Vol 54, No 3 (2020)
Review Article
Published online: 2020-05-28

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Biomarkers in Multiple Sclerosis: a review of diagnostic and prognostic factors

Klaudia Sapko1, Anna Jamroz-Wiśniewska1, Michał Marciniec1, Marcin Kulczyński1, Anna Szczepańska-Szerej1, Konrad Rejdak1
Pubmed: 32462652
Neurol Neurochir Pol 2020;54(3):252-258.


Introduction. Multiple Sclerosis (MS) is a chronic, demyelinating disease of the central nervous system which affects mostly young people. Because it leads to disability and cognitive impairment, it is crucial to recognise MS at an early stage.

State of the art. Magnetic resonance imaging is the golden standard in MS diagnosis. However, it is not an infallible diagnostic tool, especially at the stage of clinically isolated syndrome. The incorporation of oligoclonal bands in the diagnostic process of MS is a step towards the extension of diagnostic methods. Recently, a lot of research has been carried out on potential biomarkers in blood serum and cerebrospinal fluid that may be useful in the diagnosis of MS.

Clinical implications.
This article summarises current knowledge on the use of new prognostic factors such as neurofilament light chain, chitinase 3-like 1 and 2, heat shock proteins, and tubulins in MS.

Future directions. Despite numerous studies on the use of biomarkers in the diagnosis of MS, more extensive research is needed to determine the clinical usefulness of these molecules and to develop diagnostic tests applicable in everyday practice. This in turn may result in earlier MS detection, faster implementation of treatment, and better therapeutic effects.

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  1. Kantarci OH, Weinshenker BG. Natural history of multiple sclerosis. Neurol Clin. 2005; 23: 17–38.
  2. Rejdak K, Jackson S, Giovannoni G. Multiple sclerosis: a practical overview for clinicians. Br Med Bull. 2010; 95: 79–104.
  3. Efendi H. Clinically Isolated Syndromes: Clinical Characteristics, Differential Diagnosis, and Management. Noro Psikiyatr Ars. 2015; 52: 1–11.
  4. Miller D, Barkhof F, Montalban X, et al. Clinically isolated syndromes suggestive of multiple sclerosis, part I: natural history, pathogenesis, diagnosis, and prognosis. Lancet Neurol. 2005; 4: 281–288.
  5. Miller DH, Chard DT, Ciccarelli O. Clinically isolated syndromes. Lancet Neurol. 2012; 11(2): 157–169.
  6. Kuhle J, Disanto G, Dobson R, et al. Conversion from clinically isolated syndrome to multiple sclerosis: A large multicentre study. Mult Scler. 2015; 21(8): 1013–1024.
  7. Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018; 17(2): 162–173.
  8. Gaetani L, Fanelli F, Riccucci I, et al. High risk of early conversion to multiple sclerosis in clinically isolated syndromes with dissemination in space at baseline. J Neurol Sci. 2017; 379: 236–240.
  9. Marcus JF, Waubant EL. Updates on clinically isolated syndrome and diagnostic criteria for multiple sclerosis. Neurohospitalist. 2013; 3(2): 65–80.
  10. Brownlee WJ, Hardy TA, Fazekas F, et al. Diagnosis of multiple sclerosis: progress and challenges. Lancet. 2017; 389(10076): 1336–1346.
  11. Bankoti J, Apeltsin L, Hauser SL, et al. In multiple sclerosis, oligoclonal bands connect to peripheral B-cell responses. Ann Neurol. 2014; 75(2): 266–276.
  12. Serafini B, Rosicarelli B, Magliozzi R, et al. Detection of ectopic B-cell follicles with germinal centers in the meninges of patients with secondary progressive multiple sclerosis. Brain Pathol. 2004; 14(2): 164–174.
  13. Dobson R, Ramagopalan S, Davis A, et al. 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; 84(8): 909–914.
  14. Jarius S, König FB, Metz I, et al. Pattern II and pattern III MS are entities distinct from pattern I MS: evidence from cerebrospinal fluid analysis. J Neuroinflammation. 2017; 14(1): 171.
  15. Pinar A, Kurne AT, Lay I, et al. Cerebrospinal fluid oligoclonal banding patterns and intrathecal immunoglobulin synthesis: Data comparison from a wide patient group. Neurological Sciences and Neurophysiology. 2018; 35(1): 21–28.
  16. Huss AM, Halbgebauer S, Öckl P, 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. J Neurol. 2016; 263(12): 2499–2504.
  17. Schwenkenbecher P, Sarikidi A, Bönig L, et al. Clinically Isolated Syndrome According to McDonald 2010: Intrathecal IgG Synthesis Still Predictive for Conversion to Multiple Sclerosis. Int J Mol Sci. 2017; 18(10).
  18. Huss A, Abdelhak A, Halbgebauer S, et al. Intrathecal immunoglobulin M production: A promising high-risk marker in clinically isolated syndrome patients. Ann Neurol. 2018; 83(5): 1032–1036.
  19. Ferraro D, Galli V, Simone AM, et al. Cerebrospinal fluid anti-Epstein-Barr virus specific oligoclonal IgM and IgG bands in patients with clinically isolated and Guillain-Barré syndrome. J Neurovirol. 2017; 23(2): 329–334.
  20. Schwenkenbecher P, Pul R, Wurster U, et al. Common and uncommon neurological manifestations of neuroborreliosis leading to hospitalization. BMC Infect Dis. 2017; 17(1): 90.
  21. Khalil M, Salzer J. CSF neurofilament light: A universal risk biomarker in multiple sclerosis? Neurology. 2016; 87(11): 1068–1069.
  22. Gnanapavan S, Grant D, Morant S, et al. Biomarker report from the phase II lamotrigine trial in secondary progressive MS - neurofilament as a surrogate of disease progression. PLoS One. 2013; 8(8): e70019.
  23. Gunnarsson M, Malmeström C, Axelsson M, et al. Neurofilament and glial fibrillary acidic protein in multiple sclerosis. Neurology. 2004; 63(9): 1586–1590.
  24. Soelberg Sorensen P, Sellebjerg F. Neurofilament in CSF-A biomarker of disease activity and long-term prognosis in multiple sclerosis. Mult Scler. 2016; 22(9): 1112–1113.
  25. Kuhlmann T, Lingfeld G, Bitsch A, et al. Acute axonal damage in multiple sclerosis is most extensive in early disease stages and decreases over time. Brain. 2002; 125(Pt 10): 2202–2212.
  26. Disanto G, Barro C, Benkert P, et al. Swiss Multiple Sclerosis Cohort Study Group. Serum Neurofilament light: A biomarker of neuronal damage in multiple sclerosis. Ann Neurol. 2017; 81(6): 857–870.
  27. Håkansson I, Tisell A, Cassel P, et al. Neurofilament light chain in cerebrospinal fluid and prediction of disease activity in clinically isolated syndrome and relapsing-remitting multiple sclerosis. Eur J Neurol. 2017; 24(5): 703–712.
  28. Varhaug KN, Barro C, Bjørnevik K, et al. Neurofilament light chain predicts disease activity in relapsing-remitting MS. Neurol Neuroimmunol Neuroinflamm. 2018; 5(1): e422.
  29. Modvig S, Degn M, Sander B, et al. Cerebrospinal fluid levels of chitinase 3-like 1 and neurofilament light chain predict multiple sclerosis development and disability after optic neuritis. Mult Scler. 2015; 21(14): 1761–1770.
  30. Matute-Blanch C, Villar LM, Álvarez-Cermeño JC, et al. Neurofilament light chain and oligoclonal bands are prognostic biomarkers in radiologically isolated syndrome. Brain. 2018; 141(4): 1085–1093.
  31. Bhan A, Jacobsen C, Myhr KM, et al. Neurofilaments and 10-year follow-up in multiple sclerosis. Mult Scler. 2018; 24(10): 1301–1307.
  32. Kuhle J, Barro C, Disanto G, et al. Serum neurofilament light chain in early relapsing remitting MS is increased and correlates with CSF levels and with MRI measures of disease severity. Mult Scler. 2016; 22(12): 1550–1559.
  33. Novakova L, Zetterberg H, Sundström P, et al. Monitoring disease activity in multiple sclerosis using serum neurofilament light protein. Neurology. 2017; 89(22): 2230–2237.
  34. Bonneh-Barkay D, Bissel SJ, Kofler J, et al. Astrocyte and macrophage regulation of YKL-40 expression and cellular response in neuroinflammation. Brain Pathol. 2012; 22(4): 530–546.
  35. Bonneh-Barkay D, Wang G, Starkey A, et al. In vivo CHI3L1 (YKL-40) expression in astrocytes in acute and chronic neurological diseases. J Neuroinflammation. 2010; 7: 34.
  36. Comabella M, Fernández M, Martin R, et al. Cerebrospinal fluid chitinase 3-like 1 levels are associated with conversion to multiple sclerosis. Brain. 2010; 133(Pt 4): 1082–1093.
  37. Cantó E, Tintoré M, Villar LM, et al. Chitinase 3-like 1: prognostic biomarker in clinically isolated syndromes. Brain. 2015; 138(Pt 4): 918–931.
  38. Matute-Blanch C, Río J, Villar LM, et al. Chitinase 3-like 1 is associated with the response to interferon-beta treatment in multiple sclerosis. J Neuroimmunol. 2017; 303: 62–65.
  39. Møllgaard M, Degn M, Sellebjerg F, et al. Cerebrospinal fluid chitinase-3-like 2 and chitotriosidase are potential prognostic biomarkers in early multiple sclerosis. Eur J Neurol. 2016; 23(5): 898–905.
  40. Daugaard M, Rohde M, Jäättelä M. The heat shock protein 70 family: Highly homologous proteins with overlapping and distinct functions. FEBS Lett. 2007; 581(19): 3702–3710.
  41. Pockley AG, Henderson B, Multhoff G. Extracellular cell stress proteins as biomarkers of human disease. Biochem Soc Trans. 2014; 42(6): 1744–1751.
  42. Radons J. The human HSP70 family of chaperones: where do we stand? Cell Stress Chaperones. 2016; 21(3): 379–404.
  43. Mansilla MJ, Montalban X, Espejo C. Heat shock protein 70: roles in multiple sclerosis. Mol Med. 2012; 18: 1018–1028.
  44. Turturici G, Tinnirello R, Sconzo G, et al. Positive or negative involvement of heat shock proteins in multiple sclerosis pathogenesis: an overview. J Neuropathol Exp Neurol. 2014; 73(12): 1092–1106.
  45. Boiocchi C, Monti MC, Osera C, et al. Heat shock protein 70-hom gene polymorphism and protein expression in multiple sclerosis. J Neuroimmunol. 2016; 298: 189–193.
  46. Lechner P, Buck D, Sick L, et al. Serum heat shock protein 70 levels as a biomarker for inflammatory processes in multiple sclerosis. Mult Scler J Exp Transl Clin. 2018; 4(2): 2055217318767192.
  47. Khandia R, Munjal AK, Iqbal HMN, et al. Heat Shock Proteins: Therapeutic Perspectives in Inflammatory Disorders. Recent Pat Inflamm Allergy Drug Discov. 2017; 10(2): 94–104.
  48. Matysiak M, Makosa B, Walczak A, et al. Patients with multiple sclerosis resisted to glucocorticoid therapy: abnormal expression of heat-shock protein 90 in glucocorticoid receptor complex. Mult Scler. 2008; 14(7): 919–926.
  49. Madeddu R, Farace C, Tolu P, et al. Cytoskeletal proteins in the cerebrospinal fluid as biomarker of multiple sclerosis. Neurol Sci. 2013; 34(2): 181–186.
  50. Gil-Perotin S, Castillo-Villalba J, Cubas-Nuñez L, et al. Combined Cerebrospinal Fluid Neurofilament Light Chain Protein and Chitinase-3 Like-1 Levels in Defining Disease Course and Prognosis in Multiple Sclerosis. Front Neurol. 2019; 10: 1008.
  51. Sellebjerg F, Royen L, Soelberg Sørensen P, et al. Prognostic value of cerebrospinal fluid neurofilament light chain and chitinase-3-like-1 in newly diagnosed patients with multiple sclerosis. Mult Scler. 2019; 25(11): 1444–1451.

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