TY - JOUR
T1 - 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
AU - Chekmeneva, Elena
AU - Dos Santos Correia, Gonçalo
AU - Gómez-Romero, María
AU - Stamler, Jeremiah
AU - Chan, Queenie
AU - Elliott, Paul
AU - Nicholson, Jeremy K.
AU - Holmes, Elaine
N1 - Funding Information:
E.C., G.d.S.C., M.G.-R., and J.K.N. are supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research, or the Department of Health. J.K.N. is director of the MRC-NIHR National Phenome Centre (MC-PC-12025). The INTERMAP Study is supported by grants R01-HL50490, R01-HL84228, and R01-HL135486 from the National Heart, Lung, and Blood Institute, National Institutes of Health (Bethesda, MD) and by national agencies in China, Japan, and the U.K. Q.C. and E.H. are investigators of the MRC-PHE Centre for Environment and Health. P.E. is Director of the MRC-PHE Centre for Environment and Health and acknowledges support from the Medical Research Council and Public Health England (MR/L01341X/1). P.E. acknowledges support from the NIHR Biomedical Research Centre at Imperial College Healthcare NHS Trust and Imperial College London and the NIHR Health Protection Research Unit in Health Impact of Environmental Hazards (HPRU-2012-10141).
Publisher Copyright:
© Copyright 2018 American Chemical Society.
PY - 2018/10/5
Y1 - 2018/10/5
N2 - 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 with an ultra-performance liquid chromatography (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 optimized to allow the 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 5 days compared with 9 h 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 of 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. A further twenty metabolites showed acceptable correlation between the two methods with only five metabolites showing weak correlation (Pearson's r < 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS.
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 with an ultra-performance liquid chromatography (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 optimized to allow the 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 5 days compared with 9 h 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 of 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. A further twenty metabolites showed acceptable correlation between the two methods with only five metabolites showing weak correlation (Pearson's r < 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS.
KW - direct infusion mass spectrometry
KW - exploratory analysis
KW - high-throughput analysis
KW - metabolic profiling
KW - quantitative analysis
KW - ultra-performance liquid chromatography
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U2 - 10.1021/acs.jproteome.8b00413
DO - 10.1021/acs.jproteome.8b00413
M3 - Article
C2 - 30183320
AN - SCOPUS:85053903502
SN - 1535-3893
VL - 17
SP - 3492
EP - 3502
JO - Journal of Proteome Research
JF - Journal of Proteome Research
IS - 10
ER -