Biomarkers in Progressive Multiple Sclerosis: An Updated Review



Abstract Views
244

Downloads
187

Citations

Share

##plugins.themes.bootstrap3.article.sidebar##

Submitted Apr 10, 2023
Published Jul 4, 2023
10.24018/ejmed.2023.5.4.1760

Abstract viewed = 244 times

Table of Contents

##plugins.themes.bootstrap3.article.main##

Multiple sclerosis (MS) may begin with a relapsing-remitting course followed by insidious disability worsening independent of clinically apparent relapses. Sometimes the progression is subtle and cannot be detected with routine clinical and imaging assessments. In this review, we focus on emerging biomarkers that can be representatives of MS progression. Early detection of MS progression will result in choosing the appropriate treatments which would result in better long-term outcomes.

Keywords: Biomarker CSF MS Multiple Sclerosis Progression serum

Downloads

Download data is not yet available.

References

  1. Thompson AJ, Baranzini SE, Geurts J, Hemmer B, Ciccarelli O. Multiple sclerosis. Lancet. 2018; 391(10130): 1622-1636.
     Google Scholar
  2. Klineova S, Lublin FD. Clinical Course of Multiple Sclerosis. Cold Spring Harbor Perspectives in Medicine. 2018; 8(9): a028928.
     Google Scholar
  3. Cree BAC, Arnold DL, Chataway J, Chitnis T, Fox RJ, Pozo Ramajo A, Murphy N, Lassmann H. Secondary Progressive Multiple Sclerosis: New Insights. Neurology. 2021; 97(8): 378-388.
     Google Scholar
  4. Confavreux C, Vukusic S. Natural history of multiple sclerosis: a unifying concept. Brain. 2006; 129(Pt 3): 606-16.
     Google Scholar
  5. Confavreux C, Vukusic S. Natural history of multiple sclerosis: implications for counselling and therapy. Current Opinion in Neurology. 2002; 15(3): 257–266.
     Google Scholar
  6. Kappos L, Wolinsky JS, Giovannoni G, Arnold DL, Wang Q, Bernasconi C, Model F, et al. Contribution of Relapse-Independent Progression vs Relapse-Associated Worsening to Overall Confirmed Disability Accumulation in Typical Relapsing Multiple Sclerosis in a Pooled Analysis of 2 Randomized Clinical Trials. JAMA Neurology. 2020; 77(9): 1132–1140.
     Google Scholar
  7. Klinsing, S, Yalachkov, Y, Foerch, C. Difficulty in identification of patients with active secondary progressive multiple sclerosis by clinical classification tools. Eur J Neurol. 2022; 29: 1100-1105.
     Google Scholar
  8. Bridel C, Leurs CE, van Lierop ZYGJ, van Kempen ZLE, Dekker I, Twaalfhoven HAM, et al. Serum Neurofilament Light Association With Progression in Natalizumab-Treated Patients With Relapsing-Remitting Multiple Sclerosis. Neurology. 2021; 97(19): e1898-e1905.
     Google Scholar
  9. Pérez-Miralles F, Prefasi D, García-Merino A, Gascón-Giménez F, Medrano N, Castillo-Villalba J, et al. CSF chitinase 3-like-1 association with disability of primary progressive MS. Neurology-Neuroimmunology Neuroinflammation. 2020; 7(5).
     Google Scholar
  10. Axelsson M, Malmeström C, Nilsson S, Haghighi S, Rosengren L, Lycke J. Glial fibrillary acidic protein: a potential biomarker for progression in multiple sclerosis. Journal of Neurology. 2011; 258: 882-8.
     Google Scholar
  11. Gafson AR, Jiang X, Shen C, Kapoor R, Zetterberg H, Fox RJ, Belachew S. Serum neurofilament light and multiple sclerosis progression independent of acute inflammation. JAMA Network Open. 2022; 5(2): e2147588.
     Google Scholar
  12. Siller N, Kuhle J, Muthuraman M, Barro C, Uphaus T, Groppa S, et al. Serum neurofilament light chain is a biomarker of acute and chronic neuronal damage in early multiple sclerosis. Multiple Sclerosis Journal. 2019; 25(5): 678-86.
     Google Scholar
  13. Barro C, Benkert P, Disanto G, Tsagkas C, Amann M, Naegelin Y, et al. Serum neurofilament as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis. Brain. 2018; 141(8): 2382-91.
     Google Scholar
  14. Novakova L, Axelsson M, Khademi M, Zetterberg H, Blennow K, Malmeström C, et al. Cerebrospinal fluid biomarkers as a measure of disease activity and treatment efficacy in relapsing‐remitting multiple sclerosis. Journal of Neurochemistry. 2017; 141(2): 296-304.
     Google Scholar
  15. Malmeström C, Haghighi S, Rosengren L, Andersen O, Lycke J. Neurofilament light protein and glial fibrillary acidic protein as biological markers in MS. Neurology. 2003; 61(12): 1720-5.
     Google Scholar
  16. Benkert P, Meier S, Schaedelin S, Manouchehrinia A, Yaldizli Ö, Maceski A, et al. Serum neurofilament light chain for individual prognostication of disease activity in people with multiple sclerosis: a retrospective modelling and validation study. The Lancet Neurology. 2022; 21(3): 246-57.
     Google Scholar
  17. Martínez MA, Olsson B, Bau L, Matas E, Calvo ÁC, Andreasson U, et al. Glial and neuronal markers in cerebrospinal fluid predict progression in multiple sclerosis. Multiple Sclerosis Journal. 2015; 21(5): 550-61.
     Google Scholar
  18. Verbeek MM, Notting EA, Faas B, Claessens‐Linskens R, Jongen PJ. Increased cerebrospinal fluid chitotriosidase index in patients with multiple sclerosis. Acta Neurologica Scandinavica. 2010; 121(5): 309-14.
     Google Scholar
  19. Olsson B, Malmeström C, Basun H, Annas P, Höglund K, Lannfelt L, Andreasen N, Zetterberg H, Blennow K. Extreme stability of chitotriosidase in cerebrospinal fluid makes it a suitable marker for microglial activation in clinical trials. Journal of Alzheimer's Disease. 2012; 32(2): 273-6.
     Google Scholar
  20. Oldoni E, Smets I, Mallants K, Vandebergh M, Van Horebeek L, Poesen K, et al. CHIT1 at diagnosis reflects long‐term multiple sclerosis disease activity. Annals of Neurology. 2020; 87(4): 633-45.
     Google Scholar
  21. Hinsinger G, Galéotti N, Nabholz N, Urbach S, Rigau V, Demattei C, et al. Chitinase 3-like proteins as diagnostic and prognostic biomarkers of multiple sclerosis. Mult Scler. 2015; 21(10): 1251-61.
     Google Scholar
  22. Dahshan A, Ragaie C, Talaat FE. Chitinase-3 Like-Protein-1 in CSF: A Novel Biomarker for Progression in Multiple Sclerosis Patients. Multiple Sclerosis and Related Disorders. 2022; 59.
     Google Scholar
  23. Burman J, Raininko R, Blennow K, Zetterberg H, Axelsson M, Malmeström C. YKL-40 is a CSF biomarker of intrathecal inflammation in secondary progressive multiple sclerosis. J Neuroimmunol. 2016; 292: 52-7.
     Google Scholar
  24. Comabella M, Fernández M, Martin R, Rivera-Vallve S, Borrás E, Chiva C, et al. Cerebrospinal fluid chitinase 3-like 1 levels are associated with conversion to multiple sclerosis. Brain. 2010; 133(4): 1082-93.
     Google Scholar
  25. Schneider R, Bellenberg B, Gisevius B, Hirschberg S, Sankowski R, Prinz M, et al. Chitinase 3-like 1 and neurofilament light chain in CSF and CNS atrophy in MS. Neurol Neuroimmunol Neuroinflamm. 2021; 8(1).
     Google Scholar
  26. Comabella M, Sastre-Garriga J, Borras E, Villar LM, Saiz A, Martínez-Yélamos S, et al. CSF Chitinase 3-Like 2 Is Associated With Long-term Disability Progression in Patients With Progressive Multiple Sclerosis. Neurol Neuroimmunol Neuroinflamm. 2021; 8(6).
     Google Scholar
  27. Allen SJ, Crown SE, Handel TM. Chemokine: receptor structure, interactions, and antagonism. Annu Rev Immunol. 2007; 25: 787-820.
     Google Scholar
  28. Ziliotto, N., Bernardi F, Jakimovski D, Baroni M, Bergsland N, Ramasamy DP, et al., Increased CCL18 plasma levels are associated with neurodegenerative MRI outcomes in multiple sclerosis patients. Multiple Sclerosis and Related Disorders, 2018. 25: p. 37-42.
     Google Scholar
  29. Liu C, Cui G, Zhu M, Kang X, Guo H. Neuroinflammation in Alzheimer's disease: chemokines produced by astrocytes and chemokine receptors. Int J Clin Exp Pathol. 2014; 7(12): 8342-55.
     Google Scholar
  30. Omari KM, John G, Lango R, Raine CS. Role for CXCR2 and CXCL1 on glia in multiple sclerosis. Glia. 2006; 53(1): 24-31.
     Google Scholar
  31. Khademi M, Kockum I, Andersson ML, Iacobaeus E, Brundin L, Sellebjerg F, et al. Cerebrospinal fluid CXCL13 in multiple sclerosis: a suggestive prognostic marker for the disease course. Mult Scler. 2011; 17(3): 335-43.
     Google Scholar
  32. Franciotta D, Martino G, Zardini E, Furlan R, Bergamaschi R, Andreoni L, et al. Serum and CSF levels of MCP-1 and IP-10 in multiple sclerosis patients with acute and stable disease and undergoing immunomodulatory therapies. J Neuroimmunol. 2001; 115(1-2): 192-8.
     Google Scholar
  33. Jaworski J, Psujek M, Janczarek M, Szczerbo-Trojanowska M, Bartosik-Psujek H. Total-tau in cerebrospinal fluid of patients with multiple sclerosis decreases in secondary progressive stage of disease and reflects degree of brain atrophy. Ups J Med Sci. 2012; 117(3): 284-92.
     Google Scholar
  34. Islas-Hernandez A, Aguilar-Talamantes HS, Bertado-Cortes B, Mejia-delCastillo GD, Carrera-Pineda R, Cuevas-Garcia CF, et al. BDNF and Tau as biomarkers of severity in multiple sclerosis. Biomarkers in Medicine. 2018; 12(7): 717-726.
     Google Scholar
  35. Henderson APD, Trip SA, Schlottmann PG, Altmann DR, Garway-Heath DF, Plant GT, et al. An investigation of the retinal nerve fibre layer in progressive multiple sclerosis using optical coherence tomography. Brain. 2007; 131(1): 277-287.
     Google Scholar
  36. Saidha S, Syc SB, Durbin MK, Eckstein C, Oakley JD, Meyer SA, et al. Visual dysfunction in multiple sclerosis correlates better with optical coherence tomography derived estimates of macular ganglion cell layer thickness than peripapillary retinal nerve fiber layer thickness. Mult Scler. 2011; 17(12): 1449-63.
     Google Scholar
  37. Eklund A, Huang-Link Y, Kovácsovics B, Dahle C, Vrethem M, Lind J. OCT and VEP correlate to disability in secondary progressive multiple sclerosis. Multiple Sclerosis and Related Disorders. 2022. 68: 104255.
     Google Scholar
  38. Estiasari R, Diwyacitta A, Sidik M, Rida Ariarini NN, Sitorus F, Marwadhani SS, et al. Evaluation of Retinal Structure and Optic Nerve Function Changes in Multiple Sclerosis: Longitudinal Study with 1-Year Follow-Up. Neurol Res Int. 2021: 5573839.
     Google Scholar
  39. Sotirchos ES, Gonzalez Caldito N, Filippatou A, Fitzgerald KC, Murphy OC, Lambe J, et al. Progressive Multiple Sclerosis Is Associated with Faster and Specific Retinal Layer Atrophy. Ann Neurol. 2020; 87(6): 885-896.
     Google Scholar
  40. Jakimovski D, Zivadinov R, Vaughn CB, Ozel O, Weinstock-Guttman B. Clinical effects associated with five-year retinal nerve fiber layer thinning in multiple sclerosis. J Neurol Sci. 2021; 427: 117552.
     Google Scholar
  41. Cellerino M, Priano L, Bruschi N, Boffa G, Petracca M, Novi G, et al. Relationship Between Retinal Layer Thickness and Disability Worsening in Relapsing-Remitting and Progressive Multiple Sclerosis. Journal of Neuro-Ophthalmology. 2021; 41(3): 329-34.
     Google Scholar
  42. Oberwahrenbrock T, Schippling S, Ringelstein M, Kaufhold F, Zimmermann H, Keser N, et al. Retinal Damage in Multiple Sclerosis Disease Subtypes Measured by High-Resolution Optical Coherence Tomography. Multiple Sclerosis International. 2012; 2012: 530305.
     Google Scholar
  43. Elliott C, Wolinsky JS, Hauser SL, Kappos L, Barkhof F, Bernasconi C, et al. Slowly expanding/evolving lesions as a magnetic resonance imaging marker of chronic active multiple sclerosis lesions. Mult Scler. 2019; 25(14): 1915-1925.
     Google Scholar
  44. Elliott C, Belachew S, Wolinsky JS, Hauser SL, Kappos L, Barkhof F, et al. Chronic white matter lesion activity predicts clinical progression in primary progressive multiple sclerosis. Brain. 2019; 142(9): 2787-2799.
     Google Scholar
  45. Beynon V, George IC, Elliott C, Arnold DL, Ke J, Chen H, et al. Chronic lesion activity and disability progression in secondary progressive multiple sclerosis. BMJ Neurology Open. 2022; 4(1): e000240.
     Google Scholar


Most read articles by the same author(s)