There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.
The time-related metabolic events in rat liver, plasma, and urine following hepatotoxic insult with allyl formate (75 mg/kg) were studied using a combination of high-resolution liquid state and magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopic methods together with pattern recognition analysis. The metabonomics results were compared with the results of conventional plasma chemistry and histopathological assessments of liver damage. Various degrees of liver damage were observed in different animals, and this variation was reflected in all of the analyses. Furthermore, each analysis revealed a high degree of functional and structural recovery by the end of the study. The allyl formate-induced changes included hepatocellular necrosis, hepatic lipidosis, decreased liver glycogen and glucose, decreased plasma lipids, increased plasma creatine and tyrosine, increased urinary taurine and creatine, and decreased urinary TCA cycle intermediates. The observed reductions in hepatic glycogen and glucose suggest increased glucose utilization and are consistent with the expected depletion of hepatic ATP following mitochondrial impairment, assuming that there is a consequent increase in energy production from glycolysis. The increase in plasma tyrosine is consistent with impaired protein synthesis, a known consequence of ATP depletion. Partial least squares-based cross-correlation of the variation in the liver and plasma NMR profiles indicated that the allyl formate-induced increase in liver lipids correlated with the decrease in plasma lipids. This suggests disruption in lipid transport from the liver to plasma, which could arise through impaired apolipoprotein synthesis, as with ethionine.
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