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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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Sha’aban A, Zainal H, Khalil NA, Abd Aziz F, Ch’ng ES, Teh CH, Mohammed M, Ibrahim B. Prediction of Low-Dose Aspirin-Induced Gastric Toxicity Using Nuclear Magnetic Resonance Spectroscopy-Based Pharmacometabolomics in Rats. Molecules 2022; 27:2126. [PMID: 35408523 PMCID: PMC9000689 DOI: 10.3390/molecules27072126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 03/21/2022] [Accepted: 03/22/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Low-dose aspirin (LDA) is the backbone for secondary prevention of coronary artery disease, although limited by gastric toxicity. This study aimed to identify novel metabolites that could predict LDA-induced gastric toxicity using pharmacometabolomics. METHODS Pre-dosed urine samples were collected from male Sprague-Dawley rats. The rats were treated with either LDA (10 mg/kg) or 1% methylcellulose (10 mL/kg) per oral for 28 days. The rats' stomachs were examined for gastric toxicity using a stereomicroscope. The urine samples were analyzed using a proton nuclear magnetic resonance spectroscopy. Metabolites were systematically identified by exploring established databases and multivariate analyses to determine the spectral pattern of metabolites related to LDA-induced gastric toxicity. RESULTS Treatment with LDA resulted in gastric toxicity in 20/32 rats (62.5%). The orthogonal projections to latent structures discriminant analysis (OPLS-DA) model displayed a goodness-of-fit (R2Y) value of 0.947, suggesting near-perfect reproducibility and a goodness-of-prediction (Q2Y) of -0.185 with perfect sensitivity, specificity and accuracy (100%). Furthermore, the area under the receiver operating characteristic (AUROC) displayed was 1. The final OPLS-DA model had an R2Y value of 0.726 and Q2Y of 0.142 with sensitivity (100%), specificity (95.0%) and accuracy (96.9%). Citrate, hippurate, methylamine, trimethylamine N-oxide and alpha-keto-glutarate were identified as the possible metabolites implicated in the LDA-induced gastric toxicity. CONCLUSION The study identified metabolic signatures that correlated with the development of a low-dose Aspirin-induced gastric toxicity in rats. This pharmacometabolomic approach could further be validated to predict LDA-induced gastric toxicity in patients with coronary artery disease.
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Affiliation(s)
- Abubakar Sha’aban
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia; (F.A.A.); (M.M.)
- Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical Sciences, Ahmadu Bello University, Zaria 810107, Nigeria
| | - Hadzliana Zainal
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia; (F.A.A.); (M.M.)
| | - Nor Azlina Khalil
- Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang 13200, Malaysia; (N.A.K.); (E.S.C.)
| | - Fatimatuzzahra’ Abd Aziz
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia; (F.A.A.); (M.M.)
| | - Ewe Seng Ch’ng
- Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang 13200, Malaysia; (N.A.K.); (E.S.C.)
- School of Medical and Life Sciences, Sunway University, Bandar Sunway 47500, Malaysia
| | - Chin-Hoe Teh
- Bruker (Malaysia) Sdn Bhd, Bayan Lepas 11900, Malaysia;
| | - Mustapha Mohammed
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia; (F.A.A.); (M.M.)
- Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical Sciences, Ahmadu Bello University, Zaria 810107, Nigeria
| | - Baharudin Ibrahim
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia; (F.A.A.); (M.M.)
- Faculty of Pharmacy, Universiti Malaya, Kuala Lumpur 50603, Malaysia
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Hiraishi K, Jimma F, Soma H, Kagawa T, Yamaoka I. Investigating a novel hepatoprotective substance from ume extract (heated Japanese apricot juice concentrate). Part 1: Finding an active substance using a liver injury rat model. NFS JOURNAL 2022. [DOI: 10.1016/j.nfs.2021.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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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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Ma J, Wu C, Hart GW. Analytical and Biochemical Perspectives of Protein O-GlcNAcylation. Chem Rev 2021; 121:1513-1581. [DOI: 10.1021/acs.chemrev.0c00884] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Junfeng Ma
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Georgetown University, Washington D.C. 20057, United States
| | - Ci Wu
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Georgetown University, Washington D.C. 20057, United States
| | - Gerald W. Hart
- Department of Biochemistry and Molecular Biology, Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia 30602, United States
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Czekaj P, Król M, Limanówka Ł, Michalik M, Lorek K, Gramignoli R. Assessment of animal experimental models of toxic liver injury in the context of their potential application as preclinical models for cell therapy. Eur J Pharmacol 2019; 861:172597. [PMID: 31408648 DOI: 10.1016/j.ejphar.2019.172597] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 08/04/2019] [Accepted: 08/08/2019] [Indexed: 02/06/2023]
Abstract
Preclinical animal models allow to study development and progression of several diseases, including liver disorders. These studies, for ethical reasons and medical limits, are impossible to carry out in human patients. At the same time, such experimental models constitute an important source of knowledge on pathomechanisms for drug- and virus-induced hepatotoxicity, both acute and chronic. Carbon tetrachloride, D-Galactosamine, and retrorsine are xenobiotics that can be used in immunocompetent animal models of hepatotoxicity, where chemical-intoxicated livers present histological features representative of human viruses-related infection. A prolonged derangement into liver architecture and functions commonly lead to cirrhosis, eventually resulting in hepatocellular carcinoma. In human, orthotopic liver transplantation commonly resolve most the problems related to cirrhosis. However, the shortage of donors does not allow all the patients in the waiting list to receive an organ on time. A promising alternative treatment for acute and chronic liver disease has been advised in liver cell transplantation, but the limited availability of hepatocytes for clinical approaches, in addition to the immunosuppressant regiment required to sustain cellular long-term engraftment have been encouraging the use of alternative cell sources. A recent effective source of stem cells have been recently identified in the human amnion membrane. Human amnion epithelial cells (hAEC) have been preclinically tested and proven sufficient to rescue immunocompetent rodents lethally intoxicated with drugs. The adoption of therapeutic procedures based on hAEC transplant in immunocompetent recipients affected by liver diseases, as well as patients with immune-related disorders, may constitute a successful new alternative therapy in regenerative medicine.
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Affiliation(s)
- Piotr Czekaj
- Department of Cytophysiology, Chair of Histology and Embryology, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland, Medyków 18 str., 40-752, Katowice, Poland.
| | - Mateusz Król
- Students Scientific Society, Department of Cytophysiology, Chair of Histology and Embryology, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland, Medyków 18 str., 40-752, Katowice, Poland.
| | - Łukasz Limanówka
- Students Scientific Society, Department of Cytophysiology, Chair of Histology and Embryology, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland, Medyków 18 str., 40-752, Katowice, Poland
| | - Marcin Michalik
- Students Scientific Society, Department of Cytophysiology, Chair of Histology and Embryology, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland, Medyków 18 str., 40-752, Katowice, Poland
| | - Katarzyna Lorek
- Students Scientific Society, Department of Cytophysiology, Chair of Histology and Embryology, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland, Medyków 18 str., 40-752, Katowice, Poland
| | - Roberto Gramignoli
- Department of Laboratory Medicine (LABMED), H5, Division of Pathology, Karolinska Institutet, Alfred Nobels Allé 8, 14152, Huddinge, Sweden.
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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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Gao Y, Li W, Chen J, Wang X, Lv Y, Huang Y, Zhang Z, Xu F. Pharmacometabolomic prediction of individual differences of gastrointestinal toxicity complicating myelosuppression in rats induced by irinotecan. Acta Pharm Sin B 2019; 9:157-166. [PMID: 30766787 PMCID: PMC6362258 DOI: 10.1016/j.apsb.2018.09.006] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 08/21/2018] [Accepted: 08/30/2018] [Indexed: 12/13/2022] Open
Abstract
Pharmacometabolomics has been already successfully used in toxicity prediction for one specific adverse effect. However in clinical practice, two or more different toxicities are always accompanied with each other, which puts forward new challenges for pharmacometabolomics. Gastrointestinal toxicity and myelosuppression are two major adverse effects induced by Irinotecan (CPT-11), and often show large individual differences. In the current study, a pharmacometabolomic study was performed to screen the exclusive biomarkers in predose serums which could predict late-onset diarrhea and myelosuppression of CPT-11 simultaneously. The severity and sensitivity differences in gastrointestinal toxicity and myelosuppression were judged by delayed-onset diarrhea symptoms, histopathology examination, relative cytokines and blood cell counts. Mass spectrometry-based non-targeted and targeted metabolomics were conducted in sequence to dissect metabolite signatures in predose serums. Eventually, two groups of metabolites were screened out as predictors for individual differences in late-onset diarrhea and myelosuppression using binary logistic regression, respectively. This result was compared with existing predictors and validated by another independent external validation set. Our study indicates the prediction of toxicity could be possible upon predose metabolic profile. Pharmacometabolomics can be a potentially useful tool for complicating toxicity prediction. Our findings also provide a new insight into CPT-11 precision medicine.
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Key Words
- AUC-ROC, area under receiver operating characteristic
- BHB, β-hydroxybutyric acid
- Biomarkers
- C, control group
- CA, cholic acid
- CPT-11, irinotecan
- Complicating toxicity
- DBIL, direct bilirubin
- DCA, deoxycholic acid
- Diarrhea
- FDR, false discovery rate
- GCA, glycocholic acid
- Gastrointestinal toxicity
- IBIL, indirect bilirubin
- IT-TOF/MS, ion trap/time-offlight hybrid mass spectrometry
- Individual differences
- Irinotecan
- Lys, lysine
- MSTFA, N-methyl-N-trifluoroacetamide
- Metabolomics
- NS, non-sensitive group
- NSgt, non-sensitive for gastrointestinal toxicity
- NSmt, non-sensitive for myelosuppression toxicity
- OPLS-DA, orthogonal partial least-squares-discriminant analysis
- PCA, principal component analysis
- PLS-DA, partial least-squares-discriminant analysis
- Phe, phenylalanine
- Prediction
- QC, quality control
- RSD, relative standard deviation
- S, sensitive group
- Sgt, sensitive for gastrointestinal toxicity
- Smt, sensitive for myelosuppression toxicity
- T, CPT-11 treated group
- Trp, tryptophan
- UFLC, ultrafast liquid chromatography
- VIP, variable importance in the projection
- pFDR, false-discovery-rate-adjusted P value
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Affiliation(s)
- Yiqiao Gao
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
| | - Wei Li
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
| | - Jiaqing Chen
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
| | - Xu Wang
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
| | - Yingtong Lv
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
| | - Yin Huang
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
| | - Zunjian Zhang
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
| | - Fengguo Xu
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, China
- Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China
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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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Pharmacokinetics, Pharmacodynamics, and Pharmacogenomics of Immunosuppressants in Allogeneic Hematopoietic Cell Transplantation: Part II. Clin Pharmacokinet 2016; 55:551-93. [PMID: 26620047 DOI: 10.1007/s40262-015-0340-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Part I of this article included a pertinent review of allogeneic hematopoietic cell transplantation (alloHCT), the role of postgraft immunosuppression in alloHCT, and the pharmacokinetics, pharmacodynamics, and pharmacogenomics of the calcineurin inhibitors and methotrexate. In this article (Part II), we review the pharmacokinetics, pharmacodynamics, and pharmacogenomics of mycophenolic acid (MPA), sirolimus, and the antithymocyte globulins (ATG). We then discuss target concentration intervention (TCI) of these postgraft immunosuppressants in alloHCT patients, with a focus on current evidence for TCI and on how TCI may improve clinical management in these patients. Currently, TCI using trough concentrations is conducted for sirolimus in alloHCT patients. Several studies demonstrate that MPA plasma exposure is associated with clinical outcomes, with an increasing number of alloHCT patients needing TCI of MPA. Compared with MPA, there are fewer pharmacokinetic/dynamic studies of rabbit ATG and horse ATG in alloHCT patients. Future pharmacokinetic/dynamic research of postgraft immunosuppressants should include '-omics'-based tools: pharmacogenomics may be used to gain an improved understanding of the covariates influencing pharmacokinetics as well as proteomics and metabolomics as novel methods to elucidate pharmacodynamic responses.
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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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Zou X, Holmes E, Nicholson JK, Loo RL. Automatic Spectroscopic Data Categorization by Clustering Analysis (ASCLAN): A Data-Driven Approach for Distinguishing Discriminatory Metabolites for Phenotypic Subclasses. Anal Chem 2016; 88:5670-9. [PMID: 27149575 DOI: 10.1021/acs.analchem.5b04020] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
We propose a novel data-driven approach aiming to reliably distinguish discriminatory metabolites from nondiscriminatory metabolites for a given spectroscopic data set containing two biological phenotypic subclasses. The automatic spectroscopic data categorization by clustering analysis (ASCLAN) algorithm aims to categorize spectral variables within a data set into three clusters corresponding to noise, nondiscriminatory and discriminatory metabolites regions. This is achieved by clustering each spectral variable based on the r(2) value representing the loading weight of each spectral variable as extracted from a orthogonal partial least-squares discriminant (OPLS-DA) model of the data set. The variables are ranked according to r(2) values and a series of principal component analysis (PCA) models are then built for subsets of these spectral data corresponding to ranges of r(2) values. The Q(2)X value for each PCA model is extracted. K-means clustering is then applied to the Q(2)X values to generate two clusters based on minimum Euclidean distance criterion. The cluster consisting of lower Q(2)X values is deemed devoid of metabolic information (noise), while the cluster consists of higher Q(2)X values is then further subclustered into two groups based on the r(2) values. We considered the cluster with high Q(2)X but low r(2) values as nondiscriminatory, while the cluster with high Q(2)X and r(2) values as discriminatory variables. The boundaries between these three clusters of spectral variables, on the basis of the r(2) values were considered as the cut off values for defining the noise, nondiscriminatory and discriminatory variables. We evaluated the ASCLAN algorithm using six simulated (1)H NMR spectroscopic data sets representing small, medium and large data sets (N = 50, 500, and 1000 samples per group, respectively), each with a reduced and full resolution set of variables (0.005 and 0.0005 ppm, respectively). ASCLAN correctly identified all discriminatory metabolites and showed zero false positive (100% specificity and positive predictive value) irrespective of the spectral resolution or the sample size in all six simulated data sets. This error rate was found to be superior to existing methods for ascertaining feature significance: univariate t test by Bonferroni correction (up to 10% false positive rate), Benjamini-Hochberg correction (up to 35% false positive rate) and metabolome wide significance level (MWSL, up to 0.4% false positive rate), as well as by various OPLS-DA parameters: variable importance to projection, (up to 15% false positive rate), loading coefficients (up to 35% false positive rate), and regression coefficients (up to 39% false positive rate). The application of ASCLAN was further exemplified using a widely investigated renal toxin, mercury II chloride (HgCl2) in rat model. ASCLAN successfully identified many of the known metabolites related to renal toxicity such as increased excretion of urinary creatinine, and different amino acids. The ASCLAN algorithm provides a framework for reliably differentiating discriminatory metabolites from nondiscriminatory metabolites in a biological data set without the need to set an arbitrary cut off value as applied to some of the conventional methods. This offers significant advantages over existing methods and the possibility for automation of high-throughput screening in "omics" data.
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Affiliation(s)
- Xin Zou
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University , 800 Dongchuan Road, Shanghai 200240, China.,Medway Metabonomics Research Group, Medway School of Pharmacy, Universities of Kent and Greenwich , Chatham Maritime, Kent, ME4 4TB, U.K
| | - Elaine Holmes
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , London SW7 2AZ, U.K.,MRC-NIHR Phenome Centre, Imperial College London , London SW7 2AZ, U.K
| | - Jeremy K Nicholson
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , London SW7 2AZ, U.K.,MRC-NIHR Phenome Centre, Imperial College London , London SW7 2AZ, U.K
| | - Ruey Leng Loo
- Medway Metabonomics Research Group, Medway School of Pharmacy, Universities of Kent and Greenwich , Chatham Maritime, Kent, ME4 4TB, U.K.,Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , London SW7 2AZ, U.K
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Smirnov KS, Maier TV, Walker A, Heinzmann SS, Forcisi S, Martinez I, Walter J, Schmitt-Kopplin P. Challenges of metabolomics in human gut microbiota research. Int J Med Microbiol 2016; 306:266-279. [PMID: 27012595 DOI: 10.1016/j.ijmm.2016.03.006] [Citation(s) in RCA: 91] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Revised: 03/08/2016] [Accepted: 03/09/2016] [Indexed: 01/17/2023] Open
Abstract
The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine.
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Affiliation(s)
- Kirill S Smirnov
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Tanja V Maier
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Alesia Walker
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Silke S Heinzmann
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Sara Forcisi
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Inés Martinez
- Department of Agriculture, Food and Nutritional Science, University of Alberta, T6G 2E1 Edmonton, AB, Canada
| | - Jens Walter
- Department of Agriculture, Food and Nutritional Science, University of Alberta, T6G 2E1 Edmonton, AB, Canada
| | - Philippe Schmitt-Kopplin
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany; Chair of Analytical Food Chemistry, Technische Universität München, Alte Akademie 10, 85354 Freising, Germany; ZIEL, Institute for Food & Health, Weihenstephaner Berg 1, 85354 Freising, Germany.
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15
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The Need for Biomarkers in Diagnosis and Prognosis of Drug-Induced Liver Disease: Does Metabolomics Have Any Role? BIOMED RESEARCH INTERNATIONAL 2015; 2015:386186. [PMID: 26824035 PMCID: PMC4707380 DOI: 10.1155/2015/386186] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Accepted: 12/02/2015] [Indexed: 12/13/2022]
Abstract
Drug-induced liver injury (DILI) is a potentially fatal adverse event and the leading cause of acute liver failure in the US and in the majority of Europe. The liver can be affected directly, in a dose-dependent manner, or idiosyncratically, independently of the dose, and therefore unpredictably. Currently, DILI is a diagnosis of exclusion that physicians should suspect in patients with unexplained elevated liver enzymes. Therefore, new diagnostic and prognostic biomarkers are necessary to achieve an early and reliable diagnosis of DILI and thus improve the prognosis. Although several DILI biomarkers have been found through analytical and genetic tests and pharmacokinetic approaches, none of them have been able to display enough specificity and sensitivity, so new approaches are needed. In this sense, metabolomics is a strongly and promising emerging field that, from biofluids collected through minimally invasive procedures, can obtain early biomarkers of toxicity, which may constitute specific indicators of liver damage.
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16
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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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17
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Jones MD, Rainville PD, Isaac G, Wilson ID, Smith NW, Plumb RS. Ultra high resolution SFC–MS as a high throughput platform for metabolic phenotyping: Application to metabolic profiling of rat and dog bile. J Chromatogr B Analyt Technol Biomed Life Sci 2014; 966:200-7. [DOI: 10.1016/j.jchromb.2014.04.017] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2013] [Revised: 04/03/2014] [Accepted: 04/05/2014] [Indexed: 01/10/2023]
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18
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Development of blood biomarkers for drug-induced liver injury: an evaluation of their potential for risk assessment and diagnostics. Mol Diagn Ther 2014; 17:343-54. [PMID: 23868512 DOI: 10.1007/s40291-013-0049-0] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Drug-induced liver injury (DILI) remains a rare but serious complication in drug therapy that is a primary cause of drug failure during clinical trials. Conventional biomarkers, particularly the serum transaminases and bilirubin, serve as useful indicators of hepatocellular or cholestatic liver injury, respectively, but only after substantial and sometimes irreversible tissue damage. Ideally, more sensitive biomarkers that respond very early before irreversible injury has occurred would offer improved outcomes. Novel biomarkers are initially being developed in animal models exposed to intrinsically hepatotoxic stimuli. However, the eventual translation to human populations, even those with known risk factors that predispose the liver to drug toxicity, would be the fundamental goal. Ultimately, some might even be applicable for the early identification of individuals predisposed to idiosyncratic hepatotoxicity potential. This article reviews recent progress in the discovery and qualification of novel biomarkers for DILI and delineates the path to eventual utilization for risk assessment. Some major categories of plasma or serum biomarkers surveyed include proteins, cytokines, circulating mRNAs, and microRNAs.
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19
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Zou X, Holmes E, Nicholson JK, Loo RL. Statistical HOmogeneous Cluster SpectroscopY (SHOCSY): an optimized statistical approach for clustering of ¹H NMR spectral data to reduce interference and enhance robust biomarkers selection. Anal Chem 2014; 86:5308-15. [PMID: 24773160 PMCID: PMC4110102 DOI: 10.1021/ac500161k] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2014] [Accepted: 04/28/2014] [Indexed: 12/24/2022]
Abstract
We propose a novel statistical approach to improve the reliability of (1)H NMR spectral analysis in complex metabolic studies. The Statistical HOmogeneous Cluster SpectroscopY (SHOCSY) algorithm aims to reduce the variation within biological classes by selecting subsets of homogeneous (1)H NMR spectra that contain specific spectroscopic metabolic signatures related to each biological class in a study. In SHOCSY, we used a clustering method to categorize the whole data set into a number of clusters of samples with each cluster showing a similar spectral feature and hence biochemical composition, and we then used an enrichment test to identify the associations between the clusters and the biological classes in the data set. We evaluated the performance of the SHOCSY algorithm using a simulated (1)H NMR data set to emulate renal tubule toxicity and further exemplified this method with a (1)H NMR spectroscopic study of hydrazine-induced liver toxicity study in rats. The SHOCSY algorithm improved the predictive ability of the orthogonal partial least-squares discriminatory analysis (OPLS-DA) model through the use of "truly" representative samples in each biological class (i.e., homogeneous subsets). This method ensures that the analyses are no longer confounded by idiosyncratic responders and thus improves the reliability of biomarker extraction. SHOCSY is a useful tool for removing irrelevant variation that interfere with the interpretation and predictive ability of models and has widespread applicability to other spectroscopic data, as well as other "omics" type of data.
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Affiliation(s)
- Xin Zou
- Medway
School of Pharmacy, Universities of Kent
and Greenwich, Anson
Building, Central Avenue, Chatham, Kent ME4 4TB, U.K.
| | - Elaine Holmes
- Section
of Biomolecular Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
- MRC-HPA
Centre for Environment and Health, Imperial
College London, 150 Stamford
Street, London SE1 9NH, U.K.
| | - Jeremy K. Nicholson
- Section
of Biomolecular Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
- MRC-HPA
Centre for Environment and Health, Imperial
College London, 150 Stamford
Street, London SE1 9NH, U.K.
| | - Ruey Leng Loo
- Medway
School of Pharmacy, Universities of Kent
and Greenwich, Anson
Building, Central Avenue, Chatham, Kent ME4 4TB, U.K.
- Section
of Biomolecular Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London SW7 2AZ, U.K.
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20
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Bouhifd M, Hartung T, Hogberg HT, Kleensang A, Zhao L. Review: toxicometabolomics. J Appl Toxicol 2013; 33:1365-83. [PMID: 23722930 PMCID: PMC3808515 DOI: 10.1002/jat.2874] [Citation(s) in RCA: 118] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2012] [Revised: 02/10/2013] [Accepted: 02/11/2013] [Indexed: 12/19/2022]
Abstract
Metabolomics use in toxicology is rapidly increasing, particularly owing to advances in mass spectroscopy, which is widely used in the life sciences for phenotyping disease states. Toxicology has the advantage of having the disease agent, the toxicant, available for experimental induction of metabolomics changes monitored over time and dose. This review summarizes the different technologies employed and gives examples of their use in various areas of toxicology. A prominent use of metabolomics is the identification of signatures of toxicity - patterns of metabolite changes predictive of a hazard manifestation. Increasingly, such signatures indicative of a certain hazard manifestation are identified, suggesting that certain modes of action result in specific derangements of the metabolism. This might enable the deduction of underlying pathways of toxicity, which, in their entirety, form the Human Toxome, a key concept for implementing the vision of Toxicity Testing for the 21st century. This review summarizes the current state of metabolomics technologies and principles, their uses in toxicology and gives a thorough overview on metabolomics bioinformatics, pathway identification and quality assurance. In addition, this review lays out the prospects for further metabolomics application also in a regulatory context.
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Affiliation(s)
| | - Thomas Hartung
- Correspondence to: T. Hartung, Johns Hopkins Bloomberg School of Public Health, Environmental Health Sciences, Chair for Evidence-based Toxicology, Center for Alternatives to Animal Testing, 615 N. Wolfe St., Baltimore, MD, 21205, USA.
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21
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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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22
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The metabolomic window into hepatobiliary disease. J Hepatol 2013; 59:842-58. [PMID: 23714158 PMCID: PMC4095886 DOI: 10.1016/j.jhep.2013.05.030] [Citation(s) in RCA: 165] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2013] [Revised: 05/14/2013] [Accepted: 05/21/2013] [Indexed: 12/11/2022]
Abstract
The emergent discipline of metabolomics has attracted considerable research effort in hepatology. Here we review the metabolomic data for non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), cirrhosis, hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), alcoholic liver disease (ALD), hepatitis B and C, cholecystitis, cholestasis, liver transplantation, and acute hepatotoxicity in animal models. A metabolomic window has permitted a view into the changing biochemistry occurring in the transitional phases between a healthy liver and hepatocellular carcinoma or cholangiocarcinoma. Whether provoked by obesity and diabetes, alcohol use or oncogenic viruses, the liver develops a core metabolomic phenotype (CMP) that involves dysregulation of bile acid and phospholipid homeostasis. The CMP commences at the transition between the healthy liver (Phase 0) and NAFLD/NASH, ALD or viral hepatitis (Phase 1). This CMP is maintained in the presence or absence of cirrhosis (Phase 2) and whether or not either HCC or CCA (Phase 3) develops. Inflammatory signalling in the liver triggers the appearance of the CMP. Many other metabolomic markers distinguish between Phases 0, 1, 2 and 3. A metabolic remodelling in HCC has been described but metabolomic data from all four Phases demonstrate that the Warburg shift from mitochondrial respiration to cytosolic glycolysis foreshadows HCC and may occur as early as Phase 1. The metabolic remodelling also involves an upregulation of fatty acid β-oxidation, also beginning in Phase 1. The storage of triglycerides in fatty liver provides high energy-yielding substrates for Phases 2 and 3 of liver pathology. The metabolomic window into hepatobiliary disease sheds new light on the systems pathology of the liver.
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23
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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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24
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Brown HR, Mellon-Kusibab K, Bertram R, Tillman T, Arrington-Brown L, Jordan H, Gates L, Miller RT. Brief Communication. Toxicol Pathol 2013; 42:622-5. [DOI: 10.1177/0192623313495602] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Previous reports investigating the mechanisms of galactosamine toxicity have discussed the presence of responders and nonresponders after intraperitoneal (IP) administration of a toxic dose. The incidence of nonresponders has been reported to be as high as 47%. To rule out inadvertent intestinal, solid organ, or subcutaneous injection as at least a partial cause for the variability, we performed midline incisions and dosed 10 rats via a flexible catheter, with a toxic dose of galactosamine. Results were compared to a previous range finding study with IP-injected rats. As opposed to the IP-injected rats that had a roughly 50% response rate (based on serum alanine aminotransferase [ALT] elevation) and 100% of the midline incision catheter-instilled rats had elevations in ALT. Saline controls had no elevations. Histopathologic examination of livers from 5 midline-incisioned rats euthanized 48 hr after dosing with the lowest ALT responses revealed portal eosinophilic infiltrates and biliary hypertrophy/hyperplasia contiguous with areas of necrosis. Examination of 5 rats with the highest ALT elevations euthanized 10 days post dose revealed similar lesions to be resolving. We conclude that a significant contribution to variability in response to IP-injected galactosamine and possibly other investigative drugs is inadvertent misinjection of all or part of the dose.
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Affiliation(s)
- H. Roger Brown
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Kathy Mellon-Kusibab
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Rick Bertram
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Tony Tillman
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Leigh Arrington-Brown
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Holly Jordan
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Lisa Gates
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Richard T. Miller
- Department of Safety Assessment, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
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25
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Coen M, Rademacher PM, Zou W, Scott M, Ganey PE, Roth R, Nelson SD. Comparative NMR-Based Metabonomic Investigation of the Metabolic Phenotype Associated with Tienilic Acid and Tienilic Acid Isomer. Chem Res Toxicol 2012; 25:2412-22. [DOI: 10.1021/tx3002803] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Muireann Coen
- Biomolecular
Medicine, Department
of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Peter M. Rademacher
- Department of Medicinal Chemistry, University of Washington, 1959 NE Pacific Street, Health
Sciences Building, Seattle, Washington 98195-7610, United States
| | - Wei Zou
- Department of Microbiology and
Molecular Genetics, 2215 Biomedical Physical Sciences, Michigan State University, East Lansing, Michigan 48824-1302,
United States
| | - Michael Scott
- Department
of Pathobiology and
Diagnostic Investigation, G-347 Veterinary Medical Center, Michigan State University, East Lansing, Michigan 48824-1314,
United States
| | - Patricia E. Ganey
- Department
of Pharmacology and
Toxicology, 221 Food Safety and Toxicology Building, Michigan State University, East Lansing, Michigan 48824-1302,
United States
| | - Robert Roth
- Department
of Pharmacology and
Toxicology, 221 Food Safety and Toxicology Building, Michigan State University, East Lansing, Michigan 48824-1302,
United States
| | - Sidney D. Nelson
- Department of Medicinal Chemistry, University of Washington, 1959 NE Pacific Street, Health
Sciences Building, Seattle, Washington 98195-7610, United States
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