Introduction

The disciplines evolving from the sequencing of the human genome, transcriptomics and proteomics, have the potential to facilitate the drug discovery process but the greatest value lies in the integration of these areas of research focus. At the same time, another "omics" discipline has been significantly improving our decades-long knowledge of metabolites. Rather than quantifying one or two metabolites at a time, researchers involved in metabonomics (see Box 10.1) are attempting the comprehensive and quantitative study of changes in the metabolome (the molecules representative of the substrates, products, and intermediates of biochemical pathways on which proteins act). Historically, the focus of researchers has been a single gene or protein or metabolite. With the advances in the array concept, multiplexing of gene or protein expressions and support vector machine analyses of data generated from these platforms, clustering of such data has led to more predictive and robust interpretations. It is no surprise that interpretation of quantitative patterns of metabolites should follow since small molecules can be monitored in bodily fluids obtained with minimal or no invasion of the body. Traditionally, clinicians have measured single-metabolite markers and have intuitively bunched several together for confirmation or for eliminating a certain disease or metabolic condition. However, the greatest potential lies in the challenge of integrating all of these "omics" into a Systems Biology approach. With such an understanding, there is a promise of great value to drug discovery and development.

Box 10.1

Although the terms "metabonomics" and "metabolomics" are not always used consistently, Jeremy K. Nicholson of Imperial College and his colleagues coined the term "metabonomics"1 in 1996 to refer to the "quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification." According to this group, metabonomics is derived from "meta" and "nomics" derived from the Greek words for change and rules, respectively.2 It does not measure the metabolism of the compound itself, but rather looks for a pattern of change in hundreds or thousands of endogenous biomolecules that is a "fingerprint" of efficacy or toxicity. "Metabolomics," is then reserved for the metabolic regulation and fluxes in individual cells or cell types and the measurement thereof. Others use the two terms interchangeably and as with any new field, nomenclature discussions are unavoidable, until we have a clear understanding of the boundaries. While this chapter attempts to follow the spirit of this distinction, the literature is not always in agreement.

The National Institutes of Health (NIH) has characterized "[t]he general aim of metabolomics ... to identify, measure and interpret the complex, time-related concentration, activity and flux of endogenous metabolites in cells, tissues and other biosamples such as blood, urine and saliva."3 Taken together, the three "omics" disciplines represent a systemic and powerful approach to mapping cellular networks, allowing for faster and more predictive biology in terms of risk assessment, potential therapeutic benefit, as well as diagnosis.

Metabonomics data complement gene expression and proteomic data. Whereas the latter reflect calculations of the potential for disease or toxicity, metabonomics reflects actual biological events. Focusing on metabolites allows monitoring a dynamic profile rather than a snapshot, creating a mechanistic level of understanding of toxicology.4 Unlike transcriptomics and proteomics, metabonomics can give information on a whole organism's functional integrity over time after drug exposure.5

Moreover, the metabolome is more sensitive to changes in individual enzyme or transcript levels than the transcriptome or proteome. While metabolic fluxes are not always affected by changes in quantities of individual enzymes, when concentrations of individual metabolites do change, they are more closely linked than the transcriptome or pro-teome to variations in phenotype that are most relevant to human health. Often enzyme concentrations change to maintain concentrations of certain metabolites essential to physiological equilibrium associated with human health. Adelbert Roscher of the University of Munich succinctly characterized the relationship that metabolite profiling "measures the real outcome of potential changes suggested by genomics and proteomics."6

Metabonomics shows promise for other applications in drug discovery and development. Clinicians already use metabolic biomarkers to diagnose disease; it is not difficult to transfer the concept of patterns in gene expression to patterns of metabolites to describe and define the subtleties of disease that may be unique to a single individual. Furthermore, since stages of a disease may be further defined, treatments can be more rational and optimized. Genetic and proteinaceous changes could be compensated for elsewhere in the organism so that they are not necessarily part of the pathology. Many pathway feedback mechanisms are not reflected in protein concentration or gene expression changes. Mammalian metabolic control functions are dispersed across many cell types in topographically distinct locations that are in different physiological stages, raising serious questions about the value of simple pathway modeling. Environment and diet can also affect disease and toxicity, and both have an impact on the organism independent of gene expression or proteomic activity. In addition, there must be an accounting for the entire gut microflora to understand the dynamics of drug efficacy and adverse reactions.7

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