Cai Jing, Zhang Jun, Wang Kai, Dai Zhixiang, Hu Zhiliang, Dong Yueping, Peng Zhihang
School of Public Health, Nanjing Medical University, 101 Longmian Road, Nanjing, 211166, Jiangsu, China.
School of Mathematics and Statistics, and Key Laboratory of Nonlinear Analysis and Applications (Ministry of Education), Central China Normal University, 152 Luoyu Road, Wuhan, 430079, Hubei, China.
J Math Biol. 2025 Mar 1;90(4):36. doi: 10.1007/s00285-025-02196-y.
Current HIV/AIDS treatments effectively reduce viral loads to undetectable levels as measured by conventional clinical assays, but immune recovery remains highly variable among patients. To assess the long-term treatment efficacy, we propose a mathematical model that incorporates latently infected CD4 T cells and the homeostatic proliferation of CD4 T cells. We investigate the dynamics of this model both theoretically and numerically, demonstrating that homeostatic proliferation can induce bistability, which implies that steady-state CD4 T cell count is sensitively affected by initial conditions. The model exhibits rich dynamics, including saddle node bifurcations, Hopf bifurcations, and saddle node bifurcations related to periodic orbits. The interplay between homeostatic proliferation and latent HIV infection significantly influences the model's dynamic behavior. Additionally, we integrate combination antiretroviral therapy (cART) into the model and fit the revised model to clinical data on long-term CD4 T cell counts before and after treatment. Quantitative analysis estimates the effects of long-term cART, revealing an increasing sensitivity of steady-state CD4 T cell count to drug efficacy. Correlation analysis indicates that the heightened activation of latently infected cells helps enhance treatment efficacy. These findings underscore the critical roles of CD4 T cell homeostatic proliferation and latently infected cell production in HIV persistence despite treatment, providing valuable insights for understanding disease progression and developing more effective therapies, potentially towards eradication.
目前的艾滋病毒/艾滋病治疗方法可有效将病毒载量降低到传统临床检测方法无法检测到的水平,但患者之间的免疫恢复情况仍存在很大差异。为了评估长期治疗效果,我们提出了一个数学模型,该模型纳入了潜伏感染的CD4 T细胞和CD4 T细胞的稳态增殖。我们从理论和数值两方面研究了该模型的动力学,证明稳态增殖可诱导双稳态,这意味着稳态CD4 T细胞计数受初始条件的影响很敏感。该模型表现出丰富的动力学,包括鞍结分岔、霍普夫分岔以及与周期轨道相关的鞍结分岔。稳态增殖与潜伏性艾滋病毒感染之间的相互作用显著影响模型的动态行为。此外,我们将联合抗逆转录病毒疗法(cART)纳入模型,并将修订后的模型与治疗前后长期CD4 T细胞计数的临床数据进行拟合。定量分析估计了长期cART的效果,揭示了稳态CD4 T细胞计数对药物疗效的敏感性增加。相关性分析表明,潜伏感染细胞的激活增强有助于提高治疗效果。这些发现强调了CD4 T细胞稳态增殖和潜伏感染细胞产生在艾滋病毒治疗后持续存在中的关键作用,为理解疾病进展和开发更有效的治疗方法(可能朝着根除方向发展)提供了有价值的见解。