.

TMC125 exerts similar initial antiviral potency as a five-drug, triple class antiretroviral regimen

OBJECTIVE

TMC125, a next generation, non-nucleoside reverse transcriptase inhibitor (NNRTI), demonstrated a remarkable decline of plasma HIV-1 RNA during a phase IIa study. We compared the initial rate of decline of plasma HIV-1 RNA achieved by TMC125 monotherapy with that of a triple class, five-drug regimen, containing drugs from all three currently licensed classes (zidovudine, lamivudine, abacavir, indinavir and nevirapine).

METHODS

The decline in plasma HIV-1 RNA of 12 HIV-1 infected, antiretroviral (ART) naive patients treated for 1 week with TMC125 monotherapy was compared with that observed in the ERA study (n = 11). The plasma HIV-1 RNA elimination rate constant was calculated based on at least four plasma HIV-1 RNA measurements during the first week of treatment (first-order elimination) and compared using the Student's t test.

RESULTS

Median ages were 23 and 38 years for TMC125 and ERA patients, respectively (P = 0.001), median baseline plasma HIV-1 RNA levels were 4.2 and 4.8 log10 copies/ml (P = 0.001) and median baseline CD4 T-cell counts were 458 x 10(6) and 360 x 10(6) cells/l (P = 0.08). The median plasma HIV-1 RNA elimination rate constant was 0.68/day in TMC125 treated patients, and 0.56/day in ERA participants (P = 0.24). The median decline in plasma HIV-1 RNA after 7 days was 1.92 and 1.76 log10 copies (P = 0.77) and the median increase of CD4 T cells was 119 x 10(6) and 60 x 10(6) cells/l, respectively (P = 0.29).

CONCLUSION

Monotherapy with TMC125 in ART-naive, HIV-1-infected individuals resulted in a similar rate of decline of plasma HIV-1 RNA during 1 week of therapy as therapy with a five-drug regimen.

Viral dynamics and their relations to baseline factors and longer term virologic responses in treatment-naive HIV-1-infected patients receiving abacavir in combination with HIV-1 protease inhibitors

From a study of 71 HIV-1-infected patients receiving abacavir in combination with 1 of 5 different HIV-1 protease inhibitors (indinavir, ritonavir, saquinavir, nelfinavir, or amprenavir), we found that the baseline HIV-1 RNA levels were highly predictive of the viral decay rates. The baseline HIV-1 RNA levels were negatively correlated with the first phase viral decay rates (r = -0.77, P < 0.001) and positively correlated with the second phase viral decay rates (r = 0.68, P < 0.001). In addition, the first phase viral decay rate was positively correlated with CD4+ cell increases. No significant correlation was found between viral decay rates and longer term (24 weeks) virologic responses, and no difference in viral decay rates was found among the 5 study regimens. These data suggest that the potency of the 5 treatment regimens was similar and was not predictive of long-term virologic failure.

Viral and Cellular Dynamics in HIV Disease

The control mechanisms that maintain a steady-state viral load during chronic HIV-1 infection are critical to understanding the pathophysiology of HIV disease. This paper compares the conceptual features of the two alternative models of viral control, target cell limitation and immune control, with available data on the viral and cellular dynamics of HIV-1 infection and the pattern of changes induced by effective antiretroviral drug therapy. These data suggest that an antigen-driven immune response is the primary control mechanism for in vivo viral growth.

Short-term measures of relative efficacy predict longer-term reductions in human immunodeficiency virus type 1 RNA levels following nelfinavir monotherapy

We calculated the relative efficacy of treatment, defined as the rate of decline of virus levels in plasma during treatment relative to the rate of decline during highly potent combination therapy, in human immunodeficiency virus type 1 (HIV-1) patients treated for 56 days with different doses of the protease inhibitor nelfinavir. Relative efficacies based on the rate of decline of HIV-1 RNA levels in plasma over the first 14 to 21 days correlated with drug dose and viral load reduction by day 56. Calculation of relative treatment efficacies over the first 2 to 3 weeks of treatment can allow rapid assessment of new antiretroviral agents and dosing regimens, reducing the need to keep subjects in clinical trials on monotherapy for prolonged periods of time. Relative efficacy may also serve as a measure of treatment efficacy in patients in initiating established therapies.

Release of virus from lymphoid tissue affects human immunodeficiency virus type 1 and hepatitis C virus kinetics in the blood

Kinetic parameters of human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) infections have been estimated from plasma virus levels following perturbation of the chronically infected (quasi-) steady state. We extend previous models by also considering the large pool of virus localized in the lymphoid tissue (LT) compartment. The results indicate that the fastest time scale of HIV-1 plasma load decay during therapy probably reflects the clearance rate of LT virus and not, as previously supposed, the clearance rate of virus in plasma. This resolves the discrepancy between the clearance rate estimates during therapy and those based on plasma apheresis experiments. In the extended models plasma apheresis measurements are indeed expected to reflect the plasma decay rate. We can reconcile all current HIV-1 estimates with this model when, on average, the clearance rate of virus in plasma is approximately 20 day(-1), that of LT virus is approximately 3 day(-1), and the death rate of virus-producing cells is approximately 0.5 day(-1). The fast clearance in the LT compartment increases current estimates for total daily virus production. Because HCV is produced in the liver, we let virus be produced into the blood compartment of our model. The results suggest that extending current HCV models with an LT compartment is not likely to affect current estimates for kinetic parameters and virus production. Estimates for treatment efficacy might be affected, however.

Small variations in multiple parameters account for wide variations in HIV-1 set-points: a novel modelling approach

Steady-state levels of HIV-1 viraemia in the plasma vary more than a 1,000-fold between HIV-positive patients and are thought to be influenced by several different host and viral factors such as host target cell availability, host anti-HIV immune response and the virulence of the virus. Previous mathematical models have taken the form of classical ecological food-chain models and are unable to account for this multifactorial nature of the disease. These models suggest that the steady-state viral load (i.e. the set-point) is determined by immune response parameters only. We have devised a generalized consensus model in which the conventional parameters are replaced by so-called 'process functions'. This very general approach yields results that are insensitive to the precise form of the mathematical model. Here we applied the approach to HIV-1 infections by estimating the steady-state values of several process functions from published patient data. Importantly, these estimates are generic because they are independent of the precise form of the underlying processes. We recorded the variation in the estimated steady-state values of the process functions in a group of HIV-1 patients. We developed a novel model by providing explicit expressions for the process functions having the highest patient-to-patient variation in their estimated values. Small variations from patient to patient for several parameters of the new model collectively accounted for the large variations observed in the steady-state viral burden. The novel model remains in full agreement with previous models and data.

Slower decline of plasma HIV-1 RNA following highly suppressive antiretroviral therapy in primary compared with chronic infection

OBJECTIVES

To study the effect of highly suppressive antiretroviral therapy on the slopes of HIV-1 RNA decline in primary compared with chronic HIV-1 infection.

METHODS

Slopes of HIV-1 RNA decline in plasma were compared before and after the start of highly suppressive antiretroviral therapy from five acutely infected patients who started treatment 2 to 5 weeks following the onset of clinical symptoms. Slopes of decline after the initiation of therapy were also compared with those found in 12 chronically infected individuals on the same therapy. Numbers and percentages of activated CD4 and CD8 T cells at baseline were compared as well.

RESULTS

The pre-treatment slopes of HIV-1 RNA decline in the acutely infected individuals increased significantly (P = 0.0001) after the start of anti-retroviral therapy. However, these post-treatment slopes were lower than those found in the chronically infected individuals (P= 0.012). Slopes were inversely correlated (P= 0.012) with baseline HIV-1 RNA. Although the number of CD38+HLA-DR+ CD4 cells was higher in primary infection (P= 0.02), the percentage did not differ between primary and chronic infection.

CONCLUSIONS

These findings indicate that antiretroviral therapy contributes significantly to the clearance of HIV-1 during primary infection. Based on the mathematical model the less steep RNA slope following the start of treatment in primary infection can be predicted to be the result of lower clearance of productively infected cells and higher burst size per cell per unit time. This may indicate a growing immune response to HIV-1 in this very early stage of infection.

Evaluation of a second-generation nucleic acid sequence-based amplification assay for quantification of HIV type 1 RNA and the use of ultrasensitive protocol adaptations

Accurate assessment of plasma HIV RNA levels at low concentrations is clinically important. We evaluated a second-generation quantitative HIV RNA assay (NucliSens HIV-1 QT), and three simple adaptations of the NucliSens standard protocol to lower the lower cutoff level. The assays were evaluated in constructed panels with known HIV RNA concentrations and in clinical samples. Results were compared with those obtained with the first generation (NASBA HIV-1 QT) and with two other commercially available assays: the Amplicor HIV Monitor test and the Quantiplex assay. In a constructed panel, results obtained by NASBA QT were on average 0.13 log(10) copies/ml (SD 0.15) higher than those of NucliSens. The NucliSens assay could quantify HIV RNA in at least 50% of the samples down to 518 (2.71 log(10)) copies/ml and NASBA QT to 5.80 x 10(3) (3.76 log(10)) copies/ml). Both assays correlated well with the known input (R NucliSens = 0.99; R NASBA QT = 0.996), but results were more variable at lower input levels. With the three different ultrasensitive NucliSens adaptations, HIV RNA could be quantified in at least 50% of the samples down to 100 (2.00 log(10)), 46 (1.66 log(10)), and 10 (1.00 log(10)) copies/ml, respectively. In patient samples, Amplicor results were on average 0.11 (SD 0.20) log(10) copies/ml above, NucliSens 0.02 (SD 0.29) copies/ml above, and Quantiplex 0.13 (SD 0.19) copies/ml below the mean of the three assay results per sample. The variation remained the same over the range of RNA levels with all three assays. The NucliSens assay can quantify HIV RNA at lower levels than the NASBA QT and is comparable to other commercially available assays. The lower cutoff of the NucliSens can be lowered down to 10 copies/ml.

Evidence of a source of HIV type 1 within the central nervous system by ultraintensive sampling of cerebrospinal fluid and plasma

Defining the source of HIV-1 RNA in cerebrospinal fluid (CSF) will facilitate studies of treatment efficacy in the brain. Four antiretroviral drug-naive adults underwent two 48-hr ultraintensive CSF sampling procedures, once at baseline and again beginning on day 4 after initiating three-drug therapy with stavudine, lamivudine, and nelfinavir. At baseline, constant CSF HIV-1 RNA concentrations were maintained by daily entry of at least 10(4) to 10(6) HIV-1 RNA copies into CSF. Change from baseline to day 5 ranged from -0.38 to -1.18 log(10) HIV-1 RNA copies/ml in CSF, and from -0.80 to -1.33 log(10) HIV-1 RNA copies/ml in plasma, with no correlation between CSF and plasma changes. There was no evidence of genotypic or phenotypic viral resistance in either CSF or plasma. With regard to pharmacokinetics, mean CSF-to-plasma area-under-the-curve (AUC) ratios were 38.9% for stavudine and 15.3% for lamivudine. Nelfinavir and its active M8 metabolite could not be accurately quantified in CSF, although plasma M8 peak level and AUC(0-8hr) correlated with CSF HIV-1 RNA decline. This study supports the utility of ultraintensive CSF sampling for studying HIV-1 pathogenesis and therapy in the CNS, and provides strong evidence that HIV-1 RNA in CSF arises, at least in part, from a source other than plasma.

Influence of follicular dendritic cells on decay of HIV during antiretroviral therapy

Drug treatment of HIV type 1 (HIV-1) infection leads to a rapid initial decay of plasma virus followed by a slower second phase of decay. To investigate the role of HIV-1 retained on follicular dendritic cells (FDCs) in this process, we have developed and analyzed a mathematical model for HIV-1 dynamics in lymphoid tissue (LT) that includes FDCs. Analysis of clinical data using this model indicates that decay of HIV-1 during therapy may be influenced by release of FDC-associated virus. The biphasic character of viral decay can be explained by reversible multivalent binding of HIV-1 to receptors on FDCs, indicating that the second phase of decay is not necessarily caused by long-lived or latently infected cells. Furthermore, viral clearance and death of short-lived productively infected cells may be faster than previously estimated. The model, with reasonable parameter values, is consistent with kinetic measurements of viral RNA in plasma, viral RNA on FDCs, productively infected cells in LT, and CD4(+) T cells in LT during therapy.

Influence of follicular dendritic cells on HIV dynamics

In patients infected with human immunodeficiency virus type 1 (HIV-1), a large amount of virus is associated with follicular dendritic cells (FDCs) in lymphoid tissue. To assess the influence of FDCs on viral dynamics during antiretroviral therapy we have developed a mathematical model for treatment of HIV-1 infection that includes FDCs. Here, we use this model to analyse measurements of HIV-1 dynamics in the blood and lymphoid tissue of a representative patient, who was treated with a combination of HIV-1 reverse transcriptase and protease inhibitors. We show that loss of virus from FDCs during therapy can make a much larger contribution to plasma virus than production of virus by infected cells. This result challenges the notion that long-lived infected cells are a significant source of HIV-1 during drug therapy. Due to release of FDC-associated virus, we find that it is necessary to revise upward previous estimates of c, the rate at which free virus is cleared, and delta, the rate at which productively infected cells die. Furthermore, we find that potentially infectious virus, present before treatment, is released from FDCs during therapy and that the persistence of this virus can be affected by whether therapy includes reverse transcriptase inhibitors.