Evaluating the long-term effects of combination antiretroviral therapy of HIV infection: a modeling study

被引:1
作者
Cai, Jing [1 ]
Zhang, Jun [2 ,3 ]
Wang, Kai [4 ]
Dai, Zhixiang [1 ]
Hu, Zhiliang [5 ]
Dong, Yueping [2 ,3 ]
Peng, Zhihang [1 ,6 ,7 ]
机构
[1] Nanjing Med Univ, Sch Publ Hlth, 101 Longmian Rd, Nanjing 211166, Jiangsu, Peoples R China
[2] Cent China Normal Univ, Sch Math & Stat, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[3] Cent China Normal Univ, Key Lab Nonlinear Anal & Applicat, Minist Educ, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China
[4] China Japan Friendship Hosp, Dept Pulm & Crit Care Med, 2 East Cherry Garden St, Beijing 100029, Peoples R China
[5] Second Hosp Nanjing, Nanjing Infect Dis Ctr, Tangshan St, Nanjing 211113, Jiangsu, Peoples R China
[6] Chinese Ctr Dis Control & Prevent, Natl Key Lab Intelligent Tracking & Forecasting In, 155 Changbai Rd, Beijing 102206, Peoples R China
[7] Chinese Ctr Dis Control & Prevent, Natl Inst Viral Dis Control & Prevent, 155 Changbai Rd, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
Latent HIV infection; Within-host model; Bistability; Bifurcations and periodic orbits; Data fitting; DYNAMICS IN-VIVO; VIRAL DYNAMICS; BAYESIAN-APPROACH; T-CELLS; VIRUS; PERSISTENCE; RESERVOIR; LOAD; BIFURCATION; ADHERENCE;
D O I
10.1007/s00285-025-02196-y
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<^>+$$\end{document} T cells and the homeostatic proliferation of CD4+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<^>+$$\end{document} 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+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<^>+$$\end{document} 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+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<^>+$$\end{document} T cell counts before and after treatment. Quantitative analysis estimates the effects of long-term cART, revealing an increasing sensitivity of steady-state CD4+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<^>+$$\end{document} 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+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$<^>+$$\end{document} 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.
引用
收藏
页数:32
相关论文
共 55 条
[51]   HIV low viral load persistence under treatment: Insights from a model of cell-to-cell viral transmission [J].
Wang, Xia ;
Rong, Libin .
APPLIED MATHEMATICS LETTERS, 2019, 94 :44-51
[52]   Influence of raltegravir intensification on viral load and 2-LTR dynamics in HIV patients on suppressive antiretroviral therapy [J].
Wang, Xia ;
Mink, Gregory ;
Lin, Daniel ;
Song, Xinyu ;
Rong, Libin .
JOURNAL OF THEORETICAL BIOLOGY, 2017, 416 :16-27
[53]   Modeling long-term HIV dynamics and antiretroviral response - Effects of drug potency, pharmacokinetics, adherence, and drug resistance [J].
Wu, HL ;
Huang, YX ;
Acosta, EP ;
Rosenkranz, SL ;
Kuritzkes, DR ;
Eron, JJ ;
Perelson, AS ;
Gerber, JG .
JAIDS-JOURNAL OF ACQUIRED IMMUNE DEFICIENCY SYNDROMES, 2005, 39 (03) :272-283
[54]   Threshold dynamics for an HIV model in periodic environments [J].
Yang, Youping ;
Xiao, Yanni .
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, 2010, 361 (01) :59-68
[55]   Modelling the preventive treatment under media impact on tuberculosis: A comparison in four regions of China [J].
Zhang, Jun ;
Takeuchi, Yasuhiro ;
Dong, Yueping ;
Peng, Zhihang .
INFECTIOUS DISEASE MODELLING, 2024, 9 (02) :483-500