CORRELATION OF IgG AND IgM OLIGOCLONAL BANDS IN CSF AND SERUM WITH PROGRESSION AND DEGREE OF DISABILITY IN PATIENTS WITH MULTIPLE SCLEROSIS
Abstract
Objective: Our aim was to determine whether there was a correlation between IgG and IgM oligoclonal bands in CSF and serum and the EDSS score in patients with multiple sclerosis (MS). Methods: The material for this clinical, retrospective, and prospective, observational study consisted of patients with MS, treated at the University Clinic for Neurology, and outpatients followed in different stages of the disease. This study included 58 patients with confirmed MS diagnosis only. MS diagnosis was established according to widely accepted and revised McDonald's criteria for MS (MRI of the brain and spine, EP, routine laboratory blood tests) and who had a lumbar puncture during the diagnostic protocol. This paper included patients with various clinical forms of MS (RRMS, SPMS, PPMS). From all patients diagnosed with MS, demographic (age of onset of the first symptoms and sex) and clinical data (clinical course of the disease, duration of symptoms, degree of disability) were taken. The degree of disability was measured using a measurement scale of disability Kurz (EDSS). Matched cerebrospinal fluid (CSF) and plasma samples were analyzed using isoelectric focusing and IgG specific immunofixation to test for the presence of intrathecal specific OCB. Results: OCB are important biomarkers that can support MRI diagnostics and help to avoid false-positive MS diagnoses. Therefore, the revised McDonalds criteria have increased the importance of OCB. Using both cross-sectional samples and serial sampling in a subgroup of patients we found that the presence of CSF-restricted IgM OCB (but not of IgG OCB) was associated with an active inflammatory disease phenotype in PPMS patients. The presence of CSF IgM OCB may be a biomarker for a subset of PPMS patients with more active inflammatory disease, who may benefit from immune-directed treatments.
Keywords:oligoclonal bands, EDSS score, multiple sclerosis.
References
doi:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3351877/
2. Oksenberg JR, Baranzini SE, Sawcer S, Hauser SL. The genetics of multiple sclerosis: SNPs to pathways to
pathogenesis. Nat Rev Genet. 2008. doi:10.1038/nrg2395
3. Dendrou CA, Fugger L, Friese MA. Immunopathology of multiple sclerosis. Nat Rev Immunol. 2015.
doi:10.1038/nri3871
4. Polman CH, Reingold SC, Banwell B, et al. Diagnostic criteria for multiple sclerosis: 2010 Revisions to the
McDonald criteria. Ann Neurol. 2011. doi:10.1002/ana.22366
5. Aktas O, Wattjes MP, Stangel M, Hartung HP. Diagnosis of multiple sclerosis: revision of the McDonald criteria
2017. Nervenarzt. 2018.
6. Sand IBK, Lublin FD. Diagnosis and differential diagnosis of multiple sclerosis.Contin Lifelong Learn Neurol.
2013. doi:10.1212/01.CON.0000433290.15468.21
7. 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 Neurol
Neurosurg Psychiatry. 2013. doi:10.1136/jnnp-2012-304695
8. Dujmovic I. Cerebrospinal Fluid and Blood Biomarkers of Neuroaxonal Damage in Multiple Sclerosis. Mult Scler
Int. 2011;2011:1-18. doi:10.1155/2011/767083
9. Andersson M, Alvarez-CermeÑo J, Bernardi G, et al. Cerebrospinal fluid in the diagnosis of multiple sclerosis: a
consensus report.J Neurol Neurosurg Psychiatry. 1994;57(8):897-902. doi:10.1136/jnnp. 57.8.897
10. Freedman MS, Thompson EJ, Deisenhammer F, et al. Recommended standard of cerebrospinal fluid analysis
in the diagnosis of multiple sclerosis: a consensus statement. Arch Neurol. 2005;62(6): 865-870.
doi:10.1001/archneur.62.6.865
11. Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald
criteria. Lancet Neurol. 2018;17(2):162-17.
12. Rudick RA, Lee JC, Cutter GR, et al. Disability progression in a clinical trial of relapsing-remitting multiple
sclerosis: eight-year follow-up. Arch Neurol. 2010;67(11):1329-1335. doi:10.1001/archneurol. 2010.150
13. Alharbi FM. Update in vitamin D and multiple sclerosis. Neurosciences. 2015.
doi:10.17712/nsj.2015.4.20150357
14. Wingerchuk DM. Smoking: Effects on multiple sclerosis susceptibility and disease progression. Ther Adv
Neurol Disord. 2012. doi:10.1177/1756285611425694
15. Ferraro D, Simone AM, Bedin R, et al. Cerebrospinal fluid oligoclonal IgM bands predict early conversion to
clinically definite multiple sclerosis in patients with clinically isolated syndrome.J Neuroimmunol. 2013;257(1-
2):76-81. doi:10.1016/j.jneuroim.2013.01.011.
16. Magraner MJ, Bosca I, Simу-Castellу M, et al. Brain atrophy and lesion load are related to CSF lipid-specific
IgM oligoclonal bands in clinically isolated syndromes. Neuroradiology. 2012;54(1):5- 12. doi:10.1007/s00234-
011-0841-7.
17. Harris VK, Tuddenham JF, Sadiq SA. Biomarkers of multiple sclerosis: current findings. Degener Neurol
Neuromuscul Dis. 2017;7(7):19-29.
18. Vrethem M, Fernlund I, Ernerudh J, Ohman S. Prognostic value of cerebrospinal fluid IgA and IgG in multiple
sclerosis. Mult Scler. 2004;10(4):469-471. doi:10.1191/1352458504ms1052sr
19. Katsavos S, Anagnostouli M. Biomarkers in Multiple Sclerosis: An Up-to-Date Overview. Mult Scler Int.
2013;2013(ii):340508. doi:10.1155/2013/340508
20. Tremlett H, Paty D, Devonshire V. Disability progression in multiple sclerosis is slower than previously
reported. Neurology. 2006.
