Application of metabolomics to the evaluation of renal function in kidney transplantation

Kidney transplantation (KTx) represents nowadays the best treatment for patients with end-stage kidney disease. Allograft dysfunction post-transplantation currently represents the leading cause of altered kidney function and rejection. For this reason, the long-term success of a transplantation depends on the graft quality at transplantation time and of a continuous follow-up of kidney transplant recipient. In this work we propose the application of a metabolomics approach to explore several challenges linked to KTx: (1) the accurate assessment of graft quality before-transplantation; (2) a consistent and precise monitoring of patients during post-transplantation period. To achieve these goals two different cohorts were analyzed in parallel. The first cohort consists of urine samples collected at 3-and 12-months post-transplantation with patient’s stratification based on mGFR value. Combination of NMR and MS-based metabolomics approaches were used to predict and monitor kidney function decline. For the second cohort, samples of perfusate collected during transplantation
were used for the analysis. NMR metabolomics was employed in this cohort with the aims to define a panel of biomarkers predicting the occurrence of kidney dysfunction in post-graft period. The primary goals of this thesis are to create tools helping clinicians in patient management and follow-up within their clinical practice.