Establishment of a novel diagnostic model for Sjögren’s syndrome by proteomic fingerprinting View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-12

AUTHORS

Yuhui Li, Xiaolin Sun, Xuewu Zhang, Yuqin Yang, Rulin Jia, Xu Liu, Ru Li, Yanying Liu, Zhanguo Li

ABSTRACT

Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease that lacks sensitive and specific diagnostic methods. The aim of this study was to identify potential biomarkers specific for pSS and to establish a diagnostic model. Serum samples from patients with pSS, disease controls (DC, patients with systemic lupus erythematosus (SLE), rheumatoid arthritis (RA)), and healthy controls (HC)) were randomly divided into a training set (35 pSS, 50 DC, and 26 HC) and a testing set (25 pSS, 50 DC, and 25 HC). Weak cationic exchange (WCX) magnetic beads were used to differentially capture serum proteins prior to proteomic analysis. Proteomic mass spectra were generated by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). One hundred differential M/Z peaks associated with pSS were identified, and the m/z peaks at 8,133.85, 11,972.8, 2,220.81, and 4,837.66 were used to establish a diagnostic model for pSS. This diagnostic model was able to distinguish pSS from non-pSS controls with a sensitivity of 77.1 % and a specificity of 85.5 %, and its efficacy was confirmed in our blinded testing set with good sensitivity and specificity of 95.5 and 88 %, respectively. The results indicated that the proteomic fingerprinting model was effective in the diagnosis of pSS. More... »

PAGES

1745-1750

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10067-014-2762-4

DOI

http://dx.doi.org/10.1007/s10067-014-2762-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047291846

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25178777


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