Understanding Immune Dynamics in Liver Transplant Through Mathematical Modeling
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909406040424448 |
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| author | Bruner, Julia Adams, Kyle Grey, Skylar Aghaee, Mahya Duarte, Sergio Zarrinpar, Ali Moore, Helen |
| author_facet | Bruner, Julia Adams, Kyle Grey, Skylar Aghaee, Mahya Duarte, Sergio Zarrinpar, Ali Moore, Helen |
| contents | Liver transplant can be a life-saving procedure for patients with end-stage liver disease. With the introduction of modern immunosuppressive therapies, short-term survival has significantly improved. However, long-term survival has not substantially improved in decades. Consequently, causes of death are now more likely to be due to the toxicities and side-effects of long-term immunosuppression rather than rejection. In order to study the balance of immunosuppression and rejection, we developed the first mechanistic mathematical model of liver transplant and immune system dynamics. We determined key cells and interactions in the model using literature information; we then used sensitivity analysis to determine key pathways driving the health status of the transplanted liver. We found that dynamics related to cytotoxic T cells and IL-2, in addition to the liver itself, are key determinants of liver graft injury. This has significant implications for the use of tests to monitor patients, and therapeutic strategies to prevent or treat liver transplantation rejection. Future work to collect appropriate data and parametrize the model would be valuable in improving our understanding of the dynamics of this system. We also note that our model could be tailored to model transplant of other organs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_17789 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding Immune Dynamics in Liver Transplant Through Mathematical Modeling Bruner, Julia Adams, Kyle Grey, Skylar Aghaee, Mahya Duarte, Sergio Zarrinpar, Ali Moore, Helen Quantitative Methods Liver transplant can be a life-saving procedure for patients with end-stage liver disease. With the introduction of modern immunosuppressive therapies, short-term survival has significantly improved. However, long-term survival has not substantially improved in decades. Consequently, causes of death are now more likely to be due to the toxicities and side-effects of long-term immunosuppression rather than rejection. In order to study the balance of immunosuppression and rejection, we developed the first mechanistic mathematical model of liver transplant and immune system dynamics. We determined key cells and interactions in the model using literature information; we then used sensitivity analysis to determine key pathways driving the health status of the transplanted liver. We found that dynamics related to cytotoxic T cells and IL-2, in addition to the liver itself, are key determinants of liver graft injury. This has significant implications for the use of tests to monitor patients, and therapeutic strategies to prevent or treat liver transplantation rejection. Future work to collect appropriate data and parametrize the model would be valuable in improving our understanding of the dynamics of this system. We also note that our model could be tailored to model transplant of other organs. |
| title | Understanding Immune Dynamics in Liver Transplant Through Mathematical Modeling |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2411.17789 |