The Role of Metabonomics in Organ Transplantation

Elaine Holmes, Imperial College of London, London, UK

Key Learning Objectives:

1. To understand the basis of metabolic profiling of biofluids and tissues using spectroscopic technology.
2. To understand the potential of the technology in biomarker identification.
3. To follow selected case histories of metabonomic applications in different aspects of organ transplantation.

Organ transplantation has become a widely accepted form of treatment for numerous end-stage liver and kidney diseases. Metabolic profiling strategies using high-resolution spectroscopic platforms, predominantly based on nuclear magnetic resonance spectroscopy or ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) have been used to improve therapeutic intervention following transplantation and to optimise patient management. Spectral profiles of biological samples can be analysed using multivariate statistical approaches to generate models that characterise ‘good’ or ‘bad’ outcomes and that can predict the risk of post transplant dysfunction. Here we show preliminary studies relating to assessment of organ quality prior to transplantation based on biofluid and biopsy metabolite profiles, and also explore the use of the technology in the early detection of biomarkers of graft dysfunction post-transplant.

The identification of biomarkers is a crucial step towards improving current diagnosis of organs before transplant, either by identifying high-risk interventions or by increasing the pool of donors for transplant. The expanding use of "sub-optimal" grafts due to donor organ shortage increases the importance of accurate graft assessment before liver transplantation. In a preliminary study using UPLC-MS, hepatic bile acids were shown to have an important role as biomarkers of liver quality, in particular GUDCA, TUDCA, GLCA and TLCA concentrations correlated with graft dysfunction following transplantation.

Similarly, a panel of NMR-detected urinary and serum metabolites following renal transplantation were shown to be more sensitive to indicating early rejection episodes or toxicity than conventional clinical indices of renal function. Parallel development of spectroscopic profiling technology and mathematical modelling of complex data have resulted in the creation of a powerful tool kit for biomarker detection and for patient stratification across multiple pathologies and has clear application in organ transplantation.