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