Proteomic analysis of cerebrospinal fluid for relapsing-remitting multiple sclerosis and clinically isolated syndrome

Abstract

Early diagnosis and treatment of multiple sclerosis (MS) in the initial stages of the disease can significantly retard its progression. The aim of the present study was to identify changes in the cerebrospinal fluid proteome in patients with relapsing-remitting MS and clinically isolated MS syndrome who are at high risk of developing MS (case group) compared to healthy population (control) in order to identify potential new markers, which could ultimately aid in early diagnosis of MS. The protein concentrations of each of the 11 case and 15 control samples were determined using a bicinchoninic acid assay. Nanoscale liquid chromatography coupled with tandem mass spectrometry was used for protein identification. Proteomics data were processed using the Perseus software suite and R. The results were filtered using the Benjamini-Hochberg procedure for the false discovery rate (FDR) correction (FDR<0.05). The results showed that, 26 proteins were significantly dysregulated in case samples compared to the controls. Nine proteins were found to be significantly less abundant in case samples, while the abundance of 17 proteins was significantly increased in case samples compared to controls. Three of the proteins were previously linked to RR MS, including immunoglobulin (Ig) γ-1 chain C region, Ig heavy chain V-III region BRO and Ig κ chain C region. Three proteins that were uniquely expressed in patients with RR MS were identified and these proteins may serve as prognostic biomarkers for identifying patients with a high risk of developing RR MS.

Keywords: biomarkers; cerebrospinal fluid; clinically isolated syndrome; multiple sclerosis; proteins; proteomic analysis.

Figure 1.

Pearson's correlation of protein LFQ intensities between the two technical replicates of one representative sample, R=0.976.

Figure 2.

Volcano plot showing significantly dysregulated proteins. The -log (P-value) is plotted against the difference of the means of the two groups (case and control). Points above the non-axial horizontal line are significantly differentially abundant proteins. Seventeen proteins were found to be significantly (P<0.002) more abundant in the case samples, while nine proteins were significantly less abundant in the case samples.

Figure 3.

A boxplot graph showing differences in controls (blue bars) vs. case (red bars) for each of the dysregulated proteins. Each boxplot shows protein concentration median, interquartile ranges and the most extreme values.