Immune control of HIV-1 infection after therapy interruption: immediate versus deferred antiretroviral therapy

Optimal treatment strategies to control acute HIV infection

Various antiretroviral therapies (ART) are administered to symptomatic human immunodeficiency virus (HIV) infected individuals to improve their health. The treatment effectiveness may depend on suppressing development of drug resistance, reduce evolution of new viral strains, minimize serious side effects and the costs of drugs. This paper deals with some results concerning optimal drug administration scheme successful in improving patients' health especially in poorly resourced settings. The model under consideration describes the interaction between the uninfected cells, the latently infected cells, the productively infected cells, and the free viruses. Generally, in viral infection, the drug strategy aspects either the virus infectivity or reduce the virion production. The mathematical model proposed here, deals with both situations with the objective function based on a combination of maximizing benefit relied on T cells count (the white cells that coordinate activities of the immune system) and minimizing the systemic cost. The existence of the optimal control pair is established and the Pontryagin's minimum principle is used to characterize these two optimal controls. The optimality system is derived and solved numerically using the forward and backward sweep method (FBSM). Our results indicate that early initiation of treatment makes a profound impact in both improving the quality of life and reducing the economic costs of therapy.

Optimal Treatment Strategies in the Context of 'Treatment for Prevention' against HIV-1 in Resource-Poor Settings

An estimated 2.7 million new HIV-1 infections occurred in 2010. `Treatment-for-prevention’ may strongly prevent HIV-1 transmission. The basic idea is that immediate treatment initiation rapidly decreases virus burden, which reduces the number of transmittable viruses and thereby the probability of infection. However, HIV inevitably develops drug resistance, which leads to virus rebound and nullifies the effect of `treatment-for-prevention’ for the time it remains unrecognized. While timely conducted treatment changes may avert periods of viral rebound, necessary treatment options and diagnostics may be lacking in resource-constrained settings. Within this work, we provide a mathematical platform for comparing different treatment paradigms that can be applied to many medical phenomena. We use this platform to optimize two distinct approaches for the treatment of HIV-1: (i) a diagnostic-guided treatment strategy, based on infrequent and patient-specific diagnostic schedules and (ii) a pro-active strategy that allows treatment adaptation prior to diagnostic ascertainment. Both strategies are compared to current clinical protocols (standard of care and the HPTN052 protocol) in terms of patient health, economic means and reduction in HIV-1 onward transmission exemplarily for South Africa. All therapeutic strategies are assessed using a coarse-grained stochastic model of within-host HIV dynamics and pseudo-codes for solving the respective optimal control problems are provided. Our mathematical model suggests that both optimal strategies (i)-(ii) perform better than the current clinical protocols and no treatment in terms of economic means, life prolongation and reduction of HIV-transmission. The optimal diagnostic-guided strategy suggests rare diagnostics and performs similar to the optimal pro-active strategy. Our results suggest that ‘treatment-for-prevention’ may be further improved using either of the two analyzed treatment paradigms.

HIV-1 continues to spread globally. Antiviral treatment cannot cure patients, but it slows disease progression and may prevent HIV transmission by decreasing the amount of transmittable viruses in treated individuals. ‘Treatment-for-prevention’ argues for immediate treatment initiation and may reduce transmission by 96% (CI: 73–99%), according to the results of a large clinical study (HPTN052). In order to ensure long-lasting treatment success, early therapy initiation demands more sophisticated treatment strategies & exceeding funds. However, countries facing the highest HIV burden are among the poorest. Within this work, we provide a mathematical framework that allows assessing different treatment paradigms using optimal control theory together with stochastic modelling of within-host viral dynamics and drug resistance development. We use this framework to compute and evaluate two distinct optimal long-term treatment strategies for resource-constrained settings: (i) a diagnostic-guided and (ii) a pro-active treatment strategy. The cost of a strategy is evaluated from a national economic perspective, valuating a severe patient health status in terms of an economic loss. The optimal strategies are compared with current clinical treatment protocols and no treatment in terms of costs, life expectation and reduction of secondary cases. Our simulations indicate that the pro-active treatment strategy performs comparably to the diagnostic-guided treatment strategy. Both strategies perform better than current clinical protocols, suggesting directions for improvement.

A lower viral set point but little immunological impact after early treatment during primary HIV infection

The Primo-SHM trial, a multicenter randomized trial comparing no treatment with 24 or 60 weeks of combination antiretroviral therapy (cART) during primary human immunodeficiency virus (HIV) infection (PHI), recently demonstrated that temporary early cART lowered the viral set point and deferred the need for re-initiation of cART during chronic HIV infection. This study examined whether the beneficial effect of early treatment was caused by preservation of immunological responses. Twenty-seven treated and 20 untreated PHI individuals participating in the Primo-SHM trial were compared at viral set point, that is, 36 weeks after baseline or after treatment interruption, respectively, for a diverse set of immunological parameters. The results show no differences between treated and untreated individuals at the level of effector T-cell formation or replication capacity of the T-cells; regulation of various T, B, natural killer, or dendritic cells; polyfunctionality of the CD8 T-cells; preservation of CD4 T-cells in the gut associated lymphoid tissue; or immune activation. There were subtle differences in the quality of the cytolytic CD4 T-cell response: 11% (median) of CD4 T-cells of the early treated individuals produced the cytolytic molecule perforin compared to 5% in untreated individuals (p=0.046), and treatment caused a modest increase in CD4 T-cells expressing both perforin and granzyme B (median 9% vs. 4% of CD4 T-cells; p=0.045). Early treatment had a modest positive effect on the quality of the CD4 T-cell response. It remains unclear, however, whether these subtle immunological differences were the cause or a result of the lower viral set point in patients who received early treatment.

HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions: a computational study

Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity compared to continuous treatment. The cause of this failure is poorly understood and often attributed to drug resistance. Here we show that structured treatment interruptions would fail regardless of the emergence of drug resistance. Our computational model of the HIV infection dynamics in lymphoid tissue inside lymph nodes, demonstrates that HIV reservoirs and evasion from immune surveillance themselves are sufficient to cause the failure of structured interruptions. We validate our model with data from a clinical trial and show that it is possible to optimize the schedule of interruptions to perform as well as the continuous treatment in the absence of drug resistance. Our methodology enables studying the problem of treatment optimization without having impact on human beings. We anticipate that it is feasible to steer new clinical trials using computational models.

Immunological analysis of treatment interruption after early highly active antiretroviral therapy

We longitudinally evaluated HIV-specific T-cell immunity after discontinuation of highly active antiretroviral therapy (HAART). After treatment interruption (TI), some individuals could maintain a low plasma viral load (<15,000 copies/mL), whereas others could not (>50,000 copies/mL). Before HAART was initiated, plasma viral load was similar. After TI, the numbers of CD8(+) T cells increased more in individuals without viral control, whereas individuals maintaining a low viral load showed a more pronounced increase in HIV-specific CD8(+) T-cell numbers. No differences were seen in the number or percentage of cytokine-producing HIV-1-specific CD4(+) T cells, or in proliferative capacity of T cells. Four weeks after TI, the magnitude of the total HIV-1-specific CD8(+) T-cell response (IFN-γ(+) and/or IL-2(+) and/or CD107a(+)) was significantly higher in individuals maintaining viral control. Degranulation contributed more to the overall CD8(+) T-cell response than cytokine production. Whether increased T-cell functionality is a cause or consequence of low viral load remains to be elucidated.

Timely HAART initiation may pave the way for a better viral control

BACKGROUND

When to initiate antiretroviral therapy in HIV infected patients is a difficult clinical decision. Actually, it is still a matter of discussion whether early highly active antiretroviral therapy (HAART) during primary HIV infection may influence the dynamics of the viral rebound, in case of therapy interruption, and overall the main disease course.

METHODS

In this article we use a computational model and clinical data to identify the role of HAART timing on the residual capability to control HIV rebound after treatment suspension. Analyses of clinical data from three groups of patients initiating HAART respectively before seroconversion (very early), during the acute phase (early) and in the chronic phase (late), evidence differences arising from the very early events of the viral infection.

RESULTS

The computational model allows a fine grain assessment of the impact of HAART timing on the disease outcome, from acute to chronic HIV-1 infection. Both patients' data and computer simulations reveal that HAART timing may indeed affect the HIV control capability after treatment discontinuation. In particular, we find a median time to viral rebound that is significantly longer in very early than in late patients.

CONCLUSIONS

A timing threshold is identified, corresponding to approximately three weeks post-infection, after which the capability to control HIV replication is lost. Conversely, HAART initiation occurring within three weeks from the infection could allow to preserve a significant control capability. This time could be related to the global triggering of uncontrolled immune activation, affecting residual immune competence preservation and HIV reservoir establishment.

Criticality of timing for anti-HIV therapy initiation

The time of initiation of antiretroviral therapy in HIV-1 infected patients has a determinant effect on the viral dynamics. The question is, how far can the therapy be delayed? Is sooner always better? We resort to clinical data and to microsimulations to forecast the dynamics of the viral load at therapy interruption after prolonged antiretroviral treatment. A computational model previously evaluated, produces results that are statistically adherent to clinical data. In addition, it allows a finer grain analysis of the impact of the therapy initiation point to the disease course. We find a swift increase of the viral density as a function of the time of initiation of the therapy measured when the therapy is stopped. In particular there is a critical time delay with respect to the infection instant beyond which the therapy does not affect the viral rebound. Initiation of the treatment is beneficial because it can down-regulate the immune activation, hence limiting viral replication and spread.

Innate and adaptive factors regulating human immunodeficiency virus type 1 genomic activation

Over the past decade, antiretroviral therapy targeting the viral entry process, reverse transcriptase, integrase, and protease, has prolonged the lives of people infected with human immunodeficiency virus type 1 (HIV-1). However, despite the development of more effective therapeutic strategies, reservoirs of viral infection remain. This review discusses molecular mechanisms surrounding the development of latency from the site of integration to pre- and post-integration maintenance of latency, including epigenetic factors. In addition, an overview of innate and adaptive cells important to HIV-1 infection are examined from the viewpoint of cytokines released and cytokines that act on these cells to explore an overall understanding of HIV-1 proviral genome activation. Finally, this review is discussed from the viewpoint of how an understanding of the interplay of all of these factors will help guide the next generation of therapies.