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Variability in long-term hepatitis B virus dynamics under antiviral therapy
John M Murray1, Ognjen Stancevic1, Marc Lütgehetmann2
1School of Mathematics and Statistics, UNSW Australia, Sydney, NSW, Australia.
Journal of Theoretical Biology
|January 3, 2016
Summary
Hepatitis B virus (HBV) treatment response varies significantly. Mathematical modeling suggests viral clone dynamics and delayed antibody response explain diverse patient outcomes despite similar liver viral loads.
Area of Science:
- Hepatology and Virology
- Immunology
- Pharmacodynamics
Background:
- Hepatitis B virus (HBV) infection dynamics during treatment are complex and distinct from other viral infections.
- Understanding these dynamics is crucial for optimizing antiviral therapy.
Purpose of the Study:
- To analyze the dynamics of liver and serum HBV DNA in patients undergoing combination therapy and monotherapy.
- To identify factors influencing diverse treatment responses and viral load oscillations.
Main Methods:
- Longitudinal analysis of serum and liver HBV DNA, HBsAg, ALT, and cccDNA in 24 chronically HBV-infected individuals over 3 years.
- Patient stratification into four response groups based on serum viral load kinetics.
- Mathematical modeling to simulate viral dynamics and immune recognition.
Main Results:
- Four distinct patient response groups emerged, not predictable by baseline viral markers or liver cccDNA levels.
- Despite varied serum HBV DNA levels, no significant differences in liver HBV DNA or cccDNA were observed between groups after 3 years.
- Serum HBsAg levels were significantly lower in the best response group (GRP1) compared to the virological failure group (GRP4).
- Mathematical modeling indicated that sequential outgrowth of viral clones with delayed antibody recognition could explain the observed diverse dynamics and oscillations.
Conclusions:
- Serum viral load dynamics are a key differentiator of treatment response in HBV infection.
- Liver viral DNA and cccDNA levels may not fully reflect serum viral load responses or predict long-term outcomes.
- Oscillations in viremia suggest complex interactions between viral evolution and the host immune response during therapy.
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