Abstract
The addition of ribavirin to alpha interferon therapy significantly increases response rates for patients with chronic hepatitis C virus (HCV) infection, but ribavirin's antiviral mechanisms are unknown. Ribavirin has been suggested to have mutagenic potential in vitro that would lead to “error catastrophe,” i.e., the generation of nonviable viral quasispecies due to the increment in the number of mutant genomes, which prevents the transmission of meaningful genetic information. We used extensive sequence-based analysis of two independent genomic regions in order to test in vivo the hypothesis that ribavirin administration accelerates the accumulation of mutations in the viral genome and that this acceleration occurs only when HCV replication is profoundly inhibited by coadministered alpha interferon. The rate of variation of the consensus sequence, the frequency of mutation, the error generation rate, and the between-sample genetic distance were measured for patients receiving ribavirin monotherapy, a combination of alpha interferon three times per week plus ribavirin, or a combination of alpha interferon daily plus ribavirin. Ribavirin monotherapy did not increase the rate of variation of the consensus sequence, the mutation frequency, the error generation rate, or the between-sample genetic distance. The accumulation of nucleotide substitutions did not accelerate, relative to the pretreatment period, during combination therapy with ribavirin and alpha interferon, even when viral replication was profoundly inhibited by alpha interferon. This study strongly undermines the hypothesis whereby ribavirin acts as an HCV mutagen in vivo.
Hepatitis C virus (HCV) infection is a major cause of chronic liver diseases and a global public health problem. Chronic HCV infection affects more than 170 million individuals worldwide, of whom an estimated 20% have or will develop cirrhosis. Furthermore, the annual risk of progression towards hepatocellular carcinoma is 1% to 4% among patients with cirrhosis (36). The combination of pegylated alpha interferon (IFN-α) and ribavirin is the current standard treatment for chronic HCV infection. This treatment yields a sustained virological response (SVR), defined by the lack of detectable HCV RNA in serum 24 weeks after the end of therapy, in 40 to 50% of patients infected by HCV genotype 1 and in 70% to 80% of patients infected by genotype 2 or 3 (14, 17, 27). The vast majority of patients who have an SVR are cured of the infection.
Ribavirin (1-β-d-ribofuranosyl-1,2,4-triazole-3-carboxamide) is a guanosine analogue with a broad spectrum of activity against DNA and RNA viruses (45). Its use in the treatment of chronic HCV infection has been essentially empirical (36). Indeed, the addition of ribavirin to standard or pegylated IFN-α therapy significantly increases the SVR rate over that with IFN monotherapy (14, 17, 27, 30, 39) and ribavirin can exert this antiviral effect through several possible mechanisms. HCV clearance is biphasic in responders to IFN-α therapy (32, 33). The first rapid phase, which occurs on days 1 and 2, reflects direct inhibition of viral replication by IFN-induced antiviral effectors. Mathematical modeling suggests that the second, slower phase, which starts during the first week of administration, reflects gradual clearance of infected cells in a context of potent inhibition of viral replication (32, 33). Two recent studies by our group suggest that ribavirin impacts both phases (4, 37). Indeed, ribavirin monotherapy exerts significant, moderate, early (days 2 and 3), and transient inhibition of viral replication for approximately half of the patients, and this effect appears to be additive with that of IFN during the first days of therapy (37). This inhibition correlates with the concentration and elimination half-life of ribavirin in peripheral blood (37). We have also recently shown in a prospective randomized trial involving patients infected by HCV genotype 1 that the principal effect of ribavirin is to prevent breakthroughs during and relapses after therapy for individuals who initially respond to the pegylated IFN-α-ribavirin combination (4). This suggests that ribavirin shortens the half-life of infected cells during IFN administration, allowing their complete elimination during the standard 48-week treatment period in the majority of patients who initially respond to combination therapy.
The mechanisms by which ribavirin modestly inhibits HCV replication and prevents relapses during IFN-ribavirin combination therapy are totally unknown. In vivo, ribavirin is converted into ribavirin 5′-monophosphate (RMP), ribavirin 5′-diphosphate, and ribavirin 5′-triphosphate (RTP) by adenosine kinase and possibly cytosolic 5′-nucleotidase II (51). RTP is the principal intracellular metabolite of ribavirin in mammals, and its intracellular concentration appears to vary according to the cell type (15, 35). A number of putative mechanisms have been proposed to explain the efficacy of ribavirin against HCV infection (13, 22).
(i) Direct inhibition of HCV RNA-dependent RNA polymerase: RTP can be incorporated as a substrate by viral polymerases and can thereby inhibit RNA elongation. However, RTP has been shown to be a weak inhibitor of a variety of viral polymerases, including HCV RNA-dependent RNA polymerase (26, 50). Given the modest antiviral effect of ribavirin monotherapy in vivo (37), ribavirin's direct antiviral properties are unlikely to play a major role in HCV elimination during combination therapy.
(ii) Inhibition of IMPDH: ribavirin 5′-monophosphate, which is a minor intracellular metabolite, competitively inhibits both isoforms of IMP dehydrogenase (IMPDH). IMPDH inhibition leads to the depletion of intracellular pools of GTP and dGTP, which are necessary for viral replication (28). IMPDH inhibition has been reported to be the main mechanism whereby ribavirin acts against yellow fever virus and human parainfluenza virus 3 (23, 24). In contrast, recent results with potent specific IMPDH inhibitors, used alone or in combination with ribavirin or IFN-α for patients with chronic HCV infection, suggest that IMPDH inhibition is not the mechanism of ribavirin action in chronic hepatitis C (18, 31).
(iii) Immunomodulatory properties: several reports suggest that at clinically relevant concentrations, ribavirin acts as an immunomodulator, enhancing the production of Th1 cytokines (interleukin-2 and gamma interferon) while suppressing Th2 cytokine production both in murine models and in humans; it is also suggested that these properties might enhance the activity of IFN-α (6, 19, 29, 34, 46). However, the l-eniantomer of ribavirin, levovirin, which has the same immunomodulatory properties as ribavirin but no activity against DNA and RNA viruses in vitro (because it cannot be converted into 5′-phosphate derivatives (41, 47), does not share ribavirin's clinical properties when administered to HCV-infected patients in combination with pegylated IFN-α (38).
(iv) Mutagenic properties leading to “error catastrophe”: the most popular hypothesis forwarded to explain the role of ribavirin in hepatitis C therapy is its putative mutagenic potential, which would lead to “error catastrophe,” i.e., disorganization of the mutant distribution of the quasipecies and the generation of nonviable viral populations. This concept was recently introduced by Crotty et al., based on the in vitro poliovirus model. These authors reported that ribavirin induced a high frequency of genomic mutations that generated viral progeny with reduced infectivity (7, 8). A similar effect of high concentrations of ribavirin has been found in cell cultures infected by RNA viruses belonging to several families, including foot-and-mouth disease virus, Hantaan virus, West Nile virus, and GB virus B, a member of the Flaviviridae family that is closely related to HCV (1, 9, 16, 20, 44). In addition, ribavirin has been reported to exert an antiviral effect related to error-prone replication in HCV subgenomic replicons, both in Huh7 cell lines and in a full-length binary HCV replication system (5, 20, 21, 48, 53). However, error-prone replication is not the mechanism by which ribavirin acts against arenavirus lymphocytic choriomeningitidis virus or the yellow fever virus, another member of the Flaviviridae family that is related to HCV (24, 42). Conflicting results have been obtained with HCV-infected patients receiving ribavirin (3, 25, 43, 52).
A recent study based on mathematical modeling of viral decay in 17 patients receiving the combination of standard IFN-α and ribavirin suggested that ribavirin acts mainly by reducing the infectivity of HCV virions produced during therapy in a dose-dependent manner and that this effect may appear only when viral replication is profoundly reduced by IFN-α, thereby explaining the poor antiviral effect of ribavirin monotherapy (10). Although mathematical modeling can only raise hypotheses, the authors suggested that such a reduction in virus infectivity would be in keeping with the “error catastrophe” hypothesis (10).
The aims of this study were to determine, by means of thorough quasispecies sequence analysis targeting two independent genomic regions, the following: (i) whether ribavirin acts as an RNA mutagenic agent during treatment of patients with chronic HCV genotype 1 infection and (ii) whether ribavirin's mutagenic effect (if any) occurs only in patients with low-level virus production due to potent inhibition by coadministered IFN.
MATERIALS AND METHODS
Patients.
Eleven treatment-naive patients with chronic hepatitis C due to HCV genotype 1b were randomly selected for this study among a group of patients enrolled in a previously published randomized trial comparing viral kinetics during exposure to various regimens of IFN-α and/or ribavirin (37). The patients were eight men and three women, and their mean age was 38 ± 5 years (range, 31 to 52 years). All of the patients had anti-HCV antibodies in serum, detectable HCV RNA (>50 IU/ml), elevated alanine aminotransferase levels, and compensated chronic liver disease. Four patients (group A) received ribavirin (Rebetol; Schering-Plough Oncology, Kenilworth, NJ) monotherapy at a dose of 1.0 or 1.2 g/day, depending on body weight (below or above 75 kg, respectively). Four patients (group B) received the combination of standard IFN-α2b (Intron-A; Schering-Plough Oncology) at a dose of 3 million units (MU) three times per week, plus ribavirin, 1.0 or 1.2 g/day depending on body weight. The remaining three patients (group C) were treated with the combination of standard IFN-α2b 3 MU daily plus ribavirin 1.0 or 1.2 g/day, depending on body weight. All patients were treated with the relevant regimen for 24 weeks, as previously reported (37). Written informed consent was obtained from all patients, and the study was approved by the local ethics committee (Comité Consultatif de Protection des Personnes dans la Recherche Biomédicale) in accordance with the Helsinki Declaration.
Materials.
Blood samples were taken at four time points for sequence analyses: 14 days before the initiation of therapy (d−14), at the initiation of therapy (d0), on day 14 of therapy (d14) and on day 28 of therapy (d28). At each time point and for each patient, extensive quasispecies sequence characterization (20 clones) of both the full-length nonstructural protein 3 (NS3) protease domain and the full-length NS5A protein was performed. The rate of variation of the consensus sequence, the frequency of mutation, the error generation rate, and the between-sample genetic distance were calculated during the three successive periods for each patient, i.e., between d−14 and d0 (natural genetic drift in the absence of therapy, used as the control period for each patient), between d0 and d14 of therapy, and between d14 and d28 of therapy (when viral replication was profoundly inhibited by IFN-α in groups B and C). HCV RNA was quantified at d−14, at baseline (d0), and on days 1, 2, 3, 14, and 28 of therapy. Blood samples for serum ribavirin assay were obtained at d0, hours 4, 8, 12, 18, 24, 30, 36, 42, 48, 62, 70, 86, and 94, and on days 14 and 28.
HCV RNA quantification.
HCV RNA was quantified by using the SuperQuant assay (National Genetics Institute, Los Angeles, CA), as previously described (37). The detection limit of this assay is 30 IU/ml (1.5 log10 IU/ml).
Serum ribavirin assay.
Serum ribavirin concentrations were determined by means of a high-performance liquid chromatography tandem mass spectrometric method at MDS Pharma Services (Saint-Laurent, Québec, Canada), as previously reported (40).
Generation of NS3 and NS5A quasispecies sequences. (i) RNA extraction.
RNA was extracted from 200 μl of serum by using the High Pure viral RNA kit (Roche Molecular Biochemicals, Mannheim, Germany), according to the manufacturer's instructions. The RNA pellet was eluted with 50 μl of diethyl pyrocarbonate-treated water and stored at −70°C until analysis.
(ii) cDNA synthesis.
For cDNA synthesis, 5 μl of viral RNA was used with 10 pmol of antisense primers 3EAS and R3EAS for NS3 and NS5A, respectively (Table 1). The reaction mixture (20 μl) contained 50 mM Tris-HCl, pH 8.3, 75 mM KCl, 3 mM MgCl2, 10 Mm deoxynucleoside triphosphates, 100 mM dithiothreitol, 40 U of RNase inhibitor (RNaseOUT; Invitrogen, Carlsbad, CA), and 200 U of Superscript III reverse transcriptase (Invitrogen). The reaction mixture was incubated for 1 h at 55°C, and the enzyme was then inactivated for 15 min at 70°C.
TABLE 1.
Primers used for PCR amplification of full-length NS3 and NS5A protein-encoding sequences of HCV genotype 1ba
| Target | Primer description | Primer name | Sequence | Nucleotide positions |
|---|---|---|---|---|
| NS3 | Outer | |||
| Sense | 3ES | 5′-TGTGGGGACATCATCTTGG-3′ | 3224-3306 | |
| Antisense | 3EAS | 5′-ACTTTGGTGCTCTTGCCGCT-3′ | 4029-4048 | |
| Inner | ||||
| Sense | 3IS | 5′-GAGATACTTTTGGGACCGGCT-3′ | 3354-3374 | |
| Antisense | 3IAS | 5′-GGAGATGAGTTGTCTGTGAA-3′ | 3957-3976 | |
| NS5A | Outer | |||
| Sense | Y4S | 5′-GTGCAGTGGATGAAYCGGCTGATAGC-3′ | 6066-6091 | |
| Antisense | R3EAS | 5′-GTGGTGACGCAGCAAAGAGT-3′ | 7669-7688 | |
| Inner | ||||
| Sense | R3ES | 5′-CAGCCTTACCATCACCCAGC-3′ | 6176-6195 |
Primer positions are given according to numbering of the HCV-J genotype 1b prototype sequence, accession number D90208.
(iii) PCR amplification.
A nested PCR method was used to amplify the full-length NS3 protein-encoding sequence, and a seminested procedure was used for the NS5A protein-encoding sequence. The primers used for amplification (Table 1) were as follows: for NS3, outer primers EAS and 3EAS and inner primers 3IS and 3IAS; for NS5A, outer primers Y4S and R3EAS and inner primers R3ES and R3EAS. Two microliters of cDNA solution was added to the PCR mixture containing 10 mM Tris-HCl (pH 8.5), 50 mM KCl, 2 mM MgCl2, 10 mM deoxynucleoside triphosphates, and 10 pmol of the primers in the presence of Taq Advantage DNA polymerase (BD Biosciences-Clontech, Mountain View, CA). Amplification included initial denaturation at 95°C for 1 min, followed by 35 cycles of denaturation at 95°C for 30 s, annealing at 53°C (NS3) or 60°C (NS5A) for 30 s, and elongation at 70°C for 30 s (NS3) or 90 s (NS5A), followed by a final elongation step at 70°C for 12 min. The second round of PCR included initial denaturation at 95°C for 1 min, followed by 30 cycles of denaturation at 95°C for 30 s, annealing at 49°C (NS3) or 55°C (NS5A) for 30 s, and elongation at 70°C for 30 s (NS3) or 90 s (NS5A), followed by a final elongation step at 70°C for 12 min. Amplification products (5 μl) were run on 1.5% agarose gels. The gels were stained with ethidium bromide, and DNA was viewed under UV light.
(iv) Purification of PCR products.
The PCR products were purified by using Microcon-100 centrifugal filters (Millipore, Bedford, MA) according to the manufacturer's instructions. Amplicons were eluted in 20 μl of sterile water and stored at −20°C until analysis.
(v) Cloning and sequencing.
Purified products were cloned into the pCR4-TOPO vector, using the TOPO TA cloning kit (Invitrogen) according to the manufacturer's protocol. Recombinant plasmids were transformed in Escherichia coli TOP10 competent cells, and transformants were grown on ampicillin plates. Cloned DNAs were PCR amplified with the M13 plasmid universal primers and Pfu DNA polymerase (Qbiogene, Irvine, CA). The amplified clones were purified by means of the Wizard SV96 PCR Clean-Up system (Promega, Madison, WI) according to the manufacturer's protocol. Twenty clones per time point per patient were sequenced with the Big-Dye Terminator Cycle v3.1 sequencing kit on the ABI 3100 sequencer (Applied Biosystems, Foster City, CA), according to the manufacturer's protocol. Both DNA strands were sequenced with the M13 universal primers.
NS3 and NS5A sequence analysis and statistical analysis.
The generated sequences were aligned by using CLUSTAL W software (49). For each sample from each patient, the consensus nucleotide sequence of the quasispecies was deduced and its rate of variation was determined by counting the number of nucleotide substitutions at each 14-day interval, dividing it by the length of the sequenced fragment, and multiplying it by 26 to give the variation per site per year.
The error generation rate was calculated by measuring the number of nucleotide substitutions in all of the sequenced clones relative to the consensus sequence at the previous time point divided by the total number of sequenced nucleotides over each 14-day interval (d−14 to d0, d0 to d14, and d14 to d28) for each patient. This number was multiplied by 26 to obtain the error generation rate, expressed as the number of substitutions per site per year.
The mutation frequency was determined as the total number of nucleotide substitutions (in the 20 clones analyzed at each time point) relative to the consensus sequence at the same time point, divided by the total number of sequenced nucleotides. The normalized Shannon entropy was calculated as −Σi(pi ln pi)/ln N, where pi represents the frequency of each sequence in the quasispecies and N is the total number of sequences analyzed. The between-sample genetic distances were calculated on the basis of distances between pairs of sequences generated at 14-day intervals.
Statistical calculations were carried out by using the descriptive statistics, linear regression, hypothesis test, and analysis-of-variance (ANOVA) packages for Mathematica 5.0 (Wolfram Research).
Nucleotide sequence accession numbers.
Sequence data from this article have been deposited in GenBank under accession numbers AM400248 to AM400838 and AM401639 to AM402384.
RESULTS
Concentrations of ribavirin in serum.
Figure 1 shows the kinetics of serum ribavirin concentrations for the patients receiving ribavirin monotherapy (group A) (Fig. 1A), those receiving a combination of IFN-α three times per week and ribavirin (group B) (Fig. 1B), and those receiving a combination of IFN-α daily and ribavirin (group C) (Fig. 1C). High ribavirin concentrations in serum were achieved within a few hours after the first oral intake, but the levels fluctuated during the first days of administration. A plateau was reached by day 14 in all cases.
FIG. 1.
Dynamics of serum ribavirin concentrations (in log ng/ml) during 28 days of oral administration for four patients receiving ribavirin monotherapy, 1.0 to 1.2 g/day according to body weight (group A), for four patients receiving a combination of standard IFN-α, 3 MU three times per week, plus ribavirin (group B), and for three patients receiving a combination of IFN-α, 3 MU daily, plus ribavirin (group C).
Dynamics of viral replication.
As shown in Fig. 2A, patients in group A (ribavirin monotherapy) had an early, moderate, and transient fall in viral replication, as previously reported (37). Their viral load fell by 0.35 to 1.55 log10 IU/ml but returned to near-baseline levels by day 14. None of these patients experienced a second slope of viral decline.
FIG. 2.
Dynamics of viral replication during the first 28 days of therapy for the four patients receiving ribavirin monotherapy, 1.0 to 1.2 g/day according to body weight (group A), for the four patients receiving a combination of standard IFN-α, 3 MU three times per week, plus ribavirin (group B), and for the three patients receiving a combination of IFN-α, 3 MU daily, plus ribavirin (group C). The viral kinetics are shown as log HCV RNA reductions relative to baseline (represented by the 0 line). No patient from group A became HCV RNA negative at any time point of therapy, whereas in groups B and C, the sample at day 28 was the last sample with detectable HCV RNA.
In group B (IFN-α three times per week plus ribavirin) (Fig. 2B) and in group C (IFN-α daily plus ribavirin) (Fig. 2C), HCV RNA showed a typical biphasic decline. The initial, rapid decline was observed on day 1 after the first IFN-α dose. It ranged from −0.22 to −2.13 log10 HCV RNA IU/ml. It was followed by a reincrease in viral replication on day 2 in group B before the second IFN-α injection (Fig. 2B) but not for group C patients, who received daily IFN-α injections (Fig. 2C). A significant second slope of viral decline was observed for all patients in these two groups and was more pronounced in group C than in group B (Fig. 2B and C). In all cases and in both groups, the sample at week 28 was the last in which HCV RNA was detectable (i.e., HCV RNA was undetectable in the next sample, 4 weeks later).
Clonal analysis of HCV quasispecies.
Overall, 1,600 quasispecies variant sequences were generated, including 20 clones per patient of the full-length NS3 protease- and NS5A-encoding regions at 4 time points for the 8 patients in groups A and B and at 3 time points for the 3 patients in group C. On day 28, for the group C patients, who received daily IFN-α and ribavirin and had a more rapid HCV RNA decline, NS3 could not be PCR amplified in one case, NS5A in another case, and both in the remaining case, owing to low HCV RNA levels. In order to determine whether our sampling was biased by a limiting-dilution effect, especially in the samples with a very low HCV RNA content, which would have hidden a possible mutagenic effect of ribavirin, all templates were diluted 1/10 and the same PCR amplification procedures were applied. All samples gave visible PCR bands in both regions, except for two samples with a very low HCV RNA content at D28 for patients receiving the combination of IFN-α and ribavirin. This experiment ruled out a sampling bias.
To determine whether the analysis of 20 clones per time point was sufficient to evaluate total viral populations, we determined the mean, standard deviation (SD), standard error of the mean (SEM), and 95% confidence intervals (CI) for the mutation frequency in both genomic regions analyzed (Table 2). As shown in Table 2, the SEM values were on average 1 order of magnitude lower than the means, suggesting that the sample size was sufficient to ensure excellent accuracy.
TABLE 2.
Mutation frequencies in viral NS3 and NS5A coding regions at each time point for samples from the 11 patientsa
| Coding region | Patient | Mutation frequency
|
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| d−14
|
d0
|
d14
|
d28
|
||||||||||
| Mean ± SD | SEM | 95% CI | Mean ± SD | SEM | 95% CI | Mean ± SD | SEM | 95% CI | Mean ± SD | SEM | 95% CI | ||
| NS3 | 1 | 0.002 ± 0.001 | 0.0004 | 0.001-0.003 | 0.004 ± 0.002 | 0.0004 | 0.003-0.005 | 0.004 ± 0.002 | 0.0005 | 0.003-0.005 | 0.004 ± 0.003 | 0.0006 | 0.003-0.006 |
| 2 | 0.010 ± 0.010 | 0.0026 | 0.004-0.015 | 0.012 ± 0.003 | 0.0008 | 0.010-0.013 | 0.002 ± 0.003 | 0.0008 | 0.001-0.004 | 0.004 ± 0.002 | 0.0004 | 0.003-0.005 | |
| 3 | 0.006 ± 0.005 | 0.0012 | 0.004-0.009 | 0.007 ± 0.006 | 0.0015 | 0.004-0.010 | 0.007 ± 0.004 | 0.0009 | 0.005-0.009 | 0.006 ± 0.004 | 0.0011 | 0.003-0.008 | |
| 4 | 0.002 ± 0.001 | 0.0004 | 0.001-0.002 | 0.003 ± 0.002 | 0.0005 | 0.002-0.005 | 0.004 ± 0.004 | 0.0009 | 0.002-0.006 | 0.006 ± 0.004 | 0.0010 | 0.004-0.008 | |
| 5 | 0.005 ± 0.002 | 0.0005 | 0.003-0.006 | 0.003 ± 0.003 | 0.0007 | 0.001-0.005 | 0.002 ± 0.002 | 0.0004 | 0.001-0.003 | 0.002 ± 0.001 | 0.0003 | 0.001-0.003 | |
| 6 | 0.003 ± 0.003 | 0.0006 | 0.002-0.005 | 0.003 ± 0.002 | 0.0005 | 0.002-0.005 | 0.005 ± 0.002 | 0.0005 | 0.002-0.005 | 0.006 ± 0.003 | 0.0008 | 0.004-0.008 | |
| 7 | 0.003 ± 0.004 | 0.0011 | 0.001-0.006 | 0.005 ± 0.004 | 0.0010 | 0.003-0.007 | 0.002 ± 0.001 | 0.0004 | 0.003-0.007 | 0.004 ± 0.003 | 0.0009 | 0.002-0.006 | |
| 8 | 0.003 ± 0.002 | 0.0005 | 0.002-0.004 | 0.004 ± 0.003 | 0.0007 | 0.003-0.005 | 0.002 ± 0.001 | 0.0004 | 0.003-0.005 | 0.002 ± 0.002 | 0.0005 | 0.001-0.003 | |
| 9 | 0.006 ± 0.003 | 0.0008 | 0.004-0.007 | 0.006 ± 0.003 | 0.0006 | 0.005-0.007 | 0.001 ± 0.001 | 0.0003 | 0.005-0.007 | NA | NA | NA | |
| 10 | 0.005 ± 0.006 | 0.0018 | 0.001-0.009 | 0.002 ± 0.002 | 0.0005 | 0.001-0.003 | 0.004 ± 0.004 | 0.0010 | 0.001-0.003 | NA | NA | NA | |
| 11 | 0.003 ± 0.003 | 0.0007 | 0.002-0.005 | 0.003 ± 0.002 | 0.0005 | 0.002-0.004 | 0.004 ± 0.002 | 0.0005 | 0.002-0.004 | 0.002 ± 0.001 | 0.0004 | 0.001-0.003 | |
| NS5A | 1 | 0.005 ± 0.002 | 0.0004 | 0.004-0.006 | 0.005 ± 0.003 | 0.0008 | 0.004-0.007 | 0.003 ± 0.004 | 0.0010 | 0.001-0.005 | 0.004 ± 0.002 | 0.0004 | 0.003-0.005 |
| 2 | 0.002 ± 0.001 | 0.0003 | 0.002-0.003 | 0.006 ± 0.006 | 0.0013 | 0.004-0.009 | 0.006 ± 0.003 | 0.0008 | 0.004-0.007 | 0.003 ± 0.002 | 0.0003 | 0.002-0.004 | |
| 3 | 0.004 ± 0.004 | 0.0008 | 0.003-0.006 | 0.005 ± 0.004 | 0.0009 | 0.003-0.007 | 0.005 ± 0.004 | 0.0009 | 0.004-0.007 | 0.004 ± 0.002 | 0.0005 | 0.003-0.006 | |
| 4 | 0.002 ± 0.001 | 0.0003 | 0.001-0.002 | 0.002 ± 0.003 | 0.0006 | 0.001-0.003 | 0.004 ± 0.004 | 0.0004 | 0.002-0.003 | 0.010 ± 0.006 | 0.0014 | 0.007-0.013 | |
| 5 | 0.003 ± 0.001 | 0.0002 | 0.003-0.004 | 0.006 ± 0.002 | 0.0005 | 0.005-0.007 | 0.002 ± 0.002 | 0.0005 | 0.001-0.004 | 0.002 ± 0.001 | 0.0003 | 0.001-0.002 | |
| 6 | 0.004 ± 0.003 | 0.0007 | 0.003-0.005 | 0.004 ± 0.003 | 0.0007 | 0.003-0.005 | 0.004 ± 0.003 | 0.0008 | 0.002-0.006 | 0.005 ± 0.003 | 0.0008 | 0.003-0.007 | |
| 7 | 0.007 ± 0.004 | 0.0010 | 0.005-0.009 | 0.007 ± 0.003 | 0.0007 | 0.006-0.008 | 0.006 ± 0.002 | 0.0005 | 0.005-0.007 | 0.008 ± 0.004 | 0.0010 | 0.006-0.010 | |
| 8 | 0.006 ± 0.004 | 0.0010 | 0.003-0.008 | 0.005 ± 0.005 | 0.0012 | 0.003-0.008 | 0.002 ± 0.001 | 0.0003 | 0.002-0.003 | 0.002 ± 0.001 | 0.0002 | 0.002-0.003 | |
| 9 | 0.007 ± 0.002 | 0.0005 | 0.006-0.008 | 0.004 ± 0.001 | 0.0003 | 0.003-0.005 | 0.006 ± 0.003 | 0.0007 | 0.005-0.008 | NA | NA | NA | |
| 10 | 0.003 ± 0.002 | 0.0004 | 0.002-0.004 | 0.001 ± 0.001 | 0.0002 | 0.001-0.002 | 0.003 ± 0.001 | 0.0002 | 0.002-0.003 | 0.002 ± 0.001 | 0.0003 | 0.001-0.002 | |
| 11 | 0.006 ± 0.003 | 0.0007 | 0.004-0.007 | 0.006 ± 0.002 | 0.0005 | 0.005-0.007 | 0.004 ± 0.002 | 0.0004 | 0.003-0.005 | NA | NA | NA | |
Mutation frequencies are expressed as number of substitutions per nucleotide. NA, not applicable.
Shannon entropy.
Shannon entropy is the probability that a given sequence or cluster of sequences will appear at a given time point. It gives a measure of the genetic diversity of a viral quasispecies at a given time point. Table 3 shows the Shannon entropy at every time point in the NS3 and NS5A coding regions for samples from the 11 patients. The values were very high at baseline, so it was not possible to detect an increase during therapy.
TABLE 3.
Shannon entropy in viral NS3 and NS5A coding regions at each time point for samples from the 11 patients
| Patient | Shannon entropya
|
|||||||
|---|---|---|---|---|---|---|---|---|
| NS3
|
NS5A
|
|||||||
| d−14 | d0 | d14 | d28 | d−14 | d0 | d14 | d28 | |
| 1 | 0.95 | 0.93 | 0.95 | 0.93 | 0.97 | 0.97 | 1.00 | 0.98 |
| 2 | 0.91 | 0.91 | 0.96 | 0.88 | 1.00 | 0.93 | 1.00 | 1.00 |
| 3 | 0.96 | 0.92 | 0.93 | 0.89 | 0.95 | 0.98 | 0.95 | 1.00 |
| 4 | 0.90 | 0.89 | 0.97 | 0.97 | 0.93 | 0.93 | 0.92 | 0.98 |
| 5 | 0.91 | 0.95 | 0.92 | 0.96 | 0.90 | 0.95 | 0.86 | 1.00 |
| 6 | 0.98 | 0.90 | 0.95 | 0.94 | 1.00 | 1.00 | 1.00 | 0.97 |
| 7 | 0.95 | 0.94 | 0.96 | 0.84 | 0.95 | 0.98 | 0.98 | 0.98 |
| 8 | 0.95 | 0.98 | 0.95 | 0.95 | 1.00 | 0.97 | 0.98 | 1.00 |
| 9 | 0.97 | 0.95 | 0.86 | NAb | 0.98 | 1.00 | 1.00 | NA |
| 10 | 0.91 | 0.93 | 0.97 | NA | 0.90 | 0.95 | 1.00 | 0.98 |
| 11 | 0.97 | 0.95 | 0.95 | 0.96 | 0.95 | 1.00 | 0.98 | NA |
For an explanation, see Materials and Methods.
NA, not applicable.
Mutation frequencies.
To determine whether the mutation frequency increased during ribavirin administration, the mean mutation frequencies at successive time points were compared by using Student's t test. As shown in Table 4, the vast majority of comparisons showed no significant differences between the viral mutation frequencies at consecutive time points for the 11 patients. The few significant differences were most often negative, indicating a trend towards a fall in the average mutation frequency over time. These occasional, randomly distributed significant differences could in fact have been due to chance, given the large number of statistical comparisons performed.
TABLE 4.
Comparison of mean viral mutation frequencies at two successive time pointsa
| Patient | Comparison of mutation frequencies for:
|
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| NS3
|
NS5A
|
|||||||||||
| d0 vs d−14
|
d14 vs d0
|
d28 vs d14
|
d0 vs d−14
|
d14 vs d0
|
d28 vs d14
|
|||||||
| Difference of means | P value | Difference of means | P value | Difference of means | P value | Difference of means | P value | Difference of means | P value | Difference of means | P value | |
| 1 | 0.002 | 0.0006 | 0.000 | 0.47 | 0.000 | 0.44 | 0.000 | 0.36 | −0.002 | 0.03 | 0.001 | 0.14 |
| 2 | 0.002 | 0.21 | −0.009 | <0.001 | 0.002 | 0.04 | 0.004 | 0.004 | 0.000 | 0.39 | −0.003 | 0.002 |
| 3 | 0.001 | 0.30 | 0.000 | 0.50 | −0.002 | 0.13 | 0.001 | 0.34 | 0.000 | 0.36 | −0.001 | 0.19 |
| 4 | 0.002 | 0.005 | 0.001 | 0.18 | 0.002 | 0.10 | 0.000 | 0.38 | 0.000 | 0.30 | 0.007 | <0.001 |
| 5 | −0.002 | 0.052 | −0.001 | 0.12 | 0.000 | 0.41 | 0.002 | <0.001 | −0.003 | <0.001 | 0.000 | 0.10 |
| 6 | 0.000 | 0.49 | 0.002 | 0.003 | 0.000 | 0.30 | 0.000 | 0.44 | 0.000 | 0.49 | 0.001 | 0.20 |
| 7 | 0.002 | 0.16 | −0.003 | 0.01 | 0.002 | 0.04 | 0.000 | 0.40 | −0.001 | 0.13 | 0.002 | 0.05 |
| 8 | 0.001 | 0.11 | −0.002 | 0.009 | 0.000 | 0.34 | 0.000 | 0.41 | −0.003 | 0.002 | 0.000 | 0.46 |
| 9 | 0.000 | 0.32 | −0.005 | 0.0001 | NAb | NA | −0.003 | <0.001 | 0.002 | 0.008 | NA | NA |
| 10 | −0.003 | 0.06 | 0.002 | 0.10 | NA | NA | −0.001 | 0.001 | 0.002 | <0.001 | −0.001 | 0.001 |
| 11 | 0.000 | 0.29 | 0.001 | 0.08 | 0.002 | 0.002 | 0.000 | 0.43 | 0.002 | <0.001 | −0.001 | 0.001 |
Mutation frequency is defined as the number of substitutions per nucleotide. The difference in means and the P value (Student's t test) are given for each 14-day interval for viral NS3 and NS5A coding regions for samples from 11 patients.
NA, not applicable.
In order to confirm the lack of an increase in mutation frequency during treatment, we performed linear regression analysis of the differences in mutation frequencies at each 14-day interval for each patient. The results showed that the accumulation of mutations did not accelerate significantly for samples from any of the patients when ribavirin was administered alone or in combination with IFN-α.
Additional regression analyses focused on the average difference in mean mutation frequencies for each 14-day period, pooling the results for the 11 patients, and for each treatment group. In the NS3 region, the P values for the slopes of the straight lines best fitting the data were always higher than 0.05 (data not shown), confirming the lack of acceleration of mutation accumulation during ribavirin administration with or without IFN-α. The P values were also nonsignificant for the NS5A region.
In a global analysis based on ANOVA, three or four groups of values were compared. The difference in the mean mutation frequencies for the d−14-to-d0 interval for samples from all patients was used as the control. It was compared with the differences in mean mutation frequencies in each treatment group for the d0-to-d14 interval on the one hand and for the d14-to-d28 interval on the other hand (group C could not be included in this last comparison because PCR amplification on d28 was possible with only one patient). This analysis showed that there was no significant difference in the mutation frequencies between the treatment groups or in either group relative to the control during either interval.
Error generation rates and between-sample genetic distances.
In order to complete the study of the diversity of HCV quasispecies during treatment with ribavirin, two additional parameters, the error generation rate and the between-sample genetic distance, were analyzed.
The error generation rate was determined as the mutation frequency relative to the consensus sequence at the previous time point, with a correction factor to obtain the rate per year (Tables 5 and 6). The error generation rate did not increase with ribavirin administration for any of the patients (regression analysis). Likewise, ANOVA showed no significant difference in the error generation rates between the controls (d−14 to d0) and the treated groups at either time interval (d0 to d14 or d14 to d28).
TABLE 5.
Error generation rates, between-sample genetic distances, and rates of variation of consensus sequences between two successive time points in the NS3 region
| Patient | Comparison of samples
|
||||||||
|---|---|---|---|---|---|---|---|---|---|
| d0 vs d−14
|
d14 vs d0
|
d28 vs d14
|
|||||||
| EGRa | Between-sample genetic distance | Rate of variation of consensus sequenceb | EGR | Between-sample genetic distance | Rate of variation of consensus sequence | EGR | Between-sample genetic distance | Rate of variation of consensus sequence | |
| 1 | 0.2586 | 0.0135 | 0.1914 | 0.1365 | 0.0094 | 0.0478 | 0.1149 | 0.0086 | 0.0478 |
| 2 | 0.5315 | 0.0226 | 0.3832 | 0.2777 | 0.0190 | 0.2392 | 0.4692 | 0.0252 | 0.4789 |
| 3 | 0.1915 | 0.0123 | 0.0000 | 0.2131 | 0.0133 | 0.0000 | 0.1101 | 0.0123 | 0.0478 |
| 4 | 0.2825 | 0.0135 | 0.1914 | 0.0982 | 0.0094 | 0.0000 | 0.1843 | 0.0129 | 0.0478 |
| 5 | 0.1413 | 0.0085 | 0.0957 | 0.0407 | 0.0065 | 0.0000 | 0.2801 | 0.0140 | 0.2392 |
| 6 | 0.1317 | 0.0084 | 0.0478 | 0.1628 | 0.0098 | 0.0000 | 0.1796 | 0.0129 | 0.1435 |
| 7 | 0.5842 | 0.0283 | 0.5746 | 0.1867 | 0.0111 | 0.1435 | 0.5099 | 0.0266 | 0.5268 |
| 8 | 0.1221 | 0.0081 | 0.0000 | 0.1820 | 0.0133 | 0.1435 | 0.1772 | 0.0106 | 0.1435 |
| 9 | 0.1676 | 0.0132 | 0.0000 | 0.0981 | 0.0106 | 0.0957 | NAc | NA | NA |
| 10 | 0.0287 | 0.0096 | 0.0000 | 0.1149 | 0.0080 | 0.0478 | NA | NA | NA |
| 11 | 0.0766 | 0.0078 | 0.0000 | 0.1221 | 0.0083 | 0.0000 | 0.1389 | 0.0112 | 0.0957 |
EGR, error generation rate (no. of nucleotides/site/year).
Rate of variation of consensus sequence is expressed as no. of nucleotides/site/year.
NA, not applicable.
TABLE 6.
Error generation rates, between-sample genetic distances, and rates of variation of consensus sequences between two successive time points in NS5A region
| Patient no. | Comparison of samples
|
||||||||
|---|---|---|---|---|---|---|---|---|---|
| d0 vs d−14
|
d14 vs d0
|
d28 vs d14
|
|||||||
| EGRa | Between-sample genetic distance | Rate of variation of consensus sequenceb | EGR | Between-sample genetic distance | Rate of variation of consensus sequence | EGR | Between-sample genetic distance | Rate of variation of consensus sequence | |
| 1 | 0.1284 | 0.0097 | 0.0187 | 0.0595 | 0.0079 | 0.0187 | 0.1227 | 0.0069 | 0.0187 |
| 2 | 0.2947 | 0.0160 | 0.2132 | 0.1638 | 0.0143 | 0.0582 | 0.1057 | 0.0099 | 0.0192 |
| 3 | 0.3611 | 0.0206 | 0.0905 | 0.3543 | 0.0229 | 0.0452 | 0.3160 | 0.0228 | 0.0452 |
| 4 | 0.6139 | 0.0264 | 0.5866 | 0.7042 | 0.0290 | 0.6318 | 0.6319 | 0.0311 | 0.1804 |
| 5 | 0.1551 | 0.0092 | 0.0192 | 0.0756 | 0.0105 | 0.0775 | 0.1861 | 0.0089 | 0.1357 |
| 6 | 0.1076 | 0.0084 | 0.0000 | 0.1241 | 0.0084 | 0.0192 | 0.1173 | 0.0093 | 0.0000 |
| 7 | 0.2123 | 0.0132 | 0.0775 | 0.1832 | 0.0124 | 0.0967 | 0.2259 | 0.0131 | 0.0000 |
| 8 | 0.1103 | 0.0102 | 0.0000 | 0.1006 | 0.0094 | 0.0385 | 0.1993 | 0.0112 | 0.1544 |
| 9 | 0.1619 | 0.0124 | 0.1160 | 0.2540 | 0.0124 | 0.1160 | NAc | NA | NA |
| 10 | 0.0950 | 0.0071 | 0.0775 | 0.1483 | 0.0070 | 0.1160 | 0.3529 | 0.0157 | 0.03448 |
| 11 | 0.3122 | 0.0135 | 0.1550 | 0.1338 | 0.0112 | 0.0385 | NA | NA | NA |
EGR, error generation rate (no. of nucleotides/site/year).
Rate of variation of consensus sequence is expressed as no. of nucleotides/site/year.
NA, not applicable.
The mean between-sample genetic distances were calculated on the basis of the distances between pairs of sequences obtained at 14-day intervals (Tables 5 and 6). Regression analysis showed no linear increase in the genetic distances with ribavirin administration, and the differences in means at consecutive time points were not significant for samples from the patients in a given group, except for one patient (patient 4), for whom a trend towards an increase in the between-sample genetic distances in the NS5A region was shown. Samples from this patient also showed a significant difference in the mutation frequencies in the same region between days 14 and 28.
A similar global ANOVA analysis of mutation frequencies and error generation rates was performed for the between-sample genetic distances and showed no difference between the three treatment groups or with the controls, either between d0 and d14 or between d14 and d28 (data not shown).
Rate of variation of the consensus sequence.
The rate of variation of the consensus sequence was also calculated in order to determine if treatment with ribavirin affects the fixation of mutations in the HCV genome, as would happen if the drug induced the selection of specific nucleotide substitutions. The results are shown in Tables 5 and 6 for the 11 patients. Regression analyses were performed with the differences in the rate of variation of the consensus sequence at 14-day intervals for samples from the 11 patients in the NS3 and NS5A coding regions. The P values for the slopes of the straight lines best fitted to the data indicated no sustained linear trend towards an increase in the fixation of mutations on ribavirin therapy (data not shown). The differences in the mean values at consecutive time points for patients belonging to a given treatment group were also not significant. A similar global ANOVA analysis of mutation frequencies was performed with this parameter and showed no significant difference between the three treatment groups or with the controls, either between d0 and d14 or between d14 and d28.
DISCUSSION
We conducted an extensive sequence-based analysis of two independent genomic regions of HCV, taking into consideration the quasispecies distribution of the viral genomes, in order to test in vivo the hypothesis that ribavirin administration accelerates the accumulation of mutations in the HCV genome and that this acceleration occurs only when HCV replication is profoundly inhibited by coadministered IFN-α. The spontaneous error generation rates observed for our three groups of patients prior to therapy, reflecting natural genetic drift, were higher than the known error rate of the HCV RNA-dependent RNA polymerase (11, 12). This was probably due to the fact that they were measured over a short period of time (14 days) and finally expressed per year.
Ribavirin monotherapy did not increase the mutation frequency, the error generation rate, or the between-sample genetic distances during either the first or the second 14-day period with treatment. Likewise, the accumulation of nucleotide substitutions did not accelerate relative to that in the pretreatment period during combination therapy with ribavirin and IFN-α at a dose of 3 MU given either daily or three times per week. Finally, these parameters did not increase between days 14 and 28 of therapy, when HCV replication was profoundly inhibited by IFN administration (day 28 corresponded to the last sample containing detectable HCV RNA for patients receiving combination therapy). Our painstaking statistical analysis showed no common trend towards an acceleration of the accumulation of mutations during ribavirin monotherapy or during IFN-ribavirin combination therapy even when viral replication was profoundly inhibited by IFN-α. These results show that ribavirin does not act as an RNA mutagen in vivo, at least at the weight-based doses used for therapy and despite relatively high concentrations in plasma (the steady-state ribavirin concentration in peripheral blood was reached on day 14).
Although we examined only viruses circulating in peripheral blood, these viral populations closely reflect virions produced in the liver, since the average half-life of free HCV virions in the general circulation is of the order of 2.7 h and about 1012 virions are produced and cleared daily (32). In addition, there is no clear reason why viruses undergoing random nucleotide substitutions under the putative mutagenic effect of ribavirin should be preferentially sequestered in the liver while nonmutated virions would be normally excreted and released into peripheral blood.
Our findings therefore show that ribavirin has no noteworthy mutagenic effect in vivo, even when HCV replication is strongly inhibited by IFN administration. This is important in light of the recent suggestion by Dixit et al., based on mathematical modeling of viral decay in patients receiving the IFN-ribavirin combination, that the main action of ribavirin is to render HCV virions less infectious and that this property is revealed only when HCV replication is profoundly inhibited by the antiviral properties of coadministered IFN (10). If this is so (and it has not yet been experimentally confirmed), our results do not suggest that the underlying mechanism is error catastrophe due to accelerated mutagenesis.
The very high concentrations of ribavirin used in in vitro studies in which the mutagenic effect of ribavirin was observed could explain the discrepancy with our results obtained in the clinical setting. Indeed, the doses used in vitro were generally near toxic (50 to 1,000 μM, doses that cannot be achieved intracellularly during human therapy), and mutagenesis appeared to be concentration dependent. Interestingly, the ribavirin concentration required to achieve a significant antiviral effect differed between HCV-unrelated viruses (100 to 1,000 μM), GB virus B (100 to 200 μM), and subgenomic HCV replicons (50 to 400 μM) (1, 5, 8, 16, 20, 21, 48). Different cell types might have different capacities to convert ribavirin into RTP, and different rates of division (primary hepatocytes versus cultured cells) could influence the size of the intracellular GTP pool and the affinity of the polymerase for ribavirin. In any case, the ribavirin concentrations achieved with these models were substantially higher than those achieved intracellularly during human therapeutics (the latter cannot easily be measured, owing to the lack of an appropriate assay).
Our results differ from those of Asahina et al. (3), who reported a significantly higher rate of HCV mutations during 4 weeks of ribavirin monotherapy than prior to therapy (3). That study was based on direct sequence analysis; however, the approach is subject to misinterpretation of mixed or ambiguous profiles. In contrast, we used extensive quasispecies analysis to evaluate any possible change in the diversity of the population that could result from an increase of the virus polymerase error rate. In addition, Asahina's study suffered from a major methodological bias, since the pretreatment control period was variable (6 months on average; range, 2 to 48 months), whereas ribavirin monotherapy always lasted 4 weeks (3). We have found that error generation rates bear a negative relation to the interval between the two time points used to calculate them (Chevaliez and Pawlotsky, unpublished observation). This is due to the increase in the numerator (duration of the interval) in a context of slow spontaneous and random accumulation of mutations and to the use of short target sequences. As a result, the error generation rates during the pretreatment period in Asahina's study were probably substantially underestimated. In order to avoid this bias, we chose to use the same duration (14 days) for each of the three studied intervals, comprising the pretreatment period (control period), the first 14 days of treatment, and the second 14-day period, during which patients receiving combination therapy had variable levels of inhibition of HCV replication by IFN-α. With this approach we were able to show that mutation accumulation in two independent HCV genomic regions did not accelerate during treatment with ribavirin either alone or combined with IFN-α. These results are in keeping with preliminary studies which found no difference in error generation rates between patients receiving ribavirin monotherapy, IFN-α monotherapy, or IFN-ribavirin combinations (2, 43, 52).
In conclusion, our study, based on a robust methodology, strongly undermines the hypothesis whereby ribavirin acts as an HCV mutagen in vivo, leading to error catastrophe and viral eradication when combined with IFN. This is not altogether surprising, since the hypothesis was based on the use of in vitro models and near-toxic ribavirin concentrations. Unfortunately, the mechanism of ribavirin action remains as elusive as ever. A direct antiviral effect does not appear to play a major role, and neither does IMPDH inhibition (18, 28, 31, 37). A breakthrough in our understanding of how ribavirin works is urgently needed in order to develop drugs that mimic the antiviral properties of ribavirin without inducing severe hemolytic anemia, an adverse effect that often leads to dose reductions or withdrawal and subsequent treatment failure.
Acknowledgments
This work is part of the activities of the VIRGIL European Network of Excellence on Antiviral Drug Resistance, supported by a grant (LSHM-CT-2004-503359) from the Priority 1 “Life Sciences, Genomics and Biotechnology for Health” program in the 6th Framework Programme of the European Union. The drugs were provided by Schering-Plough Research International, and the ribavirin and HCV RNA assays were funded by an unrestricted grant from Schering-Plough Research Institute.
We are grateful to Esteban Domingo for very helpful discussions and for his comments on the manuscript.
Footnotes
Published ahead of print on 9 May 2007.
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