BACKGROUND: NMR spectroscopy-based metabolomics is a system approach used to investigate the metabolic profile of biological fluids with multivariate data analysis tools. The aim of this study was to examine the kidney graft recovery process noninvasively through the examinations of urine samples using (1)H NMR spectroscopy combined with chemometric tools. METHODS: Urine samples were treated as the source of metabolites reflecting the pathological and clinical conditions of patients with transplanted kidneys. We observed 15 subjects (9 males and 6 females) during the graft recovery process and initial days thereafter. The patients provided at least 9 samples each, applying advanced statistical methods of analysis: Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis PLS-DA). RESULTS: The PCA model (for all subjects exp. var. PC1 13.96% and PC2 9.88%) allowed us to clearly designate 3 stages of recovery: initially the kidney is not working; in the second stage, it regains functions, and the third stage includes follow-up during hospitalization. PCA analysis of a single patient follows graft recovery based on biochemical (metabolites) information, assigning the appropriate recuperation stage. CONCLUSIONS: NMR spectroscopy together with chemometric analysis allow monitoring of kidney graft recovery to identify patients who are not progressing within the normal range.
BACKGROUND: NMR spectroscopy-based metabolomics is a system approach used to investigate the metabolic profile of biological fluids with multivariate data analysis tools. The aim of this study was to examine the kidney graft recovery process noninvasively through the examinations of urine samples using (1)H NMR spectroscopy combined with chemometric tools. METHODS: Urine samples were treated as the source of metabolites reflecting the pathological and clinical conditions of patients with transplanted kidneys. We observed 15 subjects (9 males and 6 females) during the graft recovery process and initial days thereafter. The patients provided at least 9 samples each, applying advanced statistical methods of analysis: Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis PLS-DA). RESULTS: The PCA model (for all subjects exp. var. PC1 13.96% and PC2 9.88%) allowed us to clearly designate 3 stages of recovery: initially the kidney is not working; in the second stage, it regains functions, and the third stage includes follow-up during hospitalization. PCA analysis of a single patient follows graft recovery based on biochemical (metabolites) information, assigning the appropriate recuperation stage. CONCLUSIONS: NMR spectroscopy together with chemometric analysis allow monitoring of kidney graft recovery to identify patients who are not progressing within the normal range.
Authors: Eva Baranovicova; Matej Vnucak; Karol Granak; Jan Lehotsky; Nina Kadasova; Juraj Miklusica; Ivana Dedinska Journal: Metabolites Date: 2022-07-18
Authors: Ivana Stanimirova; Mirosław Banasik; Adam Ząbek; Tomasz Dawiskiba; Katarzyna Kościelska-Kasprzak; Wojciech Wojtowicz; Magdalena Krajewska; Dariusz Janczak; Piotr Młynarz Journal: Sci Rep Date: 2020-10-14 Impact factor: 4.379
Authors: Thomas Verissimo; Anna Faivre; Sebastian Sgardello; Maarten Naesens; Sophie de Seigneux; Gilles Criton; David Legouis Journal: Metabolites Date: 2022-01-10