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.
Journal of neuroimmunology 05/2012; 250(1-2):71-6. · 2.84 Impact Factor