| Literature DB >> 27310476 |
Andrea Sebastian1, Mohamed Ali Alzain1, Collins Otieno Asweto1, Haicheng Song2, Liufu Cui2, Xinwei Yu1,3, Siqi Ge1,3, Hao Dong1, Ping Rao1, Hao Wang1, Honghong Fang1, Qing Gao1, Jie Zhang1, Dian He1, Xiuhua Guo1, Manshu Song1, Youxin Wang1, Wei Wang1,3.
Abstract
Rheumatoid arthritis (RA), a systemic, chronic, and progressive inflammatory autoimmune disease, affects up to 1.0% of the world population doubling mortality rate of patients and is a major global health burden. Worrisomely, we lack robust diagnostics of RA and its remission status. Research with the next-generation biomarker technology platforms such as glycomics offers new promises in this context. We report here a clinical case-control study comprising 128 patients suffering from chronic RA (80.22% in remission, 19.78% active clinically) and 195 gender- and age-matched controls, with a view to the putative glycan biomarkers of RA as well as its activity or remission status in Han Chinese RA patients. Hydrophilic interaction liquid chromatography-ultra-performance liquid chromatography (HILIC-UPLC) was used for the analysis of IgG glycans. The regression model identified the glycans that predict RA status, while a receiver operating characteristic (ROC) curve analysis validated the sensitivity and prediction power. Among the total 24 glycan peaks (GP1-GP24), ROC analysis showed only GP1 prediction to be highly sensitive with an area under the curve (AUC) = 0.881. Even though GP21 and GP22 could predict active status among the RA cases (p < 0.05), they had lower sensitivity of prediction with an AUC = 0.658. Taken together, these observations suggest that GP1 might have potential as a putative biomarker for RA in the Han Chinese population, while the change in IgG glycosylation shows association with the RA active and remission states. To the best of our knowledge, this is the first glycomics study with respect to disease activity and remission states in RA.Entities:
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Year: 2016 PMID: 27310476 DOI: 10.1089/omi.2016.0050
Source DB: PubMed Journal: OMICS ISSN: 1536-2310