• Nikolaos Psychogios, David D Hau, Jun Peng, An Chi Guo, Rupasri Mandal, Souhaila Bouatra, Igor Sinelnikov, Ramanarayan Krishnamurthy, Roman Eisner, Bijaya Gautam, Nelson Young, Jianguo Xia, Craig Knox, Edison Dong, Paul Huang, Zsuzsanna Hollander, Theresa L Pedersen, Steven R Smith, Fiona Bamforth, Russ Greiner, Bruce McManus, John W Newman, Theodore Goodfriend, and David S Wishart.
• Department of Computing Science, University of Alberta, Edmonton, Canada.
• Plos One. 2011 Jan 1;6(2):e16957.

AbstractContinuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.

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