LAUSR

INTRODUCTION Acute renal rejection usually fails to be diagnosed before the increase in the serum creatinine levels, and the resultant damage to the renal tissues occur in varying degrees. We hypothesized that the combined detection of human leucocyte antigen-G (HLA-G) 14-bp insertion/deletion genotypes and kidney injury molecule-1 (KIM-1) and osteopontin (OPN) levels in serum might facilitate the prediction of acute renal allograft rejections in kidney transplant recipients. METHODS HLA-G 14-bp insertion/deletion genotypes and the serum KIM-1 and OPN levels of 77 kidney transplant recipients were determined and compared before operation and on days 1, 4, and 7 after the operation (32 in acute rejection [AR] group and 45 in stable allograft function [STA] group). These 3 indicators were combined to establish a model for the early prediction of AR. RESULTS The KIM-1 levels in the serum of patients were significantly higher in the AR group than in the STA group. The area under the receiver operator characteristics (ROC) curve (AUC) of KIM-1 for the prediction of rejection was maximized on the1st day after operation, with a sensitivity of 84.4% and a specificity of 86.7%. The OPN levels in the serum of patients were significantly higher in the AR group than in the STA group only before operation and on the 7th day after operation. The AUC of OPN for the prediction of rejection was maximized on 7th day after operation, with a sensitivity of 68.8% and a specificity of 88.9%. The HLA-G + 14-bp allele frequency was also significantly higher in the AR group than in the STA group. The results of these three indicators were converted into a qualitative method. If any two of the three indicators show as positive, it was diagnosed as acute rejection, and it has the highest ability to predict acute rejection with a sensitivity and specificity of 84.38% and 91.11%, respectively. CONCLUSIONS The HLA-G 14-bp insertion/deletion genotype and KIM-1 and OPN levels in the patients' serum were significantly different between the AR and STA groups. The power of predicting acute renal allograft rejection could be improved by combined these three biomarkers.