Novel approaches to detect serum biomarkers for clinical response to interferon-beta treatment in multiple sclerosis

Abstract

Interferon beta (IFNbeta) is the most common immunomodulatory treatment for relapsing-remitting multiple sclerosis (RRMS). However, some patients fail to respond to treatment. In this study, we identified putative clinical response markers in the serum and plasma of people with multiple sclerosis (MS) treated with IFNbeta. In a discovery-driven approach, we use 2D-difference gel electrophoresis (DIGE) to identify putative clinical response markers and apply power calculations to identify the sample size required to further validate those markers. In the process we have optimized a DIGE protocol for plasma to obtain cost effective and high resolution gels for effective spot comparison. APOA1, A2M, and FIBB were identified as putative clinical response markers. Power calculations showed that the current DIGE experiment requires a minimum of 10 samples from each group to be confident of 1.5 fold difference at the p<0.05 significance level. In a complementary targeted approach, Cytometric Beadarray (CBA) analysis showed no significant difference in the serum concentration of IL-6, IL-8, MIG, Eotaxin, IP-10, MCP-1, and MIP-1alpha, between clinical responders and non-responders, despite the association of these proteins with IFNbeta treatment in MS.

Figure 1. 2DE gel images of human plasma samples generated with the different sample preparation methods used during optimization.

Method A) Crude plasma - 224 spots, Method B) Aurum serum depleted plasma without desalting– 86 spots, Method C) Aurum serum depleted plasma desalted according to Khan et al. protocol– 78 spots, Method D) Aurum serum depleted plasma cleaned up using 2D-clean up kit and alkylated using iodoacetamide - 212 spots Method E) MARS depleted plasma followed by 2D-clean up and alkylated using acrylamide– 774 spots, Method F) 17 cm gel with same protocol as E– 1041 spots. Each ladder had molecular weight ranging from 10 to 220 KDa.

Figure 2. Power curve showing the minimum % effect size (fold change) detectable as a function of sample size with 80% power at two different significance levels.

Figure 3. A 2D-DIGE image comparing the plasma proteome of CR to IFNβ treatment with CNR to IFNβ treatment with Cy3 and Cy5 channel overlap.

Samples were run on 17 cm gels after clean up and depletion. Spots Sp1, Sp2, and Sp3 were found to be increased in CR as compared to CNR based on a 1-way ANOVA with a p-value of less than 0.05 and fold change greater than 1.5.

Figure 4. IL-6 and eotaxin concentration comparison between CR and CNR in serum.