Abstract
To establish a serological classification tree model for rheumatoid arthritis (RA), protein/peptide profiles of serum were detected by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange (WCX) from Cohort 1, including 65 patients with RA and 41 healthy controls (HC). The samples were randomly divided into a training set and a test set. Twenty-four differentially expressed peaks (P < 0.05) were identified in the training set and 4 of them, namely m/z 3,939, 5,906, 8,146, and 8,569 were chosen to set up our model. This model exhibited a sensitivity of 100.0 % and a specificity of 96.0 % for differentiating RA patients from HC. The test set reproduced these high levels of sensitivity and specificity, which were 100.0 and 81.2 %, respectively. Cohort 2, which include 228 RA patients, was used to further verify the classification efficiency of this model. It came out that 97.4 % of them were classified as RA by this model. In conclusion, MALDI-TOF-MS combined with WCX magnetic beads was a powerful method for constructing a classification tree model for RA, and the model we established was useful in recognizing RA.
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Acknowledgments
This study was supported by grants from “Early diagnosis and therapy strategy for Rheumatoid Arthritis” (No. 2008BAI59B01) of the 11th Five Years Key Programs for Science and Technology Development of China. And we thank Professor Deng Haiteng (The Proteomics Resource Center of Rockfeller University,New York, USA) for technology supported.
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We declare that we have no conflict of interest to disclose.
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Zhang Yan, Hu Chaojun, and Deng Chuiwen have equally contributed to this work and should be considered the first authors.
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Yan, Z., Chaojun, H., Chuiwen, D. et al. Establishing serological classification tree model in rheumatoid arthritis using combination of MALDI-TOF-MS and magnetic beads. Clin Exp Med 15, 19–23 (2015). https://doi.org/10.1007/s10238-013-0265-2
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DOI: https://doi.org/10.1007/s10238-013-0265-2