Metabolomics in Medicine

Genomic studies provide scientists with new techniques to quickly analyse genes and their products in mass. The post genomics era has brought ever increasing demands to observe and characterize variations within biological systems. These variations have been studied under Systems Biology. Systems biology is a multi disciplinary and multi-instrumental analysis of all molecules within the cell, tissue and organism. This technology includes studies regarding genomics (gene function), transcryptomics (mRNA function), proteomics (protein regulation) and the metabolomics (low molecular weight metabolites).The suffix “– omic “is added at the end of each part of the systems. Metabolomics/metabonomics has been labeled one of the new “– omics “joining genomics. It is rapidly becoming one of the platform sciences of the “omics “, with the majority of papers in this field having been published only in the past two years (Rochfort S, 2005)and the manufacture sale rose up to $230 million in 2005 (Lok C, 2005).Metabolomics is concerned with the measurement of global sets of low-molecular weight metabolites. It is the study of metabolites and their roles in various disease states and is a novel methodology which arose in the last 3-5 years. The concept, characteristics, technologies and history of metabolomics are introduced. The techniques used in data acquisition and data analysis including NMR, GC/MS, LC/MS, and others, as well as the possibilities and the limitation of techniques are introduced.Metabolomics made on lab- on – a – chips techniques to provide earlier, faster, and more accurate diagnoses for many diseases. The major application of metabolomics is in toxicology, clinical trial testing, pharmacology and drug phenotyping,nutrient industry and food /beverage tests, cancer research, clinical pathology tests, and many others which have been tabulated in the text. Metabolomics developed mostly in plants, which are easier to study compared to mammals. Although use of metabolomics in medicine is in its infancy, this approach is considered to have the potential to revolutionize medical practice in prevention, predicting and personalizing health care. (Tanaffos 2005; 4(16): 13-22)