Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers.
PLoS Comput Biol
; 20(3): e1011238, 2024 Mar.
Article
in En
| MEDLINE
| ID: mdl-38466770
ABSTRACT
Chronic infection with hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. Thus, quantifying and understanding the dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, such study requires repeated liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because liver biopsy is potentially morbid and not common during hepatitis B treatment. We here aimed to develop a noninvasive method for quantifying cccDNA in the liver using surrogate markers in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations, integrates experimental data from in vitro and in vivo investigations. By applying this model, we roughly predicted the amount and dynamics of intrahepatic cccDNA within a certain range using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The noninvasive quantification of cccDNA using our proposed method holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Hepatitis B virus
/
Hepatitis B
Limits:
Humans
Language:
En
Journal:
PLoS Comput Biol
Journal subject:
BIOLOGIA
/
INFORMATICA MEDICA
Year:
2024
Document type:
Article
Affiliation country:
Japón