Simultaneous profiling of eicosanoid metabolome in plasma by UPLC-MS/MS method: Application to identify potential makers for rheumatoid arthritis.
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| Abstract |
To evaluate the potential relationship between rheumatoid arthritis and arachidonic acid (AA) metabonomics via cyclooxygenase (COX) and lipoxygenase (LOX) pathways, a UPLC-MS/MS method has been developed and validated for simultaneous and quantitative profiling of eicosanoid metabolome in rat plasma. The analytes were extracted from plasma samples by protein precipitation procedure, and then separated on a Shim-pack XR-ODS column with mobile phase A (0.05% formic acid in water, pH=3.3 adjusted with dilute ammonium hydroxide) and mobile phase B [methanol: acetonitrile (20:80, v/v)]. The detection was performed on UPLC-MS/MS system with an electro spray ion source in the negative ion and multiple reaction-monitoring modes. The developed method was optimized to completely separate all twenty-three analytes and three internal standards in 12min. All standard calibration curves were linear and the calibration regression coefficients were ranged from 0.9903 to 0.9992 for all analytes. The recoveries of analytes were all more than 60%. By means of the method developed, the plasma samples from model rats and normal rats had been successfully determined. Results showed that AA and fifteen kinds of metabolites by LOX and COX pathways in model rat plasma were significant higher than those in normal ones(P<0.05), while 5-HpETE and LTD4 in model rat plasma were significantly lower than those in normal ones(P<0.05). The methods demonstrated the changes of eicosanoid metabolome occurring in plasma from rat subjects with rheumatoid arthritis. It could be a powerful manner to diagnostic and/or prognostic values for rheumatoid arthritis.
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| Authors | Nannan Wang, Ronghua Dai, Weihui Wang, Yan Peng, Xiaoning Zhao, Kaishun Bi |
| Journal | Talanta (Talanta) Vol. 161 Pg. 157-164 (Dec 01 2016) ISSN: 1873-3573 [Electronic] Netherlands |
| PMID | 27769393 (Publication Type: Journal Article) |
| Copyright | Copyright © 2016 Elsevier B.V. All rights reserved. |
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