Fei Han1, Shaogui Wan2,3, Qipeng Sun1, Nan Chen3, Heng Li1, Lingling Zheng4, Nana Zhang5, Zhengyu Huang1, Liangqing Hong1, Qiquan Sun1. 1. Division of Kidney Transplantation, Department of Surgery, Organ Transplantation Research Institution, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. 2. Center for Molecular Pathology, The First Affiliated Hospital, Gannan Medical University, Ganzhou, China. 3. Laboratory of Cancer Biomarkers and Liquid Biopsy, Henan University, Kaifeng, China. 4. Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China. 5. Department of Pathology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Abstract
BACKGROUND: The lack of accurate biomarkers makes it difficult to determine whether organs are suitable for transplantation. Mitochondrial DNA (mtDNA) correlates with tissue damage and kidney disease, making it a potential biomarker in organ evaluation. METHODS: Donors who had experienced cardiac death and successfully donated their kidneys between January 2015 and May 2017 were included this study. We detected the level of mtDNA in the plasma of the donor using quantitative real-time polymerase chain reaction and then statistically analyzed the relationship between the level of mtDNA and the delayed graft function (DGF) of the recipient. RESULTS: The incidence of DGF or slowed graft function (SGF) increased by 4 times (68% versus 16%, P < 0.001) when the donor mtDNA (dmtDNA) level was >0.114. When dmtDNA levels were >0.243, DGF and primary nonfunction were approximately 100% and 44%, respectively. Moreover, dmtDNA was an independent risk factor for slowed graft function and DGF. A prediction model for DGF based on dmtDNA achieved an area under the receiver operating characteristic curve for a prediction score as high as 0.930 (95% confidence interval 0.856-1.000), and the validation cohort results showed that the sensitivity and specificity of the model were 100% and 78%, respectively. dmtDNA levels were correlated with 6-month allograft function (R=0.332, P < 0.001) and 1-year graft survival (79% versus 99%, P < 0.001). CONCLUSIONS: We conclusively demonstrated that plasma dmtDNA was an independent risk factor for DGF, which is valuable in organ evaluation. dmtDNA is a possible first predictive marker for primary nonfunction and worth further evaluation.
BACKGROUND: The lack of accurate biomarkers makes it difficult to determine whether organs are suitable for transplantation. Mitochondrial DNA (mtDNA) correlates with tissue damage and kidney disease, making it a potential biomarker in organ evaluation. METHODS: Donors who had experienced cardiac death and successfully donated their kidneys between January 2015 and May 2017 were included this study. We detected the level of mtDNA in the plasma of the donor using quantitative real-time polymerase chain reaction and then statistically analyzed the relationship between the level of mtDNA and the delayed graft function (DGF) of the recipient. RESULTS: The incidence of DGF or slowed graft function (SGF) increased by 4 times (68% versus 16%, P < 0.001) when the donor mtDNA (dmtDNA) level was >0.114. When dmtDNA levels were >0.243, DGF and primary nonfunction were approximately 100% and 44%, respectively. Moreover, dmtDNA was an independent risk factor for slowed graft function and DGF. A prediction model for DGF based on dmtDNA achieved an area under the receiver operating characteristic curve for a prediction score as high as 0.930 (95% confidence interval 0.856-1.000), and the validation cohort results showed that the sensitivity and specificity of the model were 100% and 78%, respectively. dmtDNA levels were correlated with 6-month allograft function (R=0.332, P < 0.001) and 1-year graft survival (79% versus 99%, P < 0.001). CONCLUSIONS: We conclusively demonstrated that plasma dmtDNA was an independent risk factor for DGF, which is valuable in organ evaluation. dmtDNA is a possible first predictive marker for primary nonfunction and worth further evaluation.
Authors: Sarah L Longnus; Nina Rutishauser; Mark N Gillespie; Tobias Reichlin; Thierry P Carrel; Maria N Sanz Journal: Transplant Direct Date: 2021-12-16
Authors: Yajuan Li; Bo Wang; Le Wang; Kewei Shi; Wangcheng Zhao; Sai Gao; Jiayu Chen; Chenguang Ding; Junkai Du; Wei Gao Journal: Front Med (Lausanne) Date: 2022-08-12