Elucidating time-dependent changes in the urinary metabolome of renal transplant patients by a combined 1H NMR and GC-MS approach?

Molecular BioSystems Pub Date: 2015-07-02 DOI: 10.1039/C5MB00108K

Abstract

Urine metabolomic profiling can identify biochemical alterations resulting from various injuries affecting the graft outcome after renal transplantation. Here, we aimed to describe in depth the metabolite content of urines of renal transplant patients and to link it with the major injury factors acting at critical stages following transplantation. Morning urine samples were prospectively collected from 38 kidney transplant patients at 7 days (D7), 3 months (M3) and 12 months (M12) after transplantation. Twenty-five patients were treated with tacrolimus (Tac) and thirteen patients with cyclosporine (CsA). 1H-NMR (proton nuclear magnetic resonance) and gas chromatography-mass spectrometry (GC-MS) were used to examine the overall metabolomic signature of each sample. Multivariate analysis was performed to study the changes in the metabolic profile over time and their dependency on the type of calcineurin inhibitor (CNI) administered to patients. Biological pathways affected by transplantation were identified using a metabolomics pathway analysis (MetPA) web-tool. The metabolic profile of urine samples clearly varied with time. Markers of medullary injury, tubule cell oxidative metabolism and impaired tubular reabsorption or secretion were present at D7. Differences in metabolic profiles became less marked as time passed on, urine content being quite similar at M3 and M12. The metabolite profile tended to differ between patients receiving Tac and those receiving CsA but no clear discriminating profiles can be found. The combination of 1H-NMR and GC-MS for the analysis of urine metabolomic profiles is a very useful method to study patho-physiological alterations in kidney transplant patients over time.

Graphical abstract: Elucidating time-dependent changes in the urinary metabolome of renal transplant patients by a combined 1H NMR and GC-MS approach
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