Global Dynamics and Implications of an HBV Model with Proliferating Infected Hepatocytes

Author:

Hews Sarah,Eikenberry Steffen,Nagy John D.ORCID,Phan Tin,Kuang YangORCID

Abstract

Chronic hepatitis B (HBV) infection is a major cause of human suffering, and a number of mathematical models have examined the within-host dynamics of the disease. Most previous models assumed that infected hepatocytes do not proliferate; however, the effect of HBV infection on hepatocyte proliferation is controversial, with conflicting data showing both induction and inhibition of proliferation. With a family of ordinary differential equation (ODE) models, we explored the dynamical impact of proliferation among HBV-infected hepatocytes. Here, we show that infected hepatocyte proliferation in this class of models generates a threshold that divides the dynamics into two categories. Sufficiently compromised proliferation in infected cells produces complex dynamics characterized by oscillating viral loads, whereas higher proliferation generates straightforward dynamics that always results in chronic infection, sometimes with liver failure. A global stability result of the liver failure state was included as it is unique to this class of models. Finally, the model analysis motivated a testable biological hypothesis: Healthy hepatocytes are present in chronic HBV infection if and only if the proliferation of infected hepatocytes is severely impaired.

Funder

NIH

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Phenomenology of an In-host Model of Hepatitis C;Qualitative Theory of Dynamical Systems;2023-04-19

2. Numerical study of chronic hepatitis B infection using Marchuk–Petrov model;Journal of Bioinformatics and Computational Biology;2023-03-09

3. Mathematical Modeling of HBV Infection with DNA-Containing Capsids and Therapy;Nonlinear Systems and Complexity;2022

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