A Latent Space Model for HLA Compatibility Networks in Kidney Transplantation.
A Latent Space Model for HLA Compatibility Networks in Kidney Transplantation.
复制标题
肾移植中 HLA 相容性网络的潜在空间模型。
DOI：
10.1109/bibm55620.2022.9995514
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Xu,KevinS
中科院分区：
文献类型：
--
作者：
Huang,Zhipeng;Xu,KevinS
肾移植是终末期肾病患者的首选治疗方法。随着时间的推移，成功的肾移植仍然会失败，这就是所谓的移植失败；然而，不同受者之间移植失败的时间或移植肾存活时间可能会有很大差异。影响移植物存活时间的一个重要生物学因素是供者和受者的人类白细胞抗原(HLA)之间的相容性。我们建议使用网络来模拟人类白细胞抗原的兼容性，其中节点表示供体和受体的不同的HLA，边权重表示HLA的兼容性，可以是正的或负的。网络是间接观察的，因为边缘权重是根据移植结果估计的，而不是直接观察到的。针对这类间接观测的加权和符号网络，我们提出了一个潜在空间模型。我们证明，我们的潜在空间模型不仅可以更准确地估计人类白细胞抗原的相容程度，而且还可以结合到存活分析模型中，以提高预测移植物存活时间的下游任务的准确性。
Kidney transplantation is the preferred treatment for people suffering from end-stage renal disease. Successful kidney transplants still fail over time, known as graft failure; however, the time to graft failure, or graft survival time, can vary significantly between different recipients. A significant biological factor affecting graft survival times is the compatibility between the human leukocyte antigens (HLAs) of the donor and recipient. We propose to model HLA compatibility using a network, where the nodes denote different HLAs of the donor and recipient, and edge weights denote compatibilities of the HLAs, which can be positive or negative. The network is indirectly observed, as the edge weights are estimated from transplant outcomes rather than directly observed. We propose a latent space model for such indirectly-observed weighted and signed networks. We demonstrate that our latent space model can not only result in more accurate estimates of HLA compatibilities, but can also be incorporated into survival analysis models to improve accuracy for the downstream task of predicting graft survival times.