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AIDS:
doi: 10.1097/QAD.0b013e32825eaba7
Clinical Science

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

Neumann, AUa,b; Polis, MAc; Rozenberg, La; Jackson, JOc; Reitano, KNc; McLaughlin, Mc; Koratich, Cc; Dewar, RLd; Masur, He; Haagmans, BLf; Kottilil, Shyamc

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Author Information

From the aFaculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel

bLaboratory of Biological Modeling, National Institute of Digestive Diseases and Kidney, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA

cLaboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA

dSAIC-Frederick, NCI, Frederick, Maryland, USA

eCritical Care Medicine Department, Clinical Research Center, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA

fDepartment of Virology, Erasmus Medical Center, Rotterdam, the Netherlands.

Received 20 December, 2006

Revised 6 April, 2007

Accepted 30 April, 2007

Correspondence to S. Kottilil, Immunopathogenesis Section, Laboratory of Immunoregulation, NIAID, NIH, Bldg10, Rm. 11N204, Bethesda, MD 20892, USA. Tel: +1 301 435 0936; fax: +1 301 435 3339; e-mail: skottilil@niaid.nih.gov

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Abstract

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

Methods: HIV kinetics in parallel to HCV kinetics and IFN pharmacokinetics during pegylated-IFN-α-2b (1.5 μg/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-α and antiretroviral therapy suggest a role for pharmacokinetically improved formulations of IFN as part of salvage therapy for HIV-infected individuals.

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Introduction

Co-infection with HCV is seen in 15–30% of HIV-infected individuals in the USA [1]. With the marked reduction in AIDS-associated opportunistic infections due to antiretroviral therapy (ART), liver disease is becoming a leading cause of death among patients with HIV infection [2,3]. Pegylated interferon (IFN)-α in combination with ribavirin is the standard of care for treatment of chronic hepatitis C virus (HCV) infection [4]. Combination therapy using pegylated IFN-α and ribavirin has improved cure rates for HCV monoinfected individuals [5,6], and has recently been shown to achieve higher response rates among HIV/HCV co-infected genotype 1 patients compared to therapy with standard IFN and ribavirin [7–12].

Mathematical modeling using HCV viral kinetics during therapy with IFN-α has suggested that the major anti-HCV mechanism of action of IFN is blocking production or release of new virions [13]. This has been demonstrated by in vitro assays using the HCV replicon system [14]. The use of weekly pegylated IFN injections (q.w.) has pharmacokinetics effects in addition to the HCV kinetics, most importantly the transient rebounds in viremia noted between injections found in some of the patients [15,16]. IFN also has anti-HIV activity which has been demonstrated in vitro [17]. Indeed, IFN was historically one of the first anti-HIV drugs to be used in the 1980s (reviewed in [18]), but this therapeutic approach was abandoned due to toxicity and relatively modest antiviral effect when used as a single agent. Several studies have demonstrated that IFN-α is capable of suppressing HIV replication in vivo [19,20]. Although these studies were able to demonstrate an effect of various IFN formulations on HIV replication, the exact mechanism of action of IFN against HIV infection in vivo is not yet clearly understood. Two studies of HIV/HCV co-infected patients have analyzed early frequent HIV kinetics during IFN therapy [11,15], but the data were available for only two or three patients per study which is insufficient to confirm the major mechanism of action of IFN.

In this prospective pilot study using pegylated IFN-α and ribavirin to treat HCV infection among HIV-co-infected individuals, the close monitoring of both HCV and HIV viral kinetics as well as IFN pharmacokinetics provide the data to develop mathematical models that show a striking dichotomy in the antiviral mechanism of IFN against HCV and HIV.

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Methods

Study design

This was a pilot, prospective, open-label trial performed at the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH) at Bethesda, Maryland, USA from 2001 to 2004. Thirty three HIV-infected patients were treated with PEG–IFN-α-2b at 1.5 μg/kg subcutaneously every week (Peg-Intron; Schering-Plough, Kenilworth, New Jersey, USA) and ribavirin daily at 400 mg q.a.m. and 600 mg q.p.m. for < 75 kg, 600 mg b.i.d. for > 75 kg) (Rebetol, Schering-Plough) for 48 weeks and followed up for 24 weeks after the end of treatment. Nine out of the 33 patients enrolled in the clinical trial had stable detectable HIV viremia for a period of 3 months at the time of initiation of treatment and were used in this study. All patients signed informed consent approved by the NIAID institutional review board prior to enrollment in the study.

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Study subjects

Patients were eligible for the study if they were > 18 years of age and had CD4 T-cell counts > 100 cells/μl, absolute neutrophil counts > 1000 cells/μl, HCV viral load >2000 copies/ml, histologic evidence of chronic hepatitis C and stable HIV disease with or without ART. Patients with other causes of liver disease, advanced cirrhosis or severe liver decompensation, severe psychiatric disorder(s), severe cardiopulmonary or renal disorder, severe retinopathies or who were receiving steroids or other immunosuppressive drugs were excluded. The demographic characteristics of the nine patients studied here are given in Table 1. The choice of ART for all these patients were decided by their primary care physicians and the five patients receiving ART had stable detectable viremia over a period of 6–8 weeks prior to initiation of anti-HCV therapy.

Table 1
Table 1
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Laboratory studies

Liver chemistry and safety laboratory tests were performed prior to the treatment and during each study visit. HCV and HIV RNA concentration in plasma was measured by VERSANT RNA 3.0 Assay (Bayer Diagnostics, Puteaux, France) during all study visits. The assay has a lower limit of detection for HCV of 615 IU/ml and for HIV of 50 copies/ml. HCV and HIV RNA concentration was measured in plasma on day 0, 1, 3, 5, 7, 10, 14, 21, 28, 42, 56 and then every 4 weeks for 72 weeks.

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Measurement of serum PEG–IFN-α-2b concentrations

PEG–IFN-α-2b concentrations were determined by application of a quantitative sandwich ELISA method (Bender MedSystems Diagnostics GmbH, Vienna, Austria). The assay uses a murine anti human IFN-α mAb adsorbed onto micro wells, which captures IFN-α present in the samples or controls. A horseradish peroxidase-conjugated monoclonal anti-IFN-α binds to captured IFN-α. After addition of substrate, IFN concentration is determined colorimetrically. Calibration curves were prepared by plotting the optical density versus the concentration of the standards. Standards from 78 pg/ml to 10 000 pg/ml were prepared by diluting PEG–IFN-α-2b in normal human serum (CLB, Amsterdam, the Netherlands). Plasma samples were diluted five times and tested on the same plates as the standards. All calibration standards, quality control samples and study samples were analyzed in duplicate. The detection limit of the assay was 100 pg/ml and the assay was linear up to a concentration of 5000 pg/ml. The inter assay coefficients of variation of standards and quality control samples did not exceed 20%. PEG–IFN concentrations were measured at days 0, 1, 3, 5, 7, 10, 14, 21, 28, 42, 56, and 84.

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Luciferase assay for measurements of HIV-1 DNA

Luciferase assay was performed using U87 cells as target cells for HIV infection in vitro [16]. For preincubation experiments, U87 cells were incubated with varying concentrations of PEG–IFN-α-2b overnight at 37°C and then infected with R5 or X4 luciferase pseudotype viruses. For postincubation experiments, U87 cells were infected with R5 or X4 luciferase pseudotype viruses and then incubated with varying concentrations of PEG–IFN-α-2b overnight at 37°C. Each experiment was performed in triplicate. Cells were then lysed and an LD reading was obtained for each well.

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Quantitative real-time PCR for measurements of HIV-1 DNA

CD8 depleted peripheral blood mononuclear cell (PBMC) blasts were used as targets for in vitro infection with HIV BaL. These target cells were either preincubated with varying concentrations of PEG–IFN-α-2b overnight at 37°C prior to infection or infected and treated with varying concentrations of PEG–IFN-α-2b overnight at 37°C. Cells were then lysed and real time PCR was performed as described [21].

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Mathematical modeling

A mathematical model of viral dynamics [13] was used to simulate and fit the viral kinetics:

Equation (Uncited)
Equation (Uncited)
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Where T(t) represents target cells, I(t) represents productively infected cells and V(t) free virus. We assumed that during the early period of treatment there is no need to consider the dynamics of long-lived HIV productively infected cells or latently infected cells [22]. ST represents the source rate of target cells and dT their loss rate constant; β is the de novo infection rate constant; p is the rate of virion release/production from each infected cell; δ is the infected cells loss rate constant with infected cells half life of ln(2)/δ; c is the intrinsic clearance rate constant of free virus with free virions half life of ln(2)/c.

The following potential antiviral effects of IFN were studied: (i) &epsiv; = effectiveness (0 < &epsiv; ≤ 1) in blocking of production/release of virions from infected cells; (ii) η = effectiveness (0 < η ≤ 1) in blocking de novo infection.

We assumed that before treatment (t < 0, &epsiv; = η = 0) the intrinsic clearance of viral particles is in equilibrium with viral particles production/release on the time scale of days, and that there is equilibrium between infection rate and loss rate of infected cells, thus giving rise to a steady state. Viral load at beginning of treatment is measurable, V0, and thus from the above steady-state assumption we obtain I0 = cV0/p.

During treatment with continuous viral decline we can assume that the number of target cells does not change significantly during the first 7 days (T = T0) [11] and that the blocking effectiveness parameters (&epsiv; and η) are approximately constant time. Using the above initial conditions we can then solve the model:

Equation (Uncited)
Equation (Uncited)
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thus allowing us to use Eq. 4 for non-linear fitting (Madonna, Berkeley) of the data by varying only the four parameters &epsiv;, η, c and δ.

More precisely, PEG–IFN injections give rise to a non-constant level of IFN during the week until the next injection, and thus its pharmacokinetics need to be taken into consideration:

Equation (Uncited)
Equation (Uncited)
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Where IFN(t) are IFN concentration in circulation after each injection, ka is the rate of IFN absorption from the depot compartment, ke is the rate of IFN elimination from circulation and IFN0 is the amount of bio-available injected IFN scaled by the volume of distribution.

In that case, a varying blocking effectiveness as function of IFN(t) levels needs to be considered:

Equation (Uncited)
Equation (Uncited)
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where &epsiv;max and ηmax are the maximum effectiveness possible for blocking production and blocking infection accordingly, &epsiv;c50 and ηc50 represent the IFN levels giving 50% sensitivity to IFN in blocking production and infection accordingly, and N&epsiv; and Nη are the power of the Hill function representing the second order sensitivity to changes in IFN levels for blocking production and infection accordingly.

Note that when using Eqs 6–7 to study the effect of IFN pharmacokinetics, the solution in Eq. 4 is not valid and Eqs 6–7 need to be used directly within the Ordinary Differential Equations (ODE) model Eqs 1–3. Also, when rebound in viremia is studied (for example in response to decline in IFN levels) one cannot use the approximation that the number of target cells is constant (this is especially true when rebound is due to decline in blocking infection; when blocking production varies the approximation dT/dt = 0 is still reasonably valid). Thus, we had set the following parameter values: ST = 10 000 and dT = 0.01 to obtain a normal CD4 cell count of 1 × 106 cells per ml, P = 10 and the parameter β is set using the pretreatment steady state assumption and the measured initial viral load. We then fit Eqs 1–3 together with Eqs 5–7 to estimate the parameters c, δ, &epsiv;max, N&epsiv;, &epsiv;c50, ηmax, Nη and ηc50.

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Statistical analysis

The nonparametric Mann–Whitney U test was used to test the significance of differences in distribution of continuous variables between the viruses. The non-parametric Spearman test was used to test the significance of correlation between variables. Significance was assumed at P < 0.03.

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Results

HIV versus HCV kinetics during PEG–IFN treatment

Following PEG–IFN injection, IFN concentrations in serum rise to a mean Cmax of 3.9 log10 pg/ml at day 1 and thereafter decline with a mean half life of 1.85 days to lower trough levels (mean 3.0 log10 pg/ml) 7 days after, in agreement with previous results [23]. An immediate decline in both HIV RNA and HCV RNA was observed in circulation as early as 1 day after initiation of treatment in eight out of nine patients with stable HIV viremia (Fig. 1). However, the magnitude and slope of viral decline in the first day is significantly (P < 0.01) different between HIV (mean 0.26 log10 copies/ml) and HCV (0.65 log10 IU/ml) (Fig. 2a). HCV decline is consistent with the rapid half life of free virus as shown in previous studies of the effect of IFN [11,13,15,24]. Moreover, first phase decline of HCV at days 1 or 3 is correlated with IFN Cmax per patient (r, 0.8; P < 0.01) as expected, but the decline in HIV at days 1 or 3 is not related to IFN levels. Also, while higher baseline HIV RNA is significantly correlated with lower HIV decline (r, 0.8; P < 0.02), HCV decline tends to be larger for higher baseline HIV RNA levels (Fig. 2b).

Fig. 1
Fig. 1
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Fig. 2
Fig. 2
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After the initial decline, a transient rebound in HCV (mean 0.33 log10) between days 3 and 7 (before the next PEG–IFN injection) was observed in all patients (Fig. 2c), while at the same time HIV continues to decline in most patients (mean, −0.50 log; P < 0.01). Indeed, the HCV rebound is expected due to the decline in IFN levels at the end of each week [25,26], while the fact that HIV did not similarly rebound warrants further investigation.

The HIV RNA decline during the first week (mean 1.23 log10 copies/ml) is of the same order of magnitude as HIV decline at day 7 for patients treated with ART (Table 2 and Fig. 2d). However, during ART, the decline of HIV during the first week is positively correlated with baseline HIV RNA (r, 0.7; P < 0.02) [27,28], while the decline of HIV during the first week of PEG–IFN therapy is inversely correlated with baseline HIV level (r, 0.7; P < 0.03). Specifically, patient I5 with the highest baseline HIV load, showed no decline in HIV RNA during the first 2 weeks following treatment, at which time he discontinued further therapy. No correlation between HIV kinetics and baseline CD4 cell count was observed. There were no differences in HIV decline or HIV dynamic parameters between African–American and Caucasian patients.

Table 2
Table 2
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After the first week decline, HIV in the four patients with higher baseline HIV RNA (3.4–4.5 log10 copies/ml) reached a minimum level between the second and third week (Table 2). A rebound in HIV from that time to the end of treatment wass observed in these four patients (Fig. 1), although in two of them HIV viral load at the end of treatment (48 weeks) was 1 log10 lower than baseline. Conversely, in the four patients with lower baseline HIV load (< 3.3 log10), HIV viral load fell below the level of detection (< 50 copies/ml) by days 3–42 and stayed at that level until the end of treatment. At the end of treatment, HIV levels rebounded back to baseline for all patients, reiterating that the consistent viral suppression is a direct effect of the PEG–IFN and ribavirin therapy.

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In vivo antiviral mechanism of IFN against HIV and HCV

The significant qualitative differences between HIV and HCV kinetics in the same patients indicate that PEG–IFN possibly has a different antiviral mechanism for these two viruses. HCV kinetics seen in these nine patients are consistent with the assumption that IFN blocks HCV production from infected cells [13] as a function of PEG–IFN pharmacokinetics [25,26]. In contrast, HIV kinetics are not readily explained by fitting the data with the assumption that the major antiviral effect of IFN is blocking virion production. Simulation of a mathematical model of viral dynamics (Fig. 3a, Eqs 1–4) shows that blocking virion production gives rise to a bi-phasic decline (Fig. 3b), where the first phase slope is governed by the half life of free virus and IFN dose or concentration [11] and the second phase slope is determined by the half life of infected cells (scaled by the effectiveness in blocking production). Such bi-phasic decline is observed here for HCV but not for HIV.

Fig. 3
Fig. 3
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Nevertheless, it is possible to fit the HIV decline assuming a large blocking virion production effect (&epsiv; = 0.76–0.97) and thus making the decline during the whole first week part of the first phase (Fig. 3c, d). However, to fit the data in that case, HIV free virus half life must be very long (shortest estimate of 10.4–20.8 h, maximal estimate of c = 0.8–1.6, Table 2), which is significantly longer than the half life of 2–6 h known from previous studies during ART [29] or 0.5–2 h found during apheresis [30]. Alternatively, it is also possible to fit HIV decline by assuming a low effectiveness in blocking virion production (&epsiv; = 0.22–0.58), without blocking de novo infection (η = 0.0), thus obtaining a very small first phase decline (Fig. 3c,d). However, in that case the half life of infected cells needs to be in the range of 0.3–0.8 days (minimal estimate of δ = 0.8–2.2, Table 2), in order to fit HIV decline during the first week, which is again inconsistent with the half life of 1.1–1.8 days shown in previous studies [22,27,29]. Thus, we conclude that blocking virion production/release from infected cells as the major antiviral effect of IFN against HIV cannot explain the kinetics of HIV during PEG–IFN/ribavirin treatment.

On the other hand, if one assumes that the major (or even the only) effect of IFN on HIV is blocking de novo infection then it is possible to fit the data for HIV decline with half-lives of free virus and of infected cells that are consistent with the values described in the literature (Fig. 3e,f, Table 2). Due to the infrequent sampling during the first day it is not possible to obtain an accurate estimate of the free virus half life (or of c), but any value between 2 and 8 h allows a good fit. Also, similar to previous studies [13], since the parameters η and δ are coupled (Eq. 4), only their product, and the half life of the decline slope, can be estimated. However, an effectiveness of blocking infection in the range 70–100% gives a reasonable estimate of the half life of productively infected cells. The non-linear best fit of the data when allowing blocking both de novo infection and virion production (Fig. 3e,f, Table 2) shows that a low effectiveness of blocking virion production (mean &epsiv; = 31%) is possible together with a larger effectiveness of blocking de novo infection.

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In vivo IFN pharmacokinetics effect on HIV versus HCV

The decline in HIV RNA was independent of IFN concentration. Also, in eight of nine patients HIV RNA decline did not show a pharmacokinetic effect due to the decline in IFN levels at days 1–7 after the injection (three patients have HIV RNA<50 cp/ml from day 3 or 7 on; four patients had slightly slower decline at days 5–7 compare to days 1–5 but the slowing down continued also at days 7–10 when IFN levels increased again; one patient had little decline during the week). Rather, high baseline HIV RNA was highly associated with a rebound in HIV RNA that started at day 10 or 14. Nevertheless, a significant correlation (r, 0.9; P < 0.002) was found between HIV decline at days 3–7 and the half life of IFN (Fig. 2c), indicating that pharmacokinetic effects may also play a partial role in determining the rebound. Indeed, the one patient (I1) with apparent pharmacokinetic related viral rebound at days 3–7 and 10–14 had the shortest IFN half life (1.3 days) in the cohort.

The above results indicate a high sensitivity of HIV to the IFN effect in blocking de novo infection, such that the 90% effective IFN concentration is low enough (maximal estimate of ηc90 of the order of 1000–3000 pg/ml) for the decline in IFN levels over time to not play a significant role. Unfortunately, due to the non-frequent sampling it is difficult to obtain an accurate estimate of ηc90 in all patients. Nevertheless, we were able to fit HIV kinetics as a function of the IFN pharmacokinetics in one patient (Fig. 3g), in parallel to fitting HCV kinetics as a function of the same pharmacokinetic profile (Fig. 3h). As above, the results show that if one assumes that HIV is more sensitive to blocking virion production by IFN than blocking infection then the half-lives of free virions or of the infected cells are not in agreement with previously described data. On the other hand, if one allows for HIV to be more sensitive to blocking infection by HIV (ηc90, 5400 pg/ml and Nη, 5.7 versus &epsiv;c90, 93 000 pg/ml and N&epsiv;, 1.7) then a fit of the viral rebound as function of IFN pharmacokinetics (IFN0, 36 400; ka, 1.54; ke, 0.54) is obtained with appropriate half-lives (2–6 h for free virus and 1.1 days for infected cells). Interestingly, HCV was more sensitive to blocking production by IFN (&epsiv;c90, 9900 pg/ml and N&epsiv;, 2), but unfortunately, as previously shown [11], it is not possible to estimate the effectiveness in blocking infection for HCV. Note that these parameter values are to be used only qualitatively as a range of values allows the data to fit due to the non-frequent sampling and the large number of parameters involved.

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In vitro suppression of HIV replication by PEG–IFN

To test the above hypothesis we performed HIV replication suppression experiments using PEG–IFN in vitro. When U87 cells were used as targets for luciferase-pseudotype R5 and X4 viruses, PEG–IFN treatment resulted in a dose-dependent suppression of HIV replication of both R5 and X4 strains (Fig. 4a,b). Incubation with PEG–IFN prior to infection provided superior suppression of HIV replication when compared to treatment of target cells after infection. When low doses of PEG–IFN were added after infection, the suppression was minimal or not observed, whereas when the same PEG–IFN doses were used preincubation suppression of HIV replication was 40–80%.

Fig. 4
Fig. 4
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Similar results were obtained when real-time PCR was used to detect HIV copy numbers after infection of CD8 depleted PBMC with R5 virus (Fig. 4c). Again, this dichotomous suppressive effect was more pronounced with preincubation of target cells with IFN than with IFN treatment postinfection, which is consistent with our in vivo results that the predominant anti-HIV effect of IFN is to block de novo infection rather than block production from already infected cells.

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Discussion

HIV and HCV exhibit significantly different viral kinetics during treatment with PEG–IFN-α-2b, possibly indicating that IFN has a different antiviral effect against HIV than it does against HCV. Mathematical modeling of our data indicates that the major effect of IFN against HIV is to block de novo infection, while the major IFN effect against HCV is blocking virion production. This conclusion is corroborated by in vitro studies showing that IFN induces more potent suppression of HIV replication when it is preincubated prior to infection of target cells with HIV, rather than IFN treatment postinfection with HIV. Thus, IFN seems to have a predominant preintegration effect rather than postintegration in suppressing HIV replication in vitro, consistent with our in vivo results.

HIV decline during IFN treatment has been previously described in two patients [16] treated with PEG–IFN-α-2b and three patients treated with standard IFN-α [15] and the assumption that IFN blocks virion production was used there to fit the data. Re-examination of the data in the three patients in the Talal et al. study [15], who had large fluctuations in HIV RNA over the first day and no sampling between days 3 and 7, shows that blocking infection as the major antiviral effect will better fit the decline in HIV RNA. Interestingly, three other patients in that study who had higher baseline HIV RNA (>104 copies/ml) as compared to the first three patients, showed no decline in HIV supporting our results. Torriani et al. [16] studied two patients with detectable HIV RNA in the APRICOT study and found a low effectiveness of blocking virion production (35–52%) and very variable viral kinetic profiles. Indeed, retrospective analysis of that data, considering also blocking de novo infection, improves the fit of the HIV kinteics. It is important to note that fitting the data with one mathematical model or the other is not a sufficient evidence for the validity of that model. As we have shown, while it is possible to fit the data by assuming that IFN either blocks viral infection or blocks virion production, the latter does not give realistic parameter estimates. Our results, consistent with some heterogeneity in the patient population, therefore indicate a different antiviral mechanism for IFN against HIV. In any case, mathematical modeling is to be used only to generate hypothesis to be corroborated by experimental results, as was done in this study, or to evaluate the in vivo significance of results found in vitro.

Indeed, a recent study suggested that the major antiviral effect of IFN is mediated by induction of APOBEC3G genes in monocytes [31] and in resting primary T lymphocytes [32]. APOBEC3G is an innate host intracellular antiviral factor that is constitutively expressed on resting T cells and monocytes [31,33,34]. APOBEC3G functions as a cytidine deaminase, which catalyzes the deamination of cytosine to uracil, leading to accumulation of adenine nucleotides into the viral DNA and resulting in incorporation of lethal mutations into the HIV genome [35–38]. These results suggest that IFN induces up-regulation of an innate anti-HIV mechanism at the level of preintegration. Indeed, it has been shown that IFN-α induces APOBEC3A in lymphocytes, thereby suppressing HIV replication (Peng et al. unpublished data). The exact mechanism by which APOBEC3A suppresses HIV replication is not yet clearly understood, but our results would suggest that it also acts at the preintegration level. Induction of host innate antiviral machinery is a novel approach to develop newer therapeutic agents, and our study indicates that such mechanisms can indeed be a viable option in the treatment of HIV infection.

When the antiviral effect of IFN is compared to that described with the use of protease inhibitor (PI)-containing ART, the magnitude and durability of HIV viral load suppression is quite similar [27,29]. However, the IFN-induced antiviral effect seem to be inversely related to the baseline viral levels, while there is a direct relationship between the baseline HIV viremia and antiviral response to PI-containing ART [27,29]. These findings suggest that IFN may have a completely different antiviral mechanism against HIV than that described with ART. The lack of HIV decline in patient I5, who had the highest baseline HIV viral load, and the rebound found in patients with higher baseline viral load indicate that the IFN-induced antiviral effect is higher in patients with relatively low levels of HIV replication. It should be further verified if preexisting high levels of endogenous IFN in patients with high viral load potentially gives rise to insensitivity to IFN treatment and may explain the lack of response to IFN in these patients [39]. These findings also suggest that IFN may have a complementary antiviral mechanism against HIV to that described with ART, and that their combination may have a synergistic effect in suppressing HIV replication in vivo. Such therapeutic approaches will expand the options available to clinicians to target HIV and attain maximal suppression of HIV replication.

IFN has been used as an anti-HIV agent in the past and in some recent studies as well [17,18] However, most clinicians have reservations about using IFN as an anti-HIV agent due to its adverse event profile [40]. IFN use is associated with several serious adverse events which are much more pronounced in HIV-infected individuals [40]. However, our study implies that IFN does have significant anti-HIV activity and could have a role in the treatment of HIV infection. Recent advances in developing newer IFN formulations (for example, albumin conjugated IFN [41,42]) could enable clinicians to administer IFN every 2–4 weeks with fewer adverse events. Furthermore, our pharmacodynamical results indicate that although low levels of IFN may suffice to give rise to an HIV decline, nevertheless an improved pharmacokinetic profile [36] could improve the antiviral effect of IFN. A significant number of patients develops treatment failure in response to ART, due to the emergence of antiviral drug resistance, and exhibit consistent low levels of viremia [43]. An IFN product could suppress HIV replication in these patients in combination with other antiretroviral agents and prevent the development of complete viral resistance. Clinical trials to test this hypothesis will be valuable in expanding our therapeutic options against HIV infection.

Disclaimer: The content of this publication does not necessarily reflect the views of policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organization imply endorsement by the U.S. Government.

Sponsorship: Supported in whole by the Intramural Research Program of the NIH, (National Institute of Allergy and Infectious Diseases and National Institute of Digestive Diseases and Kidney).

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Keywords:

antiviral effect; HCV; HIV; interferon

© 2007 Lippincott Williams & Wilkins, Inc.

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