The Role of Metabolic Profiling in Epidemiology

Elaine Holmes

Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics (SORA), Imperial College London, Exhibition Road, London, SW7 2AZ, UK

Metabonomics / Metabolomics is a rapidly emerging field of research combining sophisticated analytical tools such as NMR spectroscopy and mass spectrometry with multivariate statistical analysis to generate complex metabolic profiles of biofluids and tissues. Metabonomics provides a systems approach to measuring dynamic biochemical responses of organisms to pathological stimuli or genetic modification and operates by profiling the metabolic responses of key intermediary biochemical pathways. Such analysis has been shown to be of considerable value in providing detailed information regarding the metabolic status of an organism, in characterizing the metabolic phenotype of genetically modified organisms and in discerning and predicting a wide range of pathological conditions. Moreover, this approach has proven value in assessing the efficacy of therapeutic interventions in animals and man.

More recently metabolite profiling strategies have been applied in epidemiological studies. Large scale screening of human populations is now possible and models of metabolic phenotype can be constructed for populations. However, the complexity and interactive nature of biological systems introduce confounding variation into the metabonomic data. Various chemometric and bioinformatic strategies for optimizing the characterization and prediction of pathological conditions can be adopted in order to increase the sensitivity of metabonomic analysis by reducing the influence of confounding random and systematic noise, accommodating the presence of large dynamic range in the measurement variables and/or incorporating the temporal dependence of pathologies.

Using a range of multivariate analytical strategies, metabonomic data can be integrated with gene expression and proteomic data to provide a more holistic vision of biological processes at a whole systems level. Gene-metabolite interactions can be probed using a range of chemometric tools and the metabolic signature used to direct appropriate sampling points for genomic/proteomic analysis. Examples of this integrative approach will be drawn from a number of fields including dysmetabolic syndrome and insulin resistance, cardiovascular disease, neurodegenerative disorders, cancer and infectious diseases. Metabolic responses to therapeutic and nutritional intervention are also considered.