From Human Genetics and Genomics to Pharmacogenetics and Pharmacogenomics: Past Lessons, Future Directions

Nebert, Daniel W.; Zhang, Ge; Vesell, Elliot S.

doi:10.1080/03602530801952864

Cited by 167 publications

(90 citation statements)

References 220 publications

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“…However, environmental factors (such as nutritional status, gut bacterial activities, age, disease, and other drug use) are also important determinants of individual metabolic phenotypes, which modulate drug metabolism, efficacy, and toxicity. Such environmental complications, which may also alter gene expression, will tend to limit the usefulness of predictions of drug-induced responses that are based only on genomic differences (7,8). For instance, for many classes of compound, enzyme induction state, which is environmentally determined, influences drug metabolism and toxicity and this is not captured in genomic data.…”

mentioning

confidence: 99%

Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism

Clayton

Baker

Lindon

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

696

573

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We provide a demonstration in humans of the principle of pharmacometabonomics by showing a clear connection between an individual's metabolic phenotype, in the form of a predose urinary metabolite profile, and the metabolic fate of a standard dose of the widely used analgesic acetaminophen. Predose and postdose urinary metabolite profiles were determined by 1 H NMR spectroscopy. The predose spectra were statistically analyzed in relation to drug metabolite excretion to detect predose biomarkers of drug fate and a human-gut microbiome cometabolite predictor was identified. Thus, we found that individuals having high predose urinary levels of p-cresol sulfate had low postdose urinary ratios of acetaminophen sulfate to acetaminophen glucuronide. We conclude that, in individuals with high bacterially mediated p-cresol generation, competitive O-sulfonation of p-cresol reduces the effective systemic capacity to sulfonate acetaminophen. Given that acetaminophen is such a widely used and seemingly well-understood drug, this finding provides a clear demonstration of the immense potential and power of the pharmacometabonomic approach. However, we expect many other sulfonation reactions to be similarly affected by competition with p-cresol and our finding also has important implications for certain diseases as well as for the variable responses induced by many different drugs and xenobiotics. We propose that assessing the effects of microbiome activity should be an integral part of pharmaceutical development and of personalized health care. Furthermore, we envisage that gut bacterial populations might be deliberately manipulated to improve drug efficacy and to reduce adverse drug reactions.T he effects of drug treatments can vary greatly between different individuals, and pharmacogenomics has been widely advocated as a potential means of personalizing human drug treatments to increase drug efficacy and to decrease adverse reactions (1-6). However, environmental factors (such as nutritional status, gut bacterial activities, age, disease, and other drug use) are also important determinants of individual metabolic phenotypes, which modulate drug metabolism, efficacy, and toxicity. Such environmental complications, which may also alter gene expression, will tend to limit the usefulness of predictions of drug-induced responses that are based only on genomic differences (7,8). For instance, for many classes of compound, enzyme induction state, which is environmentally determined, influences drug metabolism and toxicity and this is not captured in genomic data. Recognizing this important limitation of pharmacogenomics, a different approach to personalized drug treatment has recently been proposed wherein predose metabolite profiling would instead be used to predict a subject's responses to potential drug interventions (9). This ''pharmacometabonomic'' approach has a number of major advantages, which include the ready availability and relative ease of analysis of biofluids, such as urine and blood plasma, as well as the fact that ...

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mentioning

confidence: 99%

Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism

Clayton

Baker

Lindon

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

696

573

View full text Add to dashboard Cite

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“…These relationships are present in monogenic diseases or in extreme phenotypes that have little or no biologic redundancy in the system [30,34]. An example of a simple genetically identifiable phenotype is Gaucher's disease.…”

Section: Monogenetic Versus Polygenetic Diseasesmentioning

confidence: 99%

“…Independent of drug-CYP interactions, clinical response to drugs is affected by polymorphism in the drug targets [30].…”

Section: Polymorphisms In Drug Targetsmentioning

confidence: 99%

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Prediction of Drug Response and Safety in Clinical Practice

2011

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Many clinicians hoped that the completion of the Human Genome Project would result in "individualized drug therapy," i.e., determining the right medication at the right dose 100% of the time based upon the individual's genetics. The pharmacogenomic prediction of drug efficacy and safety has not become a reality due to continuing realization of the complexity dictating the human-drug interaction. New methods of metabolomics, proteomics, and transcriptomics that account for this complexity hold promise for translational researchers hoping to increase drug efficacy and decrease drug toxicity.

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“…one encompassing multiple genetic profiles capable of affecting response. Current pharmacogenetic studies are exploring individual responses to drugs in relation to the genetic variations in the proteins involved in pharmacokinetics (absorption, distribution, metabolism and excretion) and pharmacodynamics (receptors, ion channels and other enzymes) (Roses A, 2000;Nebert, 2008) (figure 1).…”

Section: Pharmacogenetic Variability In Drug Responsementioning

confidence: 99%