Variability in long-term hepatitis B virus dynamics under antiviral therapy

Modeling reveals no direct role of the extent of HBV DNA integrations on the outcome of infection

Hepatitis B virus (HBV) with its high prevalence and death toll is one of the most important infectious diseases to study. Yet, there is very little progress in the development of within-host models for HBV, which has subsequently hindered our understanding of this virus. The uncertainty around the proliferation of infected hepatocytes has been studied but never in association with other important biological continuous events such as integrations and superinfections. This is despite the fact that these processes affect the diversity and composition of infected cell population in the liver and an improved understanding of the cellular composition will undoubtedly assist in strategizing against this viral infection. Here, we developed novel mathematical models that incorporate these key biological processes and analyzed them both analytically and numerically. Unaffected by the extent of integrated DNA (IDNA), the outcome of HBV infection was primarily dictated by the balance between processes generating and killing infected hepatocytes containing covalent closed circular DNA (cccDNA). The superinfection was found to be a key process in the spread of HBV infection as its exclusion could not reproduce experimentally observed composition of infected hepatocytes at peak of acute HBV infection, a stage where our model predicts that infected hepatocytes most likely carry both cccDNA and IDNA. Our analysis further suggested the existence of some form of selective advantage of infected hepatocytes containing only IDNA to explain the viral dynamics observed during antiviral treatment and the transition from peak to acute infection. Finally, the fine line between liver destruction and resolution of acute HBV infection was found to be highly influenced by the fate of cccDNA during cellular proliferation.

Within-host mathematical models of hepatitis B virus infection: Past, present, and future

Mathematical modeling has been instrumental in enhancing our understanding of the viral dynamics of hepatitis B virus (HBV) infection. We give a primer on HBV infection in humans and a brief overview of the development of within-host mathematical models of HBV infection. In the last decade, models have advanced from considering chronic HBV infections under therapy to the pathogenesis of infection. We also summarize estimates of key viral dynamic parameters that have varied greatly among studies, and show that they impact model predictions. Future directions for mathematical modeling of HBV infection are proposed to better understand emerging therapies, the HBV life cycle, predicting cure, and the mechanisms involved in the immune response to HBV infection.

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

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.

The review of differential equation models of HBV infection dynamics

Understanding the infection and pathogenesis mechanism of hepatitis B virus (HBV) is very important for the prevention and treatment of hepatitis B. Mathematical models contribute to illuminate the dynamic process of HBV replication in vivo. Therefore, in this paper we review the viral dynamics in HBV infection, which may help us further understand the dynamic mechanism of HBV infection and efficacy of antiviral treatment. Firstly, we introduce a family of deterministic models by considering different biological mechanisms, such as, antiviral therapy, CTL immune response, multi-types of infected hepatocytes, time delay and spatial diffusion. Particularly, we briefly describe the stochastic models of HBV infection. Secondly, we introduce the commonly used parameter estimation methods for HBV viral dynamic models and briefly discuss how to use these methods to estimate unknown parameters (such as drug efficacy) through two specific examples. We also discuss the idea and method of model identification and use a specific example to illustrate its application. Finally, we propose three new research programs, namely, considering HBV drug-resistant strain, coupling within-host and between-host dynamics in HBV infection and linking population dynamics with evolutionary dynamics of HBV diversity.

How to prevent viremia rebound? Evidence from a PRRSv data-supported model of immune response

Background

Understanding what determines the between-host variability in infection dynamics is a key issue to better control the infection spread. In particular, pathogen clearance is desirable over rebounds for the health of the infected individual and its contact group. In this context, the Porcine Respiratory and Reproductive Syndrome virus (PRRSv) is of particular interest. Numerous studies have shown that pigs similarly infected with this highly ubiquitous virus elicit diverse response profiles. Whilst some manage to clear the virus within a few weeks, others experience prolonged infection with a rebound. Despite much speculation, the underlying mechanisms responsible for this undesirable rebound phenomenon remain unclear.

Results

We aimed at identifying immune mechanisms that can reproduce and explain the rebound patterns observed in PRRSv infection using a mathematical modelling approach of the within-host dynamics. As diverse mechanisms were found to influence PRRSv infection, we established a model that details the major mechanisms and their regulations at the between-cell scale. We developed an ABC-like optimisation method to fit our model to an extensive set of experimental data, consisting of non-rebounder and rebounder viremia profiles. We compared, between both profiles, the estimated parameter values, the resulting immune dynamics and the efficacies of the underlying immune mechanisms. Exploring the influence of these mechanisms, we showed that rebound was promoted by high apoptosis, high cell infection and low cytolysis by Cytotoxic T Lymphocytes, while increasing neutralisation was very efficient to prevent rebounds.

Conclusions

Our paper provides an original model of the immune response and an appropriate systematic fitting method, whose interest extends beyond PRRS infection. It gives the first mechanistic explanation for emergence of rebounds during PRRSv infection. Moreover, results suggest that vaccines or genetic selection promoting strong neutralising and cytolytic responses, ideally associated with low apoptotic activity and cell permissiveness, would prevent rebound.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0666-7) contains supplementary material, which is available to authorized users.

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

Around 90-95% of hepatitis B virus (HBV) infected adults do not progress to the chronic phase and, instead, recover naturally. The strengths of the cytolytic and non-cytolytic immune responses are key players that decide the fate of acute HBV infection. In addition, it has been hypothesized that proliferation of infected cells resulting in uninfected progeny and/or cytokine-mediated degradation of covalently closed circular DNA (cccDNA) leading to the cure of infected cells are two major mechanisms assisting the adaptive immune response in the clearance of acute HBV infection in humans. We employed fitting of mathematical models to human acute infection data together with physiological constraints to investigate the role of these hypothesized mechanisms in the clearance of infection. Results suggest that cellular proliferation of infected cells resulting in two uninfected cells is required to minimize the destruction of the liver during the clearance of acute HBV infection. In contrast, we find that a cytokine-mediated cure of infected cells alone is insufficient to clear acute HBV infection. In conclusion, our modeling indicates that HBV clearance without lethal loss of liver mass is associated with the production of two uninfected cells upon proliferation of an infected cell.

Chronic hepatitis B surface antigen seroclearance-related immune factors

The ultimate aims of the treatment of hepatitis B virus infection are the loss of hepatitis B surface antigen (HBsAg) and hepatitis B surface antibody seroconversion. Unfortunately, these goals are rarely reached. Many factors are associated with HBsAg seroconversion, including genetic, immune, and viral factors. However, the mechanism of HBsAg seroclearance, and particularly the immune mechanism, is still difficult to elucidate. The immune factor interferon-α is currently the main antiviral therapy for chronic hepatitis B virus infection. However, a sustained shift from response of HBsAg to hepatitis B surface antibody seroconversion is rarely obtained. Recent studies have revealed that several of the newly identified immune factors are closely related to the removal of HBsAg. In this article, we review recent studies on these immune factors, their influence on hepatitis B progression, and HBsAg seroconversion.