TY - JOUR
T1 - Comparison of kit-based metabolomics with other methodologies in a large cohort, towards establishing reference values
AU - Saigusa, Daisuke
AU - Hishinuma, Eiji
AU - Matsukawa, Naomi
AU - Takahashi, Masatomo
AU - Inoue, Jin
AU - Tadaka, Shu
AU - Motoike, Ikuko N.
AU - Hozawa, Atsushi
AU - Izumi, Yoshihiro
AU - Bamba, Takeshi
AU - Kinoshita, Kengo
AU - Ekroos, Kim
AU - Koshiba, Seizo
AU - Yamamoto, Masayuki
N1 - Funding Information:
Funding: This work was supported in part by the Tohoku Medical Megabank Project from MEXT, Japan Agency for Medical Research and Development (AMED; under grant numbers JP20km0105001 and JP20km0105002), Project for Promoting Public Utilization of Advanced Research Infrastructure (MEXT), Sharing and administrative network for research equipment (MEXT). This work was also supported by KAKENHI Grant Number JP20H03374 [D.S.], JP16H05241 [A.H], JP19H03893 [A.H.], the Grant-in-Aid for Scientific Research on Innovative Areas from the Japan Society for the Promotion of Science (JSPS), Grant Number 17H06304 [T.B.], and AMED LEAP under Grant Number J200001087 [D.S.].
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/10
Y1 - 2021/10
N2 - Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.
AB - Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.
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U2 - 10.3390/metabo11100652
DO - 10.3390/metabo11100652
M3 - Article
AN - SCOPUS:85116353498
VL - 11
JO - Metabolites
JF - Metabolites
SN - 2218-1989
IS - 10
M1 - 652
ER -