Search for Novel Biomarkers to Predict Cytochrome P450 2C19 Activity Using Untargeted Metabolomics of Human Plasma

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.

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Publication Details

Journal
Metabolites
Published
2026-09-11
DOI
https://doi.org/10.3390/metabo16090670
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
Field-Weighted Citation Impact
0.00

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article

Search for Novel Biomarkers to Predict Cytochrome P450 2C19 Activity Using Untargeted Metabolomics of Human Plasma

Ryosuke Tatsuta, Masahiro Nakatochi, Teruhide Koyama, Etsuko Ozaki et al.
Metabolites
Pharmacogenetics and Drug Metabolism
article

Search for Novel Biomarkers to Predict Cytochrome P450 2C19 Activity Using Untargeted Metabolomics of Human Plasma

Ryosuke Tatsuta, Masahiro Nakatochi, Teruhide Koyama, Etsuko Ozaki, Keitaro Matsuo, Hiroki Itoh, Ryota Tanaka, Natsuki Kamio, Nao Yamagishi, Sakura Suzuki, Yasuyuki Yamamoto, Koudai Iino, Takahiro Sumimoto, Yosuke Suzuki, Ayako Oda, Jun Negami, Hiroyuki Ono, Naoyuki Takashima, Yukihide Momozawa, Keiko Ohno
article en

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.

MetabolitesVol. 16(9)
Meiji Pharmaceutical University (JP), Kyoto Prefectural University of Medicine (JP), Kyoto College of Medical Science (JP), Aichi Cancer Center (JP), Nara Prefectural University (JP), RIKEN Center for Integrative Medical Sciences (JP), Oita University Hospital (JP), Nagoya University (JP)
Japan Agency for Medical Research and Development, Japan Society for the Promotion of Science
Peace, Justice and strong institutions
Openalex Percentile: Top 9%
Pharmacogenetics and Drug Metabolism
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