Urinary metabolite signatures to detect and differentiate graft injury in kidney transplant patients.

Current biomarkers are either lagging indicators of injury or have been developed to maximize negative predictive value only for active rejection. In this study, we aimed to demonstrate the utility of urinary metabolites to detect and differentiate types of graft injury. Retrospective urine samples from a training cohort of 102 patients were used to develop a metabolite signature to detect and differentiate a stable graft from graft injury including borderline rejection, active rejection due to under-immunosuppression, and polyomavirus-associated nephropathy (PVAN) due to over-immunosuppression (0.867 area under the curve (AUC), 0.843 accuracy, 0.843 sensitivity, and 0.843 specificity). The signature was validated in an independent retrospective validation cohort of 43 patients (0.878 AUC, 0.864 accuracy, 0.957 sensitivity, and 0.762 specificity). All training and validation samples had matched surveillance and/or indication biopsies. Further, we were also able to nearly perfectly differentiate borderline or active rejection from PVAN. These results could be used to reduce the need for surveillance biopsies and to personalize immunosuppressive therapy to prevent graft injury.