HBV Translational Science
Despite an effective vaccine, hepatitis B virus (HBV) remains a growing health concern and burden on systems. Hundreds of millions globally are infected. The virus in adults will typically be an acute infection but for children and infants, the rate of HBV as a chronic infection can be as high as 90%. This presents a serious health issue for the patient and strains healthcare resources. Additionally, HBV carries are at risk of co-infection with hepatitis D which is more aggressive in its attack on the liver. Previous research was limited by lack of in vitro cultures and small animal models to study both the infection and treatment. Now we are able to observe the HBV lifecycle and treatment response in cell cultures as well as mice. This will lead to a better understanding of the virus at the molecular level and is critical to developing more effective treatment strategies. Mathematical modelling has played a key role in filling previous clinical gaps and will deepen our understanding as the research evolves. The goal is to map and understand the detailed molecular biological processes that regulate HBV infection. In Dahari Lab we work with a cross disciplinary team of virologists, animal modeling experts, computational scientists, clinicians and pharmaceutical companies, we aim to better understand the virus-host interplay, the mode of actions of current and new antivirals, and treatment strategies. All of this is possible with more sophisticated models and is key to achieving a cure.
Understanding hepatitis B virus RNA kinetics
In two letters published in Hepatology and Journal of Viral Hepatitis, Dahari Lab and partners underscored some interesting data in the search for better treatments and ultimately a cure for HBV. Specifically, the Lab identified two areas of interest.
One is HBV RNA as additional new marker in the blood when trying to understand the status of HBV infection in patients (Journal of Viral Hepatitis). Current markers such as HBV DNA in the blood stream, have proven to be limited in their indication of covalently closed circular DNA (cccDNA) clearance for HBV. The research on HBV RNA kinetics suggests this marker may be more reliable in understanding the viral levels present.
The second is nucleos(t)ide analogue (NA) therapy (Hepatology). Using mathematical modeling it is possible to gain a clearer understanding of the NA mode of actions, especially as it relates to the interplay with RNA kinetics. Further study of RNA kinetics during NA treatment in patients could yield significant data that informs more effective therapies for clearing the virus.
We are excited to explore this next phase with our research partners.
New Drug Research for Improved Treatments for HBV: RNAi-based Therapy
Current drugs are effective in suppressing the virus but do not lead to cure. Achieving HBV cure is early stages for for hepatitis B sice Current treatment options available focus on removing circulating HBV DNA but not effective however in removing the HBV surface- and e- antigens that allow patients’ immune response to fight the virus.
Why does this matter? What are their functions?
Recent clinical studies showed promising results in the use of an RNA interference-based (RNAi) treatment to address this short coming of the existing treatment. By mathematically modeling available HBV kinetic data under RNAi treatment, we were able to provide insights into HBV-host dynamics and estimate RNAi efficacy in reducing circulating virus, s and e antigens (BIORXIV). Further research in this area could aid in the development of 2nd generation RNAi-based therapies.
Understanding HBV at the Cellular Level through Modeling
Mathematical modeling was used to provide insights into interferon-a (INF) treatment and viral-host interplay at the molecular level. The research was possible through the use of data from chimeric mice with humanized livers. One of the outcomes of this research was to better understand the dynamics of HBV treatment response and the mode of action of INF against HBV. Details of the dynamic of HBV infection and treatment at the molecular level are necessary to develop effective treatment strategies (BIORXIV)
Research in chimeric mice with humanized livers provides insights into the early dynamics of acute HBV infection
Two significant pieces of collaborative research with Prof. Chayama at Hiroshima University, revealed, and further explored the multiphasic nature of HBV. The first piece of research (HEPATOLOGY) uncovered and characterized the surprising multiphasic nature of HBV infection. This finding is especially significant when it was revealed that the virus moves through these phases without the host producing a specific anti-HBV adaptive immune response.
The second study is more theoretical and builds on this knowledge. It describes in greater detail the multiphasic viral host dynamics (JOURNAL OF HEPATOLOGY). The humanized chimeric mice allow for researchers to track from the exact moment of infection which allows for more accurate HBV infection patterns to be studied. The combined efforts of observational study and the ongoing theoretical modeling allow for a better understanding of the release of virions (infective form of the virus) over time from the moment of infection.
Understanding HBV dynamics and the antiviral effect of interferon-α treatment in humanized chimeric mice
Tracking virus kinetics via the blood/serum is very common and data is abundant from patients, whereas the dynamics of the virus at the cellular level (in the liver) is still in the early stages of data collection. Collaboration with Prof. Chayama of Hiroshima University resulted in a deeper understanding of the mode of action of interferon-α-based treatments. However, this research is important beyond showing differences in the efficacy of these treatments (BIORXIV). The ability to compare the results simultaneously of the viral kinetics in the blood as well as “inside” the liver at the cellular level is an important contribution to the study of HBV. The richer data gathered through chimeric mice with humanized livers results in a more accurate model. This liver-based cellular data is necessary to build a strong foundational knowledge for more advanced research.