Phan Tin, Conway Jessica M, Pagane Nicole, Kreig Jasmine, Sambaturu Narmada, Iyaniwura Sarafa, Li Jonathan Z, Ribeiro Ruy M, Ke Ruian, Perelson Alan S
Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA.
Department of Mathematics, Pennsylvania State University, College Township, PA, USA.
bioRxiv. 2024 May 5:2024.05.03.592318. doi: 10.1101/2024.05.03.592318.
Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.
大多数感染HIV-1的人在抗逆转录病毒治疗中断后会经历病毒快速反弹;然而,一小部分人会在较长时间内保持病毒缓解状态。了解治疗中断后决定病毒反弹可能性的因素,有助于制定最佳治疗方案和治疗干预措施,从而有可能实现对HIV-1的功能性治愈。我们基于康威和佩雷尔森提出的理论框架,构建病毒-免疫相互作用的动态模型,以研究影响病毒反弹动态的因素。我们使用24名个体在抗逆转录病毒治疗中断后的病毒载量数据对这些模型进行了评估。表现最佳的模型准确地捕捉了病毒动态的异质性,并突出了效应细胞扩增率的重要性。我们的结果表明,在我们的模型中,治疗后病毒控制者和非控制者可以根据效应细胞扩增率来区分。此外,这些结果证明了使用纳入效应细胞反应的动态模型来理解抗逆转录病毒治疗中断后早期病毒反弹动态的潜力。