Imperial College London
Alternate

Emeritus ProfessorJeremyNicholson

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Emeritus Professor of Biological Chemistry
 
 
 
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Contact

 

+44 (0)20 7594 3195j.nicholson Website

 
 
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Assistant

 

Ms Wendy Torto +44 (0)20 7594 3225

 
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Location

 

Office no. 665Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Chekmeneva:2018:10.1021/acs.jproteome.8b00413,
author = {Chekmeneva, E and Dos, Santos Correia G and Gomez, Romero M and Stamler, J and Chan, Q and Elliott, P and Nicholson, J and Holmes, E},
doi = {10.1021/acs.jproteome.8b00413},
journal = {Journal of Proteome Research},
pages = {3492--3502},
title = {Ultra performance liquid chromatography-high resolution mass spectrometry and direct infusion-high resolution mass spectrometry for combined exploratory and targeted metabolic profiling of human urine},
url = {http://dx.doi.org/10.1021/acs.jproteome.8b00413},
volume = {17},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The application of metabolic phenotyping to epidemiological studies involving thousands of biofluid samples presents a challenge for the selection of analytical platforms that meet the requirements of high-throughput precision analysis and cost-effectiveness. Here, direct infusion nanoelectrospray (DI-nESI)- was compared to an ultra-performance (UPLC)-high resolution mass spectrometry (HRMS) method for metabolic profiling of an exemplary set of 132 human urine samples from a large epidemiological cohort. Both methods were developed and optimised to allow simultaneous collection of high resolution urinary metabolic profiles and quantitative data for a selected panel of 35 metabolites. The total run time for measuring the sample set in both polarities by UPLC-HRMS was of 5 days compared to 9 hours by DI-nESI-HRMS. To compare the classification ability of the two MS methods we performed exploratory analysis of the full-scan HRMS profiles to detect sex-related differences in biochemical composition. Although metabolite identification is less specific in DI-nESI-HRMS, the significant features responsible for discrimination between sexes were mostly the same in both MS-based platforms. Using the quantitative data we showed that 10 metabolites have strong correlation (Pearson’s r > 0.9 and Passing-Bablok regression slope 0.8-1.3) and good agreement assessed by Bland-Altman plots between UPLC-HRMS and DI-nESI-HRMS and thus, can be measured using a cheaper and less sample- and time-consuming method. Only five metabolites showed weak correlation (Pearson’s r< 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS, and the rest of metabolites showed acceptable correlation between the two methods.
AU  - Chekmeneva,E
AU  - Dos,Santos Correia G
AU  - Gomez,Romero M
AU  - Stamler,J
AU  - Chan,Q
AU  - Elliott,P
AU  - Nicholson,J
AU  - Holmes,E
DO  - 10.1021/acs.jproteome.8b00413
EP  - 3502
PY  - 2018///
SN  - 1535-3893
SP  - 3492
TI  - Ultra performance liquid chromatography-high resolution mass spectrometry and direct infusion-high resolution mass spectrometry for combined exploratory and targeted metabolic profiling of human urine
T2  - Journal of Proteome Research
UR  - http://dx.doi.org/10.1021/acs.jproteome.8b00413
UR  - http://hdl.handle.net/10044/1/64378
VL  - 17
ER  -
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