Session 6: Emerging Technologies
Jeremy K. Nicholson, Biological Chemistry, Biomedical Sciences Division, Imperial College, University of London.
High frequency proton NMR spectroscopy provides a rapid method of characterizing and quantifying a wide range of metabolites in untreated biological fluids and a powerful means of exploring the biochemical consequences of disease and toxicological processes (1). The coupling biofluid NMR spectroscopy to mathematical data reduction methods gives us a new Metabonomic approach to disease diagnosis, which is complementary to Proteomics and Genomics and can readily be applied in vivo in essentially non-invasive studies (2). NMR spectra of biofluids such as urine and plasma are highly complex, containing signals from hundreds of metabolites that represent many key biochemical pathways. The NMR-generated biofluid metabolite profiles are characteristically changed in different disease conditions according to the exact site and mechanism of the lesion. Thus interrogation of the biofluid NMR data can give direct diagnostic information and aid the detection of novel biomarkers, which give insight into disease mechanisms. Recent advances in Magic angle spinning-NMR also allow high resolution data to be collected on small intact tissue samples, thus giving metabolic information that is complementary to those obtained from biofluid NMR. By use of computer pattern recognition (PR) methods, complex biofluid/tissue NMR data can be reduced and analyzed quantitatively to provide PR maps that can assist in disease classification. Metabonomic diagnostics can be extremely sensitive for the detection of low-level damage in a variety of organ systems and is potentially a powerful new adjunct to conventional pathological procedures and to assist in functional genomics problems. The Metabonomic approach will be illustrated for a range of experimental lesions and human diseases
- Nicholson, J.K. and Wilson, I.D. (1989) Progress in NMR Spectroscopy 21 449-501.
- Nicholson, J.K. Lindon, J.C. and Holmes, E. Xenobiotica 29 1181-1189.
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