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

Mol Biosyst

Cellules dendritiques, immuno-intervention et greffes, EA4245, Université François Rabelais, Faculté de médecine, bâtiment Vialle, 10 Boulevard Tonnellé, 37032 Tours Cedex 1, France.

Published: September 2015

AI Article Synopsis

  • - Urine metabolomic profiling helps identify biochemical changes in kidney transplant patients that can influence graft success, particularly after injury events.
  • - The study involved collecting morning urine samples from 38 transplant patients at several time points (7 days, 3 months, and 12 months post-transplant) and analyzing them using (1)H-NMR and gas chromatography-mass spectrometry to track changes in metabolic profiles.
  • - Findings indicated that metabolite profiles varied significantly shortly after surgery, showing markers for kidney injury, but became more similar over time; while some differences emerged between patients treated with different medications (tacrolimus vs. cyclosporine), no definitive distinct profiles were identified.

Article 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). (1)H-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 (1)H-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.

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Source
http://dx.doi.org/10.1039/c5mb00108kDOI Listing

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