Graves' disease (GD) is an autoimmune disorder that causes the overproduction of thyroid hormones and consequent cascade of systemic metabolism dysfunction. Moreover, Graves' ophthalmopathy (GO) is the main extrathyroidal manifestation of Graves' disease (GD). The goal of the study was to identify metabolic signatures in association with diagnostic biomarkers of GD without GO and GO, respectively. Ninety metabolites were profiled and analyzed based on a non-targeted primary metabolite profiling from plasma samples of 21 GD patients without GO, 26 subjects with GO, and 32 healthy subjects. Multivariate statistics showed a clear discrimination between healthy controls and disease group (R2Y = 0.518, Q2 = 0.478) and suggested a biomarker panel consisting of 10 metabolites. Among them, most of metabolites showed the positive association with the levels of thyrotropin receptor antibodies. With combination of proline and 1,5-anhydroglucitol, which were identified as GO-specific modulators, the re-constructed biomarker model greatly improved the statistical power and also facilitated simultaneous discrimination among healthy control, GO, and GD without GO groups (AUC = 0.845-0.935). Finally, the comparative analysis of tissue metabolite profiles from GO patients proposed putative metabolic linkage between orbital adipose/connective tissues and the biofluidic consequences, in which fumarate, proline, phenylalanine, and glycerol were coordinately altered with the blood metabolites.
Bibliographical noteFunding Information:
This study was supported by grants (grant number: NRF-2014M3A9B6069341 to E.J.L. and NRF-2013M3A9B6046519, NRF-2014M3A9B6069340 and NRF-2016R1C1B2007982 to D.Y.L.) from the Bio & Medical Technology Development Program of the National Research Foundation funded by the Korean government.
This study was supported by grants (grant number: NRF-2014M3A9B6069341 to E.J.L. and NRF- 2013M3A9B6046519, NRF-2014M3A9B6069340 and NRF-2016R1C1B2007982 to D.Y.L.) from the Bio & Medical Technology Development Program of the National Research Foundation funded by the Korean government.
© 2018 The Author(s).
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