The Role of Infected Cell Proliferation in the Clearance of Acute HBV Infection in Humans

Goyal, Ashish; Ribeiro, Ruy M.; Perelson, Alan S.

doi:10.3390/v9110350

Cited by 33 publications

(46 citation statements)

References 96 publications

(178 reference statements)

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“…Mathematical techniques alongside biological data have been used for the last 20 years in the study of hepatitis B infection, immune pathogenesis, and disease treatment. They were instrumental in determining virus characteristics, such as virus production levels, virus clearance rates, and half‐life of infected cells . Moreover, they investigated the relative contribution of immune responses in resolving acute infection in humans and animal models; the role of serum HBeAg in inducing immune exhaustion, and the relation between HBeAg loss and therapy success; the efficacy of drug therapy in removing HBV DNA; the amount of liver turnover; and the optimal control of HBV therapy …”

Section: Discussionmentioning

confidence: 99%

“…By contrast, only 1‐3 copies of cccDNA were reported in human infections . Mathematical models and experimental studies have investigated the role of cccDNA, in particular the contribution of recycling and loss through cell division in disease maintenance or resolution . Computational studies have investigated the possibility of cccDNA removal through gene therapy; while others proposed phenomena for cccDNA maintenance inside a cell, with recycling and amplification versus superinfection being proposed as explanatory mechanisms .…”

Section: Discussionmentioning

confidence: 99%

“…It is known that liver has a great ability to regenerate following injury . To account for this, logistic proliferation terms were introduced into both the uninfected and infected hepatocyte populations, with [ r T ] and [ r I ] being per capita proliferation rates and [ K ] the liver carrying capacity . Last, a cure of an infected cell at rate [ ρ ] through non‐cytopathic effects has been included .…”

Section: Basic Chronic Hbv Modelmentioning

confidence: 99%

“…39,43 To account for this, logistic proliferation terms were introduced into both the uninfected and infected hepatocyte populations, with [r T ] and [r I ] being per capita proliferation rates and [K] the liver carrying capacity. [19][20][21]23,32 Last, a cure of an infected cell at rate [ρ] through non-cytopathic effects has been included. 44 A model diagram for these interactions is given in (Figure 2) and the corresponding dynamical system describing the hepatitis B infection is The model given by (Equation 1) explains the dynamics seen during chronic HBV infection in the absence of therapy, with high peaks of ≥10 8 HBV DNA 26,45 copies per mL during the acute stage, [19][20][21] followed in many individuals by the attainment of a steady state viral load whose level varies among individuals.…”

Section: Ba S Ic Chronic Hbv Modelmentioning

confidence: 99%

“…Mathematical models have been developed and used for insight into the hepatitis B infection, treatment, and progression. Some studies investigated the mechanisms behind progression from acute to chronic disease in humans and animal models . Others estimated the efficacy of mono‐ and combination drug therapy, the virological‐immunological mechanisms associated with the therapy, and the role of immune responses in HBV DNA removal .…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Modeling the dynamics of hepatitis B infection, immunity, and drug therapy

Ciupe

2018

Immunological Reviews

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Hepatitis B virus infection is the cause of liver diseases such as cirrhosis and liver cancer. Understanding the host-virus mechanisms that mediate virus pathogenesis can help design better preventive measures for disease control. Mathematical models have been used alongside experimental data to provide insight into the role of immune responses during the acute and chronic hepatitis B infections as well as virus dynamics following administration of combined drug therapy. In this paper, we review several modeling studies on virus-host interactions during acute infection, the virus-host characteristics responsible for transition to chronic disease, and the efficacy and optimal control measures of drug therapy. We conclude by presenting our opinion on the future directions of the field.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Basic Chronic Hbv Modelmentioning

confidence: 99%

Section: Ba S Ic Chronic Hbv Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modeling the dynamics of hepatitis B infection, immunity, and drug therapy

Ciupe

2018

Immunological Reviews

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Mechanistic Modeling of SARS‐CoV‐2 and Other Infectious Diseases and the Effects of Therapeutics

Perelson

2021

Clin Pharma and Therapeutics

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Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical, and modeling communities during the early days of the AIDS epidemic. Its successes led to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus and cytomegalovirus, which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus, West Nile virus, Zika virus, and severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. We then focus on recent efforts and contributions of applying these models towards understanding SARS‐CoV‐2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize nonpharmaceutical and pharmaceutical interventions of the coronavirus disease 2019 (COVID‐19) pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein, “Everything should be made as simple as possible, but not simpler,” and this idea underlies the modeling we describe below.

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A Semi‐mechanistic Model to Characterize the Long‐Term Dynamics of Hepatitis B Virus Markers During Treatment With Lamivudine and Pegylated Interferon

Messaoudi

Lemenuel‐Diot

Gonçalves

et al. 2023

Clin Pharma and Therapeutics

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Antiviral treatments against hepatitis B virus (HBV) suppress viral replication but do not eradicate the virus, and need therefore to be taken lifelong to avoid relapse. Mathematical models can be useful to support the development of curative anti-HBV agents; however, they mostly focus on short-term HBV DNA data and neglect the complex hostpathogen interaction. This work aimed to characterize the effect of treatment with lamivudine and/or pegylated interferon (Peg-IFN) in 1,300 patients (hepatitis B envelope antigen (HBeAg)-positive and HBeAg-negative) treated for 1 year. A mathematical model was developed incorporating two populations of infected cells, namely I 1 , with a high transcriptional activity, that progressively evolve into I 2 , at a rate tr , representing cells with integrated HBV DNA that have a lower transcriptional activity. Parameters of the model were estimated in patients treated with lamivudine or Peg-IFN alone (N = 894), and the model was then validated in patients treated with lamivudine plus Peg-IFN (N = 436) to predict the virological response after a year of combination treatment. Lamivudine had a larger effect in blocking viral production than Peg-IFN (99.4-99.9% vs. 91.8-95.1%); however, Peg-IFN had a significant immunomodulatory effect, leading to an enhancement of the loss rates of I 1 (×1.7 in HBeAg-positive patients), I 2 (> ×7 irrespective of HBeAg status), and tr (×4.6 and ×2.0 in HBeAg-positive and HBeAg-negative patients, respectively). Using this model, we were able to describe the synergy of the different effects occurring during treatment with combination and predicted an effect of 99.99% on blocking viral production. This framework can therefore support the optimization of combination therapy with new anti-HBV agents.Chronic hepatitis B virus (CHB) infection is a leading cause of liver disease, including cirrhosis and hepatocellular carcinoma. In 2021, nearly 300 million people were chronically infected worldwide, resulting in more than 800,000 deaths. 1 To reduce disease progression, antiviral treatments rely on two therapeutic classes, nucleoside analogs (NUCs) and pegylated interferons (Peg-IFNs), which are

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The Role of Infected Cell Proliferation in the Clearance of Acute HBV Infection in Humans

Cited by 33 publications

References 96 publications

Modeling the dynamics of hepatitis B infection, immunity, and drug therapy

Modeling the dynamics of hepatitis B infection, immunity, and drug therapy

Mechanistic Modeling of SARS‐CoV‐2 and Other Infectious Diseases and the Effects of Therapeutics

A Semi‐mechanistic Model to Characterize the Long‐Term Dynamics of Hepatitis B Virus Markers During Treatment With Lamivudine and Pegylated Interferon

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