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

被引:17
|
作者
Chekmeneva, Elena [1 ,5 ]
Correia, Goncalo dos Santos [1 ,5 ]
Gomez-Romero, Maria [1 ,5 ]
Stamler, Jeremiah [2 ]
Chan, Queenie [3 ,4 ]
Elliott, Paul [3 ,4 ]
Nicholson, Jeremy K. [1 ,5 ]
Holmes, Elaine [1 ,4 ]
机构
[1] Imperial Coll London, Dept Surg & Canc, Div Integrat Syst & Digest Med, Sir Alexander Fleming Bldg, London SW7 2AZ, England
[2] Northwestern Univ, Dept Prevent Med, Feinberg Sch Med, Chicago, IL 60611 USA
[3] Imperial Coll London, Sch Publ Hlth, Dept Epidemiol & Biostat, St Marys Campus, London W2 1PG, England
[4] Imperial Coll London, Sch Publ Hlth, MRC PHE Ctr Environm & Hlth, St Marys Campus, London W2 1PG, England
[5] Imperial Coll London, Dept Surg & Canc, NIHR BRC Clin Phenotyping Ctr, Sir Alexander Fleming Bldg, London SW7 2AZ, England
基金
英国医学研究理事会; 美国国家卫生研究院;
关键词
ultra performance liquid chromatography; direct infusion mass spectrometry; metabolic profiling; exploratory analysis; quantitative analysis; high-throughput analysis; LARGE-SCALE; NMR-SPECTROSCOPY; BIOLOGICAL SAMPLES; MS; IDENTIFICATION; PLASMA; SERUM; ANNOTATION; PHENOTYPE; DILUTION;
D O I
10.1021/acs.jproteome.8b00413
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:3492 / 3502
页数:11
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