Metabolomics最新文献

{"title":"Combining clinical chemistry with metabolomics for metabolic phenotyping at population levels.","authors":"Yun Xu, Ian D Wilson, Royston Goodacre","doi":"10.1007/s11306-025-02331-2","DOIUrl":"https://doi.org/10.1007/s11306-025-02331-2","url":null,"abstract":"<p><strong>Introduction: </strong>Untargeted metabolic phenotyping (metabolomics/metabonomics), also known as metabotyping, has been shown to be able to discriminate reliably between different physiological or clinical conditions. However, we believe that standard panels of routinely collected clinical and clinical chemistry data also have the potential to provide assay panels that complement metabotyping.</p><p><strong>Objectives: </strong>To test the above hypothesis and evaluate the use of multivariate statistical analyses to provided panels of clinical/clinical chemistry data measurements that predict the age, sex and body mass index (BMI) of 977 normal subjects and compare these predictions with results acquired by metabotyping on the same healthy individuals.</p><p><strong>Methods: </strong>Metabotyping involved serum metabolomics using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) previously reported in our HUSERMET study (Dunn et al., 2015), while clinical chemistry data were obtained in clinic for 19 measurements assessing liver and kidney function, blood pressure, serum glucose, cations, as well as lipids. Multivariate analyses involved using support vector machines, random forest and partial least squares, to predict sex, age and BMI. These models used as inputs: (i) the clinical chemistry data alone; (ii) three metabolomics datasets; (iii) combinations of clinical chemistry with the metabolomics data. Model predictions were rigorously validated using 1,000 bootstrapping re-sampling coupled with permutation tests.</p><p><strong>Results: </strong>Multivariate statistical analyses on the clinical chemistry data obtained for these healthy participants could be used to predict: their sex, based on creatinine; their age, based on systolic blood pressure, total serum protein and serum glucose; as well as BMI using alanine transaminase, total cholesterol (Total-c) to high-density lipoprotein cholesterol (HDL-c) ratio and diastolic blood pressure. Combining clinical chemistry and metabolomics data sets enhanced the predictions of these characteristics. Moreover, this powerful combination allowed for quantitative predictions of age and BMI.</p><p><strong>Conclusion: </strong>Multivariate statistical analysis on clinical chemistry data from the HUSERMET study obtained similar predictions of age, sex or BMI, compared to metabotyping using GC-MS and LC-MS. These predictions from clinical chemistry data were between 71 and 85% accurate (depending on the MVA used) and compared favourably with metabolomics (71-91 depending on analytical method). Combining clinical chemistry and metabolomics data sets enhanced the predictions of these characteristics to 77-93% accuracy, suggesting that this augmentation of methods may be a useful approach in the search for clinical biomarkers.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"126"},"PeriodicalIF":3.3,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pre-partum feeding strategies affect colostrum metabolite levels related to nitrogen and energy metabolism in Holstein dairy cows.","authors":"Paraskevi Tsermoula, Niels Bastian Kristensen, Bekzod Khakimov","doi":"10.1007/s11306-025-02329-w","DOIUrl":"https://doi.org/10.1007/s11306-025-02329-w","url":null,"abstract":"<p><strong>Introduction: </strong>Cow colostrum synthesis takes place during the last month of pregnancy. Its composition is influenced by individual and environmental factors, such as cow parity, feeding, season and environmental conditions. Therefore, colostrum metabolomic profiling may provide information about the physiological status of cows around calving.</p><p><strong>Objectives: </strong>The cow colostrum metabolome was analyzed to determine whether its variability could be used to elucidate the cows' physiological status around calving and provide insights into the outcomes of cow transition programs.</p><p><strong>Methods: </strong>The factors assessed included a control feeding based on grass-clover silage and barley straw (FAR), two phase feedings based on acidified corn silage and canola cake, supplemented with magnesium chloride (MGC) or magnesium chloride and ammonium chloride (NH₄) and a feeding consisting of one week of grass-diluted MGC followed by two weeks of the NH₄. Colostrum was collected from 89 dairy cows, which were randomly allocated to the feedings three weeks before the expected calving date during spring, summer and autumn. Cow colostrum samples were analyzed using proton nuclear magnetic resonance spectroscopy.</p><p><strong>Results: </strong>Our results show that calving season influenced the levels of 14 metabolites. Independent of seasonal variation, acidified corn silage diets resulted in consistent decreased levels of tryptophan, acetate and cytidine, while the non-acidified grass-based diet resulted in increased concentrations of fucose.</p><p><strong>Conclusions: </strong>Although colostrum is physiologically regulated, our findings, for the first time, indicate that the four feeding strategies induce shifts in fucose, tryptophan, acetate and cytidine levels, reflecting the energy and nitrogen metabolism of cows before parturition.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"128"},"PeriodicalIF":3.3,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397122/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasma non-targeted metabolomics unravels the metabolic features of normal trans-right heart.","authors":"Xifeng Qian, Yuanrui Deng, Tingting Guo, Xin Huang, Chaowu Yan, Xin Gao, Yan Wu, Xinxin Yan, Zhiqiang Liu, Song Hu, Jiangshan Tan, Lingtao Chong, Shengsong Zhu, Mingjie Ma, Mengting Ye, Lu Hua, Jian Cao, Xiaojian Wang","doi":"10.1007/s11306-025-02317-0","DOIUrl":"https://doi.org/10.1007/s11306-025-02317-0","url":null,"abstract":"<p><strong>Introduction: </strong>Right heart (RH), as a junction between the venous system and pulmonary circulation, gains great emphasis on exploring the relevant pathological mechanism of many cardiopulmonary diseases. Although these pathogensis researches centering on RH-related diseases advance, the physiological mechanism research of the RH is scarce.</p><p><strong>Objectives: </strong>This study aimed to accurately unravel the metabolic features of normal trans-RH through non-targeted metabolomics.</p><p><strong>Methods: </strong>Patent foramen ovale (PFO) participants with normal function of RH were recruited and their blood samples from superior vena cava (SVC) and pulmonary artery (PA) were collected through right cardiac catheterization. Non-targeted metabolomics analysis based on UHPLC-MS/MS was utilized to generate the metabolic feature of trans-RH by comparing the metabolites change from SVC to PA, revealing its physiological gradient metabolic mechanism.</p><p><strong>Results: </strong>1060 metabolites were tentatively identified in blood samples from 28 PFO participants. 51 differential metabolites were defined based on screening criteria after flowing through RH, including 39 down-regulated metabolites and 12 up-regulated metabolites. Among them, phosphatidylcholines, sphingomyelins, amino acids, triacylglycerol, neopterin, and tetradecanedioic acid were the most relevant.</p><p><strong>Conclusion: </strong>Our study provides a more profound and extensive understanding of the psychological metabolism of trans-RH, expanding the current knowledge of normal RH function and providing clues for the pathogenesis research of RH-related diseases.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"130"},"PeriodicalIF":3.3,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of acute administration of melatonin immediately after physical exercise on the amino acid profile of rat's skeletal muscle and liver.","authors":"Alinson Eduardo Cipriano, Alex Ap Rosini Silva, Andreia M Porcari, Leonardo Henrique Dalcheco Messias, Vanessa Bertolucci, Wladimir Rafael Beck","doi":"10.1007/s11306-025-02326-z","DOIUrl":"https://doi.org/10.1007/s11306-025-02326-z","url":null,"abstract":"<p><strong>Introduction: </strong>Melatonin has been proposed to aid recovery following physical exercise; however, few studies have investigated its effects on tissue amino acid profile.</p><p><strong>Objective: </strong>This study aimed to evaluate the effects of post-exercise melatonin administration on tissue amino acid concentration and metabolic regulation.</p><p><strong>Methods: </strong>Thirty Wistar rats engaged in a 60-minute swimming session at 90% of their individual maximal aerobic capacity (iMAC), followed by the intraperitoneal administration of melatonin (EM; 10 mg·kg⁻¹) or a vehicle solution (Ex) of equivalent volume. The animals were euthanized at 1, 3, or 24 h post-treatment to facilitate the collection of liver and skeletal muscle samples. Tissue amino acid profiles were analyzed using flow-injection analysis (FIA) in conjunction with targeted mass spectrometry (MS). Statistical analyses were conducted using the Friedman test, two-way analysis of variance (ANOVA), Newman-Keuls post hoc test, and effect size (ES), with significance determined at p < 0.05.</p><p><strong>Results: </strong>No significant effects were observed in the liver tissue. However, in skeletal muscle, melatonin significantly increased the levels of several amino acids, including arginine, glutamic acid, glutamine, ornithine, proline, and serine. Additionally, glycine levels were elevated 3 h post-exercise (EM3 > Ex3; p < 0.05), whereas methionine levels were reduced 24 h post-exercise in the melatonin group compared to control groups (EM24 < Ex24; p < 0.01).</p><p><strong>Conclusion: </strong>Melatonin modulated the post-exercise amino acid profile in skeletal muscle, enhancing the levels of key metabolites involved in recovery and metabolic regulation, with no effects observed in liver tissue. These findings suggest a muscle-specific role for melatonin in supporting metabolic recovery after exercising.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"129"},"PeriodicalIF":3.3,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative analysis of transcriptome and metabolome profiles reveals immune-metabolic alterations in pulmonary sarcoidosis.","authors":"Sanjukta Dasgupta, Priyanka Choudhury, Sankalp Patidar, Mamata Joshi, Riddhiman Dhar, Sushmita Roychowdhury, Parthasarathi Bhattacharyya, Koel Chaudhury","doi":"10.1007/s11306-025-02325-0","DOIUrl":"https://doi.org/10.1007/s11306-025-02325-0","url":null,"abstract":"<p><strong>Background: </strong>Pulmonary sarcoidosis, a disease of unknown etiology, is characterized by the presence of noncaseating granulomas in lung parenchyma. This present study combines metabolomic and transcriptomic data to determine the metabolic and differentially expressed genes (DEGs) and associated pathways in sarcoidosis patients as compared to healthy controls. It is envisioned that a better understanding of the underlying mechanism will help in diagnosis and future treatment strategies.</p><p><strong>Methods: </strong>Using proton nuclear magnetic resonance (NMR) the altered serum metabolites were annotated in two groups of patients (discovery and validation cohorts). In addition, DEGs in blood samples were identified by analyzing a Gene Expression Omnibus (GEO) database. Next, a classification model using machine learning approach is developed to evaluate the predictive ability of these key metabotypes and DEGs. Finally, the pathways associated with these candidate metabolites and genetic features were investigated using IMPaLA version 13 tool.</p><p><strong>Results: </strong>The expression of six metabolites was found to be significantly altered in sarcoidosis patients as compared to controls. The transcriptomics analysis of microarray-based data revealed 10 DEGs to be significantly dysregulated in patients with sarcoidosis. The classification model using these key metabolites and DEGs showed the prediction ability to be 84% and 82% for metabolites and DEGs, respectively. Metabolite-DEG integrated model indicated significant association of IFN-γ signaling pathway in patients with sarcoidosis.</p><p><strong>Conclusions: </strong>The findings of this study indicate an increased energy demand and dysregulation of inflammatory pathways in patients with sarcoidosis.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"131"},"PeriodicalIF":3.3,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Translating metabolomic evidence gathered from an animal model to a real human scenario: the post-mortem interval issue.","authors":"Alberto Chighine, Matteo Stocchero, Fabio De-Giorgio, Matteo Nioi, Ernesto d'Aloja, Emanuela Locci","doi":"10.1007/s11306-025-02321-4","DOIUrl":"https://doi.org/10.1007/s11306-025-02321-4","url":null,"abstract":"<p><strong>Introduction: </strong>Translating findings from animal models to human applications remains a fundamental challenge across scientific research, with unique implications for post-mortem metabolomics.</p><p><strong>Objectives: </strong>This work is aimed at applying NMR metabolomics to human aqueous humour for post-mortem interval estimation, based on a previously studied ovine model.</p><p><strong>Methods: </strong>Quantitative metabolomic profiling of 21 aqueous humour samples collected during from 11 forensic autopsies, with post-mortem intervals between 225 and 1164 min has been performed by ¹H NMR spectroscopy.</p><p><strong>Results: </strong>Most of the identified metabolites in human aqueous humour samples are shared with those previously identified in ovine samples, showing qualitative similarities, while quantitative differences in metabolites such as lactate and glutamate are observed due to species-specific factors. Partial least squares regression models for post-mortem interval estimation resulted less accurate in human model with respect to the ovine one underscoring translational complexity. Of note, taurine and hypoxanthine were identified as post-mortem interval-specific metabolites independently on the species, suggesting their relevance in the post-mortem.</p><p><strong>Conclusions: </strong>This study is the first attempt to translate animal to human post-mortem metabolomics using a rigorous methodology. Direct translation to humans seems possible for a limited part of the metabolome, with key metabolites such as taurine and hypoxanthine showing some consistency. These findings support animal model metabolomics as a guide for human studies across diverse metabolomics investigations, promoting human studies on larger cohorts and more specific experimental designs.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"125"},"PeriodicalIF":3.3,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of omics discovery studies to identify pertinent metabolic pathways for locally advanced rectal cancer in response to neoadjuvant chemoradiotherapy.","authors":"Aaron Kler, Matthew Fok, Gabrielle J Grundy, Marco Sciacovelli, Warwick B Dunn, Dale Vimalachandran","doi":"10.1007/s11306-025-02319-y","DOIUrl":"https://doi.org/10.1007/s11306-025-02319-y","url":null,"abstract":"<p><strong>Background: </strong>Locally advanced rectal cancer (LARC) has variable responses to neoadjuvant therapy (NAT). Therefore, identifying changes in biological pathways involved when LARC is treated with NAT is crucial for developing treatments to improve clinical outcomes, as NAT is both variable and unpredictable. Although individual studies have attempted to discern how the response differs at a transcriptomic, proteomic and metabolomic level, there has not been a unifying systematic review discerning the key changes in metabolic pathways in this patient population.</p><p><strong>Aim of review: </strong>This systematic review aims to understand how metabolomics, proteomics and transcriptomics can demonstrate how the perturbed metabolic pathways of the NAT response in LARC can provide targets for further clinical research.</p><p><strong>Key scientific concepts of review: </strong>Thirteen studies met the inclusion criteria, including seven metabolomic, five proteomic, and one transcriptomic study. Metabolomic analyses revealed consistent alterations in amino acid metabolism, the tricarboxylic acid (TCA) cycle, and glycerophospholipid metabolism. Proteomic findings supported these results, highlighting disruptions in glycolysis and gluconeogenesis. Joint pathway analysis demonstrated a strong correlation (r = 0.99, p < 0.0001) between metabolic changes observed across omics platforms. Key pathways such as alanine, branched-chain amino acid, and aspartate metabolism were commonly altered and may contribute to radio-resistance through enhanced energy production, reactive oxygen species (ROS) neutralization, and DNA repair mechanisms. The convergence of multi-omic data underscores the biological relevance of these metabolic reprogramming events. However, due to the limited availability of transcriptomic data meeting inclusion criteria, these findings are primarily driven by metabolomic and proteomic analyses, which constrains the extent of full multi-omic integration. Future studies should aim to validate these findings in clinical cohorts and explore how targeting these \"survival\" pathways could optimize treatment response in LARC.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"124"},"PeriodicalIF":3.3,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal metabolic profiling of women using selective serotonin reuptake inhibitors during pregnancy.","authors":"Anna Itkonen, Olli Kärkkäinen, Heidi Sahlman, Leea Keski-Nisula, Jaana Rysä","doi":"10.1007/s11306-025-02334-z","DOIUrl":"https://doi.org/10.1007/s11306-025-02334-z","url":null,"abstract":"<p><strong>Introduction: </strong>Selective serotonin reuptake inhibitors (SSRIs) are the most prescribed antidepressants for pregnant women. While SSRIs are known to alter the circulating metabolic profile in non-pregnant individuals, the association between SSRIs and the changes in circulating metabolome during pregnancy remains unstudied. Pregnancy itself induces significant metabolic adjustments to meet the increased nutritional demands, and these maternal metabolic changes are crucial for the normal development and growth of the fetus.</p><p><strong>Objectives: </strong>To study the impact of SSRI usage on circulating maternal metabolome during pregnancy.</p><p><strong>Methods: </strong>A targeted nuclear magnetic resonance (NMR) spectroscopy method was used to analyze maternal serum samples obtained from the first trimester of pregnancy and at the time of the delivery from both SSRI users (n = 122) and non-depressive controls without antidepressants (n = 117) for concentrations of metabolites and lipoproteins.</p><p><strong>Results: </strong>During the first trimester of pregnancy, SSRI usage was associated with increased lipid content in sixteen very low-density lipoprotein (VLDL) and chylomicron subtypes. At delivery, SSRI users exhibited alterations in lipoprotein lipid and fatty acid ratios. Similarly, while investigating the influence of SSRI usage on the pregnancy-driven changes in the metabolome, the interplay between pregnancy progression and SSRI usage lowered the lipoprotein lipid ratios.</p><p><strong>Conclusion: </strong>Our analysis revealed a significant association between SSRIs and lipid metabolism. However, the observed changes were minor, suggesting a limited clinical impact. The findings enhance our understanding of the safe usage of SSRI medication during pregnancy.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"123"},"PeriodicalIF":3.3,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370871/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144960490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical greenness metrics for metabolomics.","authors":"Ren-Qi Wang, Yun Wang, Juan-Na Song, Huai-Dong Yu, Xi-Zhi Niu, Elize Smit","doi":"10.1007/s11306-025-02323-2","DOIUrl":"10.1007/s11306-025-02323-2","url":null,"abstract":"<p><strong>Background: </strong>Metabolomics is rapidly evolving, addressing analytical chemistry challenges in the qualification and quantitation of metabolites in extremely complex samples. Targeted metabolomics involves the extraction and analysis of target compounds, often present at extremely low concentrations, whilst untargeted metabolomics requires the use of sophisticated analytical techniques to deal with the simultaneous identification or quantitation of hundreds of compounds. Given the high energy consumption and excessive amounts of waste generated by metabolomics studies, greenness metrics are essential to account for sustainable development.</p><p><strong>Aim of review: </strong>To determine the applicability of the Analytical GREEnness calculator (AGREE) in evaluating the analytical greenness of metabolomics methods. Specifically, the analytical protocols of 16 state-of-art metabolomics studies, including nine targeted and seven untargeted metabolomics studies, are fully dissected, and detailed greenness parameters for each procedure are rationally estimated.</p><p><strong>Key scientific concepts of review: </strong>The calculated AGREE metrics unequivocally show the main weaknesses of greenness in current research, and guidelines for sustainable practices in metabolomics are provided. The results indicate that offline sample preparation and the lack of automation and miniaturization are key areas that must be addressed to make metabolomics more sustainable. Important aspects that should be considered include the complexity of sample preparation procedures, the use of toxic reagents and derivatizing agents, the amount of waste generated, and sample throughput.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"121"},"PeriodicalIF":3.3,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144883158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pharmacometabolomics uncovers key metabolic changes in the first-in-human study of β-lapachone derivative.","authors":"Yeonseo Jang, Jihyun Kang, Yufei Li, Woori Chae, Eunsol Yang, SeungHwan Lee, Joo-Youn Cho","doi":"10.1007/s11306-025-02332-1","DOIUrl":"10.1007/s11306-025-02332-1","url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"122"},"PeriodicalIF":3.3,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12364990/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144883160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}