Molecular phenotyping of a UK population: defining the human serum metabolome

Warwick B. Dunn(University of Manchester), Wanchang Lin(University of Manchester), David Broadhurst(University of Manchester), Paul Begley(University of Manchester), Marie Brown(University of Manchester), Eva Zelena(University of Manchester), Andrew A. Vaughan(University of Manchester), Antony Halsall(University of Manchester), Nadine Harding(University of Manchester), Joshua Knowles(University of Manchester), Sue Francis‐McIntyre(University of Manchester), Andy Tseng(University of Manchester), David I. Ellis(University of Manchester), Steve O’Hagan(University of Manchester), Gill Aarons(University of Manchester), Boben Benjamin(University of Manchester), Stephen Chew-Graham(University of Manchester), Carly Moseley(University of Manchester), Paula W. Potter(University of Manchester), Catherine Winder(University of Manchester), Catherine Potts(University of Manchester), Paula Thornton(University of Manchester), Catriona McWhirter(University of Manchester), Mohammed Zubair(University of Manchester), Martin Pan(GlaxoSmithKline (United Kingdom)), Alistair Burns(University of Manchester), J. CRUICKSHANK(University of Manchester), Gordon C. Jayson(University of Manchester), Nitin Purandare(University of Manchester), Frederick C. W. Wu(University of Manchester), Joe D. Finn(University of Manchester), John N. Haselden(GlaxoSmithKline (United Kingdom)), Andrew W. Nicholls(GlaxoSmithKline (United Kingdom)), Ian D. Wilson(Imperial College London), Royston Goodacre(University of Manchester), Douglas B. Kell(University of Manchester)
Metabolomics
July 24, 2014
Cited by 260Open Access
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Abstract

Phenotyping of 1,200 'healthy' adults from the UK has been performed through the investigation of diverse classes of hydrophilic and lipophilic metabolites present in serum by applying a series of chromatography-mass spectrometry platforms. These data were made robust to instrumental drift by numerical correction; this was prerequisite to allow detection of subtle metabolic differences. The variation in observed metabolite relative concentrations between the 1,200 subjects ranged from less than 5 % to more than 200 %. Variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking. Investigations suggest that a sample size of 600 subjects is both necessary and sufficient for robust analysis of these data. Overall, this is a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes. This work provides an important baseline or reference dataset for understanding the 'normal' relative concentrations and variation in the human serum metabolome. These may be related to our increasing knowledge of the human metabolic network map. Information on the Husermet study is available at http://www.husermet.org/. Importantly, all of the data are made freely available at MetaboLights (http://www.ebi.ac.uk/metabolights/).


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