Serum Arginine Level for Predicting Early Allograft Dysfunction in Liver Transplantation Recipients by Targeted...

Early allograft dysfunction (EAD) is a frequent phenomenon, leading to increased graft loss and higher mortality after liver transplantation (LT). Despite significant efforts for early diagnosis of EAD, there is no existing approach that can predict EAD on the first post-operative day. The aim is to define a metabolite-based biomarker on the first day after LT complicated with EAD. Ten patients diagnosed with EAD and 26 non-EAD are recruited for the study. A HPLC-MS/MS is used to determine 14 amino acids and 15 bile acids serum concentration. Comparative analyses are conducted between EAD and non-EAD groups. Arginine is identified as the most significant metabolite distinguishing the EAD and non-EAD groups, and therefore, is identified as a potential biomarker of EAD. The optimal cut-off value for arginine is 52.09 µmol L^-1, with an AUROC of 0.804 (95% confidence interval: 0.638-0.917, p < 0.001), yielding a sensitivity of 100%, specificity of 53.8%, and Youden index of 0.54, NPVof 100%, and PPV of 45.45%. In summary, the study indicated that targeted metabolomics analysis would be a promising strategy for discovering novel biomarkers to predict EAD. The identified arginine may be helpful in developing an objective diagnostic method for EAD.