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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15984

Title: Identification of the chemical shifts of a series of metabolites appearing in the 1H-NMR spectrum of blood plasma by spiking
Authors: BERVOETS, Liene
LOUIS, Evelyne
THOMEER, Michiel
Issue Date: 2013
Citation: Metabolomics 2013 - 9th Annual International Conference of the Metabolomics Society, Glasgow, UK, July 1 to 4, 2013
Abstract: Background: Instead of using reported chemical shift values of metabolites, which differ seriously from study to study due to differences in e.g. biofluid, temperature and pH, the chemical shifts of metabolites could be determined more accurately by spiking the biofluid itself. Objective: To compare the discriminative power of spectral regions of plasma metabolites derived from literature with those obtained by spiking between lung cancer patients and controls. Methods: Fasting plasma samples, collected from a 44-year-old healthy female, were spiked. One plasma sample was used as reference. The remaining plasma samples were spiked with 37 known metabolites (i.e. components of the glycolysis and Krebs cycle, and all amino acids) at a known concentration (1 mg compound/100 µl plasma). Subsequently, 10 µl spiked plasma was added to 200 µl plasma and 600 µl D2O and prepared for analysis with 1H-NMR spectroscopy. The 1H-NMR spectra were recorded on a 400 MHz Varian Inova spectrometer using a CPMG pulse sequence with water suppression. TSP was used to calibrate the ppm scale at 0.015. The chemical shifts and J-coupling patterns of the spiked metabolites were determined, allowing to rationally define integration regions. An OPLS-DA multivariate analysis was carried out on 78 lung cancer patients and 78 controls in order to compare integration regions based on diverse literature chemical shift information and spiking. Results: Sensitivity increased from 81% to 86% and specificity increased from 88% to 95% when using integration regions on plasma spectra defined by spiking. Conclusion: Spiking experiments seem necessary in order to more accurately identify the chemical shifts of plasma metabolites in a 1H-NMR spectrum. Moreover, it could lead to an enhancement of the discriminative power of the cluster analysis and a better understanding and/or explanation of the clinical relevance of study findings.
URI: http://hdl.handle.net/1942/15984
Category: C2
Type: Conference Material
Appears in Collections: Research publications

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