Related Experiment Video
Updated: Sep 26, 2026

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
Published on: May 20, 2013
Search for Novel Biomarkers to Predict Cytochrome P450 2C19 Activity Using Untargeted Metabolomics of Human Plasma
Ayako Oda1, Yosuke Suzuki1, Teruhide Koyama2,3
1Department of Medication Use Analysis and Clinical Research, Meiji Pharmaceutical University, 2-522-1 Noshio, Kiyose 204-8588, Tokyo, Japan.
Abstract:
Background/Objectives: Cytochrome P450(CYP)2C19 activity varies widely among individuals. As genetic factors, CYP2C19*2 and CYP2C19*3 alleles reduce CYP2C19 activity, while the CYP2C19*17 allele increases CYP2C19 activity. However, environmental and physiological factors can also influence individual CYP2C19 activity. In this study, we searched for novel endogenous biomarkers for CYP2C19 activity using CYP2C19 gene polymorphism data combined with results of untargeted metabolomic analysis. Methods: 431 general adults analyzed in the Kyoto J-MICC Study and 255 patients who visited Oita University Hospital were studied. Plasma samples were pretreated by solid-phase and liquid-liquid extraction and subjected to untargeted metabolomic analysis using ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. Based on CYP2C19 gene polymorphism data, participants were classified into extensive metabolizers (EM), intermediate metabolizers (IM), and poor metabolizers (PM). Compounds showing significant differences in abundance among the three groups were considered candidate compounds for predicting CYP2C19 activity. The predictive performance of candidate compounds for CYP2C19 PM status was evaluated using covariate-adjusted receiver operating characteristic (ROC) analysis. Results: The normalized abundance of compounds with m/z 160.1342, 303.2319 (a fatty acyl or prenol lipid), 314.2309, 449.3238, 653.3021, 792.5744, and 811.5988 (a glycerophospholipid or sphingolipid), and 902.5404 (a fatty acyl) differed significantly among CYP2C19 EM, IM, and PM groups (p < 0.05), and these eight compounds were considered candidate compounds. Covariate-adjusted ROC analysis showed that none of the candidate compounds significantly improved the discrimination of CYP2C19 PM status. Conclusions: Untargeted metabolomics combined with CYP2C19 gene polymorphism data yielded eight compounds associated with CYP2C19 phenotype. Further studies are needed to evaluate the usefulness of these compounds as biomarkers of CYP2C19 activity.
