Glycan Biomarkers for Rheumatoid Arthritis and Its Remission Status in Han Chinese Patients.

Citation data:

Omics : a journal of integrative biology, ISSN: 1557-8100, Vol: 20, Issue: 6, Page: 343-51

Publication Year:
2016
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Citations 8
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Repository URL:
http://ro.ecu.edu.au/ecuworkspost2013/1959
PMID:
27310476
DOI:
10.1089/omi.2016.0050
Author(s):
Sebastian, Andrea; Alzain, Mohamed Ali; Asweto, Collins Otieno; Song, Haicheng; Cui, Liufu; Yu, Xinwei; Ge, Siqi; Dong, Hao; Rao, Ping; Wang, Hao; Fang, Honghong; Gao, Qing; Zhang, Jie; He, Dian; Guo, Xiuhua; Song, Manshu; Wang, Youxin; Wang, Wei Show More Hide
Publisher(s):
Mary Ann Liebert Inc; Mary Ann Liebert Inc.
Tags:
Biochemistry, Genetics and Molecular Biology; Medicine and Health Sciences
article description
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.