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.

Biomedical Research Center University Hospital Hradec Králové CZ 500 05 Hradec Králové Czech Republic

Department of Neurology Faculty of Medicine and University Hospital Brno CZ 639 00 Brno Czech Republic

Department of Neurology Faculty of Medicine and University Hospital Hradec Králové Charles University Prague CZ 500 05 Hradec Králové Czech Republic

See more in PubMed

Krejsek J. News in the pathogenesis of multiple sclerosis. What is hidden behind the disability of MS patients. Remedia. 2014;2014:S2–S4. (In Czech)

Cree B, Vollmer TL. Clinically isolated syndrome: Evaluation, risk stratification, and treatment decisions. Adv Stud Med. 2008;8:257–265.

Garcea O, Villa A, Cáceres F, Adoni T, Alegría M, Barbosa Thomaz R, Buzo R, Llamas López L, Rivera Kindel M. Early treatment of multiple sclerosis: A Latin American experts meeting. Mult Scler. 2009;15(Suppl 3):S1–S12. doi: 10.1177/1352458509106419. PubMed DOI

Schumacher GA, Beebe G, Kibler RF, Kurland LT, Kurtzke JF, McDowell F, Nagler B, Sibley WA, Tourtellotte WW, Willmon TL. Problems of experimental trials of therapy in multiple sclerosis: report by the panel on the evaluation of experimental trials of therapy in multiple sclerosis. Ann N Y Acad Sci. 1965;122:552–568. doi: 10.1111/j.1749-6632.1965.tb20235.x. PubMed DOI

Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC, Johnson KP, Sibley WA, Silberberg DH, Tourtellotte WW. New diagnostic criteria for multiple sclerosis: Guidelines for research protocols. Ann Neurol. 1983;13:227–231. doi: 10.1002/ana.410130302. PubMed DOI

McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, McFarland HF, Paty DW, Polman CH, Reingold SC, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol. 2001;50:121–127. doi: 10.1002/ana.1032. PubMed DOI

Polman CH, Reingold SC, Edan G, Filippi M, Hartung HP, Kappos L, Lublin FD, Metz LM, McFarland HF, O'Connor PW, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the ‘McDonald Criteria’. Ann Neurol. 2005;58:840–846. doi: 10.1002/ana.20703. PubMed DOI

Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, Fujihara K, Havrdova E, Hutchinson M, Kappos L, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69:292–302. doi: 10.1002/ana.22366. PubMed DOI PMC

Tintoré M. Rationale for early intervention with immunomodulatory treatments. J Neurol. 2008;255(Suppl 1):37–43. doi: 10.1007/s00415-008-1006-4. PubMed DOI

Miller JR. The importace of early diagnosis of multiple sclerosis. J Manag Care Pharm. 2004;10:S4–S11. PubMed

Kroksveen AC, Guldbrandsen A, Vedeler C, Myhr KM, Opsahl JA, Berven FS. Cerebrospinal fluid proteome comparison between multiple sclerosis patients and controls. Acta Neurol Scand Suppl. 2012;195:90–96. doi: 10.1111/ane.12029. PubMed DOI

Kroksveen AC, Opsahl JA, Aye TT, Ulvik RJ, Berven FS. Proteomics of human cerebrospinal fluid: discovery and verification of biomarker candidates in neurodegenerative diseases using quantitative proteomics. J Proteomics. 2011;74:371–388. doi: 10.1016/j.jprot.2010.11.010. PubMed DOI

Ottervald J, Franzén B, Nilsson K, Andersson LI, Khademi M, Eriksson B, Kjellström S, Marko-Varga G, Végvári A, Harris RA, et al. Multiple sclerosis: identification and clinical evaluation of novel CSF biomarkers. J Proteomics. 2010;73:1117–1132. doi: 10.1016/j.jprot.2010.01.004. PubMed DOI

Kroksveen AC, Aasebø E, Vethe H, Van Pesch V, Franciotta D, Teunissen CE, Ulvik RJ, Vedeler C, Myhr KM, Barsnes H, et al. Discovery and initial verification of differentially abundant proteins between multiple sclerosis patients and controls using iTRAQ and SID-SRM. J Proteomics. 2013;78:312–325. doi: 10.1016/j.jprot.2012.09.037. PubMed DOI

Comabella M, Fernández M, Martin R, Rivera-Vallvé S, Borrás E, Chiva C, Julià E, Rovira A, Cantó E, Alvarez-Cermeño JC, et al. Cerebrospinal fluid chitinase 3-like 1 levels are associated with conversion to multiple sclerosis. Brain. 2010;133:1082–1093. doi: 10.1093/brain/awq035. PubMed DOI

Stoop MP, Singh V, Dekker LJ, Titulaer MK, Stingl C, Burgers PC, Sillevis Smitt PA, Hintzen RQ, Luider TM. Proteomics comparison of cerebrospinal fluid of relapsing remitting and primary progressive multiple sclerosis. PLoS One. 2010;5:e12442. doi: 10.1371/journal.pone.0012442. PubMed DOI PMC

Cox J, Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008;26:1367–1372. doi: 10.1038/nbt.1511. PubMed DOI

Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res. 2011;10:1794–1805. doi: 10.1021/pr101065j. PubMed DOI

Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics. 2014;13:2513–2526. doi: 10.1074/mcp.M113.031591. PubMed DOI PMC

Gautier L, Cope L, Bolstad BM, Irizarry RA. affy - analysis of Affymetrix GeneChip data at the probe level. Bioinformatics. 2004;20:307–315. doi: 10.1093/bioinformatics/btg405. PubMed DOI

Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 2002;30:e15. doi: 10.1093/nar/30.4.e15. PubMed DOI PMC

Christin C, Hoefsloot HC, Smilde AK, Hoekman B, Suits F, Bischoff R, Horvatovich P. A critical assessment of feature selection methods for biomarker discovery in clinical proteomics. Mol Cell Proteomics. 2013;12:263–276. doi: 10.1074/mcp.M112.022566. PubMed DOI PMC

Clough T, Thaminy S, Ragg S, Aebersold R, Vitek O. Statistical protein quantification and significance analysis in label-free LC-MS experiments with complex designs. BMC Bioinformatics. 2012;13(Suppl 16):S6. doi: 10.1186/1471-2105-13-S16-S6. PubMed DOI PMC

Lipsy RJ, Schapiro RT, Prostko CR. Current and future directions in MS management: key considerations for managed care pharmacists. J Manag Care Pharm. 2009;15(Suppl A):S2–S15. quiz S16–S17. PubMed PMC

Mareš J. Early treatment of multiple sclerosis - treatment of clinically isolated syndrome, conditions of early diagnosis and treatment of multiple sclerosis. Remedia. 2011:S5–S6. (In Czech)

Tintoré M, Rovira A, Río J, Nos C, Grivé E, Téllez N, Pelayo R, Comabella M, Sastre-Garriga J, Montalban X. Baseline MRI predicts future attacks and disability in clinically isolated syndromes. Neurology. 2006;67:968–972. doi: 10.1212/01.wnl.0000237354.10144.ec. PubMed DOI

Fisniku LK, Brex PA, Altmann DR, Miszkiel KA, Benton CE, Lanyon R, Thompson AJ, Miller DH. Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis. Brain. 2008;131:808–817. doi: 10.1093/brain/awm329. PubMed DOI

Pérez-Miralles F, Sastre-Garriga J, Tintoré M, Arrambide G, Nos C, Perkal H, Río J, Edo MC, Horga A, Castilló J, et al. Clinical impact of early brain atrophy in clinically isolated syndromes. Mult Scler. 2013;19:1878–1886. doi: 10.1177/1352458513488231. PubMed DOI

Sastre-Garriga J, Tintoré M, Rovira A, Grivé E, Pericot I, Comabella M, Thompson AJ, Montalban X. Conversion to multiple sclerosis after a clinically isolated syndrome of the brainstem: cranial magnetic resonance imaging, cerebrospinal fluid and neurophysiological findings. Mult Scler. 2003;9:39–43. doi: 10.1191/1352458503ms847oa. PubMed DOI

Neuteboom RF, Boon M, Catsman Berrevoets CE, Vles JS, Gooskens RH, Stroink H, Vermeulen RJ, Rotteveel JJ, Ketelslegers IA, Peeters E, et al. Prognostic factors after a first attack of inflammatory CNS demyelination in children. Neurology. 2008;71:967–973. doi: 10.1212/01.wnl.0000316193.89691.e1. PubMed DOI

Tintoré M, Rovira A, Río J, Tur C, Pelayo R, Nos C, Téllez N, Perkal H, Comabella M, Sastre-Garriga J, et al. Do oligoclonal bands add information to MRI in first attacks of multiple sclerosis? Neurology. 2008;70:1079–1083. doi: 10.1212/01.wnl.0000280576.73609.c6. PubMed DOI

Ingram G, Loveless S, Howell OW, Hakobyan S, Dancey B, Harris CL, Robertson NP, Neal JW, Morgan BP. Complement activation in multiple sclerosis plaques: an immunohistochemical analysis. Acta Neuropathol Commun. 2014;2:53. doi: 10.1186/2051-5960-2-53. PubMed DOI PMC

Ekdahl NK, Blomberg C, Henningsson JA, Dahle C, Håkanssone I, Sandholm K, Ernerudh J. Systemic and intrathecal complement activation in multiple sclerosis and Guillan-Barré syndrome. Mol Immunol. 2009;46:2848. doi: 10.1016/j.molimm.2009.05.268. DOI

Ingram G, Hakobyan S, Robertson NP, Morgan BP. Complement in multiple sclerosis: its role in disease and potential as a biomarker. Clin Exp Immunol. 2009;155:128–139. doi: 10.1111/j.1365-2249.2008.03830.x. PubMed DOI PMC

Hinsinger G, Galéotti N, Nabholz N, Urbach S, Rigau V, Demattei C, Lehmann S, Camu W, Labauge P, Castelnovo G, et al. Chitinase 3-like proteins as diagnostic and prognostic biomarkers of multiple sclerosis. Mult Scler. 2015;21:1251–1261. doi: 10.1177/1352458514561906. PubMed DOI

Greenstein J, Cunningham T. Neuroprotective, anti-inflammatory and immune Tolerizing properties of peptides derived from diffusion survival Evasion protein (DSEP)/Dermcidin. Neurology. 2014;82:P1.175.

Bioproduced Nanoparticles Deliver Multiple Cargoes via Targeted Tumor Therapy In Vivo

Investigation of Protein Corona Formed around Biologically Produced Gold Nanoparticles