Gut microbial metabolites, short-chain fatty acids (SCFAs), are found at multiple locations in the host body and are identified as important metabolites in gut microbiome-associated diseases. Quantifying SCFAs in diverse biological samples is important to understand their roles in host health. This study developed an accurate SCFA quantification method by performing gas chromatography–mass spectrometry (GC/MS) in human plasma, serum, feces, and mouse cecum tissue. The samples were acidified with hydrochloric acid, and the SCFAs were extracted using methyl tert-butyl ether. In this method, distilled water was selected as a surrogate matrix for the quantification of SCFAs in target biological samples. The method was validated in terms of linearity, parallelism, precision, recovery, and matrix effect. The developed method was further applied in target biological samples. In conclusion, this optimized method can be used as a simultaneous SCFA quantification method in diverse biological samples.

Childhood obesity has increased worldwide, and many clinical and public interventions have attempted to reduce morbidity. We aimed to determine the metabolomic signatures associated with weight control interventions in children with obesity. Forty children from the “Intervention for Children and Adolescent Obesity via Activity and Nutrition (ICAAN)” cohort were selected according to intervention responses. Based on changes in body mass index z-scores, 20 were responders and the remaining non-responders. Their serum metabolites were quantitatively analyzed using capillary electrophoresis time-of-flight mass spectrometry at baseline and after 6 and 18 months of intervention. After 18 months of intervention, the metabolite cluster changes in the responders and non-responders showed a difference on the heatmap, but significant metabolites were not clear. However, regardless of the responses, 13 and 49 metabolites were significant in the group of children with obesity intervention at 6 months and 18 months post-intervention compared to baseline. In addition, the top five metabolic pathways (D-glutamine and D-glutamate metabolism; arginine biosynthesis; alanine, aspartate, and glutamate metabolism; TCA cycle (tricarboxylic acid cycle); valine, leucine, and isoleucine biosynthesis) including several amino acids in the metabolites of obese children after 18 months were significantly changed. Our study showed significantly different metabolomic profiles based on time post obesity-related intervention. Through this study, we can better understand and predict childhood obesity through metabolite analysis and monitoring.

Several adult omics studies have been conducted to understand the pathophysiology of nonalcoholic fatty liver disease (NAFLD). However, the histological features of children are different from those of adults, and the onset and progression of pediatric NAFLD are not fully understood. In this study, we aimed to evaluate the metabolome profile and metabolic pathway changes associated with pediatric NAFLD to elucidate its pathophysiology and to develop machine learning-based NAFLD diagnostic models. We analyzed the metabolic profiles of healthy control, lean NAFLD, overweight control, and overweight NAFLD groups of children and adolescent participants (N = 165) by assessing plasma samples. Additionally, we constructed diagnostic models by applying three machine learning methods (ElasticNet, random forest, and XGBoost) and multiple logistic regression by using NAFLD-specific metabolic features, genetic variants, and clinical data. We identified 18 NAFLD-specific metabolic features and metabolic changes in lipid, glutathione-related amino acid, and branched-chain amino acid metabolism by comparing the control and NAFLD groups in the overweight pediatric population. Additionally, we successfully developed and cross-validated diagnostic models that showed excellent diagnostic performance (ElasticNet and random forest model: area under the receiver operating characteristic curve, 0.95). Metabolome changes in the plasma of pediatric patients with NAFLD are associated with the pathophysiology of the disease and can be utilized as a less-invasive approach to diagnosing the disease.

Cytochrome P450 (CYP) 3A enzymes, the most important phase 1 drug-metabolizing enzymes, are responsible for 50% of the metabolism of clinically used drugs. CYP3A activity varies widely among individuals, which can affect the probability of adverse drug reactions and drug-drug interactions mediated by the induction or inhibition of the enzyme. Hence, it is important to be able to predict CYP3A activity in individuals to reduce the incidence of unexpected drug responses. To specifically and quickly measure CYP3A activity, we developed method based on gas chromatography interfaced with triple-quadrupole mass spectrometry for the quantification of cortisol, cortisone, 6 beta-hydroxycortisol, and 6 beta-hydroxycortisone simultaneously in urine and 4 beta-hydroxycholesterol in plasma. The results were calculated based on charcoal-stripped steroid-free urine and plasma control samples. The accuracy and precision were 93.18% to 110.0% and 1.96% to 5.34%, respectively. This method was then applied to measure endogenous steroids from urine and plasma samples of healthy Korean males and females. The calibration curves of all analytes showed good linearity with a correlation coefficient (r(2)) that ranged from 0.9953 to 0.9999. Therefore, this validated method can be used to measure endogenous biomarkers to predict CYP3A activity and might be applicable in the prediction of CYP3A-mediated drug interactions of new drug candidates.

Introduction: WK0202, a β-lapachone derivative under clinical development, activates NAD(P)H quinone dehydrogenase 1 (NQO1), acting as a detoxifying and antioxidant agent. In this study, a metabolomics investigation of β-lapachone derivatives in humans is performed to characterize drug-induced alterations in endogenous metabolic pathways. Objectives: This study investigated metabolic alterations induced by WK0202 administration and their potential association with its therapeutic mechanism and efficacy. Using targeted and untargeted metabolomics approaches, we identified potential pharmacodynamic biomarker candidates that may reflect the drug’s activity and metabolic effects. Methods: Plasma samples from healthy subjects who received multiple doses of WK0202 were compared with a placebo control group. The metabolomic profiles were compared pre- and post-dose to identify significant metabolic changes. Significant metabolites were identified using statistical analyses, focusing on key metabolic pathways. To further investigate NQO1 genotype effects, Spearman correlation analysis was performed between post/pre-dose concentration ratios and genotypes. Results: Following WK0202 administration, significant changes were observed in the alanine, aspartate and glutamate metabolism, arginine biosynthesis, and lipid metabolism. Although most metabolites were not strongly dependent on NQO1 genotype or dose group, they exhibited an overall consistent trend. These alterations were indicative of Nrf2 pathway activation, possibly by NQO1-mediated drug activity. Conclusion: These metabolic alterations highlight the potential of endogenous metabolites as surrogate markers for identifying novel therapeutic targets and assessing the efficacy of WK0202 in future clinical studies.

CYP2D6‐mediated drug–drug–gene interactions (DDGIs) are known to influence the pharmacokinetics of venlafaxine and its metabolism to O‐desmethylvenlafaxine. Solanidine and 3,4‐seco‐solanidine‐3,4‐dioic acid (SSDA) have recently been investigated as candidate endogenous CYP2D6 biomarkers; however, they remain unexplored in East Asian populations, where dietary potato intake is relatively lower than that in Western populations. A prospective clinical study aimed to characterize venlafaxine DDGIs and explore the potential of solanidine as a candidate biomarker of CYP2D6 activity in healthy Korean adults. Twenty participants including 14 CYP2D6 normal metabolizers (NMs) and 6 intermediate metabolizers (IMs)—all confirmed as CYP2C19 NMs—were enrolled. Serial plasma samples for pharmacokinetic assessment were collected before and after coadministration of paroxetine, a potent CYP2D6 inhibitor. Solanidine and SSDA were also measured in plasma and urine. Compared to CYP2D6 NMs, IMs exhibited higher venlafaxine exposure but lower O‐desmethylvenlafaxine exposure. Following CYP2D6 inhibition, phenotype‐dependent differences in venlafaxine and O‐desmethylvenlafaxine pharmacokinetics were attenuated. The metabolic ratio (MR) of plasma solanidine showed a modest positive correlation with both the MR of venlafaxine and CYP2D6 activity score. The MR of plasma solanidine decreased when CYP2D6 activity was reduced by paroxetine coadministration. These findings demonstrate phenotype‐dependent DDGIs of venlafaxine and suggest the exploratory potential of solanidine as an endogenous biomarker of CYP2D6 activity in the Korean population, despite relatively lower dietary exposure to potato‐derived precursors. This study provides preliminary evidence extending endogenous CYP2D6 biomarkers to an East Asian population with distinct dietary backgrounds.