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整合细胞内和细胞间病毒传播以分析细胞外病毒标志物的乙肝病毒感染多尺度建模

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation for analyzing extracellular viral markers.

作者信息

Kitagawa Kosaku, Kim Kwang Su, Iwamoto Masashi, Hayashi Sanae, Park Hyeongki, Nishiyama Takara, Nakamura Naotoshi, Fujita Yasuhisa, Nakaoka Shinji, Aihara Kazuyuki, Perelson Alan S, Allweiss Lena, Dandri Maura, Watashi Koichi, Tanaka Yasuhito, Iwami Shingo

机构信息

interdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.

Department of Scientific Computing, Pukyong National University; Busan, South Korea.

出版信息

bioRxiv. 2023 Jun 7:2023.06.06.543822. doi: 10.1101/2023.06.06.543822.

Abstract

Chronic infection of 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. The quantifying and understanding dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, it requires a liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because of the ethical aspect. We here aimed to develop a non-invasive method for quantifying cccDNA in the liver using surrogate markers present 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 (PDEs), integrates experimental data from in vitro and in vivo investigations. By applying this model, we successfully predicted the amount and dynamics of intrahepatic cccDNA 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 non-invasive quantification of cccDNA using our proposed methodology 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.

摘要

乙型肝炎病毒(HBV)的慢性感染是由感染的肝细胞细胞核中闭合环状DNA(cccDNA)的持续存在引起的。尽管有可用的抗HBV治疗药物,但消除cccDNA仍然具有挑战性。量化和了解cccDNA的动态对于制定有效的治疗策略和开发新药至关重要。然而,测量肝内cccDNA需要进行肝活检,由于伦理方面的原因,这基本上不被接受。我们的目标是开发一种使用外周血中存在的替代标志物来量化肝脏中cccDNA的非侵入性方法。我们构建了一个多尺度数学模型,该模型明确纳入了细胞内和细胞间的HBV感染过程。该模型基于年龄结构偏微分方程(PDE),整合了来自体外和体内研究的实验数据。通过应用该模型,我们成功地使用血清样本中的特定病毒标志物(包括HBV DNA、HBsAg、HBeAg和HBcrAg)预测了肝内cccDNA的数量和动态。我们的研究代表了在推进对慢性HBV感染理解方面的重要一步。使用我们提出的方法对cccDNA进行非侵入性量化有望改善临床分析和治疗策略。通过全面描述HBV感染中所有相关成分的相互作用,我们的多尺度数学模型为进一步研究和开发靶向干预措施提供了一个有价值的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0830/10274663/1e520a9cde25/nihpp-2023.06.06.543822v1-f0001.jpg

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