Association of IL28B gene variations with mathematical modeling of viral kinetics in chronic hepatitis C patients with IFN plus ribavirin therapy

Hsu, Ching–Sheng; Hsu, Shih‐Jer; Chen, Hung-Chia; Tseng, Tai‐Chung; Liu, Chen–Hua; Niu, Wei-Fang; Jeng, Jenher; Liu, Chun‐Jen; Lai, Ming-Yang; Chen, Pei‐Jer; Kao, Jia‐Horng; Chen, Ding‐Shinn

doi:10.1073/pnas.1100349108

Cited by 57 publications

(48 citation statements)

References 51 publications

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“…We appreciate the comments of Guedj et al (1) on our paper addressing the association of IL28B gene variations with mathematical modeling of viral kinetics in patients with chronic hepatitis C treated with pegylated IFN plus ribavirin therapy (2). Regarding the distribution of the blips among hepatitis C virus (HCV) genotypes, we not only found a lower virion production rate but earlier blips among patients with HCV genotype 2 infection than those with genotype 1 infection.…”

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confidence: 63%

Reply to Guedj et al.: Early transient increase of hepatitis C virus viral load in genotype 1 and 2 infections, and the use of mathematical modeling

Hsu¹,

Chen²,

Jeng³

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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We appreciate the comments of Guedj et al.(1) on our paper addressing the association of IL28B gene variations with mathematical modeling of viral kinetics in patients with chronic hepatitis C treated with pegylated IFN plus ribavirin therapy (2). Regarding the distribution of the blips among hepatitis C virus (HCV) genotypes, we not only found a lower virion production rate but earlier blips among patients with HCV genotype 2 infection than those with genotype 1 infection. The time for the observed maximal viral load and the estimated time for maximal viral load were significantly different between these two genotypes (genotype 1 vs. 2: 0.33 ± 0.35 vs. 0.19 ± 0.12; P = 0.0048 and P = 0.0106 for the t test and Wilcoxon test), and the time for the maximal value also showed that patients with HCV genotype 1 infection had a poorer virological response than those with genotype 2 infection (Table 1). However, as reported in our paper, although HCV genotype has long been known as a predictor of achieving sustained virological response (SVR) in patients treated with combination therapy, it also serves as a latent factor of viral kinetics, especially for virion production rate. Thus, the impact of HCV genotype on SVR was not significant in our regression models, and viral kinetic parameters were still better than HCV genotype in the prediction of SVR.As to the modeling of HCV kinetics during combination therapy, we assumed that target cells remained constant in the first 2 wk and estimated K 1 ′ and K 2 ′ by fitting the viral load data of the first 3 d for each patient. Because all patients had persistent HCV infection, their viral loads would be in the steady state (a state of equilibrium), almost remain constant before therapy, and not increase before therapy, as raised by Guedj et al. (1). However, this does not indicate that the viral loads will surely decline after treatment because there could be a transition state in the very early stage of therapy. Thus, we chose the solution (three-parameter solution) that could model the observed earlier blips of the earlier transition state. The earlier transition state corresponds to the condition δ = c, which is necessary for the three-parameter solution to hold. In other words, we have a state of equilibrium, δ = c, in the earlier transition state. On the other hand, the four-parameter solution, the choice of the standard mathematical model for HCV infection and treatment (3), represents the other state of "equilibrium." According to this standard model, "c is approximately 50 times larger than δ" (4), and we believe that the patients with this kind of condition are not analyzed under the consideration of earlier transition state but are only focused on in the state of viral load progression before SVR and that this later equilibrium is achieved under the complex interactions of therapy, the host immune system, and HCV from the earlier transition state.Therefore, our three-parameter model and the standard model indeed present different equilibrium states of HCV kinetics. F...

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confidence: 63%

Reply to Guedj et al.: Early transient increase of hepatitis C virus viral load in genotype 1 and 2 infections, and the use of mathematical modeling

Hsu¹,

Chen²,

Jeng³

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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“…In the absence of large studies with time scales of hours, it is difficult to verify if all the blips observed were generated by IFN/ribavirin therapy. Nonetheless, Hsu et al (1) showed that among patients who had blips, a significantly higher proportion of patients with SVR had early blips, suggesting that a large proportion of the blips were related to therapy. Because patients infected with HCV genotype 1 respond poorly to IFN/ ribavirin compared with those infected with HCV genotype 2, the distribution of the blips among HCV genotypes would be relevant.…”

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confidence: 99%

“…In PNAS, Hsu et al (1) observed an early transient increase (here, termed a blip) in hepatitis C virus (HCV) viral load in 92 out of 145 Taiwanese patients with chronic hepatitis C treated with pegylated IFN-α (IFN) and ribavirin and found that these blips were significantly associated with the outcome of therapy [i.e., sustained virologic response (SVR)]. Further, they sought to explain the origin and time of these blips using a version of a well-studied mathematical model of HCV infection and treatment (2) in a nonstandard way.…”

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confidence: 99%

“…If one makes this assumption, one can then show that therapy, which decreases viral production, will lead to a decrease in viral load and cannot reproduce viral blips. In the three-parameter model solution used by Hsu et al (1) [i.e., V(t = time) = (K 1 ′t + K 2 ′)e −ct )], imposing pretreatment steady state implies K 2 ′ = V 0 , the baseline viral load, and K 1 ′ = (1 − ε)cV 0 , where ε is the effectiveness of treatment in blocking virion production and c is the virion clearance rate (2). Hsu et al (1) did not assume viral steady state before therapy and left K 1 ′ and K 2 ′ as free parameters without justification.…”

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Understanding the nature of early HCV RNA blips and the use of mathematical modeling of viral kinetics during IFN-based therapy

Guedj

Dahari²,

Perelson

2011

Proc. Natl. Acad. Sci. U.S.A.

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In PNAS, Hsu et al. (1) observed an early transient increase (here, termed a blip) in hepatitis C virus (HCV) viral load in 92 out of 145 Taiwanese patients with chronic hepatitis C treated with pegylated IFN-α (IFN) and ribavirin and found that these blips were significantly associated with the outcome of therapy [i.e., sustained virologic response (SVR)]. Further, they sought to explain the origin and time of these blips using a version of a well-studied mathematical model of HCV infection and treatment (2) in a nonstandard way. Although these blips are interesting, several concerns need to be raised before further interpretation of the findings of Hsu et al. (1) is made.During chronic HCV infection, the serum level of HCV RNA can vary (up to 0.5-log) on time scales of weeks to months (3). In the absence of large studies with time scales of hours, it is difficult to verify if all the blips observed were generated by IFN/ribavirin therapy. Nonetheless, Hsu et al. (1) showed that among patients who had blips, a significantly higher proportion of patients with SVR had early blips, suggesting that a large proportion of the blips were related to therapy. Because patients infected with HCV genotype 1 respond poorly to IFN/ ribavirin compared with those infected with HCV genotype 2, the distribution of the blips among HCV genotypes would be relevant.A basic assumption in modeling HCV kinetics during treatment is that viral load is constant before therapy, implying that the rate of viral production equals the rate of virion clearance in the absence of therapy (2). If one makes this assumption, one can then show that therapy, which decreases viral production, will lead to a decrease in viral load and cannot reproduce viral blips. In the three-parameter model solution used by Hsu et al. (1) [i.e., V(t = time) = (K 1 ′t + K 2 ′)e −ct )], imposing pretreatment steady state implies K 2 ′ = V 0 , the baseline viral load, and K 1 ′ = (1 − ε)cV 0 , where ε is the effectiveness of treatment in blocking virion production and c is the virion clearance rate (2). Hsu et al. (1) did not assume viral steady state before therapy and left K 1 ′ and K 2 ′ as free parameters without justification. Moreover, the interpretation of the blips is hampered by a number of questionable assumptions made in deriving the three-parameter model solution, such as therapy being 100% effective in blocking new infections and δ, the rate of infected cell death, set equal to c, despite prior studies showing c is ∼50-fold larger than δ (4).Clearly, if some patients were not in steady state and had viral loads increasing before therapy (i.e., viral production higher than viral clearance), then, on therapy initiation, viral loads would continue to increase until the effect of therapy reduces the viral production rate below the viral clearance rate (5). The more effective the therapy, the sooner this should occur, possibly explaining why among patients who had blips, patients with SVR had earlier blips than patients without SVR. This conclusion can be reached...

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“…Recent genome-wide association studies (GWAS) have identified strong associations of single nucleotide polymorphisms (SNPs) in the interleukin-28B (IL28B) region with spontaneous clearance of HCV [22], therapeutic response, and early viral kinetics to combination therapy in HCV-infected individuals [23,24]. Since metabolic regulation and immune response are highly integrated [25], HCV-related immune reactions may play a given role in modulating the associations between serum Apo C-III and disease progression.…”

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confidence: 99%

Hepatitis C virus and lipid profiles: more questions than answers?

Hsu

Kao

2011

Hepatol Int

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Association of IL28B gene variations with mathematical modeling of viral kinetics in chronic hepatitis C patients with IFN plus ribavirin therapy

Cited by 57 publications

References 51 publications

Reply to Guedj et al.: Early transient increase of hepatitis C virus viral load in genotype 1 and 2 infections, and the use of mathematical modeling

Reply to Guedj et al.: Early transient increase of hepatitis C virus viral load in genotype 1 and 2 infections, and the use of mathematical modeling

Understanding the nature of early HCV RNA blips and the use of mathematical modeling of viral kinetics during IFN-based therapy

Hepatitis C virus and lipid profiles: more questions than answers?

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