Oligoclonal bands as predictors of multiple sclerosis in clinically isolated syndrome

Klaudia Sapko, Anna Szczepańska-Szerej, Marcin Kulczyński, Michał Marciniec, Konrad Rejdak


Clinically Isolated Syndrome (CIS) is the first episode of inflammatory and demyelinating symptoms. According to the classification criteria of multiple sclerosis (MS) from 2013, CIS is defined as the first clinical manifestation of the disease. McDonald's 2010 criteria, considered the gold standard in the diagnosis of MS, are based on the clinical symptoms and the characteristic changes in magnetic resonance imaging (MRI). Unfortunately, up to 60-70% of patients with CIS do not meet the criteria for diagnosing MS at an early stage. At the same time, approximately 85% of patients with CIS will develop clinically defined MS (CDMS) in the future. When looking for other diagnostic tools, attention was paid to the role of oligoclonal bands (OBs) as predictors of MS development. Oligoclonal bands are immunoglobulins produced intrathecally by B-lymphocytes and plasma cells. Their level is examined in cerebrospinal fluid (CSF) collected by lumbar puncture. Studies carried out on a group of patients with CIS showed that people with positive test results for oligoclonal bands are twice as likely to develop MS than people with negative OBs. These conclusions are reflected in the revised McDonald's criteria in 2017, where OBs are used in the diagnosis of CIS patients with absence of new symptoms of the disease and changes in MRI. Early diagnosis makes possible to implement modifying disease drugs in the initial stage and, consequently, to achieve better therapeutic effects. The emphasis is also put on the development of other predictors in body fluids, which are effective in the diagnosis of people with CIS and negative oligoclonal bands. Many factors, including Epstein-Barr virus, chitinase-3 like 1, chitinase-3 like 2, chitotriosidase, multi-specific response to measles, rubella and varicella known as "MRZ reaction" or T-cell gene mutation are studied as a potential risk factors for MS development. Their use in diagnostics would improve the detection of MS in earlier stages, and thus the treatment of larger population of patients.


Oligoclonal bands; Clinically isolated syndrome; Multiple sclerosis; Cerebrospinal fluid; Predictor.

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Miller D, Barkhof F, Montalban X, Thompson A, Filippi M. Clinically isolated syndromes suggestive of multiple sclerosis, part I: natural history, pathogenesis, diagnosis, and prognosis. Lancet Neurol 2005; 4:281–288.

Marcus J, Waubant E. Updates on Clinically Isolated Syndrome and Diagnostic Criteria for Multiple Sclerosis, The Neurohospitalist. 2013; 3:65–80.

Efendi H. Clinically Isolated Syndromes: Clinical Characteristics, Differential Diagnosis, and Management, Noro Psikiyatr Ars. 2015; 52:1–11.

Lublin FD, Reingold SC, Cohen JA, Cutter GR, Sørensen PS, Thompson AJ, et al. Defining the clinical course of multiple sclerosis: The 2013 revisions. Neurology. 2014;83(3):278-286.

Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria. Ann. Neurol. 2011; 69:292–302.

Miller DH, Chard DT, Ciccarelli O. Clinically isolated syndromes. Lancet Neurol. 2012; 11:157–169.

Kuhle J, Disanto G, Dobson R, Adiutori R, Bianchi L, Topping J, et al. Conversion from clinically isolated syndrome to multiple sclerosis: A large multicentre study. Mult. Scler. 2015; 21:1013–1024.

Link H, Huang YM. Oligoclonal bands in multiple sclerosis cerebrospinal fluid: An update on methodology and clinical usefulness. J. Neuroimmunol. 2006; 180:17–28.

Thompson AJ,Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G,et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018; 17: 162–173.

Serafini B, Rosicarelli B, Magliozzi R,Stigliano E, Aloisi F. Detection of ectopic B-cell follicles with germinal centers in the meninges of patients with secondary progressive multiple sclerosis. Brain Pathol. 2004; 14:164–174.

von Büdingen HC, Kuo TC, Sirota M, van Belle CJ, Apeltsin L, Glanville J, et al. B cell exchange across the blood-brain barrier in multiple sclerosis. J Clin Invest. 2012; 122:4533–4543.

Bankoti J, Apeltsin L, Hauser SL,Allen S, Albertolle ME, Witkowska HE, et al. In multiple sclerosis, oligoclonal bands connect to peripheral B-cell responses. Annals of Neurology. 2014;75(2):266-276.

Heussinger N, Kontopantelis E, Gburek-Augustat J, Jenke A, Vollrath G, Korinthenberg R, et al. Oligoclonal bands predict multiple sclerosis in children with optic neuritis. Ann Neurol. 2015;77(6):1076–1082.

Rudick RA, Whitaker JN. Cerebrospinal fluid tests for multiple sclerosis. In Scheinberg P (Ed). Neurology/neurosurgery updata series, Vol. 7, CPEC. Princeton, NJ 1987.

Schwenkenbecher P, Sarikidi A, Bönig L, Wurster U, Bronzlik P, Sühs KW, et al. Clinically Isolated Syndrome According to McDonald 2010: Intrathecal IgG Synthesis Still Predictive for Conversion to Multiple Sclerosis. International Journal of Molecular Sciences. 2017;18(10):2061.

Huss AM, Halbgebauer S, Öckl P,Trebst C, Spreer A, Borisow N, et al. Importance of cerebrospinal fluid analysis in the era of McDonald 2010 criteria: a German–Austrian retrospective multicenter study in patients with a clinically isolated syndrome. Journal of Neurology. 2016;263(12):2499-2504.

Tintore M, Rovira A, Rio J, Tur C, Pelayo R, Nos C, et al. Do oligoclonal bands add information to MRI in first attacks of multiple sclerosis? Neurology. 2008;70 (13 Pt 2):1079–1083.

Disanto G, Morahan JM, Barnett MH, Giovannoni G, Ramagopalan SV. The evidence for a role of B cells in multiple sclerosis. Neurology. 2012;78(11):823–832.

Tintore M, Rovira A, Rio J, Otero-Romero S, Arrambide G, Tur C, et al. Defining high, medium and low impact prognostic factors for developing multiple sclerosis. Brain J Neurol. 2015;138(Pt 7):1863–1874.

Harbo HF, Isobe N, Berg-Hansen P, Bos SD, Caillier SJ, Gustavsen MW, et al. Oligoclonal bands and age at onset correlate with genetic risk score in multiple sclerosis. Multiplesclerosis (Houndmills, Basingstoke, England). 2014;20(6):660-668.

Kinoshita M, Daifu M, Tanaka K, Tanaka M. Prognostic value of oligoclonal IgG bands in Japanese clinically isolated syndrome converting to clinically definite multiple sclerosis. Journal of Neuroimmunology, Volume 307, 1 – 6.

Dobson R, Ramagopalan S, Davis A, Giovannoni G. Cerebrospinal fluid oligoclonal bands in multiple sclerosis and clinically isolated syndromes: a meta-analysis of prevalence, prognosis and effect of latitude. J NeurolNeurosurg Psychiatry 2013; 84:909-914.

Da Gama PD, Machado L dos R, Livramento JA, Gomes HR, Adoni T, Morales Rde R, et al. Oligoclonal Bands in Cerebrospinal Fluid of Black Patients with Multiple Sclerosis. BioMed Research International. 2015; 2015:217961.

Montalban X, Sastre-Garriga J, Filippi M,Khaleeli Z, Téllez N, Vellinga MM, et al. Primary progressive multiple sclerosis diagnostic criteria: a reappraisal. MultScler. 2009; 15:1459–1465.

McNicholas N,Hutchinson M, McGuigan C, Chataway J. 2017 McDonald diagnostic criteria: A review of the evidence, Multiple Sclerosis and Related Disorders. Volume 24, 48 – 54.

Mantero V, Abate L, Balgera R, La Mantia L, Salmaggi A. Clinical Application of 2017 McDonald Diagnostic Criteria for Multiple Sclerosis. J Clin Neurol. 2018 Jul;14(3):387-392.

Lunemann JD, Tintore M, Messmer B, Strowig T, Rovira A, Perkal H, et al. Elevated epstein-barr virus-encoded nuclear antigen-1 immune responses predict conversion to multiple sclerosis. Ann. Neurol. 2010; 67:159–169.

Pender MP, Burrows SR. Epstein–Barr virus and multiple sclerosis: potential opportunities for immunotherapy. Clinical & Translational Immunology. 2014;3(10): e27.

Brettschneider J, Tumani H, Kiechle U, Muche R, Richards G, Lehmensiek V, et al. Igg antibodies against measles, rubella, and varicella zoster virus predict conversion to multiple sclerosis in clinically isolated syndrome. PLoS ONE. 2009;4: e7638.

Comabella M, Fernandez M, Martin R, Rivera-Vallve S, Borras E, Chiva C, et al. Cerebrospinal fluid chitinase 3-like 1 levels are associated with conversion to multiple sclerosis. Brain. 2010; 133:1082–1093.

Quintana E, Coll C, Salavedra‐Pont J, Muñoz‐San Martín M, Robles‐Cedeño R, Tomàs‐Roig J, et al. Cognitive impairment in early stages of multiple sclerosis is associated with high cerebrospinal fluid levels of chitinase 3‐like 1 and neurofilament light chain. Eur J Neurol. 2018.

Møllgaard M, Degn M, Sellebjerg F, Frederiksen JL, Modvig S. Cerebrospinal fluid chitinase‐3‐like 2 and chitotriosidase are potential prognostic biomarkers in early multiple sclerosis. Eur J Neurol. 2016. 23: 898-905.

Corvol JC, Pelletier D, Henry RG, Caillier SJ, Wang J, Pappas D, et al. Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event. Proc. Natl. Acad. Sci. USA. 2008; 105:11839–11844.

Cameron EM, Spencer S, Lazarini J, Harp CT, Ward ES, Burgoon M, et al. Potential of a unique antibody gene signature to predict conversion to clinically definite multiple sclerosis. J. Neuroimmunol. 2009; 213:123–130.

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