Current challenges in Metabolomics for diabetes research: a vital functional genomic tool or just a ploy for gaining funding?

@article{citeulike:2799383, abstract = {Metabolomics aims to profile all the small molecule metabolites found within a cell, tissue, organ or organism and use this information to understand a biological manipulation such as a drug intervention or a gene knock out. While neither mass spectrometry or NMR spectroscopy, the two most commonly used analytical tools in metabolomics, can provide a complete coverage of the metabolome, compared with other functional genomic tools for profiling biological moieties the approach is cheap and high throughput. In diabetes and obesity research this has provided the opportunity to assess large human populations or investigate a range of different tissues in animal studies both rapidly and cheaply. However, the approach has a number of major challenges, particularly with the interpretation of the data obtained. For example, some key pathways are better represented by high concentration metabolites inside the cell and thus, the coverage of the metabolome may become biased towards these pathways (e.g. the TCA cycle, amino acid metabolism). There is also the challenge of statistically modeling datasets with large numbers of variables but relatively small sample sizes. This perspective discusses our own experience of some of the benefits and pitfalls with using metabolomics to understand diseases associated with type II diabetes. Key words: metabonomics, NMR spectoscopy, mass spectrometry, obesity, functional genomics.}, address = {Biochemistry, Cambridge University, Tennis Court Road, Cambridge, CB2 1QW, United Kingdom; Cambridge Systems Biology Centre, University of Cambridge, United Kingdom.}, author = {Griffin, Julian L L. and Vidal-Puig, Antonio }, citeulike-article-id = {2799383}, doi = {10.1152/physiolgenomics.00009.2008}, issn = {1531-2267}, journal = {Physiological genomics}, month = {April}, posted-at = {2008-05-14 17:11:34}, priority = {2}, title = {Current challenges in Metabolomics for diabetes research: a vital functional genomic tool or just a ploy for gaining funding?}, url = {http://dx.doi.org/10.1152/physiolgenomics.00009.2008}, year = {2008} }

TY - JOUR ID - citeulike:2799383 L3 - citeulike-article-id:2799383 TI - Current challenges in Metabolomics for diabetes research: a vital functional genomic tool or just a ploy for gaining funding? JF - Physiological genomics AD - Biochemistry, Cambridge University, Tennis Court Road, Cambridge, CB2 1QW, United Kingdom; Cambridge Systems Biology Centre, University of Cambridge, United Kingdom. SN - 1531-2267 N2 - Metabolomics aims to profile all the small molecule metabolites found within a cell, tissue, organ or organism and use this information to understand a biological manipulation such as a drug intervention or a gene knock out. While neither mass spectrometry or NMR spectroscopy, the two most commonly used analytical tools in metabolomics, can provide a complete coverage of the metabolome, compared with other functional genomic tools for profiling biological moieties the approach is cheap and high throughput. In diabetes and obesity research this has provided the opportunity to assess large human populations or investigate a range of different tissues in animal studies both rapidly and cheaply. However, the approach has a number of major challenges, particularly with the interpretation of the data obtained. For example, some key pathways are better represented by high concentration metabolites inside the cell and thus, the coverage of the metabolome may become biased towards these pathways (e.g. the TCA cycle, amino acid metabolism). There is also the challenge of statistically modeling datasets with large numbers of variables but relatively small sample sizes. This perspective discusses our own experience of some of the benefits and pitfalls with using metabolomics to understand diseases associated with type II diabetes. Key words: metabonomics, NMR spectoscopy, mass spectrometry, obesity, functional genomics. AU - Griffin, Julian L AU - Vidal-Puig, Antonio PY - 2008/04/15/ UR - http://dx.doi.org/10.1152/physiolgenomics.00009.2008 ER -