Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6020836 | Journal of Neuroimmunology | 2012 | 6 Pages |
Abstract
In order to investigate the biomarkers associated with relapsing-remitting multiple sclerosis (RRMS), we analyzed 72 patients with RRMS and 65 healthy controls using proteome technology. Peptides in sera were purified using magnetic beads, and analyzed by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry and ClinProTool software. Thirteen peptides were significantly different between patients with RRMS and healthy controls. Furthermore, a pattern of peaks was selected for genetic algorithm (GA), supervised neural network (SNN) and quick classifier (QC) model building. Among these three models, GA method was best with 93.49% of recognition capability and 82.66% of cross-validation and discriminated the proteomic spectra in patients with RRMS from healthy controls, with a sensitivity of 80% and a specificity of 91.3%. Meanwhile, the first peptide with m/z 2023.3 was identified as fragment of nucleolin protein. There is a possible relationship between the fragment peptide of nucleolin and the trigger of relapse in MS. Sera nucleolin may serve as a possible biomarker of RRMS.
Related Topics
Life Sciences
Immunology and Microbiology
Immunology
Authors
Jianghong Liu, Linlin Yin, Huiqing Dong, Erhe Xu, Lan Zhang, Yuchen Qiao, Yuan Liu, Lin Li, Jianping Jia,