Metabonomics
High-resolution spectroscopic profiles of biofluids and tissues can tell us an enormous amount about their chemical composition in an efficient manner.
Advanced statistical methods can be applied to sets of profile data to help derive those chemical species that report on the biochemistry of health and disease processes.
Understanding Human Health and Disease
Understanding the complex interactions that influence human health is a fundamental part of modern medicine and is of great importance in the context of public health, clinical practice, novel drug development and environmental assessment. A number of factors contribute to human health and disease risk including:
- Genetics
- Environment
- Nutrition
- Gut microflora
- Infectious agents
Top-down systems biology approaches have been proposed as an efficient means of gaining a better understanding of how these various factors interact by considering global profiles that describe various level of biological organisation an complexity, including genes, proteins and metabolites. By studying systemic responses, these top-down approaches can efficiently provide an overview of complex, multi-stage processes that are displaced in time and/or space.
What is Metabonomics?
Understanding the significance of perturbed patterns of metabolites in biological systems may give insights into mechanisms that underlie states of health and disease. NMR spectroscopy and MS spectrometry of biofluids and cells provides a unique window on changes in endogenous metabolism and we have shown that such spectroscopic profiles provide information on organ and cells type-specific damage in a variety of organs and identified several novel markers of toxicity.
Definition of Metabonomics
"the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification"
Nicholson et al. (1999)
Analysing Metabolic Profiles
However, biological spectra are extremely complex and much information can be lost even in rigorous statistical analysis of quantitative data as the essential diagnostic parameters are carried in the overall patterns of the spectra. Therefore, we are using computer pattern recognition methods such as non-linear mapping and artificial neural networks to interrogate the vast metabolic databases on toxicological events generated by conventional biochemical and spectroscopic methods. This approach allows a mathematical classification of toxicity based on a compression of disparate types of multidimensional metabolic data so giving new insights into the modes and biochemical mechanisms of toxicity.
We are also working on other types of supervised learning methods such as rule-induction approaches to the interrogation of biological spectroscopic and clinical chemical data. This work is potentially of great value in the prediction of toxicity in drug development studies should lead to the more efficient use of experimental animals, as well as new insights into the toxic side effects of drugs. However, this approach is also highly generic and has numerous potential applications in clinical diagnostics (e.g. inborn errors of metabolism) and pharmacological efficacy evaluation in man.
Instrumentation for Metabonomic Analysis
To facilitate high-throughput the group has performed pioneering research in the use of nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to characterise biofluids and tissues and are world leaders in the application of hyphenated NMR and MS techniques. The main analytical laboratory at the South Kensington campus houses a suite of state-of-the-art spectroscopic instruments for metabolic profiling (metabonomics and metabolomics).
Chemometrics for Biomarker Discovery and Classification
Biomolecular Medicine are world leaders in multivariate metabolic profiling and in the statistical integration of multi-omics data. The Section also has outstanding analytical facilities and major research programs in NMR spectroscopy, mass spectrometry and optical spectroscopy. Research in Biomolecular Medicine wide range of application areas and are underpinned by continued development of the supporting analytical platforms and chemometric methods in metabonomics.
References
Nicholson JK, Lindon JC, Holmes E. 1999. 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29(11):1181-9.
