Modeling BK Virus Infection in Renal Transplant Recipients

被引:0
|
作者
Myers, Nicholas [1 ]
Droz, Dana [1 ]
Rogers, Bruce W. [2 ,3 ]
Tran, Hien [1 ]
Flores, Kevin B. [1 ]
Chan, Cliburn [3 ,4 ]
Knechtle, Stuart J. [2 ]
Jackson, Annette M. [2 ]
Luo, Xunrong [5 ]
Chambers, Eileen T. [2 ,6 ]
Mccarthy, Janice M. [3 ,4 ]
机构
[1] North Carolina State Univ, Ctr Res Sci Computat, Dept Math, Raleigh, NC 27695 USA
[2] Duke Univ, Dept Surg, Durham, NC 27710 USA
[3] Duke Univ, Duke Ctr Human Syst Immunol, Durham, NC 27701 USA
[4] Duke Univ, Dept Biostat & Bioinformat, Durham, NC 27710 USA
[5] Duke Univ, Dept Med, Durham, NC 27710 USA
[6] Duke Univ, Dept Pediat, Durham, NC 27710 USA
来源
VIRUSES-BASEL | 2025年 / 17卷 / 01期
关键词
kidney; renal; transplant; modeling; sensitivity; BKPyV; model calibration; immunosuppression; DYNAMICS IN-VIVO; CLEARANCE; FAILURE;
D O I
10.3390/v17010050
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Kidney transplant recipients require a lifelong protocol of immunosuppressive therapy to prevent graft rejection. However, these same medications leave them susceptible to opportunistic infections. One pathogen of particular concern is human polyomavirus 1, also known as BK virus (BKPyV). This virus attacks kidney tubule epithelial cells and is a direct threat to the health of the graft. Current standard of care in BK virus-infected transplant recipients is reduction in immunosuppressant therapy, to allow the patient's immune system to control the virus. This requires a delicate balance; immune suppression must be strong enough to prevent rejection, yet weak enough to allow viral clearance. We seek to model viral and immune dynamics with the ultimate goal of applying optimal control methods to this problem. In this paper, we begin with a previously published model and make simplifying assumptions that reduce the number of parameters from 20 to 14. We calibrate our model using newly available patient data and a detailed sensitivity analysis. Numerical results for multiple patients are given to show that the newer model reflects observed dynamics well.
引用
收藏
页数:20
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