Urine Differences In Metabolites Of The Role In The Diagnosis Of Acute Rejection Of Renal Allografts

Objective:Acute allograft rejection is one of the most important events after kidney transplantation, which may reduce recipients and renal grafts survival. However, so far, we still have no effective techniques that can be used as the early diagnosis methods.Methods:We investigated urinary metabolite profiling as a non-invasive method to detect acute renal allograft rejection. Gas chromatograph mass spectrometry (GC-MS) in conjunction with modern multivariate statistical techniques was applied to analyze 30 urine samples from 15 recipients with different grades of biopsy improved acute rejection (Banff 97'I toⅢ) and 15 recipients with stable kidney function. We selected and identified urine differential metabolites by fingerprint identification method on the whole spectrum and NIST (National Institute of Standards and Technology) database. Then we verified the urine differential metabolites by the methods of partial least squares and leave-one-out. By classifying these metabolites, inquiring human metabolome database, and using molecular bioinformatics analysis, we illuminated comprehensively their metabolic characteristics and found their metabolic pathway network related to acute rejection post kidney transplantation.Results:This study showed significant alterations in metabolite expression patterns as a result of acute allograft rejection after kidney transplantation. We analyzed about 200 endogenous metabolites, and 14 of them were statistically different between the two groups with or without acute rejection after kidney transplantation. Among these 14 metabolites, the levels of 11 metabolites are higher in rejection group than those in stable group, which are threitol, inositol, glucose, xylono-1,5-lactone, xylitol, xylopyranoside,2,3-dihydroxybutanoic acid, glucitol, ribonic acid, octadecanoic acid and phosphate. The levels of fructose, glycolic acid and 3-hydroxyisovaleric acid were low in rejection group compared to stable group. We analyzed these 14 metabolites with the methods of partial least squares method and leave-one-out.13 of 15 acute rejection patients and 10 of 15 stable kidney function patients were diagnosed correctly, which sensitivity is 86.7%(sensitivity on theⅠandⅡacute rejection is 100%) and specificity is 66.7%. The same methods were applied to analysis the 3 metabolites-inositol, phosphate, and octadecanoic acid, which occur in phosphatidyl-inositol pathway. And 12 patients and 12 patients in each group were diagnosed correctly, which sensitivity and specificity are both 80%(sensitivity on the I and II acute rejection is 83.3%). We also analyzed the 4 metabolites (P＜0.001) relying on the same methods. And 12 of 15 acute rejection patients and 13 of 15 stable kidney function patients were identified correctly, which sensitivity is 80%(sensitivity on the I and II acute rejection is 83.3%) and specificity is 86.7%.Conclusion:In this study, it was indicated that kidney transplant recipients with acute rejection could be distinguished from those with stable kidney function by differential urine metabolites using GC-MS technology. And it presents high sensitivity and specificity, especially in the prediction of I and II acute rejection recipients. This method might offer a promising non-invasive diagnostic means for acute rejection after renal transplantation.