B2771 - Metabolomic profile of healthy children - 02/02/2017

B number: 
B2771
Principal applicant name: 
John Carlin | Murdoch Children's Research Institute & University of Melbourne (Australia)
Co-applicants: 
Prof. David Burgner, Prof Debbie Lawlor, Prof Kate Tilling, Dr Diana Dos Santos Ferreira, Dr Peter Wurtz
Title of project: 
Metabolomic profile of healthy children
Proposal summary: 

The "metabolome" refers to the entire array of small molecules (metabolites) of different types that are found in the body. Metabolites may be exogenous (e.g. from diet, drugs), or endogenous, reflecting the substrates, intermediates and products of biochemical reactions. Metabolites include amino acids, peptides, lipids and lipoproteins, organic acids and carbohydrates, as well as many smaller molecules.

Proton nuclear magnetic resonance (NMR) metabolomics, in contrast to the other main analytical tool (mass spectrometry), gives information regarding a few hundred larger intact molecules whose physiological roles are largely at least partly understood. NMR has higher reproducibility than mass spectrometry.

The Brainshake platform (https://www.brainshake.fi/biomarkers) allows simultaneous analysis of ~230 NMR metabolites on serum or plasma. This technology is increasingly applied to large adult cohorts, identifying metabolites individually and in combination that are strongly predictive of disease risk of various kinds, in particular cardiovascular. There are much fewer data in children, with only one published study to date. This reported the relationship between GlycA (a composite marker of inflammation derived from the NMR analysis) and obesity and fitness in early adolescence (Ref).

With local collaborators we have recently obtained Brainshake metabolomic data for two population-based cohorts (and a number of smaller groups of children) in Victoria, Australia, and are seeking to combine these data with other large series internationally in order to characterise the age-related development of the metabolome across childhood in normal healthy children. This will provide important information that will enable us and others to interpret the significance of metabolomic data from a range of clinical populations. As far as we are aware (including personal communication with Peter Wurtz of Brainshake), the age- and sex-related profile of the metabolome across childhood is largely unknown.

Date proposal received: 
Friday, 21 October, 2016
Date proposal approved: 
Monday, 7 November, 2016
Keywords: 
Epidemiology, Metabolomics, Statistical methods, Biological samples -e.g. blood, cell lines, saliva, etc., Cardiovascular, Childhood - childcare, childhood adversity, Metabolic - metabolism, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc.