Abstract

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.

Highlights

  • A metabolome is a group of small molecules that are endogenously produced as part of the end of the central dogma and have biological functions; metabolomics can be used together with other omics techniques [1]

  • We evaluated the quality of the quantified values of the metabolites in 2541 plasma samples detected by Kit-Met 2 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography mass spectrometry (MS)/MS (SFC-MS/MS) and UHPLC-Fourier transform

  • A total of 8700 plasma samples from participants in the TMM Community-based Cohort Study were selected for metabolic profiling using Kit-Mets by UHPLC-MS/MS

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Summary

Introduction

A metabolome is a group of small molecules that are endogenously produced as part of the end of the central dogma and have biological functions; metabolomics can be used together with other omics techniques [1]. Metabolic changes are directly associated with phenotypic changes and are affected by genomic factors, environmental factors (such as lifestyle, food intake, and/or the gut microbiome), and disease expression and progression [2,3]. Metabolic phenotyping has been widely used in biomarker discovery studies to identify disease-specific predictive molecules in biological specimens using several analytical platforms [4,5,6]. Mass spectrometry (MS)based metabolic profiling allows for the simultaneous and sensitive detection of metabolites, and gas chromatography MS has been traditionally utilized for this purpose [9,10]. Global metabolomics has been established to detect thousands of features as a comprehensive metabolic profiling technique using liquid chromatography

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