Endocrine Abstracts

Background: Approximately 1000 children per annum born small for gestational age (SGA) will fail to catch-up and become eligible for GH treatment. The reason for this failed growth is often not defined. Understanding mechanisms that cause growth failure in SGA and finding potential biomarkers of poor growth is therefore important. We are using the new technique of Metabolomics as one avenue to address this. Metabolomics is the quantification of small molecule metabolites in a living system, including metabolic intermediates and signalling molecules.

Aim: To compare the metabolome in fibroblast cell lines derived from SGA without catch up growth versus normal controls.

Method: Skin biopsies were obtained from four SGA children without post-natal catch up growth and aged matched controls, and fibroblast cell lines were generated. Cells were incubated with media, which was removed after 24 h for analysis (metabolomic footprint). Cells were then lysed by three freeze thaw cycles (generating a metabolomic fingerprint) and both sets of samples were analysed by gas chromatography mass spectroscopy.

Results: Twenty-one metabolites in the footprint and 18 in the fingerprint were significantly different between SGA and control samples. These included increased levels of amino acids such as alanine (P<0.05), lysine (P<0.001) and glutamine (P<0.05) in the fingerprint and secondary signalling molecules involved in the PI-3 kinase pathway were down regulated, including myoinsitol (P<0.001) and inositol-1-phosphate (P<0.05) in the footprint.

Conclusion: Samples from SGA children without post-natal catch up growth have a significantly different metabolomic profile to controls. This translates to alterations in energy producing pathways, an up-regulation of the urea cycle and potential aberrations in cell signalling. These studies are being extended into metabolomic profiling in both plasma and urine in SGA children with and without catch-up growth, in order to identify whether one or more of these metabolites may be a useful biomarker.