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Mol Hum Reprod. 2012 Nov;18(11):546-53. doi: 10.1093/molehr/gas029. Epub 2012 Jul 18.

Metabolomic biomarkers in women with polycystic ovary syndrome: a pilot study.

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Queens Medical Centre , Department of Obstetrics and Gynaecology, School of Clinical Sciences, University of Nottingham, Nottingham, D Floor, East Block, Nottingham NG7 2UH, UK.


The aim of this study was to investigate whether women with polycystic ovary syndrome (PCOS) had a unique metabolomic profile that was different from controls and to assess the feasibility of a definitive study. Twelve women with PCOS and 10 healthy women  as controls had measurements of demographic and anthropometric data, venepunctures and assays on plasma samples for metabolomic profiles using hydrogen-1, nuclear magnetic resonance ((1)H NMR) spectroscopy. There did not appear to be any clear differences between the metabolomic profiles of women with PCOS compared with controls when the NMR spectra were visually inspected and initial principal component analysis showed only a subtle differentiation between the two groups which was spread over three principal components. However, 'supervised' data analysis in the form of partial least-squares discriminant analysis (PLS-DA) and non-parametric univariate analysis allowed a stable PLS-DA model to be built, which appeared to differentiate between the two groups in a robust manner. Peak assignments for those spectral regions which appeared to differentiate between control and PCOS were consistent with amino acids (arginine, lysine, proline, glutamate and histidine), organic acids (citrate) and potentially lipids (CH(2)-CH(2)-C=C) with significant decreases noted in the levels of citrulline, lipid (CH(2)-CH(2)-C=C), arginine, lysine, ornithine, proline, glutamate, acetone, citrate and histidine in PCOS compared with controls. Women with PCOS may have a unique metabolomic finger print and a definitive study is feasible. These findings may enable sample size calculations for confirmatory studies and stimulate further research using metabolomics to improve the understanding and management of PCOS.

[Indexed for MEDLINE]

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