Pharmacometabonomic Characterization of Xenobiotic and Endogenous Metabolic Phenotypes That Account for Inter-individual Variation in Isoniazid-Induced Toxicological Response

Cunningham, Katharine; Claus, Sandrine P.; Lindon, John C.; Holmes, Elaine; Everett, Jeremy R.; Nicholson, Jeremy K.; Coen, Muireann

doi:10.1021/pr300430u

Cited by 36 publications

(25 citation statements)

References 55 publications

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“…18–24 For example, recent metabolomics studies have provided insight regarding potential biomarkers for graft versus host disease (GVHD) in allogeneic HCT recipients. 25, 26 More specifically, Clayton, et al, introduced the concept of personalized drug treatment using pre-dose metabolite profiling to predict drug response in individual subjects, which the authors termed, “pharmacometabonomics”.…”

Section: Introductionmentioning

confidence: 99%

Pharmacometabonomic Prediction of Busulfan Clearance in Hematopoietic Cell Transplant Recipients

et al. 2016

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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 and 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 the only pathway 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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Section: Introductionmentioning

confidence: 99%

Pharmacometabonomic Prediction of Busulfan Clearance in Hematopoietic Cell Transplant Recipients

et al. 2016

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“…Cunningham et al [85] also used an NMR-based approach to predict the central nervous system (CNS) toxicity of the anti-tubercular drug isoniazid in rats when dosed at 200 and 400 mg/kg. Isoniazid has a complex metabolic fate, including conjugating with pyruvate and pyridoxal to form pyruvate isonicotinylhydrazone and isoniazidyl-pyridoxal metabolites respectively.…”

Section: Nmr-based Pre-clinical Pharmacometabonomics Studiesmentioning

confidence: 99%

“…It was hoped that this pre-clinical study, the first to identify multiple isoniazid urinary metabolites, would have the ability to translate its finding to the human clinical setting. [85] Coen et al [86] used an NMR-based approach to investigate variability in the response of rats to the toxicity of galactosamine, a drug whose variable responses in rats triggered the design of the original pharmacometabonomics experiment. [46] Male Sprague-Dawley rats were dosed intraperitoneally with 415 mg/kg galactosamine and classified as responders or non-responders based on clinical pathology.…”

Section: Nmr-based Pre-clinical Pharmacometabonomics Studiesmentioning

confidence: 99%

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

Everett

2017

Progress in Nuclear Magnetic Resonance Spectroscopy

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Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systemsbased 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 predose metabolite profiles between groups of subjects are used to predict postdose 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 21 st century healthcare. Highlights metabonomics or metabolomics involves metabolic profiling by NMR or MS methods  metabonomics is used in a diagnostic mode to study the effects of an intervention  pharmacometabonomics is a prognostic method to predict the effects of drugs  pharmacometabonomics is a special case of predictive metabonomics  pharmacometabonomics will help to deliver personalised medicine in the future Graphical AbstractNMR-Based Pharmacometabonomics PNMRS 2017

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“…Similarly, Cunningham et al found a metabolite signature response to isoniazid in urine that could be used to determine an individual's risk for certain ADRs. 81 However, a drug's effect on urine metabolites can be mitigated or exacerbated by other factors, such as diet, culture, and ethnicity. 82 In summary, understanding a patient's precise microbiome, metabolome, and diet can help researchers understand the underlying cause of an ADR in a population subset.…”

Section: Lifestyle-induced Adr Susceptibilitymentioning

confidence: 99%

Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms

Boland

Alexandra

Lorberbaum

et al. 2015

WIREs Mechanisms of Disease

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Small molecules are indispensable to modern medical therapy. However, their use may lead to unintended, negative medical outcomes commonly referred to as adverse drug reactions (ADRs). These effects vary widely in mechanism, severity, and populations affected, making ADR prediction and identification important public health concerns. Current methods rely on clinical trials and post-market surveillance programs to find novel ADRs; however, clinical trials are limited by small sample size, while post-market surveillance methods may be biased and inherently leave patients at risk until sufficient clinical evidence has been gathered. Systems pharmacology, an emerging interdisciplinary field combining network and chemical biology, provides important tools to uncover and understand ADRs and may mitigate the drawbacks of traditional methods. In particular, network analysis allows researchers to integrate heterogeneous data sources and quantify the interactions between biological and chemical entities. Recent work in this area has combined chemical, biological, and large-scale observational health data to predict ADRs in both individual patients and global populations. In this review, we explore the rapid expansion of systems pharmacology in the study of ADRs. We enumerate the existing methods and strategies and illustrate progress in the field with a model framework that incorporates crucial data elements, such as diet and comorbidities, known to modulate ADR risk. Using this framework, we highlight avenues of research that may currently be underexplored, representing opportunities for future work.

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Pharmacometabonomic Characterization of Xenobiotic and Endogenous Metabolic Phenotypes That Account for Inter-individual Variation in Isoniazid-Induced Toxicological Response

Cited by 36 publications

References 55 publications

Pharmacometabonomic Prediction of Busulfan Clearance in Hematopoietic Cell Transplant Recipients

Pharmacometabonomic Prediction of Busulfan Clearance in Hematopoietic Cell Transplant Recipients

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms

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