1
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Jian J, He D, Gao S, Tao X, Dong X. Pharmacokinetics in Pharmacometabolomics: Towards Personalized Medication. Pharmaceuticals (Basel) 2023; 16:1568. [PMID: 38004434 PMCID: PMC10675232 DOI: 10.3390/ph16111568] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 10/19/2023] [Accepted: 10/27/2023] [Indexed: 11/26/2023] Open
Abstract
Indiscriminate drug administration may lead to drug therapy results with varying effects on patients, and the proposal of personalized medication can help patients to receive effective drug therapy. Conventional ways of personalized medication, such as pharmacogenomics and therapeutic drug monitoring (TDM), can only be implemented from a single perspective. The development of pharmacometabolomics provides a research method for the realization of precise drug administration, which integrates the environmental and genetic factors, and applies metabolomics technology to study how to predict different drug therapeutic responses of organisms based on baseline metabolic levels. The published research on pharmacometabolomics has achieved satisfactory results in predicting the pharmacokinetics, pharmacodynamics, and the discovery of biomarkers of drugs. Among them, the pharmacokinetics related to pharmacometabolomics are used to explore individual variability in drug metabolism from the level of metabolism of the drugs in vivo and the level of endogenous metabolite changes. By searching for relevant literature with the keyword "pharmacometabolomics" on the two major literature retrieval websites, PubMed and Web of Science, from 2006 to 2023, we reviewed articles in the field of pharmacometabolomics that incorporated pharmacokinetics into their research. This review explains the therapeutic effects of drugs on the body from the perspective of endogenous metabolites and pharmacokinetic principles, and reports the latest advances in pharmacometabolomics related to pharmacokinetics to provide research ideas and methods for advancing the implementation of personalized medication.
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Affiliation(s)
- Jingai Jian
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
| | - Donglin He
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
| | - Songyan Gao
- Institute of Translational Medicine, Shanghai University, Shanghai 200444, China;
| | - Xia Tao
- Department of Pharmacy, Changzheng Hospital, Second Military Medical University, Shanghai 200003, China
| | - Xin Dong
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
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2
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Corona G, Di Gregorio E, Buonadonna A, Lombardi D, Scalone S, Steffan A, Miolo G. Pharmacometabolomics of trabectedin in metastatic soft tissue sarcoma patients. Front Pharmacol 2023; 14:1212634. [PMID: 37637412 PMCID: PMC10450632 DOI: 10.3389/fphar.2023.1212634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 07/20/2023] [Indexed: 08/29/2023] Open
Abstract
Objective: Trabectedin is an anti-cancer drug commonly used for the treatment of patients with metastatic soft tissue sarcoma (mSTS). Despite its recognized efficacy, significant variability in pharmacological response has been observed among mSTS patients. To address this issue, this pharmacometabolomics study aimed to identify pre-dose plasma metabolomics signatures that can explain individual variations in trabectedin pharmacokinetics and overall clinical response to treatment. Methods: In this study, 40 mSTS patients treated with trabectedin administered by 24 h-intravenous infusion at a dose of 1.5 mg/m2 were enrolled. The patients' baseline plasma metabolomics profiles, which included derivatives of amino acids and bile acids, were analyzed using multiple reaction monitoring LC-MS/MS together with their pharmacokinetics profile of trabectedin. Multivariate Partial least squares regression and univariate statistical analyses were utilized to identify correlations between baseline metabolite concentrations and trabectedin pharmacokinetics, while Partial Least Squares-Discriminant Analysis was employed to evaluate associations with clinical response. Results: The multiple regression model, derived from the correlation between the AUC of trabectedin and pre-dose metabolomics, exhibited the best performance by incorporating cystathionine, hemoglobin, taurocholic acid, citrulline, and the phenylalanine/tyrosine ratio. This model demonstrated a bias of 4.6% and a precision of 17.4% in predicting drug AUC, effectively accounting for up to 70% of the inter-individual pharmacokinetic variability. Through the use of Partial least squares-Discriminant Analysis, cystathionine and hemoglobin were identified as specific metabolic signatures that effectively distinguish patients with stable disease from those with progressive disease. Conclusions: The findings from this study provide compelling evidence to support the utilization of pre-dose metabolomics in uncovering the underlying causes of pharmacokinetic variability of trabectedin, as well as facilitating the identification of patients who are most likely to benefit from this treatment.
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Affiliation(s)
- Giuseppe Corona
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Emanuela Di Gregorio
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Angela Buonadonna
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Davide Lombardi
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Simona Scalone
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
| | - Gianmaria Miolo
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, Aviano, Italy
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3
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Macioszek S, Dudzik D, Biesemans M, Wozniak A, Schöffski P, Markuszewski MJ. A multiplatform metabolomics approach for comprehensive analysis of GIST xenografts with various KIT mutations. Analyst 2023; 148:3883-3891. [PMID: 37458061 DOI: 10.1039/d3an00599b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Metabolites in biological matrices belong to diverse chemical groups, ranging from non-polar long-chain fatty acids to small polar molecules. The goal of untargeted metabolomic analysis is to measure the highest number of metabolites in the sample. Nevertheless, from an analytical point of view, no single technique can measure such a broad spectrum of analytes. Therefore, we selected a method based on GC-MS and LC-MS with two types of stationary phases for the untargeted profiling of gastrointestinal stromal tumours. The procedure was applied to GIST xenograft samples (n = 71) representing four different mutation models, half of which were treated with imatinib. We aimed to verify the method coverage and advantages of applying each technique. RP-LC-MS measured most metabolites due to a significant fraction of lipid components of the tumour tissue. What is unique and worth noting is that all applied techniques were able to distinguish between different mutation models. However, for detecting imatinib-induced alterations in the GIST metabolome, RP-LC-MS and GC-MS proved to be more relevant than HILIC-LC-MS, resulting in a higher number of significantly changed metabolites in four treated models. Undoubtedly, the inclusion of all mentioned techniques makes the method more comprehensive. Nonetheless, for green chemistry and time and labour saving, we assume that RP-LC-MS and GC-MS analyses are sufficient to cover the global GIST metabolome.
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Affiliation(s)
- Szymon Macioszek
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland.
| | - Danuta Dudzik
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland.
| | - Margot Biesemans
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland.
| | - Agnieszka Wozniak
- Laboratory of Experimental Oncology, Department of Oncology, KU Leuven, and Department of General Medical Oncology, University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium
| | - Patrick Schöffski
- Laboratory of Experimental Oncology, Department of Oncology, KU Leuven, and Department of General Medical Oncology, University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium
| | - Michal J Markuszewski
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland.
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4
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Fecke A, Saw NMMT, Kale D, Kasarla SS, Sickmann A, Phapale P. Quantitative Analytical and Computational Workflow for Large-Scale Targeted Plasma Metabolomics. Metabolites 2023; 13:844. [PMID: 37512551 PMCID: PMC10383057 DOI: 10.3390/metabo13070844] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/04/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Quantifying metabolites from various biological samples is necessary for the clinical and biomedical translation of metabolomics research. One of the ongoing challenges in biomedical metabolomics studies is the large-scale quantification of targeted metabolites, mainly due to the complexity of biological sample matrices. Furthermore, in LC-MS analysis, the response of compounds is influenced by their physicochemical properties, chromatographic conditions, eluent composition, sample preparation, type of MS ionization source, and analyzer used. To facilitate large-scale metabolite quantification, we evaluated the relative response factor (RRF) approach combined with an integrated analytical and computational workflow. This approach considers a compound's individual response in LC-MS analysis relative to that of a non-endogenous reference compound to correct matrix effects. We created a quantitative LC-MS library using the Skyline/Panorama web platform for data processing and public sharing of data. In this study, we developed and validated a metabolomics method for over 280 standard metabolites and quantified over 90 metabolites. The RRF quantification was validated and compared with conventional external calibration approaches as well as literature reports. The Skyline software environment was adapted for processing such metabolomics data, and the results are shared as a "quantitative chromatogram library" with the Panorama web application. This new workflow was found to be suitable for large-scale quantification of metabolites in human plasma samples. In conclusion, we report a novel quantitative chromatogram library with a targeted data analysis workflow for biomedical metabolomic applications.
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Affiliation(s)
- Antonia Fecke
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
- Department Hamm 2, Hochschule Hamm-Lippstadt, Marker-Allee 76-78, 59063 Hamm, Germany
| | - Nay Min Min Thaw Saw
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Dipali Kale
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Siva Swapna Kasarla
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Albert Sickmann
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Prasad Phapale
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
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5
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Joncquel M, Labasque J, Demaret J, Bout MA, Hamroun A, Hennart B, Tronchon M, Defevre M, Kim I, Kerckhove A, George L, Gilleron M, Dessein AF, Zerimech F, Grzych G. Targeted Metabolomics Analysis Suggests That Tacrolimus Alters Protection against Oxidative Stress. Antioxidants (Basel) 2023; 12:1412. [PMID: 37507951 PMCID: PMC10376759 DOI: 10.3390/antiox12071412] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/06/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Tacrolimus (FK506) is an immunosuppressant that is experiencing a continuous rise in usage worldwide. The related side effects are known to be globally dose-dependent. Despite numerous studies on FK506, the mechanisms underlying FK506 toxicity are still not well understood. It is therefore essential to explore the toxicity mediated by FK506. To accomplish this, we conducted a targeted metabolomic analysis using LC-MS on the plasma samples of patients undergoing FK506 treatment. The aim was to identify any associated altered metabolic pathway. Another anti-calcineurin immunosuppressive therapy, ciclosporin (CSA), was also studied. Increased plasma concentrations of pipecolic acid (PA) and sarcosine, along with a decrease in the glycine/sarcosine ratio and a tendency of increased plasma lysine was observed in patients under FK506 compared to control samples. Patients under CSA do not show an increase in plasma PA compared to the control samples, which does not support a metabolic link between the calcineurin and PA. The metabolomics changes observed in patients under FK506 highlight a possible link between FK506 and the action of an enzyme involved in both PA and sarcosine catabolism and oxidative pathway, the Peroxisomal sarcosine oxidase (PIPOX). Moreover, PA could be investigated as a potential biomarker of early nephrotoxicity in the follow-up of patients under FK506.
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Affiliation(s)
- Marie Joncquel
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Julie Labasque
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Julie Demaret
- CHU Lille, Centre de Biologie Pathologie Génétique, Institut d'Immunologie, F-59000 Lille, France
| | - Marie-Adélaïde Bout
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Aghilès Hamroun
- UMR1167 RIDAGE, Institut Pasteur de Lille, Inserm, Université de Lille, CHU Lille, F-59000 Lille, France
| | - Benjamin Hennart
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Toxicologie et Génopathies, F-59000 Lille, France
| | - Mathieu Tronchon
- CHU Lille, Centre de Biologie Pathologie Génétique, Institut d'Immunologie, F-59000 Lille, France
| | - Magali Defevre
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Isabelle Kim
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Alain Kerckhove
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Laurence George
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Mylène Gilleron
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Anne-Frédérique Dessein
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
| | - Farid Zerimech
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
- Institut Pasteur de Lille, Université de Lille, ULR 4483, IMPECS, F-59000 Lille, France
| | - Guillaume Grzych
- CHU Lille, Centre de Biologie Pathologie Génétique, Service Hormonologie Métabolisme Nutrition Oncologie, F-59000 Lille, France
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6
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Shen G, Moua KTY, Perkins K, Johnson D, Li A, Curtin P, Gao W, McCune JS. Precision sirolimus dosing in children: The potential for model-informed dosing and novel drug monitoring. Front Pharmacol 2023; 14:1126981. [PMID: 37021042 PMCID: PMC10069443 DOI: 10.3389/fphar.2023.1126981] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 02/14/2023] [Indexed: 04/07/2023] Open
Abstract
The mTOR inhibitor sirolimus is prescribed to treat children with varying diseases, ranging from vascular anomalies to sporadic lymphangioleiomyomatosis to transplantation (solid organ or hematopoietic cell). Precision dosing of sirolimus using therapeutic drug monitoring (TDM) of sirolimus concentrations in whole blood drawn at the trough (before the next dose) time-point is the current standard of care. For sirolimus, trough concentrations are only modestly correlated with the area under the curve, with R 2 values ranging from 0.52 to 0.84. Thus, it should not be surprising, even with the use of sirolimus TDM, that patients treated with sirolimus have variable pharmacokinetics, toxicity, and effectiveness. Model-informed precision dosing (MIPD) will be beneficial and should be implemented. The data do not suggest dried blood spots point-of-care sampling of sirolimus concentrations for precision dosing of sirolimus. Future research on precision dosing of sirolimus should focus on pharmacogenomic and pharmacometabolomic tools to predict sirolimus pharmacokinetics and wearables for point-of-care quantitation and MIPD.
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Affiliation(s)
- Guofang Shen
- Department of Hematologic Malignancies Translational Sciences, City of Hope, and Department of Hematopoietic Cell Transplantation, City of Hope Medical Center, Duarte, CA, United States
| | - Kao Tang Ying Moua
- Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, United States
| | - Kathryn Perkins
- Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, United States
| | - Deron Johnson
- Clinical Informatics, City of Hope Medical Center, Duarte, CA, United States
| | - Arthur Li
- Division of Biostatistics, City of Hope, Duarte, CA, United States
| | - Peter Curtin
- Department of Hematologic Malignancies Translational Sciences, City of Hope, and Department of Hematopoietic Cell Transplantation, City of Hope Medical Center, Duarte, CA, United States
| | - Wei Gao
- Division of Engineering and Applied Science, Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, United States
| | - Jeannine S. McCune
- Department of Hematologic Malignancies Translational Sciences, City of Hope, and Department of Hematopoietic Cell Transplantation, City of Hope Medical Center, Duarte, CA, United States
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7
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Zhu H, Wang M, Xiong X, Du Y, Li D, Wang Z, Ge W, Zhu Y. Plasma metabolomic profiling reveals factors associated with dose-adjusted trough concentration of tacrolimus in liver transplant recipients. Front Pharmacol 2022; 13:1045843. [PMID: 36386159 PMCID: PMC9659571 DOI: 10.3389/fphar.2022.1045843] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/13/2022] [Indexed: 07/30/2023] Open
Abstract
Inter- and intrapatient variability of tacrolimus exposure is a vital prognostic risk factor for the clinical outcome of liver transplantation. New factors or biomarkers characterizing tacrolimus disposition is essential for optimal dose prediction in recipients of liver transplant. The aim of the study was to identify potential plasma metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients by using a global metabolomic approach. A total of 693 plasma samples were collected from 137 liver transplant recipients receiving tacrolimus and regular therapeutic drug monitoring. Untargeted metabolomic analysis was performed by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. Univariate and multivariate analyses with a mixed linear model were conducted, and the results showed that the dose-adjusted tacrolimus trough concentration was associated with 31 endogenous metabolites, including medium- and long-chain acylcarnitines such as stearoylcarnitine (β = 0.222, p = 0.001), microbiota-derived uremic retention solutes such as indolelactic acid (β = 0.194, p = 0.007), bile acids such as taurohyodeoxycholic acid (β = -0.056, p = 0.002), and steroid hormones such as testosterone (β = 0.099, p = 0.001). A multiple linear mixed model including 11 metabolites and clinical information was established with a suitable predictive performance (correlation coefficient based on fixed effects = 0.64 and correlation coefficient based on fixed and random effects = 0.78). These data demonstrated that microbiota-derived uremic retention solutes, bile acids, steroid hormones, and medium- and long-chain acylcarnitines were the main metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients.
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Affiliation(s)
- Huaijun Zhu
- Department of Pharmacology, School of Pharmacy, Fudan University, Shanghai, China
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Min Wang
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Xiaofu Xiong
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yao Du
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Danying Li
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Zhou Wang
- State Key Laboratory of Quality Research in Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
| | - Weihong Ge
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Yizhun Zhu
- Department of Pharmacology, School of Pharmacy, Fudan University, Shanghai, China
- State Key Laboratory of Quality Research in Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
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He X, Yang X, Yan X, Huang M, Xiang Z, Lou Y. Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27113517. [PMID: 35684454 PMCID: PMC9182099 DOI: 10.3390/molecules27113517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/19/2022] [Accepted: 05/27/2022] [Indexed: 11/16/2022]
Abstract
The clinical pharmacodynamics of tacrolimus in renal transplant patients has significant interindividual variability. T lymphocytes were selected to study the pharmacodynamic response of tacrolimus, which was significantly correlated with renal function and the outcome of renal transplant patients. Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectroscopy (UPLC/Q-TOF-MS) was performed to obtain the metabolic profiles of 109 renal transplant patients. A partial least squares (PLS) model was constructed to screen potential biomarkers that could predict the efficacy of tacrolimus. Multinomial logistic regression analysis established a bridge that could quantify the relationship between the efficacy of tacrolimus and biomarkers. The results showed a good correlation between endogenous molecules and the efficacy of tacrolimus. Metabolites such as serum creatinine, mesobilirubinogen, L-isoleucine, 5-methoxyindoleacetate, eicosapentaenoic acid, N2-succinoylarginine, tryptophyl-arginine, and butyric acid were indicated as candidate biomarkers. In addition, the key biomarkers could correctly predict the efficacy of tacrolimus with an accuracy of 82.5%. Finally, we explored the mechanism of individual variation by pathway analysis, which showed that amino acid metabolism was significantly related to the efficacy of tacrolimus. Moreover, orthogonal partial least squares discriminant analysis (OPLS-DA) showed that there was no difference in key metabolites among different pharmacodynamic groups at 1 month and 3 months after dose adjustment, suggesting that pharmacometabonomics is a useful tool to predict individual differences in pharmacodynamics and thus to facilitate individualized drug therapy.
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Affiliation(s)
- Xiaoying He
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
| | - Xi Yang
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
| | - Xiaoting Yan
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
| | - Mingzhu Huang
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
- Correspondence: (M.H.); (Z.X.); (Y.L.); Tel.: +86-571-8723-6871 (Y.L.)
| | - Zheng Xiang
- School of Pharmaceutical Sciences, Zhejiang University City College, Hangzhou 310000, China
- Correspondence: (M.H.); (Z.X.); (Y.L.); Tel.: +86-571-8723-6871 (Y.L.)
| | - Yan Lou
- Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, Department of Clinical Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 QingChun Road, Hangzhou 310000, China; (X.H.); (X.Y.); (X.Y.)
- Correspondence: (M.H.); (Z.X.); (Y.L.); Tel.: +86-571-8723-6871 (Y.L.)
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9
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Du P, Liu L, Hu T, An Z. Integrative Analysis of Pharmacokinetic and Metabolomic Profiles for Predicting Metabolic Phenotype and Drug Exposure Caused by Sotorasib in Rats. Front Oncol 2022; 12:778035. [PMID: 35449573 PMCID: PMC9017425 DOI: 10.3389/fonc.2022.778035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 02/28/2022] [Indexed: 11/23/2022] Open
Abstract
Sotorasib is a novel targeted inhibitor of Kirsten rat sarcoma (KRAS) (G12C) that has shown exciting tumor-suppressing effects not only for single targeted agents but also for combination with immune checkpoint inhibitors. However, no integrative analysis of the pharmacokinetics (PK) and pharmacometabolomics (PM) of sotorasib has been reported to date. In the present study, a sensitive and robust high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS) method was firstly developed and fully validated for the quantitation of sotorasib in rat plasma. After one-step protein precipitation, sotorasib and an internal standard (carbamazepine) were separated on a Waters XBrige C18 column (50 mm × 2.1 mm, 3.5 μm) and analyzed in electrospray ionization positive ion (ESI+) mode. The optimized method was fully validated according to guidance and was successfully applied for the PK study of sotorasib at a dose of 10 mg/kg. In addition, a longitudinal and transversal PM was employed and correlated with PK using partial least squares model and Pearson’s analysis. With multivariate statistical analysis, the selected six (AUC model) and nine (Cmax model) metabolites completely distinguished the high- and low-exposure groups after sotorasib treatment, which indicates that these potential biomarkers can predict drug exposure or toxicity. The results of this study will not only shed light on how sotorasib disturbs the metabolic profiles and the relationship between PK and PM but also offer meaningful references for precision therapy in patients with the KRAS (G12C) mutation.
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Affiliation(s)
- Ping Du
- Department of Pharmacy, Research Unit, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Lihong Liu
- Department of Pharmacy, Research Unit, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Ting Hu
- Department of Pharmacy, Research Unit, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Zhuoling An
- Department of Pharmacy, Research Unit, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
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Silveira AMR, Duarte GHB, Fernandes AMADP, Garcia PHD, Vieira NR, Antonio MA, Carvalho PDO. Serum Predose Metabolic Profiling for Prediction of Rosuvastatin Pharmacokinetic Parameters in Healthy Volunteers. Front Pharmacol 2021; 12:752960. [PMID: 34867363 PMCID: PMC8633954 DOI: 10.3389/fphar.2021.752960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 10/13/2021] [Indexed: 11/23/2022] Open
Abstract
Rosuvastatin is a well-known lipid-lowering agent generally used for hypercholesterolemia treatment and coronary artery disease prevention. There is a substantial inter-individual variability in the absorption of statins usually caused by genetic polymorphisms leading to a variation in the corresponding pharmacokinetic parameters, which may affect drug therapy safety and efficacy. Therefore, the investigation of metabolic markers associated with rosuvastatin inter-individual variability is exceedingly relevant for drug therapy optimization and minimizing side effects. This work describes the application of pharmacometabolomic strategies using liquid chromatography coupled to mass spectrometry to investigate endogenous plasma metabolites capable of predicting pharmacokinetic parameters in predose samples. First, a targeted method for the determination of plasma concentration levels of rosuvastatin was validated and applied to obtain the pharmacokinetic parameters from 40 enrolled individuals; then, predose samples were analyzed using a metabolomic approach to search for associations between endogenous metabolites and the corresponding pharmacokinetic parameters. Data processing using machine learning revealed some candidates including sterols and bile acids, carboxylated metabolites, and lipids, suggesting the approach herein described as promising for personalized drug therapy.
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Affiliation(s)
| | | | | | | | - Nelson Rogerio Vieira
- Integrated Unit of Pharmacology and Gastroenterology (UNIFAG), São Francisco University-USF, Bragança Paulista, Brazil
| | - Marcia Aparecida Antonio
- Integrated Unit of Pharmacology and Gastroenterology (UNIFAG), São Francisco University-USF, Bragança Paulista, Brazil
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Phapale P. Pharmaco-metabolomics opportunities in drug development and clinical research. ANALYTICAL SCIENCE ADVANCES 2021; 2:611-616. [PMID: 38715865 PMCID: PMC10989535 DOI: 10.1002/ansa.202000178] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 08/15/2021] [Accepted: 08/24/2021] [Indexed: 07/18/2024]
Abstract
Pharmaco-metabolomics uses metabolic phenotypes for the prediction of inter-individual variations in drug response and helps in understanding the mechanisms of drug action. The field has made significant progress over the last 14 years with numerous studies providing clinical evidence for personalised medicine. However, discovered pharmaco-metabolomic biomarkers are not yet translated into clinics due to a lack of large-scale validation. Integration of targeted and untargeted metabolomics workflows into pharmacokinetic analysis and drug development can advance the field from bench to bedside. Also, Indian pharmaceutical research and its bioanalytical infrastructure are in a position to take on these opportunities by addressing challenges such as appropriate training and regulatory compliance.
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Affiliation(s)
- Prasad Phapale
- European Molecular Biology LabMetabolomics Core FacilityHeidelbergGermany
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12
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Feasibility of pharmacometabolomics to identify potential predictors of paclitaxel pharmacokinetic variability. Cancer Chemother Pharmacol 2021; 88:475-483. [PMID: 34089352 DOI: 10.1007/s00280-021-04300-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/18/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE Paclitaxel is a commonly used chemotherapy drug with substantial variability in pharmacokinetics (PK) that affects treatment efficacy and toxicity. Pharmacometabolomic signatures that explain PK variability could be used to individualize dosing to improve therapeutic outcomes. The objective of this study was to identify pretreatment metabolites or metabolomic signatures that explain variability in paclitaxel PK. METHODS This analysis was conducted using data previously collected on a prospective observational study of 48 patients with breast cancer receiving weekly 80 mg/m2 paclitaxel infusions. Paclitaxel plasma concentrations were measured during the first infusion to estimate paclitaxel time above threshold (Tc>0.05) and maximum concentration (Cmax). Metabolites measured in pretreatment whole blood by nuclear magnetic resonance spectrometry were analyzed for an association with Tc>0.05 and Cmax using Pearson correlation followed by stepwise linear regression. RESULTS Pretreatment creatinine, glucose, and lysine concentrations were positively correlated with Tc>0.05, while pretreatment betaine was negatively correlated and lactate was positively correlated with Cmax (all uncorrected p < 0.05). After stepwise elimination, creatinine was associated with Tc>0.05, while betaine and lactate were associated with Cmax (all p < 0.05). CONCLUSION This study identified pretreatment metabolites that may be associated with paclitaxel PK variability demonstrating feasibility of a pharmacometabolomics approach for understanding paclitaxel PK. However, identification of more robust pharmacometabolomic predictors will be required for broad and routine application for the clinical dosing of paclitaxel.
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Fu J, Zhang Y, Liu J, Lian X, Tang J, Zhu F. Pharmacometabonomics: data processing and statistical analysis. Brief Bioinform 2021; 22:6236068. [PMID: 33866355 DOI: 10.1093/bib/bbab138] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 02/09/2021] [Accepted: 03/23/2021] [Indexed: 12/14/2022] Open
Abstract
Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.
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Affiliation(s)
- Jianbo Fu
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Ying Zhang
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Jin Liu
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Xichen Lian
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Jing Tang
- Department of Bioinformatics in Chongqing Medical University, China
| | - Feng Zhu
- College of Pharmaceutical Sciences in Zhejiang University, China
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Saigusa D, Matsukawa N, Hishinuma E, Koshiba S. Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics. Drug Metab Pharmacokinet 2020; 37:100373. [PMID: 33631535 DOI: 10.1016/j.dmpk.2020.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
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Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
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Ntontsi P, Ntzoumanika V, Loukides S, Benaki D, Gkikas E, Mikros E, Bakakos P. EBC metabolomics for asthma severity. J Breath Res 2020; 14:036007. [PMID: 32392552 DOI: 10.1088/1752-7163/ab9220] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Asthma is a heterogeneous disease with diverse severity and represents a considerable socio-economic burden. Exhaled Breath Condensate (EBC) is a biofluid directly obtained from the airway lining fluid non-invasively. We attempted to discriminate severe from mild-to-moderate asthma using EBC metabolomics based on both NMR and UHPLC-MS techniques. 36 patients were included in this study (15 patients with severe and 21 with mild-to-moderate asthma). EBC was collected and analyzed using both NMR and UHPLC-MS techniques for possible metabolites. Using PLS and oPLS analysis for the UHPLC-MS data, no metabolite was found to be sufficient for the discrimination of asthma severity. However, when another PLS-regression model was applied five metabolites were found to discriminate severe from mild-to-moderate asthma. Amino-acid lysine was the only metabolite that discriminated the two study groups using NMR data (p= 0.04, t-test with Welch's correction, AUC 0.66). EBC is an easily available biofluid which directly represents the lower airways but difficult-to-use for metabolomic analysis. Our study presents some encouraging findings for the discrimination of asthma severity subgroups using EBC metabolomics but more well-designed studies with a higher number of patients need to be conducted.
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Affiliation(s)
- P Ntontsi
- 2nd Respiratory Medicine Department, Attikon University Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
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17
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Xing X, Ma P, Huang Q, Qi X, Zou B, Wei J, Tao L, Li L, Zhou G, Song Q. Integration analysis of metabolites and single nucleotide polymorphisms improves the prediction of drug response of celecoxib. Metabolomics 2020; 16:41. [PMID: 32172350 DOI: 10.1007/s11306-020-01659-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 03/05/2020] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Pharmacogenetics and pharmacometabolomics are the common methods for personalized medicine, either genetic or metabolic biomarkers have limited predictive power for drug response. OBJECTIVES In order to better predict drug response, the study attempted to integrate genetic and metabolic biomarkers for drug pharmacokinetics prediction. METHODS The study chose celecoxib as study object, the pharmacokinetic behavior of celecoxib was assessed in 48 healthy volunteers based on UPLC-MS/MS platform, and celecoxib related single nucleotide polymorphisms (SNPs) were also detected. Three mathematic models were constructed for celecoxib pharmacokinetics prediction, the first one was mainly based on celecoxib-related SNPs; the second was based on the metabolites selected from a pharmacometabolomic analysis by using GC-MS/MS method, the last model was based on the combination of the celecoxib-related SNPs and metabolites above. RESULTS The result proved that the last model showed an improved prediction power, the integration model could explain 71.0% AUC variation and predict 62.3% AUC variation. To facilitate clinical application, ten potential celecoxib-related biomarkers were further screened, which could explain 68.3% and predict 54.6% AUC variation, the predicted AUC was well correlated with the measured values (r = 0.838). CONCLUSION This study provides a new route for personalized medicine, the integration of genetic and metabolic biomarkers can predict drug response with a higher accuracy.
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Affiliation(s)
- Xiaoqing Xing
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
- Department of Pharmacy, Hebei General Hospital, Shijiazhuang, 050051, China
| | - Pengcheng Ma
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, 210042, China
| | - Qing Huang
- Jiangsu Institute for Food and Drug Control, Nanjing, 210008, China
| | - Xiemin Qi
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, No. 305, Zhongshan East Road, Nanjing, 210002, China
| | - Bingjie Zou
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, No. 305, Zhongshan East Road, Nanjing, 210002, China
| | - Jun Wei
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, 210042, China
| | - Lei Tao
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, 210042, China
| | - Lingjun Li
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, 210042, China
| | - Guohua Zhou
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing, 210009, China.
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, No. 305, Zhongshan East Road, Nanjing, 210002, China.
| | - Qinxin Song
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing, 210009, China.
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Xing X, Ma P, Huang Q, Qi X, Zou B, Wei J, Tao L, Li L, Zhou G, Song Q. Predicting Pharmacokinetics Variation of Faropenem Using a Pharmacometabonomic Approach. J Proteome Res 2019; 19:119-128. [PMID: 31617722 DOI: 10.1021/acs.jproteome.9b00436] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Xiaoqing Xing
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Pengcheng Ma
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Qing Huang
- Jiangsu Institute for Food and Drug Control, Nanjing 210008, China
| | - Xiemin Qi
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Bingjie Zou
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Jun Wei
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Lei Tao
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Lingjun Li
- Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing 210042, China
| | - Guohua Zhou
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
- Department of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Qinxin Song
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
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Everett JR. Pharmacometabonomics: The Prediction of Drug Effects Using Metabolic Profiling. Handb Exp Pharmacol 2019; 260:263-299. [PMID: 31823071 DOI: 10.1007/164_2019_316] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Metabonomics, also known as metabolomics, is concerned with the study of metabolite profiles in humans, animals, plants and other systems in order to assess their health or other status and their responses to experimental interventions. Metabonomics is thus widely used in disease diagnosis and in understanding responses to therapies such as drug administration. Pharmacometabonomics, also known as pharmacometabolomics, is a related methodology but with a prognostic as opposed to diagnostic thrust. Pharmacometabonomics aims to predict drug effects including efficacy, safety, metabolism and pharmacokinetics, prior to drug administration, via an analysis of pre-dose metabolite profiles. This article will review the development of pharmacometabonomics as a new field of science that has much promise in helping to deliver more effective personalised medicine, a major goal of twenty-first century healthcare.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, University of Greenwich, Kent, UK.
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Balashova EE, Maslov DL, Lokhov PG. A Metabolomics Approach to Pharmacotherapy Personalization. J Pers Med 2018; 8:jpm8030028. [PMID: 30189667 PMCID: PMC6164342 DOI: 10.3390/jpm8030028] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 08/17/2018] [Accepted: 09/03/2018] [Indexed: 12/27/2022] Open
Abstract
The optimization of drug therapy according to the personal characteristics of patients is a perspective direction in modern medicine. One of the possible ways to achieve such personalization is through the application of "omics" technologies, including current, promising metabolomics methods. This review demonstrates that the analysis of pre-dose metabolite biofluid profiles allows clinicians to predict the effectiveness of a selected drug treatment for a given individual. In the review, it is also shown that the monitoring of post-dose metabolite profiles could allow clinicians to evaluate drug efficiency, the reaction of the host to the treatment, and the outcome of the therapy. A comparative description of pharmacotherapy personalization (pharmacogenomics, pharmacoproteomics, and therapeutic drug monitoring) and personalization based on the analysis of metabolite profiles for biofluids (pharmacometabolomics) is also provided.
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Affiliation(s)
- Elena E Balashova
- Institute of Biomedical Chemistry, Pogodinskaya St. 10, Moscow 119121, Russia.
| | - Dmitry L Maslov
- Institute of Biomedical Chemistry, Pogodinskaya St. 10, Moscow 119121, Russia.
| | - Petr G Lokhov
- Institute of Biomedical Chemistry, Pogodinskaya St. 10, Moscow 119121, Russia.
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Bao X, Wu J, Kim S, LoRusso P, Li J. Pharmacometabolomics Reveals Irinotecan Mechanism of Action in Cancer Patients. J Clin Pharmacol 2018; 59:20-34. [PMID: 30052267 DOI: 10.1002/jcph.1275] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 05/31/2018] [Indexed: 12/25/2022]
Abstract
The purpose of this study was to identify early circulating metabolite changes implicated in the mechanism of action of irinotecan, a DNA topoisomerase I inhibitor, in cancer patients. A liquid chromatography-tandem mass spectrometry-based targeted metabolomic platform capable of measuring 254 endogenous metabolites was applied to profile circulating metabolites in plasma samples collected pre- and post-irinotecan treatment from 13 cancer patients. To gain further mechanistic insights, metabolic profiling was also performed for the culture medium of human primary hepatocytes (HepatoCells) and 2 cancer cell lines on exposure to SN-38 (an active metabolite of irinotecan). Intracellular reactive oxygen species (ROS) was detected by dihydroethidium assay. Irinotecan induced a global metabolic change in patient plasma, as represented by elevations of circulating purine/pyrimidine nucleobases, acylcarnitines, and specific amino acid metabolites. The plasma metabolic signature was well replicated in HepatoCells medium on SN-38 exposure, whereas in cancer cell medium SN-38 induced accumulation of pyrimidine/purine nucleosides and nucleobases while having no impact on acylcarnitines and amino acid metabolites. SN-38 induced ROS in HepatoCells, but not in cancer cells. Distinct metabolite signatures of SN-38 exposure in HepatoCells medium and cancer cell medium revealed different mechanisms of drug action on hepatocytes and cancer cells. Elevations in circulating purine/pyrimidine nucleobases may stem from nucleotide degradation following irinotecan-induced DNA double-strand breaks. Accumulations of circulating acylcarnitines and specific amino acid metabolites may reflect, at least in part, irinotecan-induced mitochondrial dysfunction and oxidative stress in the liver. The plasma metabolic signature of irinotecan exposure provides early insights into irinotecan mechanism of action in patients.
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Affiliation(s)
- Xun Bao
- Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA
| | - Jianmei Wu
- Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA
| | - Seongho Kim
- Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA
| | - Patricia LoRusso
- Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA
| | - Jing Li
- Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA
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Martínez-Ávila JC, García Bartolomé A, García I, Dapía I, Tong HY, Díaz L, Guerra P, Frías J, Carcás Sansuan AJ, Borobia AM. Pharmacometabolomics applied to zonisamide pharmacokinetic parameter prediction. Metabolomics 2018; 14:70. [PMID: 30830352 DOI: 10.1007/s11306-018-1365-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 04/25/2018] [Indexed: 10/16/2022]
Abstract
INTRODUCTION Zonisamide is a new-generation anticonvulsant antiepileptic drug metabolized primarily in the liver, with subsequent elimination via the renal route. OBJECTIVES Our objective was to evaluate the utility of pharmacometabolomics in the detection of zonisamide metabolites that could be related to its disposition and therefore, to its efficacy and toxicity. METHODS This study was nested to a bioequivalence clinical trial with 28 healthy volunteers. Each participant received a single dose of zonisamide on two separate occasions (period 1 and period 2), with a washout period between them. Blood samples of zonisamide were obtained from all patients at baseline for each period, before volunteers were administered any medication, for metabolomics analysis. RESULTS After a Lasso regression was applied, age, height, branched-chain amino acids, steroids, triacylglycerols, diacyl glycerophosphoethanolamine, glycerophospholipids susceptible to methylation, phosphatidylcholines with 20:4 FA (arachidonic acid) and cholesterol ester and lysophosphatidylcholine were obtained in both periods. CONCLUSION To our knowledge, this is the only research study to date that has attempted to link basal metabolomic status with pharmacokinetic parameters of zonisamide.
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Affiliation(s)
- J C Martínez-Ávila
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain.
| | - A García Bartolomé
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - I García
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - I Dapía
- Medical and Molecular Genetics Institute (INGEMM), La Paz University Hospital, Rare Diseases Networking Biomedical Research Center (CIBERER), ISCIII, Madrid, Spain
| | - Hoi Y Tong
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - L Díaz
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - P Guerra
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - J Frías
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - A J Carcás Sansuan
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain.
| | - A M Borobia
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
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Kuypers DRJ. “What do we know about tacrolimus pharmacogenetics in transplant recipients?”. Pharmacogenomics 2018; 19:593-597. [DOI: 10.2217/pgs-2018-0035] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
- Dirk RJ Kuypers
- Department of Nephrology & Renal Transplantation, University Hospitals Leuven, Brabant, Belgium
- Department of Microbiology & Immunology, University of Leuven, Brabant, Belgium
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Miolo G, Muraro E, Caruso D, Crivellari D, Ash A, Scalone S, Lombardi D, Rizzolio F, Giordano A, Corona G. Pharmacometabolomics study identifies circulating spermidine and tryptophan as potential biomarkers associated with the complete pathological response to trastuzumab-paclitaxel neoadjuvant therapy in HER-2 positive breast cancer. Oncotarget 2018; 7:39809-39822. [PMID: 27223427 PMCID: PMC5129972 DOI: 10.18632/oncotarget.9489] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 04/28/2016] [Indexed: 01/09/2023] Open
Abstract
Defining biomarkers that predict therapeutic effects and adverse events is a crucial mandate to guide patient selection for personalized cancer treatments. In the present study, we applied a pharmacometabolomics approach to identify biomarkers potentially associated with pathological complete response to trastuzumab-paclitaxel neoadjuvant therapy in HER-2 positive breast cancer patients. Based on histological response the 34 patients enrolled in the study were subdivided into two groups: good responders (n = 15) and poor responders (n = 19). The pre-treatment serum targeted metabolomics profile of all patients were analyzed by liquid chromatography tandem mass spectrometry and the differences in the metabolomics profile between the two groups was investigated by multivariate partial least squares discrimination analysis. The most relevant metabolites that differentiate the two groups of patients were spermidine and tryptophan. The Good responders showed higher levels of spermidine and lower amounts of tryptophan compared with the poor responders (p < 0.001, q < 0.05). The serum level of these two metabolites identified patients who achieved a pathological complete response with a sensitivity of 90% [0.79–1.00] and a specificity of 0.87% [0.67–1.00]. These preliminary results support the role played by the individual patients' metabolism in determining the response to cancer treatments and may be a useful tool to select patients that are more likely to benefit from the trastuzumab-paclitaxel treatment.
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Affiliation(s)
- Gianmaria Miolo
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Elena Muraro
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
| | - Donatella Caruso
- Department of Pharmacological and Bimolecular Science, University of Milan, Milan, Italy
| | - Diana Crivellari
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Anthony Ash
- Department of Biological Chemistry, Norwich Research Park, Norwich, United Kingdom
| | - Simona Scalone
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Davide Lombardi
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Flavio Rizzolio
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
| | - Antonio Giordano
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA, USA
| | - Giuseppe Corona
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
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Everett JR. NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2017; 102-103:1-14. [PMID: 29157489 DOI: 10.1016/j.pnmrs.2017.04.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Revised: 04/23/2017] [Accepted: 04/24/2017] [Indexed: 06/07/2023]
Abstract
Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systems-based approaches in biology and medicine. The experiments are typically done in a diagnostic fashion where changes in metabolite profiles are interpreted as a consequence of an intervention or event; be that a change in diet, the administration of a drug, physical exertion or the onset of a disease. By contrast, pharmacometabonomics takes a prognostic approach to metabolic profiling, in order to predict the effects of drug dosing before it occurs. Differences in pre-dose metabolite profiles between groups of subjects are used to predict post-dose differences in response to drug administration. Thus the paradigm is inverted and pharmacometabonomics is the metabolic equivalent of pharmacogenomics. Although the field is still in its infancy, it is expected that pharmacometabonomics, alongside pharmacogenomics, will assist with the delivery of personalised or precision medicine to patients, which is a critical goal of 21st century healthcare.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Group, University of Greenwich, Chatham Maritime, Kent ME4 4TB, UK.
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27
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Do EY, Gwon MR, Kim BK, Ohk B, Lee HW, Kang WY, Seong SJ, Kim HJ, Yoon YR. Metabolomic analysis of healthy human urine following administration of glimepiride using a liquid chromatography-tandem mass spectrometry. Transl Clin Pharmacol 2017; 25:67-73. [PMID: 32133322 PMCID: PMC7042006 DOI: 10.12793/tcp.2017.25.2.67] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2017] [Revised: 04/11/2017] [Accepted: 04/11/2017] [Indexed: 01/29/2023] Open
Abstract
Glimepiride, a third generation sulfonylurea, is an antihyperglycemic agent widely used to treat type 2 diabetes mellitus. In this study, an untargeted urinary metabolomic analysis was performed to identify endogenous metabolites affected by glimepiride administration. Urine samples of twelve healthy male volunteers were collected before and after administration of 2 mg glimepiride. These samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and then subjected to multivariate data analysis including principal component analysis and orthogonal partial least squares discriminant analysis. Through this metabolomic profiling, we identified several endogenous metabolites such as adenosine 3', 5'-cyclic monophosphate (cAMP), quercetin, tyramine, and urocanic acid, which exhibit significant metabolomic changes between pre- and posturine samples. Among these, cAMP, which is known to be related to insulin secretion, was the most significantly altered metabolite following glimepiride administration. In addition, the pathway analysis showed that purine, tyrosine, and histidine metabolism was affected by pharmacological responses to glimepiride. Together, the results suggest that the pharmacometabolomic approach, based on LC-MS/MS, is useful in understanding the alterations in biochemical pathways associated with glimepiride action.
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Affiliation(s)
- Eun Young Do
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Mi-Ri Gwon
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Bo Kyung Kim
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Boram Ohk
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Hae Won Lee
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Woo Youl Kang
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Sook Jin Seong
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Hyun-Ju Kim
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
| | - Young-Ran Yoon
- Department of Biomedical Science, BK21 Plus KNU Bio-Medical Convergence Program for Creative Talent, Cell and Matrix Research Institute, and Clinical Trial Center, Kyungpook National University Graduate School and Hospital, Daegu 41944, Korea
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28
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Lu Y, Chen C. Metabolomics: Bridging Chemistry and Biology in Drug Discovery and Development. ACTA ACUST UNITED AC 2017. [DOI: 10.1007/s40495-017-0083-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Maslov D, Balashova E, Lokhov P, Archakov A. Pharmacometabonomics – the novel way to personalized drug therapy. ACTA ACUST UNITED AC 2017; 63:115-123. [DOI: 10.18097/pbmc20176302115] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The review is devoted to pharmacometabonomics - a new branch of science focused on personalization of drug therapy through the comprehensive analysis of metabolites of patient's biological fluids. It considers the history of pharmacometabonomic, positioning to other “-omic” sciences, and system approach, realized by this science, in determination of individual therapeutic dose of the drugs and also a technical implementation of pharmacometabonomic based on direct mass spectrometry of blood plasma metabolites. Special attention is paid to a comparative analysis of pharmacometabonomics and other main approaches to personalized therapy in the clinic, such as pharmacogenetics and therapeutic drug monitoring. Finally, prospects of pharmacometabonomics applications in clinical practice were also discussed.
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Affiliation(s)
- D.L. Maslov
- Institute of Biomedical Chemistry, Moscow, Russia
| | | | - P.G. Lokhov
- Institute of Biomedical Chemistry, Moscow, Russia
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30
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Bekri S. The role of metabolomics in precision medicine. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2016. [DOI: 10.1080/23808993.2016.1273067] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, Rouen 76000, France
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, INSERM U1245, Rouen 76000, France
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31
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Kantae V, Krekels EHJ, Esdonk MJV, Lindenburg P, Harms AC, Knibbe CAJ, Van der Graaf PH, Hankemeier T. Integration of pharmacometabolomics with pharmacokinetics and pharmacodynamics: towards personalized drug therapy. Metabolomics 2016; 13:9. [PMID: 28058041 PMCID: PMC5165030 DOI: 10.1007/s11306-016-1143-1] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Accepted: 11/26/2016] [Indexed: 02/05/2023]
Abstract
Personalized medicine, in modern drug therapy, aims at a tailored drug treatment accounting for inter-individual variations in drug pharmacology to treat individuals effectively and safely. The inter-individual variability in drug response upon drug administration is caused by the interplay between drug pharmacology and the patients' (patho)physiological status. Individual variations in (patho)physiological status may result from genetic polymorphisms, environmental factors (including current/past treatments), demographic characteristics, and disease related factors. Identification and quantification of predictors of inter-individual variability in drug pharmacology is necessary to achieve personalized medicine. Here, we highlight the potential of pharmacometabolomics in prospectively informing on the inter-individual differences in drug pharmacology, including both pharmacokinetic (PK) and pharmacodynamic (PD) processes, and thereby guiding drug selection and drug dosing. This review focusses on the pharmacometabolomics studies that have additional value on top of the conventional covariates in predicting drug PK. Additionally, employing pharmacometabolomics to predict drug PD is highlighted, and we suggest not only considering the endogenous metabolites as static variables but to include also drug dose and temporal changes in drug concentration in these studies. Although there are many endogenous metabolite biomarkers identified to predict PK and more often to predict PD, validation of these biomarkers in terms of specificity, sensitivity, reproducibility and clinical relevance is highly important. Furthermore, the application of these identified biomarkers in routine clinical practice deserves notable attention to truly personalize drug treatment in the near future.
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Affiliation(s)
- Vasudev Kantae
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Elke H. J. Krekels
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Michiel J. Van Esdonk
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Peter Lindenburg
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Amy C. Harms
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Catherijne A. J. Knibbe
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Piet H. Van der Graaf
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Certara QSP, Canterbury Innovation Centre, Canterbury, UK
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
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Sun H, Luo G, Xiang Z, Cai X, Chen D. Pharmacokinetics and pharmacodynamics study of rhein treating renal fibrosis based on metabonomics approach. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2016; 23:1661-1670. [PMID: 27823631 DOI: 10.1016/j.phymed.2016.10.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2016] [Revised: 06/19/2016] [Accepted: 10/03/2016] [Indexed: 06/06/2023]
Abstract
BACKGROUND The selection of effect indicators in the pharmacokinetic/ pharmacodynamic study of complex diseases to describe the relationship between plasma concentration and effect indicators is difficult. PURPOSE Three effect indicators of renal fibrosis were successfully determined. The relationship between pharmacokinetics and pharmacodynamics of rhein in rhubarb was elucidated. STUDY DESIGN The study was a metabolomics analysis of rat plasma and pharmacokinetics/ pharmacodynamics of rhein. METHODS A sensitive and simple ultra performance liquid chromatography-tandem triple quadrupole mass spectrometry (UPLC-MS/MS) method was applied to determine the rhein plasma concentration in the rat model of renal fibrosis and rat sham-operated group after the administration of rhubarb decoction. Then, the ultra performance liquid chromatography-Micromass quadrupole-time of flight mass spectrometry (UPLC-QTOF/MS) metabolomics method was used to screen biomarkers of renal fibrosis in rat plasma. Furthermore, the relationship between the plasma concentration of rhein and the concentration of three biomarkers directly related to renal fibrosis were analyzed. RESULTS The three screened biomarkers could represent the effect of rhein treatment on renal fibrosis. Increasing the plasma concentration of rhein tended to restore the concentration of the three biomarkers in the model group compared with that in the sham-operated group. Evident differences in the area under the plasma concentration-time curve (AUC) of rhein were also observed under different pathological states. The results provide valuable information for the clinical application of rhubarb. CONCLUSION Rhein intervention could recover the physiological balance in living organisms from the pharmacokinetic/pharmacodynamic levels. New information on the pharmacokinetic/pharmacodynamic study of complex diseases is provided.
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Affiliation(s)
- Hao Sun
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Guangwen Luo
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Zheng Xiang
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
| | - Xiaojun Cai
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Dahui Chen
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
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34
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Everett JR. From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine. Front Pharmacol 2016; 7:297. [PMID: 27660611 PMCID: PMC5014868 DOI: 10.3389/fphar.2016.00297] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Accepted: 08/23/2016] [Indexed: 01/08/2023] Open
Abstract
Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, University of Greenwich Kent, UK
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35
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Navarro SL, Randolph TW, Shireman LM, Raftery D, McCune JS. Pharmacometabonomic Prediction of Busulfan Clearance in Hematopoetic Cell Transplant Recipients. J Proteome Res 2016; 15:2802-11. [PMID: 27350098 DOI: 10.1021/acs.jproteome.6b00370] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Intravenous (IV) busulfan doses are often personalized to a concentration at steady state (Css) using the patient's clearance, which is estimated with therapeutic drug monitoring. We sought to identify biomarkers of IV busulfan clearance using a targeted pharmacometabonomics approach. A total of 200 metabolites were quantitated in 106 plasma samples, each obtained before IV busulfan administration in hematopoietic cell transplant (HCT) recipients. Both univariate linear regression with false discovery rate (FDR) and pathway enrichment analyses using the Global test were performed. In the univariate analysis, glycine, N-acetylglycine, 2-hydroxyisovaleric acid, creatine, serine, and tyrosine were statistically significantly associated with IV busulfan clearance at P < 0.05, with the first three satisfying the FDR of q < 0.1. Using pathway enrichment analysis, the glycine, serine, and threonine metabolism pathway was statistically significantly associated with IV busulfan clearance at P < 0.05 and q < 0.1, and a pathway impact >0.1. Glycine is a component of glutathione, which is conjugated with busulfan via glutathione transferase enzymes. These results demonstrate the potential utility of pharmacometabonomics to inform IV busulfan dosing. Future studies are required to validate these findings.
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Affiliation(s)
- Sandi L Navarro
- Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington 98109, United States.,University of Washington , Seattle, Washington 98195, United States
| | - Timothy W Randolph
- Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington 98109, United States
| | - Laura M Shireman
- University of Washington , Seattle, Washington 98195, United States
| | - Daniel Raftery
- Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington 98109, United States.,University of Washington , Seattle, Washington 98195, United States
| | - Jeannine S McCune
- Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington 98109, United States.,University of Washington , Seattle, Washington 98195, United States
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36
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Burt T, Nandal S. Pharmacometabolomics in Early-Phase Clinical Development. Clin Transl Sci 2016; 9:128-38. [PMID: 27127917 PMCID: PMC5351331 DOI: 10.1111/cts.12396] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Accepted: 04/01/2016] [Indexed: 12/28/2022] Open
Affiliation(s)
- T Burt
- Burt Consultancy, Durham, North Carolina, USA
| | - S Nandal
- Department of Medical Oncology Novartis (Singapore) Pte Ltd, Singapore
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37
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Pharmacokinetic variations in cancer patients with liver dysfunction: applications and challenges of pharmacometabolomics. Cancer Chemother Pharmacol 2016; 78:465-89. [DOI: 10.1007/s00280-016-3028-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2016] [Accepted: 03/30/2016] [Indexed: 12/24/2022]
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38
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Davies SK, Bundy JG, Leroi AM. Metabolic Youth in Middle Age: Predicting Aging in Caenorhabditis elegans Using Metabolomics. J Proteome Res 2015; 14:4603-9. [PMID: 26381038 DOI: 10.1021/acs.jproteome.5b00442] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Many mutations and allelic variants are known that influence the rate at which animals age, but when in life do such variants diverge from normal patterns of aging? Is this divergence visible in their physiologies? To investigate these questions, we have used (1)H NMR spectroscopy to study how the metabolome of the nematode Caenorhabditis elegans changes as it grows older. We identify a series of metabolic changes that, collectively, predict the age of wild-type worms. We then show that long-lived mutant daf-2(m41) worms are metabolically youthful compared to wild-type worms, but that this relative youth only appears in middle age. Finally, we show that metabolic age predicts the timing and magnitude of differences in age-specific mortality between these strains. Thus, the future mortality of these two genotypes can be predicted long before most of the worms die.
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Affiliation(s)
- Sarah K Davies
- Department of Life Sciences and ‡Department of Surgery and Cancer, Imperial College London , Sir Alexander Fleming Building, London SW7 2AZ, U.K
| | - Jacob G Bundy
- Department of Life Sciences and ‡Department of Surgery and Cancer, Imperial College London , Sir Alexander Fleming Building, London SW7 2AZ, U.K
| | - Armand M Leroi
- Department of Life Sciences and ‡Department of Surgery and Cancer, Imperial College London , Sir Alexander Fleming Building, London SW7 2AZ, U.K
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Sikma MA, van Maarseveen EM, van de Graaf EA, Kirkels JH, Verhaar MC, Donker DW, Kesecioglu J, Meulenbelt J. Pharmacokinetics and Toxicity of Tacrolimus Early After Heart and Lung Transplantation. Am J Transplant 2015; 15:2301-13. [PMID: 26053114 DOI: 10.1111/ajt.13309] [Citation(s) in RCA: 119] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 02/16/2015] [Accepted: 03/08/2015] [Indexed: 01/25/2023]
Abstract
Annually, about 8000 heart and lung transplantations are successfully performed worldwide. However, morbidity and mortality still pose a major concern. Renal failure in heart and lung transplant recipients is an essential adverse cause of morbidity and mortality, often originating in the early postoperative phase. At this time of clinical instability, the kidneys are exposed to numerous nephrotoxic stimuli. Among these, tacrolimus toxicity plays an important role, and its pharmacokinetics may be significantly altered in this critical phase by fluctuating drug absorption, changed protein metabolism, anemia and (multi-) organ failure. Limited understanding of tacrolimus pharmacokinetics in these circumstances is hampering daily practice. Tacrolimus dose adjustments are generally based on whole blood trough levels, which widely vary early after transplantation. Moreover, whole blood trough levels are difficult to predict and are poorly related to the area under the concentration-time curve. Even within the therapeutic range, toxicity may occur. These shortcomings of tacrolimus monitoring may not hold for the unbound tacrolimus plasma concentrations, which may better reflect tacrolimus toxicity. This review focuses on posttransplant tacrolimus pharmacokinetics, discusses relevant factors influencing the unbound tacrolimus concentrations and tacrolimus (nephro-) toxicity in heart and lung transplantation patients.
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Affiliation(s)
- M A Sikma
- Department of Intensive Care Medicine and National Poisons Information Center, University Medical Center of Utrecht, the Netherlands
| | - E M van Maarseveen
- Department of Clinical Pharmacy, University Medical Center of Utrecht, the Netherlands
| | - E A van de Graaf
- Department of Lung Transplantation, University Medical Center of Utrecht, the Netherlands
| | - J H Kirkels
- Department of Heart Transplantation, University Medical Center of Utrecht, the Netherlands
| | - M C Verhaar
- Department of Nephrology and Hypertension, University Medical Center of Utrecht, the Netherlands
| | - D W Donker
- Department of Intensive Care Medicine, University Medical Center of Utrecht, the Netherlands
| | - J Kesecioglu
- Department of Intensive Care Medicine, University Medical Center of Utrecht, the Netherlands
| | - J Meulenbelt
- Department of Intensive Care Medicine, National Poisons Information Center, Institute for Risk Assessment Sciences, University of Utrecht, the Netherlands
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Huang Q, Aa J, Jia H, Xin X, Tao C, Liu L, Zou B, Song Q, Shi J, Cao B, Yong Y, Wang G, Zhou G. A Pharmacometabonomic Approach To Predicting Metabolic Phenotypes and Pharmacokinetic Parameters of Atorvastatin in Healthy Volunteers. J Proteome Res 2015. [PMID: 26216528 DOI: 10.1021/acs.jproteome.5b00440] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Qing Huang
- China Pharmaceutical
University, Nanjing 210009, China
- Jiangsu Institute
for Food and Drug Control, Nanjing 210008, China
| | - Jiye Aa
- China Pharmaceutical
University, Nanjing 210009, China
| | - Huning Jia
- China Pharmaceutical
University, Nanjing 210009, China
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Xiaoqing Xin
- China Pharmaceutical
University, Nanjing 210009, China
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Chunlei Tao
- Anhui University
of Chinese Medicine, Hefei 230038, China
| | - Linsheng Liu
- Clinical
Pharmacology Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou 215006, China
| | - Bingjie Zou
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Qinxin Song
- China Pharmaceutical
University, Nanjing 210009, China
| | - Jian Shi
- China Pharmaceutical
University, Nanjing 210009, China
| | - Bei Cao
- China Pharmaceutical
University, Nanjing 210009, China
| | - Yonghong Yong
- The First Affiliated
Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Guangji Wang
- China Pharmaceutical
University, Nanjing 210009, China
| | - Guohua Zhou
- Department
of Pharmacology, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
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41
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Everett JR. Pharmacometabonomics in humans: a new tool for personalized medicine. Pharmacogenomics 2015; 16:737-54. [PMID: 25929853 DOI: 10.2217/pgs.15.20] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Pharmacogenomics is now over 50 years old and has had some impact in clinical practice, through its use to select patient subgroups who will enjoy efficacy without side effects when treated with certain drugs. However, pharmacogenomics, has had less impact than initially predicted. One reason for this is that many diseases, and the way in which the patients respond to drug treatments, have both genetic and environmental elements. Pure genomics is almost blind to the environmental elements. A new methodology has emerged, termed pharmacometabonomics that is concerned with the prediction of drug effects through the analysis of predose, biofluid metabolite profiles, which reflect both genetic and environmental influences on human physiology. In this review we will cover what pharmacometabonomics is, how it works, what applications exist and what the future might hold in this exciting new area.
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42
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Xiao WJ, Ma T, Ge C, Xia WJ, Mao Y, Sun RB, Yu XY, Aa JY, Wang GJ. Modulation of the pentose phosphate pathway alters phase I metabolism of testosterone and dextromethorphan in HepG2 cells. Acta Pharmacol Sin 2015; 36:259-67. [PMID: 25619394 DOI: 10.1038/aps.2014.137] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 10/21/2014] [Indexed: 12/23/2022] Open
Abstract
AIM The pentose phosphate pathway (PPP) is involved in the activity of glucose-6-phosphate dehydrogenase (G6PD) and generation of NADPH, which plays a key role in drug metabolism. The aim of this study was to investigate the effects of modulation of the PPP on drug metabolism capacity in vitro. METHODS A pair of hepatic cell lines, ie, the cancerous HepG2 cells and normal L02 cells, was used. The expression of CYP450 enzymes, p53 and G6PD in the cells were analyzed. The metabolism of testosterone (TEST, 10 μmol/L) and dextromethorphan (DEM, 1 μmol/L), the two typical substrates for CYP3A4 and CYP2D6, in the cells was examined in the presence of different agents. RESULTS Both the expression and metabolic activities of CYP3A4 and CYP2D6 were considerably higher in HepG2 cells than in L02 cells. The metabolism of TEST and DEM in HepG2 cells was dose-dependently inhibited by the specific CYP3A4 inhibitor ketoconazole and CYP2D6 inhibitor quinidine. Addition of the p53 inhibitor cyclic PFT-α (5, 25 μmol/L) in HepG2 cells dose-dependently enhanced the metabolism of DEM and TEST, whereas addition of the p53 activator NSC 66811 (3, 10, 25 μmol/L) dose-dependently inhibited the metabolism. Furthermore, addition of the G6PD inhibitor 6-aminonicotinamide (5, 15 μmol/L) in HepG2 cells dose-dependently inhibited the metabolism of DEM and TEST, whereas addition of the PPP activity stimulator menadione (1, 5, 15 μmol/L) dose-dependently enhanced the metabolism. CONCLUSION Modulation of p53 and the PPP alters the metabolism of DEM and TEST, suggesting that the metabolic flux pattern of PPP may be closely involved in drug metabolism and the individual variance.
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Jadhav S, Phapale P, Thulasiram HV, Bhargava S. Polyketide synthesis in tobacco plants transformed with a Plumbago zeylanica type III hexaketide synthase. PHYTOCHEMISTRY 2014; 98:92-100. [PMID: 24355695 DOI: 10.1016/j.phytochem.2013.11.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2013] [Revised: 11/21/2013] [Accepted: 11/22/2013] [Indexed: 06/03/2023]
Abstract
A type III polyketide synthase from Plumbago zeylanica (PzPKS) was cloned and expressed in tobacco plants to study whether the transgenic tobacco plants expressing PzPKS synthesize the pharmacologically important polyketide, plumbagin. High resolution mass spectrometry based metabolite profiling of two transgenic events and wild type tobacco plants was carried out to investigate changes in polyketides, including plumbagin. Ten polyketides, which included six pyrones and four naphthalene derivatives, were identified in PzPKS transgenic plants. While one pyrone, styryl-2-pyranone, was detected in both, wild type and transgenic tobacco plants, three pyrones were expressed only in the leaves of transgenic tobacco plants. The transgenic tobacco plants did not accumulate plumbagin, but showed accumulation of isoshinanolone in the roots, which is postulated to be the reduction product of plumbagin. In addition, leaves of transgenic tobacco plants accumulated 3-methyl-1,8-naphthalenediol, a postulated precursor of plumbagin. The results indicated the requirement of additional Plumbago-specific components in the biosynthetic pathway of this polyketide.
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Affiliation(s)
- Supriya Jadhav
- Botany Department, University of Pune, Pune 411007, India.
| | - Prasad Phapale
- Chemical Biology Unit, Division of Organic Chemistry, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India.
| | - Hirekodathakallu V Thulasiram
- Chemical Biology Unit, Division of Organic Chemistry, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India.
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Kim HJ, Yoon YR. Pharmacometabolomics: Current Applications and Future Perspectives. Transl Clin Pharmacol 2014. [DOI: 10.12793/tcp.2014.22.1.8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Hyun-Ju Kim
- Department of Molecular Medicine, Cell and Matrix Research Institute, School of Medicine, Kyungpook National University, Daegu 700-422, Korea and Clinical Trial Center, Kyungpook National University Hospital, Daegu 700-721, Korea
| | - Young-Ran Yoon
- Department of Molecular Medicine, Cell and Matrix Research Institute, School of Medicine, Kyungpook National University, Daegu 700-422, Korea and Clinical Trial Center, Kyungpook National University Hospital, Daegu 700-721, Korea
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Kaddurah-Daouk R, Weinshilboum RM. Pharmacometabolomics: Implications for Clinical Pharmacology and Systems Pharmacology. Clin Pharmacol Ther 2013; 95:154-67. [DOI: 10.1038/clpt.2013.217] [Citation(s) in RCA: 146] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2013] [Accepted: 10/28/2013] [Indexed: 12/24/2022]
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Abstract
BACKGROUND Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics. METHODS A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmaco-metabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013. RESULTS Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals. CONCLUSIONS Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, School of Science, University of Greenwich, Chatham Maritime, UK
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Shin KH, Choi MH, Lim KS, Yu KS, Jang IJ, Cho JY. Evaluation of Endogenous Metabolic Markers of Hepatic CYP3A Activity Using Metabolic Profiling and Midazolam Clearance. Clin Pharmacol Ther 2013; 94:601-9. [DOI: 10.1038/clpt.2013.128] [Citation(s) in RCA: 87] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Accepted: 06/10/2013] [Indexed: 11/09/2022]
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Knops N, Levtchenko E, van den Heuvel B, Kuypers D. From gut to kidney: transporting and metabolizing calcineurin-inhibitors in solid organ transplantation. Int J Pharm 2013; 452:14-35. [PMID: 23711732 DOI: 10.1016/j.ijpharm.2013.05.033] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2013] [Revised: 05/08/2013] [Accepted: 05/10/2013] [Indexed: 12/14/2022]
Abstract
Since their introduction circa 35 years ago, calcineurin-inhibitors (CNI) have become the cornerstone of immunosuppressive therapy in solid organ transplantation. However, CNI's possess a narrow therapeutic index with potential severe consequences of drug under- or overexposure. This demands a meticulous policy of Therapeutic Drug Monitoring (TDM) to optimize outcome. In clinical practice optimal dosing is difficult to achieve due to important inter- and intraindividual variation in CNI pharmacokinetics. A complex and often interdependent set of factors appears relevant in determining drug exposure. These include recipient characteristics such as age, race, body composition, organ function, and food intake, but also graft-related characteristics such as: size, donor-age, and time after transplantation can be important. Fundamental (in vitro) and clinical studies have pointed out the intrinsic relation between the aforementioned variables and the functional capacity of enzymes and transporters involved in CNI metabolism, primarily located in intestine, liver and kidney. Commonly occurring polymorphisms in genes responsible for CNI metabolism (CYP3A4, CYP3A5, CYP3A7, PXR, POR, ABCB1 (P-gp) and possibly UGT) are able to explain an important part of interindividual variability. In particular, a highly prevalent SNP in CYP3A5 has proven to be an important determinant of CNI dose requirements and drug-dose-interactions. In addition, a discrepancy in genotype between graft and receptor has to be taken into account. Furthermore, common phenomena in solid organ transplantation such as inflammation, ischemia- reperfusion injury, graft function, co-medication, altered food intake and intestinal motility can have a differential effect on the expression enzymes and transporters involved in CNI metabolism. Notwithstanding the built-up knowledge, predicting individual CNI pharmacokinetics and dose requirements on the basis of current clinical and experimental data remains a challenge.
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Affiliation(s)
- Noël Knops
- Department of Pediatric Nephrology and Solid Organ Transplantation, University Hospitals Leuven, Belgium.
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Park J, Noh K, Lee HW, Lim MS, Seong SJ, Seo JJ, Kim EJ, Kang W, Yoon YR. Pharmacometabolomic approach to predict QT prolongation in guinea pigs. PLoS One 2013; 8:e60556. [PMID: 23593245 PMCID: PMC3617128 DOI: 10.1371/journal.pone.0060556] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2012] [Accepted: 02/26/2013] [Indexed: 12/25/2022] Open
Abstract
Drug-induced torsades de pointes (TdP), a life-threatening arrhythmia associated with prolongation of the QT interval, has been a significant reason for withdrawal of several medicines from the market. Prolongation of the QT interval is considered as the best biomarker for predicting the torsadogenic risk of a new chemical entity. Because of the difficulty assessing the risk for TdP during drug development, we evaluated the metabolic phenotype for predicting QT prolongation induced by sparfloxacin, and elucidated the metabolic pathway related to the QT prolongation. We performed electrocardiography analysis and liquid chromatography-mass spectroscopy-based metabolic profiling of plasma samples obtained from 15 guinea pigs after administration of sparfloxacin at doses of 33.3, 100, and 300 mg/kg. Principal component analysis and partial least squares modelling were conducted to select the metabolites that substantially contributed to the prediction of QT prolongation. QTc increased significantly with increasing dose (r = 0.93). From the PLS analysis, the key metabolites that showed the highest variable importance in the projection values (>1.5) were selected, identified, and used to determine the metabolic network. In particular, cytidine-5'-diphosphate (CDP), deoxycorticosterone, L-aspartic acid and stearic acid were found to be final metabolomic phenotypes for the prediction of QT prolongation. Metabolomic phenotypes for predicting drug-induced QT prolongation of sparfloxacin were developed and can be applied to cardiac toxicity screening of other drugs. In addition, this integrative pharmacometabolomic approach would serve as a good tool for predicting pharmacodynamic or toxicological effects caused by changes in dose.
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Affiliation(s)
- Jeonghyeon Park
- Department of Molecular Medicine, Kyungpook National University School of Medicine and BK21 program, Kyungpook National University School of Medicine, Daegu, South Korea
- Clinical Trial Center, Kyungpook National University Hospital, Daegu, South Korea
| | - Keumhan Noh
- College of Pharmacy, Yeungnam University, Kyoungbuk, South Korea
| | - Hae Won Lee
- Clinical Trial Center, Kyungpook National University Hospital, Daegu, South Korea
| | - Mi-sun Lim
- Clinical Trial Center, Kyungpook National University Hospital, Daegu, South Korea
| | - Sook Jin Seong
- Department of Molecular Medicine, Kyungpook National University School of Medicine and BK21 program, Kyungpook National University School of Medicine, Daegu, South Korea
- Clinical Trial Center, Kyungpook National University Hospital, Daegu, South Korea
| | - Jeong Ju Seo
- Department of Molecular Medicine, Kyungpook National University School of Medicine and BK21 program, Kyungpook National University School of Medicine, Daegu, South Korea
- Clinical Trial Center, Kyungpook National University Hospital, Daegu, South Korea
| | - Eun-Jung Kim
- National Institute of Food and Drug Safety Evaluation, Korea Food and Drug Administration, Chungbuk, South Korea
| | - Wonku Kang
- College of Pharmacy, Yeungnam University, Kyoungbuk, South Korea
| | - Young-Ran Yoon
- Department of Molecular Medicine, Kyungpook National University School of Medicine and BK21 program, Kyungpook National University School of Medicine, Daegu, South Korea
- Clinical Trial Center, Kyungpook National University Hospital, Daegu, South Korea
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Sun J, Beger RD, Schnackenberg LK. Metabolomics as a tool for personalizing medicine: 2012 update. Per Med 2013; 10:149-161. [DOI: 10.2217/pme.13.8] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Numerous factors in conjunction with an individual’s genetic make up will determine predisposition to disease, adverse or beneficial effects of drug treatment or therapy, and disease progression. A major limitation of current clinical measures is that the disease phenotype, which is comprised of the genotype and other environmental factors, is underestimated. Rather, each disease is treated similarly even though the disease process is highly complex. Methods that evaluate the interaction of genotype and environmental factors would likely be a better indicator of patients’ response to medical treatments. The omics technologies, specifically metabolomics, will play a major role in the movement towards personalized medicine. Metabolomics is phenotype driven and should provide better clinical biomarkers. Furthermore, recent studies have shown that associations between genetic variants and downstream metabolite changes can provide a unique description of an individual’s genotype and phenotype, which will further enhance the movement towards personalized medicine.
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Affiliation(s)
- Jinchun Sun
- Division of Systems Biology, National Center for Toxicological Research, US FDA, 3900 NCTR Road, Jefferson, AR 72079, USA
| | - Richard D Beger
- Division of Systems Biology, National Center for Toxicological Research, US FDA, 3900 NCTR Road, Jefferson, AR 72079, USA
| | - Laura K Schnackenberg
- Division of Systems Biology, National Center for Toxicological Research, US FDA, 3900 NCTR Road, Jefferson, AR 72079, USA
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