Approximately 50% of patients with Graves’ disease (GD) develop retracted eyelids with bulging eyes, known as Graves’ ophthalmopathy (GO). However, no simple diagnostic blood marker for distinguishing GO from GD has been developed yet. The objective of this study was to conduct comprehensive profiling of lipids using plasma and urine samples from patients with GD and GO undergoing antithyroid therapy using nanoflow ultrahigh performance liquid chromatography electrospray ionization tandem mass spectrometry. Plasma (n = 86) and urine (n = 75) samples were collected from 23 patients with GD without GO, 31 patients with GO, and 32 healthy controls. Among 389 plasma and 273 urinary lipids that were structurally identified, 281 plasma and 191 urinary lipids were quantified in selected reaction monitoring mode. High-abundance lipids were significantly altered, indicating that the development of GD is evidently related to altered lipid metabolism in both plasma and urine. Several urinary lysophosphatidylcholine species were found to be increased (3- to 10-fold) in both GD and GO. While the overall lipid profiles between GD and GO were similar, significant changes (area under receiver operating curve > 0.8) in GO vs. GD were observed in a few lipid profiles: 58:7-TG and (16:1,18:0)-DG from plasma, 16:1-PC and 50:1-TG from urine, and d18:1-S1P from both plasma and urine samples. An altered metabolism of lipids associated with the additional development of ophthalmopathy was confirmed with the discovery of several candidate markers. These can be suggested as candidate markers for differentiating the state of GO and GD patients based on plasma or urinary lipidomic analysis. [Figure not available: see fulltext.].
Bibliographical noteFunding Information:
Acknowledgments This study was supported by a grant (NRF-2015R1A2A1A01004677 to M.H.M) from the National Research Foundation (NRF) of Korea, a grant (2014M3A9B6069341 to E.J.L) from the Bio & Medical Technology Development Program of NRF. S.K.B acknowledges the support of the Yonsei University Research Fund (Post Doc. Researcher Supporting Program) of 2016 (project no.: 2016-12-0230).
All Science Journal Classification (ASJC) codes
- Analytical Chemistry