Primer | Published:

Multiple sclerosis

Nature Reviews Disease Primersvolume 4, Article number: 43 (2018) | Download Citation


Multiple sclerosis (MS) is the most common chronic inflammatory, demyelinating and neurodegenerative disease of the central nervous system in young adults. This disorder is a heterogeneous, multifactorial, immune-mediated disease that is influenced by both genetic and environmental factors. In most patients, reversible episodes of neurological dysfunction lasting several days or weeks characterize the initial stages of the disease (that is, clinically isolated syndrome and relapsing–remitting MS). Over time, irreversible clinical and cognitive deficits develop. A minority of patients have a progressive disease course from the onset. The pathological hallmark of MS is the formation of demyelinating lesions in the brain and spinal cord, which can be associated with neuro-axonal damage. Focal lesions are thought to be caused by the infiltration of immune cells, including T cells, B cells and myeloid cells, into the central nervous system parenchyma, with associated injury. MS is associated with a substantial burden on society owing to the high cost of the available treatments and poorer employment prospects and job retention for patients and their caregivers.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Additional information

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Netherlands Brain Bank:

Change history

  • 22 November 2018

    In the originally published version of this article, in Table 4, Ocrelizumab was incorrectly referred to as an anti-CD25 antibody. This has been corrected in the HTML and PDF versions of the article to an anti-CD20 antibody.


  1. 1.

    Lublin, F. D. et al. Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology 83, 278–286 (2014). This is a proposal for a redefinition of MS clinical courses on the basis of the inclusion of disease activity (considering clinical relapse rate and imaging findings) and disease progression.

  2. 2.

    Krieger, S. C., Cook, K., De Nino, S. & Fletcher, M. The topographical model of multiple sclerosis: a dynamic visualization of disease course. Neurol. Neuroimmunol. Neuroinflamm. 3, e279 (2016).

  3. 3.

    Greer, J. M. & McCombe, P. A. Role of gender in multiple sclerosis: clinical effects and potential molecular mechanisms. J. Neuroimmunol. 234, 7–18 (2011).

  4. 4.

    Yeshokumar, A. K., Narula, S. & Banwell, B. Pediatric multiple sclerosis. Curr. Opin. Neurol. 30, 216–221 (2017).

  5. 5.

    Multiple Sclerosis International Federation. Atlas of MS 2013: mapping multiple sclerosis around the world. (2013).

  6. 6.

    Gustavsson, A. et al. Cost of disorders of the brain in Europe 2010. Eur. Neuropsychopharmacol. 21, 718–779 (2011).

  7. 7.

    Chen, A. Y., Chonghasawat, A. O. & Leadholm, K. L. Multiple sclerosis: frequency, cost, and economic burden in the United States. J. Clin. Neurosci. 45, 180–186 (2017).

  8. 8.

    Rosati, G. The prevalence of multiple sclerosis in the world: an update. Neurol. Sci. 22, 117–139 (2001).

  9. 9.

    Koch-Henriksen, N. & Sorensen, P. S. The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol. 9, 520–532 (2010).

  10. 10.

    Alonso, A. & Hernan, M. A. Temporal trends in the incidence of multiple sclerosis: a systematic review. Neurology 71, 129–135 (2008).

  11. 11.

    Orton, S. M. et al. Sex ratio of multiple sclerosis in Canada: a longitudinal study. Lancet Neurol. 5, 932–936 (2006).

  12. 12.

    Scalfari, A. et al. Mortality in patients with multiple sclerosis. Neurology 81, 184–192 (2013).

  13. 13.

    Kingwell, E. et al. Relative mortality and survival in multiple sclerosis: findings from British Columbia, Canada. J. Neurol. Neurosurg. Psychiatry 83, 61–66 (2012).

  14. 14.

    Lunde, H. M. B., Assmus, J., Myhr, K. M., Bo, L. & Grytten, N. Survival and cause of death in multiple sclerosis: a 60-year longitudinal population study. J. Neurol. Neurosurg. Psychiatry 88, 621–625 (2017).

  15. 15.

    Koch-Henriksen, N., Laursen, B., Stenager, E. & Magyari, M. Excess mortality among patients with multiple sclerosis in Denmark has dropped significantly over the past six decades: a population based study. J. Neurol. Neurosurg. Psychiatry 88, 626–631 (2017).

  16. 16.

    Burkill, S. et al. Mortality trends for multiple sclerosis patients in Sweden from 1968 to 2012. Neurology 89, 555–562 (2017).

  17. 17.

    Olsson, T., Barcellos, L. F. & Alfredsson, L. Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis. Nat. Rev. Neurol. 13, 25–36 (2017). This comprehensive review summarizes recent findings on genetic, lifestyle and environmental risk factors for MS and their possible interactions.

  18. 18.

    Mirzaei, F. et al. Gestational vitamin D and the risk of multiple sclerosis in offspring. Ann. Neurol. 70, 30–40 (2011).

  19. 19.

    Endriz, J., Ho, P. P. & Steinman, L. Time correlation between mononucleosis and initial symptoms of MS. Neurol. Neuroimmunol. Neuroinflamm. 4, e308 (2017).

  20. 20.

    Haahr, S., Plesner, A. M., Vestergaard, B. F. & Hollsberg, P. A role of late Epstein-Barr virus infection in multiple sclerosis. Acta Neurol. Scand. 109, 270–275 (2004).

  21. 21.

    Healy, B. C. et al. Smoking and disease progression in multiple sclerosis. Arch. Neurol. 66, 858–864 (2009).

  22. 22.

    Pierrot-Deseilligny, C. & Souberbielle, J. C. Vitamin D and multiple sclerosis: an update. Mult. Scler. Relat. Disord. 14, 35–45 (2017).

  23. 23.

    Harirchian, M. H., Fatehi, F., Sarraf, P., Honarvar, N. M. & Bitarafan, S. Worldwide prevalence of familial multiple sclerosis: a systematic review and meta-analysis. Mult. Scler. Relat. Disord. 20, 43–47 (2017).

  24. 24.

    Compston, A. & Coles, A. Multiple sclerosis. Lancet 359, 1221–1231 (2002).

  25. 25.

    Baranzini, S. E. & Oksenberg, J. R. The genetics of multiple sclerosis: from 0 to 200 in 50 years. Trends Genet. 33, 960–970 (2017). This review presents a historical perspective on the progresses made in MS genetics and discusses the most recent findings, which have enabled the identification of>200 loci that independently contribute to disease susceptibility and pathogenesis.

  26. 26.

    Cotsapas, C. & Mitrovic, M. Genome-wide association studies of multiple sclerosis. Clin. Transl Immunol. 7, e1018 (2018).

  27. 27.

    De Jager, P. L. et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat. Genet. 41, 776–782 (2009).

  28. 28.

    International Multiple Sclerosis Genetics Consortium. Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis. Nat. Genet. 45, 1353–1360 (2013).

  29. 29.

    Hedstrom, A. K. et al. Smoking and two human leukocyte antigen genes interact to increase the risk for multiple sclerosis. Brain 134, 653–664 (2011).

  30. 30.

    Sundqvist, E. et al. Epstein-Barr virus and multiple sclerosis: interaction with HLA. Genes Immun. 13, 14–20 (2012).

  31. 31.

    Hedstrom, A. K. et al. Interaction between adolescent obesity and HLA risk genes in the etiology of multiple sclerosis. Neurology 82, 865–872 (2014).

  32. 32.

    Mokry, L. E. et al. Vitamin D and risk of multiple sclerosis: a mendelian randomization study. PLOS Med. 12, e1001866 (2015).

  33. 33.

    Minagar, A. & Alexander, J. S. Blood-brain barrier disruption in multiple sclerosis. Mult. Scler. 9, 540–549 (2003).

  34. 34.

    Ortiz, G. G. et al. Role of the blood-brain barrier in multiple sclerosis. Arch. Med. Res. 45, 687–697 (2014).

  35. 35.

    Lucchinetti, C. et al. Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination. Ann. Neurol. 47, 707–717 (2000).

  36. 36.

    Frohman, E. M., Racke, M. K. & Raine, C. S. Multiple sclerosis — the plaque and its pathogenesis. N. Engl. J. Med. 354, 942–955 (2006).

  37. 37.

    Gilmore, C. P. et al. Regional variations in the extent and pattern of grey matter demyelination in multiple sclerosis: a comparison between the cerebral cortex, cerebellar cortex, deep grey matter nuclei and the spinal cord. J. Neurol. Neurosurg. Psychiatry 80, 182–187 (2009).

  38. 38.

    Green, A. J., McQuaid, S., Hauser, S. L., Allen, I. V. & Lyness, R. Ocular pathology in multiple sclerosis: retinal atrophy and inflammation irrespective of disease duration. Brain 133, 1591–1601 (2010).

  39. 39.

    Petrova, N., Carassiti, D., Altmann, D. R., Baker, D. & Schmierer, K. Axonal loss in the multiple sclerosis spinal cord revisited. Brain Pathol. 28, 334–348 (2017).

  40. 40.

    Sormani, M. P., Rovaris, M., Comi, G. & Filippi, M. A reassessment of the plateauing relationship between T2 lesion load and disability in MS. Neurology 73, 1538–1542 (2009).

  41. 41.

    Rocca, M. A. et al. Clinical and imaging assessment of cognitive dysfunction in multiple sclerosis. Lancet Neurol. 14, 302–317 (2015).

  42. 42.

    Frischer, J. M. et al. Clinical and pathological insights into the dynamic nature of the white matter multiple sclerosis plaque. Ann. Neurol. 78, 710–721 (2015).

  43. 43.

    Machado-Santos, J. et al. The compartmentalized inflammatory response in the multiple sclerosis brain is composed of tissue-resident CD8+T lymphocytes and B cells. Brain 141, 2066–2082 (2018).

  44. 44.

    Lassmann, H., van Horssen, J. & Mahad, D. Progressive multiple sclerosis: pathology and pathogenesis. Nat. Rev. Neurol. 8, 647–656 (2012).

  45. 45.

    Mahad, D. H., Trapp, B. D. & Lassmann, H. Pathological mechanisms in progressive multiple sclerosis. Lancet Neurol. 14, 183–193 (2015). This review discusses the complex immunological and neurodegenerative phenomena causing disease progression in patients with MS.

  46. 46.

    Prineas, J. W. et al. Immunopathology of secondary-progressive multiple sclerosis. Ann. Neurol. 50, 646–657 (2001).

  47. 47.

    Dendrou, C. A., Fugger, L. & Friese, M. A. Immunopathology of multiple sclerosis. Nat. Rev. Immunol. 15, 545–558 (2015). This comprehensive review summarizes the current understanding of MS immunopathology, focusing on the complex pathophysiological substrates involving both innate and adaptive immunity.

  48. 48.

    Lassmann, H. Multiple sclerosis pathology. Cold Spring Harb. Perspect. Med. 8, a028936 (2018).

  49. 49.

    Luchetti, S. et al. Progressive multiple sclerosis patients show substantial lesion activity that correlates with clinical disease severity and sex: a retrospective autopsy cohort analysis. Acta Neuropathol. 135, 511–528 (2018).

  50. 50.

    Kutzelnigg, A. et al. Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain 128, 2705–2712 (2005). By including pathological samples obtained from patients with MS with the main clinical phenotypes of the disease, this study shows that focal inflammation characterizes the earliest phases of MS, whereas diffuse inflammation, axonal loss and cortical demyelination occur in the progressive forms of the disease.

  51. 51.

    Evangelou, N., DeLuca, G. C., Owens, T. & Esiri, M. M. Pathological study of spinal cord atrophy in multiple sclerosis suggests limited role of local lesions. Brain 128, 29–34 (2005).

  52. 52.

    Klaver, R., De Vries, H. E., Schenk, G. J. & Geurts, J. J. Grey matter damage in multiple sclerosis: a pathology perspective. Prion 7, 66–75 (2013).

  53. 53.

    Kutzelnigg, A. et al. Widespread demyelination in the cerebellar cortex in multiple sclerosis. Brain Pathol. 17, 38–44 (2007).

  54. 54.

    Giorgio, A. et al. Cortical lesions in radiologically isolated syndrome. Neurology 77, 1896–1899 (2011).

  55. 55.

    Filippi, M. et al. Prediction of a multiple sclerosis diagnosis in patients with clinically isolated syndrome using the 2016 MAGNIMS and 2010 McDonald criteria: a retrospective study. Lancet Neurol. 17, 133–142 (2018). This multicentre study compares the performance of the 2010 McDonald criteria and the 2016 Magnetic Resonance Imaging in MS (MAGNIMS) criteria for MS diagnosis in a large group of patients with CIS.

  56. 56.

    Haider, L. et al. Multiple sclerosis deep grey matter: the relation between demyelination, neurodegeneration, inflammation and iron. J. Neurol. Neurosurg. Psychiatry 85, 1386–1395 (2014).

  57. 57.

    Vercellino, M. et al. Demyelination, inflammation, and neurodegeneration in multiple sclerosis deep gray matter. J. Neuropathol. Exp. Neurol. 68, 489–502 (2009).

  58. 58.

    Choi, S. R. et al. Meningeal inflammation plays a role in the pathology of primary progressive multiple sclerosis. Brain 135, 2925–2937 (2012).

  59. 59.

    Howell, O. W. et al. Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain 134, 2755–2771 (2011).

  60. 60.

    Magliozzi, R. et al. Inflammatory intrathecal profiles and cortical damage in multiple sclerosis. Ann. Neurol. 83, 739–755 (2018).

  61. 61.

    Peterson, J. W., Bo, L., Mork, S., Chang, A. & Trapp, B. D. Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann. Neurol. 50, 389–400 (2001).

  62. 62.

    Albert, M., Antel, J., Bruck, W. & Stadelmann, C. Extensive cortical remyelination in patients with chronic multiple sclerosis. Brain Pathol. 17, 129–138 (2007).

  63. 63.

    Strijbis, E. M. M., Kooi, E. J., van der Valk, P. & Geurts, J. J. G. Cortical remyelination is heterogeneous in multiple sclerosis. J. Neuropathol. Exp. Neurol. 76, 390–401 (2017). This analysis of brain tissue sample from 21 chronic patients with MS shows more remyelination in the grey matter than in the white matter in the brains of patients with MS, with a trend towards more remyelination in patients with PPMS.

  64. 64.

    Dutta, R. et al. Demyelination causes synaptic alterations in hippocampi from multiple sclerosis patients. Ann. Neurol. 69, 445–454 (2011).

  65. 65.

    Jurgens, T. et al. Reconstruction of single cortical projection neurons reveals primary spine loss in multiple sclerosis. Brain 139, 39–46 (2016).

  66. 66.

    Bo, L., Vedeler, C. A., Nyland, H. I., Trapp, B. D. & Mork, S. J. Subpial demyelination in the cerebral cortex of multiple sclerosis patients. J. Neuropathol. Exp. Neurol. 62, 723–732 (2003).

  67. 67.

    Patrikios, P. et al. Remyelination is extensive in a subset of multiple sclerosis patients. Brain 129, 3165–3172 (2006).

  68. 68.

    Harlow, D. E., Honce, J. M. & Miravalle, A. A. Remyelination therapy in multiple sclerosis. Front. Neurol. 6, 257 (2015).

  69. 69.

    Prineas, J. W., Barnard, R. O., Kwon, E. E., Sharer, L. R. & Cho, E. S. Multiple sclerosis: remyelination of nascent lesions. Ann. Neurol. 33, 137–151 (1993).

  70. 70.

    Franklin, R. J. & Ffrench-Constant, C. Remyelination in the CNS: from biology to therapy. Nat. Rev. Neurosci. 9, 839–855 (2008).

  71. 71.

    Goldschmidt, T., Antel, J., Konig, F. B., Bruck, W. & Kuhlmann, T. Remyelination capacity of the MS brain decreases with disease chronicity. Neurology 72, 1914–1921 (2009).

  72. 72.

    Li, R., Patterson, K. & Bar-Or, A. Reassessing the contributions of B cells in multiple sclerosis. Nat. Rev. Immunol. 19, 696–707 (2018).

  73. 73.

    Lassmann, H. Targets of therapy in progressive MS. Mult. Scler. 23, 1593–1599 (2017).

  74. 74.

    Dutta, R. & Trapp, B. D. Relapsing and progressive forms of multiple sclerosis: insights from pathology. Curr. Opin. Neurol. 27, 271–278 (2014).

  75. 75.

    Baecher-Allan, C., Kaskow, B. J. & Weiner, H. L. Multiple sclerosis: mechanisms and immunotherapy. Neuron 97, 742–768 (2018).

  76. 76.

    Kaskow, B. J. & Baecher-Allan, C. Effector T cells in multiple sclerosis. Cold Spring Harb. Perspect. Med. 8, a029025 (2018).

  77. 77.

    Kitz, A., Singer, E. & Hafler, D. Regulatory T cells: from discovery to autoimmunity. Cold Spring Harb. Perspect. Med. (2018).

  78. 78.

    Viglietta, V., Baecher-Allan, C., Weiner, H. L. & Hafler, D. A. Loss of functional suppression by CD4+CD25+ regulatory T cells in patients with multiple sclerosis. J. Exp. Med. 199, 971–979 (2004).

  79. 79.

    Venken, K. et al. Compromised CD4+ CD25high regulatory T cell function in patients with relapsing-remitting multiple sclerosis is correlated with a reduced frequency of FOXP3-positive cells and reduced FOXP3 expression at the single-cell level. Immunology 123, 79–89 (2008).

  80. 80.

    Frisullo, G. et al. Regulatory T cells fail to suppress CD4+T-bet+ T cells in relapsing multiple sclerosis patients. Immunology 127, 418–428 (2009).

  81. 81.

    Astier, A. L., Meiffren, G., Freeman, S. & Hafler, D. A. Alterations in CD46-mediated Tr1 regulatory T cells in patients with multiple sclerosis. J. Clin. Invest. 116, 3252–3257 (2006).

  82. 82.

    Fletcher, J. M. et al. CD39+Foxp3+ regulatory T cells suppress pathogenic Th17 cells and are impaired in multiple sclerosis. J. Immunol. 183, 7602–7610 (2009).

  83. 83.

    Dhaeze, T. et al. Circulating follicular regulatory T cells are defective in multiple sclerosis. J. Immunol. 195, 832–840 (2015).

  84. 84.

    Kebir, H. et al. Human TH17 lymphocytes promote blood-brain barrier disruption and central nervous system inflammation. Nat. Med. 13, 1173–1175 (2007).

  85. 85.

    Kebir, H. et al. Preferential recruitment of interferon-gamma-expressing TH17 cells in multiple sclerosis. Ann. Neurol. 66, 390–402 (2009).

  86. 86.

    Huber, M. et al. IL-17A secretion by CD8+ T cells supports Th17-mediated autoimmune encephalomyelitis. J. Clin. Invest. 123, 247–260 (2013).

  87. 87.

    van Langelaar, J. et al. T helper 17.1 cells associate with multiple sclerosis disease activity: perspectives for early intervention. Brain 141, 1334–1349 (2018).

  88. 88.

    Rasouli, J. et al. Expression of GM-CSF in T cells is increased in multiple sclerosis and suppressed by IFN-beta therapy. J. Immunol. 194, 5085–5093 (2015).

  89. 89.

    Abrahamsson, S. V. et al. Non-myeloablative autologous haematopoietic stem cell transplantation expands regulatory cells and depletes IL-17 producing mucosal-associated invariant T cells in multiple sclerosis. Brain 136, 2888–2903 (2013).

  90. 90.

    Annibali, V. et al. CD161highCD8+T cells bear pathogenetic potential in multiple sclerosis. Brain 134, 542–554 (2011).

  91. 91.

    Jelcic, I. et al. Memory B cells activate brain-homing, autoreactive CD4+ T cells in multiple sclerosis. Cell 175, 85–100 (2018).

  92. 92.

    Bar-Or, A. The immunology of multiple sclerosis. Semin. Neurol. 28, 29–45 (2008).

  93. 93.

    Kroenke, M. A., Carlson, T. J., Andjelkovic, A. V. & Segal, B. M. IL-12- and IL-23-modulated T cells induce distinct types of EAE based on histology, CNS chemokine profile, and response to cytokine inhibition. J. Exp. Med. 205, 1535–1541 (2008).

  94. 94.

    Moore, C. S. et al. miR-155 as a multiple sclerosis-relevant regulator of myeloid cell polarization. Ann. Neurol. 74, 709–720 (2013).

  95. 95.

    Ronchi, F. et al. Experimental priming of encephalitogenic Th1/Th17 cells requires pertussis toxin-driven IL-1beta production by myeloid cells. Nat. Commun. 7, 11541 (2016).

  96. 96.

    Louveau, A. et al. Structural and functional features of central nervous system lymphatic vessels. Nature 523, 337–341 (2015).

  97. 97.

    Palanichamy, A. et al. Immunoglobulin class-switched B cells form an active immune axis between CNS and periphery in multiple sclerosis. Sci. Transl Med. 6, 248ra106 (2014).

  98. 98.

    Stern, J. N. et al. B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes. Sci. Transl Med. 6, 248ra107 (2014).

  99. 99.

    Larochelle, C. et al. Melanoma cell adhesion molecule-positive CD8 T lymphocytes mediate central nervous system inflammation. Ann. Neurol. 78, 39–53 (2015).

  100. 100.

    Pare, A. et al. IL-1beta enables CNS access to CCR2hi monocytes and the generation of pathogenic cells through GM-CSF released by CNS endothelial cells. Proc. Natl Acad. Sci. USA 115, E1194–E1203 (2018).

  101. 101.

    Alvarez, J. I. et al. JAML mediates monocyte and CD8 T cell migration across the brain endothelium. Ann. Clin. Transl Neurol. 2, 1032–1037 (2015).

  102. 102.

    van der Valk, P. & Amor, S. Preactive lesions in multiple sclerosis. Curr. Opin. Neurol. 22, 207–213 (2009).

  103. 103.

    Alvarez, J. I. et al. The Hedgehog pathway promotes blood-brain barrier integrity and CNS immune quiescence. Science 334, 1727–1731 (2011).

  104. 104.

    Alvarez, J. I. et al. Focal disturbances in the blood-brain barrier are associated with formation of neuroinflammatory lesions. Neurobiol. Dis. 74, 14–24 (2015).

  105. 105.

    Darlington, P. J. et al. Natural killer cells regulate Th17 cells after autologous hematopoietic stem cell transplantation for relapsing remitting multiple sclerosis. Front. Immunol. 9, 834 (2018).

  106. 106.

    Gold, R., Hartung, H. P. & Lassmann, H. T cell apoptosis in autoimmune diseases: termination of inflammation in the nervous system and other sites with specialized immune-defense mechanisms. Trends Neurosci. 20, 399–404 (1997).

  107. 107.

    Hauser, S. L. et al. Ocrelizumab versus interferon beta-1a in relapsing multiple sclerosis. N. Engl. J. Med. 376, 221–234 (2017).

  108. 108.

    Palanichamy, A. et al. Rituximab efficiently depletes increased CD20-expressing T cells in multiple sclerosis patients. J. Immunol. 193, 580–586 (2014).

  109. 109.

    Cross, A. H., Stark, J. L., Lauber, J., Ramsbottom, M. J. & Lyons, J. A. Rituximab reduces B cells and T cells in cerebrospinal fluid of multiple sclerosis patients. J. Neuroimmunol. 180, 63–70 (2006).

  110. 110.

    Monson, N. L., Cravens, P. D., Frohman, E. M., Hawker, K. & Racke, M. K. Effect of rituximab on the peripheral blood and cerebrospinal fluid B cells in patients with primary progressive multiple sclerosis. Arch. Neurol. 62, 258–264 (2005).

  111. 111.

    Bar-Or, A. et al. Abnormal B cell cytokine responses a trigger of T cell-mediated disease in MS? Ann. Neurol. 67, 452–461 (2010).

  112. 112.

    Li, R. et al. Proinflammatory GM-CSF-producing B cells in multiple sclerosis and B cell depletion therapy. Sci. Transl Med. 7, 310ra166 (2015).

  113. 113.

    Duddy, M. et al. Distinct effector cytokine profiles of memory and naive human B cell subsets and implication in multiple sclerosis. J. Immunol. 178, 6092–6099 (2007).

  114. 114.

    Barr, T. A. et al. B cell depletion therapy ameliorates autoimmune disease through ablation of IL-6-producing B cells. J. Exp. Med. 209, 1001–1010 (2012).

  115. 115.

    Li, R. et al. Cytokine-defined B cell responses as therapeutic targets in multiple sclerosis. Front. Immunol. 6, 626 (2015).

  116. 116.

    Li, R. et al. Antibody-independent function of human B cells contributes to antifungal T cell responses. J. Immunol. 198, 3245–3254 (2017).

  117. 117.

    Sergott, R. C. et al. ATON: results from a phase II randomized trial of the B cell-targeting agent atacicept in patients with optic neuritis. J. Neurol. Sci. 351, 174–178 (2015).

  118. 118.

    Piccio, L. et al. Changes in B- and T-lymphocyte and chemokine levels with rituximab treatment in multiple sclerosis. Arch. Neurol. 67, 707–714 (2010).

  119. 119.

    Srivastava, R. et al. Potassium channel KIR4.1 as an immune target in multiple sclerosis. N. Engl. J. Med. 367, 115–123 (2012).

  120. 120.

    Brickshawana, A. et al. Investigation of the KIR4.1 potassium channel as a putative antigen in patients with multiple sclerosis: a comparative study. Lancet Neurol. 13, 795–806 (2014).

  121. 121.

    Hemmer, B. Antibodies to the inward rectifying potassium channel 4.1 in multiple sclerosis: different methodologies — conflicting results? Mult. Scler. 21, 537–539 (2015).

  122. 122.

    Narayan, R. et al. MOG antibody disease: a review of MOG antibody seropositive neuromyelitis optica spectrum disorder. Mult. Scler. Relat. Disord. 25, 66–72 (2018).

  123. 123.

    Ketelslegers, I. A. et al. Anti-MOG antibodies plead against MS diagnosis in an Acquired Demyelinating Syndromes cohort. Mult. Scler. 21, 1513–1520 (2015).

  124. 124.

    Waters, P. et al. MOG cell-based assay detects non-MS patients with inflammatory neurologic disease. Neurol. Neuroimmunol. Neuroinflamm. 2, e89 (2015).

  125. 125.

    Spadaro, M. et al. Autoantibodies to MOG in a distinct subgroup of adult multiple sclerosis. Neurol. Neuroimmunol. Neuroinflamm. 3, e257 (2016).

  126. 126.

    Magliozzi, R. et al. A gradient of neuronal loss and meningeal inflammation in multiple sclerosis. Ann. Neurol. 68, 477–493 (2010).

  127. 127.

    Zrzavy, T. et al. Loss of ‘homeostatic’ microglia and patterns of their activation in active multiple sclerosis. Brain 140, 1900–1913 (2017).

  128. 128.

    Magliozzi, R. et al. B cell enrichment and Epstein-Barr virus infection in inflammatory cortical lesions in secondary progressive multiple sclerosis. J. Neuropathol. Exp. Neurol. 72, 29–41 (2013).

  129. 129.

    Lisak, R. P. et al. Secretory products of multiple sclerosis B cells are cytotoxic to oligodendroglia in vitro. J. Neuroimmunol. 246, 85–95 (2012).

  130. 130.

    Lisak, R. P. et al. B cells from patients with multiple sclerosis induce cell death via apoptosis in neurons in vitro. J. Neuroimmunol. 309, 88–99 (2017).

  131. 131.

    Touil, H. et al. Human central nervous system astrocytes support survival and activation of B cells: implications for MS. J. Neuroinflammation 15, 114 (2018).

  132. 132.

    Miller, D. H., Chard, D. T. & Ciccarelli, O. Clinically isolated syndromes. Lancet Neurol. 11, 157–169 (2012). This review provides a summary of the main risk factors associated with a conversion to clinically definite MS and disability progression in patients with CIS.

  133. 133.

    Brownlee, W. J., Hardy, T. A., Fazekas, F. & Miller, D. H. Diagnosis of multiple sclerosis: progress and challenges. Lancet 389, 1336–1346 (2017).

  134. 134.

    Toosy, A. T., Mason, D. F. & Miller, D. H. Optic neuritis. Lancet Neurol. 13, 83–99 (2014).

  135. 135.

    Petzold, A. et al. The investigation of acute optic neuritis: a review and proposed protocol. Nat. Rev. Neurol. 10, 447–458 (2014).

  136. 136.

    Galetta, S. L. et al. Acute optic neuritis: unmet clinical needs and model for new therapies. Neurol. Neuroimmunol. Neuroinflamm. 2, e135 (2015).

  137. 137.

    Rae-Grant, A. D., Eckert, N. J., Bartz, S. & Reed, J. F. Sensory symptoms of multiple sclerosis: a hidden reservoir of morbidity. Mult. Scler. 5, 179–183 (1999).

  138. 138.

    Kanchandani, R. & Howe, J. G. Lhermitte’s sign in multiple sclerosis: a clinical survey and review of the literature. J. Neurol. Neurosurg. Psychiatry 45, 308–312 (1982).

  139. 139.

    McAlpine, D. in Multiple Sclerosis: A Reappraisal 2nd edn (eds McAlpine, D., Lumsden, C. E. & Acheson, E. D.) 132–196 (Churchill Livingstone, 1972).

  140. 140.

    Dillon, B. E. & Lemack, G. E. Urodynamics in the evaluation of the patient with multiple sclerosis: when are they helpful and how do we use them? Urol. Clin. North Am. 41, 439–444 (2014).

  141. 141.

    Zipoli, V. et al. Cognitive impairment predicts conversion to multiple sclerosis in clinically isolated syndromes. Mult. Scler. 16, 62–67 (2010).

  142. 142.

    Lerdal, A., Celius, E. G., Krupp, L. & Dahl, A. A. A prospective study of patterns of fatigue in multiple sclerosis. Eur. J. Neurol. 14, 1338–1343 (2007).

  143. 143.

    Filippi, M., Preziosa, P. & Rocca, M. A. Brain mapping in multiple sclerosis: lessons learned about the human brain. Neuroimage (2017).

  144. 144.

    Brass, S. D., Duquette, P., Proulx-Therrien, J. & Auerbach, S. Sleep disorders in patients with multiple sclerosis. Sleep Med. Rev. 14, 121–129 (2010).

  145. 145.

    Veauthier, C. & Paul, F. Sleep disorders in multiple sclerosis and their relationship to fatigue. Sleep Med. 15, 5–14 (2014).

  146. 146.

    Feinstein, A. Multiple sclerosis and depression. Mult. Scler. 17, 1276–1281 (2011).

  147. 147.

    Solaro, C. et al. The prevalence of pain in multiple sclerosis: a multicenter cross-sectional study. Neurology 63, 919–921 (2004).

  148. 148.

    Kurtzke, J. F. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33, 1444–1452 (1983).

  149. 149.

    Filippi, M. et al. MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines. Lancet Neurol. 15, 292–303 (2016).

  150. 150.

    Schumacher, F. Problems of experimental trials of therapy in multiple sclerosis. Ann. NY Acad. Sci. 122, 552–568 (1965).

  151. 151.

    Poser, C. M. et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann. Neurol. 13, 227–231 (1983).

  152. 152.

    Thompson, A. J. et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 17, 162–173 (2018). This position paper presents an update to MS diagnostic criteria on the basis of a critical revision of new evidence and an expert opinion consensus from an international panel of experts.

  153. 153.

    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 84, 909–914 (2013).

  154. 154.

    Arrambide, G. et al. The value of oligoclonal bands in the multiple sclerosis diagnostic criteria. Brain 141, 1075–1084 (2018).

  155. 155.

    Kuhle, J. et al. Conversion from clinically isolated syndrome to multiple sclerosis: a large multicentre study. Mult. Scler. 21, 1013–1024 (2015).

  156. 156.

    Leocani, L., Rocca, M. A. & Comi, G. MRI and neurophysiological measures to predict course, disability and treatment response in multiple sclerosis. Curr. Opin. Neurol. 29, 243–253 (2016).

  157. 157.

    McDonald, W. I. et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann. Neurol. 50, 121–127 (2001).

  158. 158.

    Polman, C. H. et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald criteria”. Ann. Neurol. 58, 840–846 (2005).

  159. 159.

    Polman, C. H. et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 69, 292–302 (2011).

  160. 160.

    van Waesberghe, J. H. et al. Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann. Neurol. 46, 747–754 (1999).

  161. 161.

    Rovira, A. et al. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process. Nat. Rev. Neurol. 11, 471–482 (2015).

  162. 162.

    De Stefano, N. et al. Radiologically isolated syndrome or subclinical multiple sclerosis: MAGNIMS consensus recommendations. Mult. Scler. 24, 214–221 (2018).

  163. 163.

    Okuda, D. T. et al. Radiologically isolated syndrome: 5-year risk for an initial clinical event. PLOS ONE 9, e90509 (2014).

  164. 164.

    Wattjes, M. P. et al. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis — establishing disease prognosis and monitoring patients. Nat. Rev. Neurol. 11, 597–606 (2015). This paper provides an evidence-based and expert opinion consensus of the MAGNIMS experts for the application of MRI in monitoring patients with MS and their treatments on the basis of a critical revision and discussion of state of the art MRI findings in these patients.

  165. 165.

    Brex, P. A. et al. A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N. Engl. J. Med. 346, 158–164 (2002).

  166. 166.

    Fisniku, L. K. et al. Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis. Brain 131, 808–817 (2008).

  167. 167.

    Degenhardt, A., Ramagopalan, S. V., Scalfari, A. & Ebers, G. C. Clinical prognostic factors in multiple sclerosis: a natural history review. Nat. Rev. Neurol. 5, 672–682 (2009).

  168. 168.

    Charil, A. et al. MRI and the diagnosis of multiple sclerosis: expanding the concept of “no better explanation”. Lancet Neurol. 5, 841–852 (2006).

  169. 169.

    Geraldes, R. et al. The current role of MRI in differentiating multiple sclerosis from its imaging mimics. Nat. Rev. Neurol. 14, 199–213 (2018). This review from MAGNIMS experts provides an update on the imaging characteristics that contribute to differentiate the most common mimics of MS, particularly age-related cerebrovascular disease and neuromyelitis optica.

  170. 170.

    Amato, M. P. et al. Environmental modifiable risk factors for multiple sclerosis: report from the 2016 ECTRIMS focused workshop. Mult. Scler. 24, 590–603 (2017).

  171. 171.

    Sintzel, M. B., Rametta, M. & Reder, A. T. Vitamin D and multiple sclerosis: a comprehensive review. Neurol. Ther. 7, 59–85 (2018).

  172. 172.

    Granqvist, M. et al. Comparative effectiveness of rituximab and other initial treatment choices for multiple sclerosis. JAMA Neurol. 75, 320–327 (2018).

  173. 173.

    Filippini, G. et al. Immunomodulators and immunosuppressants for multiple sclerosis: a network meta-analysis. Cochrane Database Syst. Rev. 6, CD008933 (2013).

  174. 174.

    Okwuokenye, M., Zhang, A., Pace, A. & Peace, K. E. Number needed to treat in multiple sclerosis clinical trials. Neurol. Ther. 6, 1–9 (2017).

  175. 175.

    Montalban, X. et al. ECTRIMS/EAN guideline on the pharmacological treatment of people with multiple sclerosis. Mult. Scler. 24, 96–120 (2018). This paper provides the guidelines proposed by the European Committee for Treatment and Research in MS and the European Academy of Neurology for the treatment of patients with MS.

  176. 176.

    Rae-Grant, A. et al. Practice guideline recommendations summary: disease-modifying therapies for adults with multiple sclerosis. Neurology 90, 777–788 (2018). This paper provides the guidelines proposed by the American Academy of Neurology for the treatment of patients with MS.

  177. 177.

    Muraro, P. A. et al. Long-term outcomes after autologous hematopoietic stem cell transplantation for multiple sclerosis. JAMA Neurol. 74, 459–469 (2017).

  178. 178.

    Sormani, M. P. et al. Autologous hematopoietic stem cell transplantation in multiple sclerosis: a meta-analysis. Neurology 88, 2115–2122 (2017).

  179. 179.

    Comi, G., Radaelli, M. & Soelberg Sorensen, P. Evolving concepts in the treatment of relapsing multiple sclerosis. Lancet 389, 1347–1356 (2017).

  180. 180.

    Pakpoor, J. et al. No evidence for higher risk of cancer in patients with multiple sclerosis taking cladribine. Neurol. Neuroimmunol. Neuroinflamm. 2, e158 (2015).

  181. 181.

    Plavina, T. et al. Anti-JC virus antibody levels in serum or plasma further define risk of natalizumab-associated progressive multifocal leukoencephalopathy. Ann. Neurol. 76, 802–812 (2014).

  182. 182.

    Coles, A. J. et al. Alemtuzumab CARE-MS II 5-year follow-up: efficacy and safety findings. Neurology 89, 1117–1126 (2017).

  183. 183.

    Havrdova, E. et al. Alemtuzumab CARE-MS I 5-year follow-up: durable efficacy in the absence of continuous MS therapy. Neurology 89, 1107–1116 (2017).

  184. 184.

    Piehl, F. A changing treatment landscape for multiple sclerosis: challenges and opportunities. J. Intern. Med. 275, 364–381 (2014).

  185. 185.

    Hartung, H. P. et al. Mitoxantrone in progressive multiple sclerosis: a placebo-controlled, double-blind, randomised, multicentre trial. Lancet 360, 2018–2025 (2002).

  186. 186.

    Lublin, F. et al. Oral fingolimod in primary progressive multiple sclerosis (INFORMS): a phase 3, randomised, double-blind, placebo-controlled trial. Lancet 387, 1075–1084 (2016).

  187. 187.

    Kapoor, R. et al. Effect of natalizumab on disease progression in secondary progressive multiple sclerosis (ASCEND): a phase 3, randomised, double-blind, placebo-controlled trial with an open-label extension. Lancet Neurol. 17, 405–415 (2018).

  188. 188.

    Hawker, K. et al. Rituximab in patients with primary progressive multiple sclerosis: results of a randomized double-blind placebo-controlled multicenter trial. Ann. Neurol. 66, 460–471 (2009).

  189. 189.

    Montalban, X. et al. Ocrelizumab versus placebo in primary progressive multiple sclerosis. N. Engl. J. Med. 376, 209–220 (2017). This 2-year phase III randomized clinical trial shows that in patients with primary progressive MS, compared with placebo, ocrelizumab reduces focal lesion accumulation, brain volume loss and disability progression.

  190. 190.

    Amtmann, D., Bamer, A. M., Kim, J., Chung, H. & Salem, R. People with multiple sclerosis report significantly worse symptoms and health related quality of life than the US general population as measured by PROMIS and NeuroQoL outcome measures. Disabil. Health J. 11, 99–107 (2018).

  191. 191.

    Giovannoni, G. et al. Brain health: time matters in multiple sclerosis. Mult. Scler. Relat. Disord. 9, S5–S48 (2016).

  192. 192.

    Collin, C. et al. A double-blind, randomized, placebo-controlled, parallel-group study of Sativex, in subjects with symptoms of spasticity due to multiple sclerosis. Neurol. Res. 32, 451–459 (2010).

  193. 193.

    Novotna, A. et al. A randomized, double-blind, placebo-controlled, parallel-group, enriched-design study of nabiximols (Sativex®), as add-on therapy, in subjects with refractory spasticity caused by multiple sclerosis. Eur. J. Neurol. 18, 1122–1131 (2011).

  194. 194.

    Goodman, A. D. et al. A phase 3 trial of extended release oral dalfampridine in multiple sclerosis. Ann. Neurol. 68, 494–502 (2010).

  195. 195.

    Goodman, A. D. et al. Sustained-release oral fampridine in multiple sclerosis: a randomised, double-blind, controlled trial. Lancet 373, 732–738 (2009).

  196. 196.

    Moulin, D. et al. Pharmacological management of chronic neuropathic pain: revised consensus statement from the Canadian Pain Society. Pain Res. Manag. 19, 328–335 (2014).

  197. 197.

    Aharony, S. M., Lam, O. & Corcos, J. Treatment of lower urinary tract symptoms in multiple sclerosis patients: review of the literature and current guidelines. Can. Urol. Assoc. J. 11, E110–E115 (2017).

  198. 198.

    Amato, M. P. et al. Treatment of cognitive impairment in multiple sclerosis: position paper. J. Neurol. 260, 1452–1468 (2013).

  199. 199.

    Kobelt, G. et al. New insights into the burden and costs of multiple sclerosis in Europe. Mult. Scler. 23, 1123–1136 (2017).

  200. 200.

    Marrie, R. A. et al. The incidence and prevalence of psychiatric disorders in multiple sclerosis: a systematic review. Mult. Scler. 21, 305–317 (2015).

  201. 201.

    Stankoff, B. et al. Modafinil for fatigue in MS: a randomized placebo-controlled double-blind study. Neurology 64, 1139–1143 (2005).

  202. 202.

    Asano, M. & Finlayson, M. L. Meta-analysis of three different types of fatigue management interventions for people with multiple sclerosis: exercise, education, and medication. Mult. Scler. Int. 2014, 798285 (2014).

  203. 203.

    Achiron, A. et al. Effect of alfacalcidol on multiple sclerosis-related fatigue: a randomized, double-blind placebo-controlled study. Mult. Scler. 21, 767–775 (2015).

  204. 204.

    Pottgen, J. et al. Randomised controlled trial of a self-guided online fatigue intervention in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 89, 970–976 (2018).

  205. 205.

    Gaede, G. et al. Safety and preliminary efficacy of deep transcranial magnetic stimulation in MS-related fatigue. Neurol. Neuroimmunol. Neuroinflamm. 5, e423 (2018).

  206. 206.

    Veauthier, C., Hasselmann, H., Gold, S. M. & Paul, F. The Berlin Treatment Algorithm: recommendations for tailored innovative therapeutic strategies for multiple sclerosis-related fatigue. EPMA J. 7, 25 (2016).

  207. 207.

    Fiest, K. M. et al. Systematic review and meta-analysis of interventions for depression and anxiety in persons with multiple sclerosis. Mult. Scler. Relat. Disord. 5, 12–26 (2016).

  208. 208.

    Brenner, P. & Piehl, F. Fatigue and depression in multiple sclerosis: pharmacological and non-pharmacological interventions. Acta Neurol. Scand. 134, S47–S54 (2016).

  209. 209.

    Motl, R. W. et al. Exercise in patients with multiple sclerosis. Lancet Neurol. 16, 848–856 (2017).

  210. 210.

    Sormani, M. P. & Bruzzi, P. MRI lesions as a surrogate for relapses in multiple sclerosis: a meta-analysis of randomised trials. Lancet Neurol. 12, 669–676 (2013).

  211. 211.

    Pullicino, R., Radon, M., Biswas, S., Bhojak, M. & Das, K. A. Review of the current evidence on gadolinium deposition in the brain. Clin. Neuroradiol 28, 159–169 (2018).

  212. 212.

    Filippi, M. et al. Gray matter damage predicts the accumulation of disability 13 years later in MS. Neurology 81, 1759–1767 (2013).

  213. 213.

    Rocca, M. A. et al. Brain MRI atrophy quantification in MS: from methods to clinical application. Neurology 88, 403–413 (2017).

  214. 214.

    Sormani, M. P., Arnold, D. L. & De Stefano, N. Treatment effect on brain atrophy correlates with treatment effect on disability in multiple sclerosis. Ann. Neurol. 75, 43–49 (2014).

  215. 215.

    Comabella, M. & Montalban, X. Body fluid biomarkers in multiple sclerosis. Lancet Neurol. 13, 113–126 (2014).

  216. 216.

    Kappos, L. et al. Safety and efficacy of siponimod (BAF312) in patients with relapsing-remitting multiple sclerosis: dose-blinded, randomized extension of the phase 2 BOLD study. JAMA Neurol. 73, 1089–1098 (2016).

  217. 217.

    Cohen, J. A. et al. Safety and efficacy of the selective sphingosine 1-phosphate receptor modulator ozanimod in relapsing multiple sclerosis (RADIANCE): a randomised, placebo-controlled, phase 2 trial. Lancet Neurol. 15, 373–381 (2016).

  218. 218.

    van Noort, J. M., Bsibsi, M., Nacken, P. J., Verbeek, R. & Venneker, E. H. Therapeutic intervention in multiple sclerosis with alpha B-crystallin: a randomized controlled phase IIa trial. PLOS ONE 10, e0143366 (2015).

  219. 219.

    Walczak, A., Siger, M., Ciach, A., Szczepanik, M. & Selmaj, K. Transdermal application of myelin peptides in multiple sclerosis treatment. JAMA Neurol. 70, 1105–1109 (2013).

  220. 220.

    Raftopoulos, R. et al. Phenytoin for neuroprotection in patients with acute optic neuritis: a randomised, placebo-controlled, phase 2 trial. Lancet Neurol. 15, 259–269 (2016).

  221. 221.

    Green, A. J. et al. Clemastine fumarate as a remyelinating therapy for multiple sclerosis (ReBUILD): a randomised, controlled, double-blind, crossover trial. Lancet 390, 2481–2489 (2017).

  222. 222.

    Chataway, J. et al. Effect of high-dose simvastatin on brain atrophy and disability in secondary progressive multiple sclerosis (MS-STAT): a randomised, placebo-controlled, phase 2 trial. Lancet 383, 2213–2221 (2014).

  223. 223.

    Tran, J. Q. et al. Randomized phase I trials of the safety/tolerability of anti-LINGO-1 monoclonal antibody BIIB033. Neurol. Neuroimmunol. Neuroinflamm. 1, e18 (2014).

  224. 224.

    Ranger, A. et al. Anti-LINGO-1 has no detectable immunomodulatory effects in preclinical and phase 1 studies. Neurol. Neuroimmunol. Neuroinflamm. 5, e417 (2018).

  225. 225.

    Mische, L. J. & Mowry, E. M. The evidence for dietary interventions and nutritional supplements as treatment options in multiple sclerosis: a review. Curr. Treat. Options Neurol. 20, 8 (2018).

  226. 226.

    Mitchell, A. J., Benito-Leon, J., Gonzalez, J. M. & Rivera-Navarro, J. Quality of life and its assessment in multiple sclerosis: integrating physical and psychological components of wellbeing. Lancet Neurol. 4, 556–566 (2005). This review summarizes the clinical relevance of health-related quality of life assessment in patients with MS, focusing on its practical measurement and its interplay with psychosocial and emotional domains.

  227. 227.

    Solari, A. Role of health-related quality of life measures in the routine care of people with multiple sclerosis. Health Qual. Life Outcomes 3, 16 (2005).

  228. 228.

    US Department of Health and Human Services. Guidance for industry patient-reported outcome measures: use in medical product development to support labeling claims. (2009).

  229. 229.

    Committee For Medicinal Products For Human Use. Reflection paper on the regulatory guidance for the use of health-related quality of life (HRQL) measures in the evaluation of medicinal products. (2005).

  230. 230.

    Vickrey, B. G., Hays, R. D., Harooni, R., Myers, L. W. & Ellison, G. W. A health-related quality of life measure for multiple sclerosis. Qual. Life Res. 4, 187–206 (1995).

  231. 231.

    Cella, D. F. et al. Validation of the functional assessment of multiple sclerosis quality of life instrument. Neurology 47, 129–139 (1996).

  232. 232.

    Bond, T. G. & Fox, C. M. Applying the Rasch Model: Fundamental Measurement in the Human Sciences 2nd edn (Routledge, 2007).

  233. 233.

    Ford, H. L. et al. Developing a disease-specific quality of life measure for people with multiple sclerosis. Clin. Rehabil. 15, 247–258 (2001).

  234. 234.

    Doward, L. C., McKenna, S. P., Meads, D. M., Twiss, J. & Eckert, B. J. The development of patient-reported outcome indices for multiple sclerosis (PRIMUS). Mult. Scler. 15, 1092–1102 (2009).

  235. 235.

    Simeoni, M. et al. Validation of the Multiple Sclerosis International Quality of Life questionnaire. Mult. Scler. 14, 219–230 (2008).

  236. 236.

    Giordano, A. et al. Responsiveness of patient reported outcome measures in multiple sclerosis relapses: the REMS study. J. Neurol. Neurosurg. Psychiatry 80, 1023–1028 (2009).

  237. 237.

    Gold, S. M. et al. Responsiveness of patient-based and external rating scales in multiple sclerosis: head-to-head comparison in three clinical settings. J. Neurol. Sci. 290, 102–106 (2010).

  238. 238.

    Moore, F., Vickrey, B., Fortin, K. & Lee, L. Two multiple sclerosis quality-of-life measures: comparison in a national sample. Can. J. Neurol. Sci. 42, 55–63 (2015).

  239. 239.

    Rosato, R. et al. Development of a short version of MSQOL-54 using factor analysis and item response theory. PLOS ONE 11, e0153466 (2016).

  240. 240.

    Twiss, J., Doward, L. C., McKenna, S. P. & Eckert, B. Interpreting scores on multiple sclerosis-specific patient reported outcome measures (the PRIMUS and U-FIS). Health Qual. Life Outcomes 8, 117 (2010).

  241. 241.

    Reeve, B. B. et al. Psychometric evaluation and calibration of health-related quality of life item banks: plans for the patient-reported outcomes measurement information system (PROMIS). Med. Care 45, S22–S31 (2007).

  242. 242.

    Michel, P. et al. A multidimensional computerized adaptive short-form quality of life questionnaire developed and validated for multiple sclerosis: the MusiQoL-MCAT. Medicine 95, e3068 (2016).

  243. 243.

    Solomon, A. J. et al. The contemporary spectrum of multiple sclerosis misdiagnosis: a multicenter study. Neurology 87, 1393–1399 (2016).

  244. 244.

    Sati, P. et al. The central vein sign and its clinical evaluation for the diagnosis of multiple sclerosis: a consensus statement from the North American Imaging in Multiple Sclerosis Cooperative. Nat. Rev. Neurol. 12, 714–722 (2016).

  245. 245.

    Sinnecker, T. et al. Distinct lesion morphology at 7-T MRI differentiates neuromyelitis optica from multiple sclerosis. Neurology 79, 708–714 (2012).

  246. 246.

    Maggi, P. et al. Central vein sign differentiates multiple sclerosis from central nervous system inflammatory vasculopathies. Ann. Neurol. 83, 283–294 (2018).

  247. 247.

    Mistry, N. et al. Imaging central veins in brain lesions with 3-T T2*-weighted magnetic resonance imaging differentiates multiple sclerosis from microangiopathic brain lesions. Mult. Scler. 22, 1289–1296 (2016).

  248. 248.

    Solomon, A. J. et al. Diagnostic performance of central vein sign for multiple sclerosis with a simplified three-lesion algorithm. Mult. Scler. 24, 750–757 (2017).

  249. 249.

    Norgren, N., Rosengren, L. & Stigbrand, T. Elevated neurofilament levels in neurological diseases. Brain Res. 987, 25–31 (2003).

  250. 250.

    Teunissen, C. E., Malekzadeh, A., Leurs, C., Bridel, C. & Killestein, J. Body fluid biomarkers for multiple sclerosis—the long road to clinical application. Nat. Rev. Neurol. 11, 585–596 (2015).

  251. 251.

    Arrambide, G. et al. Neurofilament light chain level is a weak risk factor for the development of MS. Neurology 87, 1076–1084 (2016).

  252. 252.

    Matute-Blanch, C. et al. Neurofilament light chain and oligoclonal bands are prognostic biomarkers in radiologically isolated syndrome. Brain 141, 1085–1093 (2018).

  253. 253.

    Khalil, M. et al. CSF neurofilament and N-acetylaspartate related brain changes in clinically isolated syndrome. Mult. Scler. 19, 436–442 (2013).

  254. 254.

    Disanto, G. et al. Serum neurofilament light: a biomarker of neuronal damage in multiple sclerosis. Ann. Neurol. 81, 857–870 (2017).

  255. 255.

    Disanto, G. et al. Serum neurofilament light chain levels are increased in patients with a clinically isolated syndrome. J. Neurol. Neurosurg. Psychiatry 87, 126–129 (2016).

  256. 256.

    Siller, N. et al. Serum neurofilament light chain is a biomarker of acute and chronic neuronal damage in early multiple sclerosis. Mult. Scler. (2018).

  257. 257.

    Petzold, A., Steenwijk, M. D., Eikelenboom, J. M., Wattjes, M. P. & Uitdehaag, B. M. Elevated CSF neurofilament proteins predict brain atrophy: a 15-year follow-up study. Mult. Scler. 22, 1154–1162 (2016).

  258. 258.

    Salzer, J., Svenningsson, A. & Sundstrom, P. Neurofilament light as a prognostic marker in multiple sclerosis. Mult. Scler. 16, 287–292 (2010).

  259. 259.

    Trentini, A. et al. N-acetylaspartate and neurofilaments as biomarkers of axonal damage in patients with progressive forms of multiple sclerosis. J. Neurol. 261, 2338–2343 (2014).

  260. 260.

    Gunnarsson, M. et al. Axonal damage in relapsing multiple sclerosis is markedly reduced by natalizumab. Ann. Neurol. 69, 83–89 (2011).

  261. 261.

    Kuhle, J. et al. Fingolimod and CSF neurofilament light chain levels in relapsing-remitting multiple sclerosis. Neurology 84, 1639–1643 (2015).

  262. 262.

    Piehl, F. et al. Plasma neurofilament light chain levels in patients with MS switching from injectable therapies to fingolimod. Mult. Scler. 24, 1046–1054 (2017).

  263. 263.

    Oberwahrenbrock, T. et al. Multicenter reliability of semiautomatic retinal layer segmentation using OCT. Neurol. Neuroimmunol. Neuroinflamm. 5, e449 (2018).

  264. 264.

    Schippling, S. et al. Quality control for retinal OCT in multiple sclerosis: validation of the OSCAR-IB criteria. Mult. Scler. 21, 163–170 (2015).

  265. 265.

    Cruz-Herranz, A. et al. The APOSTEL recommendations for reporting quantitative optical coherence tomography studies. Neurology 86, 2303–2309 (2016).

  266. 266.

    Zimmermann, H. G. et al. Association of retinal ganglion cell layer thickness with future disease activity in patients with clinically isolated syndrome. JAMA Neurol. 75, 1071–1079 (2018).

  267. 267.

    Costello, F. et al. Tracking retinal nerve fiber layer loss after optic neuritis: a prospective study using optical coherence tomography. Mult. Scler. 14, 893–905 (2008).

  268. 268.

    Petzold, A. et al. Optical coherence tomography in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol. 9, 921–932 (2010).

  269. 269.

    Petzold, A. et al. Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol. 16, 797–812 (2017).

  270. 270.

    Gabilondo, I. et al. Dynamics of retinal injury after acute optic neuritis. Ann. Neurol. 77, 517–528 (2015).

  271. 271.

    Oberwahrenbrock, T. et al. Retinal ganglion cell and inner plexiform layer thinning in clinically isolated syndrome. Mult. Scler. 19, 1887–1895 (2013).

  272. 272.

    Pulicken, M. et al. Optical coherence tomography and disease subtype in multiple sclerosis. Neurology 69, 2085–2092 (2007).

  273. 273.

    Narayanan, D. et al. Tracking changes over time in retinal nerve fiber layer and ganglion cell-inner plexiform layer thickness in multiple sclerosis. Mult. Scler. 20, 1331–1341 (2014).

  274. 274.

    Lambe, J., Murphy, O. C. & Saidha, S. Can optical coherence tomography be used to guide treatment decisions in adult or pediatric multiple sclerosis? Curr. Treat. Options Neurol. 20, 9 (2018).

  275. 275.

    Gordon-Lipkin, E. et al. Retinal nerve fiber layer is associated with brain atrophy in multiple sclerosis. Neurology 69, 1603–1609 (2007).

  276. 276.

    Saidha, S. et al. Relationships between retinal axonal and neuronal measures and global central nervous system pathology in multiple sclerosis. JAMA Neurol. 70, 34–43 (2013).

  277. 277.

    Balcer, L. J., Miller, D. H., Reingold, S. C. & Cohen, J. A. Vision and vision-related outcome measures in multiple sclerosis. Brain 138, 11–27 (2015).

  278. 278.

    Seewann, A. et al. Postmortem verification of MS cortical lesion detection with 3D DIR. Neurology 78, 302–308 (2012).

  279. 279.

    Calabrese, M. et al. No MRI evidence of cortical lesions in neuromyelitis optica. Neurology 79, 1671–1676 (2012).

  280. 280.

    Absinta, M. et al. Patients with migraine do not have MRI-visible cortical lesions. J. Neurol. 259, 2695–2698 (2012).

  281. 281.

    Daams, M., Geurts, J. J. & Barkhof, F. Cortical imaging in multiple sclerosis: recent findings and ‘grand challenges’. Curr. Opin. Neurol. 26, 345–352 (2013).

  282. 282.

    Rocca, M. A. et al. Long-term disability progression in primary progressive multiple sclerosis: a 15-year study. Brain 140, 2814–2819 (2017).

  283. 283.

    Filippi, M., Preziosa, P. & Rocca, M. A. Magnetic resonance outcome measures in multiple sclerosis trials: time to rethink? Curr. Opin. Neurol. 27, 290–299 (2014).

  284. 284.

    Trojano, M. et al. Treatment decisions in multiple sclerosis — insights from real-world observational studies. Nat. Rev. Neurol. 13, 105–118 (2017).

  285. 285.

    Kalincik, T. et al. Towards personalized therapy for multiple sclerosis: prediction of individual treatment response. Brain 140, 2426–2443 (2017).

  286. 286.

    Havrdova, E. et al. Effect of natalizumab on clinical and radiological disease activity in multiple sclerosis: a retrospective analysis of the natalizumab safety and efficacy in relapsing-remitting multiple sclerosis (AFFIRM) study. Lancet Neurol. 8, 254–260 (2009).

  287. 287.

    Giovannoni, G., Tomic, D., Bright, J. R. & Havrdová, E. “No evident disease activity”: the use of combined assessments in the management of patients with multiple sclerosis. Mult. Scler. 23, 1179–1187 (2017).

  288. 288.

    Parks, N. E., Flanagan, E. P., Lucchinetti, C. F. & Wingerchuk, D. M. NEDA treatment target? No evident disease activity as an actionable outcome in practice. J. Neurol. Sci. 383, 31–34 (2017).

  289. 289.

    Rotstein, D. L., Healy, B. C., Malik, M. T., Chitnis, T. & Weiner, H. L. Evaluation of no evidence of disease activity in a 7-year longitudinal multiple sclerosis cohort. JAMA Neurol. 72, 152–158 (2015).

  290. 290.

    De Stefano, N. et al. Long-term assessment of no evidence of disease activity in relapsing-remitting MS. Neurology 85, 1722–1723 (2015).

  291. 291.

    Damasceno, A., Damasceno, B. P. & Cendes, F. No evidence of disease activity in multiple sclerosis: implications on cognition and brain atrophy. Mult. Scler. 22, 64–72 (2016).

  292. 292.

    Stangel, M., Penner, I. K., Kallmann, B. A., Lukas, C. & Kieseier, B. C. Towards the implementation of ‘no evidence of disease activity’ in multiple sclerosis treatment: the multiple sclerosis decision model. Ther. Adv. Neurol. Disord. 8, 3–13 (2015).

  293. 293.

    Kappos, L. et al. Inclusion of brain volume loss in a revised measure of ‘no evidence of disease activity’ (NEDA-4) in relapsing-remitting multiple sclerosis. Mult. Scler. 22, 1297–1305 (2016).

  294. 294.

    Marrie, R. A. & Horwitz, R. I. Emerging effects of comorbidities on multiple sclerosis. Lancet Neurol. 9, 820–828 (2010).

  295. 295.

    Marrie, R. A. Comorbidity in multiple sclerosis: implications for patient care. Nat. Rev. Neurol. 13, 375–382 (2017). This paper provides an extensive summary of the prevalence of comorbidity in MS and a discussion of the effects of comorbidity on clinically relevant outcomes in MS and of the potential implications for treatment.

  296. 296.

    Marrie, R. A. et al. Recommendations for observational studies of comorbidity in multiple sclerosis. Neurology 86, 1446–1453 (2016).

  297. 297.

    Marrie, R. A. et al. The challenge of comorbidity in clinical trials for multiple sclerosis. Neurology 86, 1437–1445 (2016).

  298. 298.

    Zhang, T. et al. Examining the effects of comorbidities on disease-modifying therapy use in multiple sclerosis. Neurology 86, 1287–1295 (2016).

  299. 299.

    Cao, Y. et al. Functional inflammatory profiles distinguish myelin-reactive T cells from patients with multiple sclerosis. Sci. Transl Med. 7, 287ra74 (2015).

  300. 300.

    Dhaunchak, A. S. et al. Implication of perturbed axoglial apparatus in early pediatric multiple sclerosis. Ann. Neurol. 71, 601–613 (2012).

  301. 301.

    Ascherio, A. & Munger, K. L. Epidemiology of multiple sclerosis: from risk factors to prevention — an update. Semin. Neurol. 36, 103–114 (2016).

  302. 302.

    Yea, C. et al. Epstein-Barr virus in oral shedding of children with multiple sclerosis. Neurology 81, 1392–1399 (2013).

  303. 303.

    Lunemann, J. D. et al. EBNA1-specific T cells from patients with multiple sclerosis cross react with myelin antigens and co-produce IFN-gamma and IL-2. J. Exp. Med. 205, 1763–1773 (2008).

  304. 304.

    Lunemann, J. D. et al. Elevated Epstein-Barr virus-encoded nuclear antigen-1 immune responses predict conversion to multiple sclerosis. Ann. Neurol. 67, 159–169 (2010).

  305. 305.

    Angelini, D. F. et al. Increased CD8+ T cell response to Epstein-Barr virus lytic antigens in the active phase of multiple sclerosis. PLOS Pathog. 9, e1003220 (2013).

  306. 306.

    Quintana, F. J. et al. Epitope spreading as an early pathogenic event in pediatric multiple sclerosis. Neurology 83, 2219–2226 (2014).

  307. 307.

    Ahmed, R. M. et al. A practical approach to diagnosing adult onset leukodystrophies. J. Neurol. Neurosurg. Psychiatry 85, 770–781 (2014).

  308. 308.

    Chun, B. Y. & Rizzo, J. F. 3rd Dominant optic atrophy and Leber’s hereditary optic neuropathy: update on clinical features and current therapeutic approaches. Semin. Pediatr. Neurol. 24, 129–134 (2017).

  309. 309.

    Kumar, N., Ahlskog, J. E., Klein, C. J. & Port, J. D. Imaging features of copper deficiency myelopathy: a study of 25 cases. Neuroradiology 48, 78–83 (2006).

  310. 310.

    Chabriat, H., Joutel, A., Dichgans, M., Tournier-Lasserve, E. & Bousser, M. G. Cadasil. Lancet Neurol. 8, 643–653 (2009).

  311. 311.

    Wingerchuk, D. M. et al. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology 85, 177–189 (2015).

  312. 312.

    Jarius, S. et al. MOG encephalomyelitis: international recommendations on diagnosis and antibody testing. J. Neuroinflamm. 15, 134 (2018).

  313. 313.

    Tenembaum, S., Chitnis, T., Ness, J. & Hahn, J. S. Acute disseminated encephalomyelitis. Neurology 68, S23–S36 (2007).

  314. 314.

    Tobin, W. O. et al. Diagnostic criteria for chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS). Brain 140, 2415–2425 (2017).

  315. 315.

    Simon, J. H. & Kleinschmidt-DeMasters, B. K. Variants of multiple sclerosis. Neuroimaging Clin. N. Am. 18, 703–716 (2008).

  316. 316.

    Lublin, F. D. & Reingold, S. C. Defining the clinical course of multiple sclerosis: results of an international survey. Neurology 46, 907–911 (1996).

  317. 317.

    McAlpine, D. Multiple sclerosis: a review. BMJ 2, 292–295 (1973).

  318. 318.

    McDonald, W. I. Relapse, remission, and progression in multiple sclerosis. N. Engl. J. Med. 343, 1486–1487 (2000).

  319. 319.

    Patzold, U. & Pocklington, P. R. Course of multiple sclerosis: first results of a prospective study carried out of 102 MS patients from 1976–1980. Acta Neurol. Scand. 65, 248–266 (1982).

  320. 320.

    Di Pauli, F. et al. Smoking is a risk factor for early conversion to clinically definite multiple sclerosis. Mult. Scler. 14, 1026–1030 (2008).

  321. 321.

    Martinelli, V. et al. Vitamin D levels and risk of multiple sclerosis in patients with clinically isolated syndromes. Mult. Scler. 20, 147–155 (2014).

  322. 322.

    Gianfrancesco, M. A. et al. Obesity during childhood and adolescence increases susceptibility to multiple sclerosis after accounting for established genetic and environmental risk factors. Obes. Res. Clin. Pract. 8, e435–e447 (2014).

  323. 323.

    Hedstrom, A. K., Olsson, T. & Alfredsson, L. High body mass index before age 20 is associated with increased risk for multiple sclerosis in both men and women. Mult. Scler. 18, 1334–1336 (2012).

  324. 324.

    De Jager, P. L. et al. Integration of genetic risk factors into a clinical algorithm for multiple sclerosis susceptibility: a weighted genetic risk score. Lancet Neurol. 8, 1111–1119 (2009).

  325. 325.

    Kelly, M. A. et al. The influence of HLA-DR and -DQ alleles on progression to multiple sclerosis following a clinically isolated syndrome. Hum. Immunol. 37, 185–191 (1993).

  326. 326.

    Mowry, E. M. et al. Clinical predictors of early second event in patients with clinically isolated syndrome. J. Neurol. 256, 1061–1066 (2009).

  327. 327.

    Sidhom, Y. et al. Fast multiple sclerosis progression in North Africans: both genetics and environment matter. Neurology 88, 1218–1225 (2017).

  328. 328.

    Dobson, R., Ramagopalan, S. & Giovannoni, G. The effect of gender in clinically isolated syndrome (CIS): a meta-analysis. Mult. Scler. 18, 600–604 (2012).

  329. 329.

    Confavreux, C., Vukusic, S. & Adeleine, P. Early clinical predictors and progression of irreversible disability in multiple sclerosis: an amnesic process. Brain 126, 770–782 (2003).

  330. 330.

    Bove, R. M. et al. Effect of gender on late-onset multiple sclerosis. Mult. Scler. 18, 1472–1479 (2012).

  331. 331.

    Guillemin, F. et al. Older age at multiple sclerosis onset is an independent factor of poor prognosis: a population-based cohort study. Neuroepidemiology 48, 179–187 (2017).

  332. 332.

    Eriksson, M., Andersen, O. & Runmarker, B. Long-term follow up of patients with clinically isolated syndromes, relapsing-remitting and secondary progressive multiple sclerosis. Mult. Scler. 9, 260–274 (2003).

  333. 333.

    Tintore, M. et al. Defining high, medium and low impact prognostic factors for developing multiple sclerosis. Brain 138, 1863–1874 (2015).

  334. 334.

    Comi, G. et al. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet 357, 1576–1582 (2001).

  335. 335.

    Nielsen, J. M. et al. MRI characteristics are predictive for CDMS in monofocal, but not in multifocal patients with a clinically isolated syndrome. BMC Neurol. 9, 19 (2009).

  336. 336.

    Scalfari, A. et al. The natural history of multiple sclerosis, a geographically based study 10: relapses and long-term disability. Brain 133, 1914–1929 (2010).

  337. 337.

    Martinez, M. A. et al. Glial and neuronal markers in cerebrospinal fluid predict progression in multiple sclerosis. Mult. Scler. 21, 550–561 (2015).

  338. 338.

    Minneboo, A. et al. Infratentorial lesions predict long-term disability in patients with initial findings suggestive of multiple sclerosis. Arch. Neurol. 61, 217–221 (2004).

  339. 339.

    Tintore, M. et al. Brainstem lesions in clinically isolated syndromes. Neurology 75, 1933–1938 (2010).

  340. 340.

    Arrambide, G. et al. Spinal cord lesions: a modest contributor to diagnosis in clinically isolated syndromes but a relevant prognostic factor. Mult. Scler. 24, 301–312 (2017).

  341. 341.

    Sombekke, M. H. et al. Spinal cord lesions in patients with clinically isolated syndrome: a powerful tool in diagnosis and prognosis. Neurology 80, 69–75 (2013).

  342. 342.

    Brownlee, W. J. et al. Association of asymptomatic spinal cord lesions and atrophy with disability 5 years after a clinically isolated syndrome. Mult. Scler. 23, 665–674 (2017).

  343. 343.

    Johnson, K. P. et al. Copolymer 1 reduces relapse rate and improves disability in relapsing-remitting multiple sclerosis: results of a phase III multicenter, double-blind placebo-controlled trial. Neurology 45, 1268–1276 (1995).

  344. 344.

    Ebers, G. C. & PRISMS Study Group. Randomised double-blind placebo-controlled study of interferon β-1a in relapsing/remitting multiple sclerosis. Lancet 352, 1498–1504 (1998).

  345. 345.

    Jacobs, L. D. et al. Intramuscular interferon beta-1a for disease progression in relapsing multiple sclerosis. Ann. Neurol. 39, 285–294 (1996).

  346. 346.

    The IFNB Multiple Sclerosis Study Group. Interferon beta-1b is effective in relapsing-remitting multiple sclerosis. Neurology 43, 655–661 (1993).

  347. 347.

    Calabresi, P. A. et al. Pegylated interferon beta-1a for relapsing-remitting multiple sclerosis (ADVANCE): a randomised, phase 3, double-blind study. Lancet Neurol. 13, 657–665 (2014).

  348. 348.

    Confavreux, C. et al. Oral teriflunomide for patients with relapsing multiple sclerosis (TOWER): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Neurol. 13, 247–256 (2014).

  349. 349.

    O’Connor, P. et al. Randomized trial of oral teriflunomide for relapsing multiple sclerosis. N. Engl. J. Med. 365, 1293–1303 (2011).

  350. 350.

    Fox, R. J. et al. Placebo-controlled phase 3 study of oral BG-12 or glatiramer in multiple sclerosis. N. Engl. J. Med. 367, 1087–1097 (2012).

  351. 351.

    Gold, R. et al. Placebo-controlled phase 3 study of oral BG-12 for relapsing multiple sclerosis. N. Engl. J. Med. 367, 1098–1107 (2012).

  352. 352.

    Kappos, L. et al. A placebo-controlled trial of oral fingolimod in relapsing multiple sclerosis. N. Engl. J. Med. 362, 387–401 (2010).

  353. 353.

    Calabresi, P. A. et al. Safety and efficacy of fingolimod in patients with relapsing-remitting multiple sclerosis (FREEDOMS II): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Neurol. 13, 545–556 (2014).

  354. 354.

    Kappos, L. et al. Daclizumab HYP versus interferon beta-1a in relapsing multiple sclerosis. N. Engl. J. Med. 373, 1418–1428 (2015).

  355. 355.

    Cohen, J. A. et al. Alemtuzumab versus interferon beta 1a as first-line treatment for patients with relapsing-remitting multiple sclerosis: a randomised controlled phase 3 trial. Lancet 380, 1819–1828 (2012).

  356. 356.

    Coles, A. J. et al. Alemtuzumab for patients with relapsing multiple sclerosis after disease-modifying therapy: a randomised controlled phase 3 trial. Lancet 380, 1829–1839 (2012).

  357. 357.

    Giovannoni, G. et al. A placebo-controlled trial of oral cladribine for relapsing multiple sclerosis. N. Engl. J. Med. 362, 416–426 (2010).

  358. 358.

    Polman, C. H. et al. A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N. Engl. J. Med. 354, 899–910 (2006).

  359. 359.

    Rudick, R. A. et al. Natalizumab plus interferon beta-1a for relapsing multiple sclerosis. N. Engl. J. Med. 354, 911–923 (2006).

Download references

Reviewer information

Nature Reviews Disease Primers thanks M. Amato, R. Gold, H. Lassman and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information


  1. Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy

    • Massimo Filippi
    • , Paolo Preziosa
    •  & Maria A. Rocca
  2. Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy

    • Massimo Filippi
    • , Paolo Preziosa
    •  & Maria A. Rocca
  3. Department of Neurology and Center for Neuroinflammation and Experimental Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Amit Bar-Or
  4. Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden

    • Fredrik Piehl
  5. Department of Neurology, Karolinska University Hospital, Stockholm, Sweden

    • Fredrik Piehl
  6. Neuroimmunology Unit, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden

    • Fredrik Piehl
  7. Unit of Neuroepidemiology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy

    • Alessandra Solari
  8. Service de Neurologie, Sclérose en Plaques, Pathologies de la Myéline et Neuro-inflammation, Fondation Eugène Devic EDMUS Contre la Sclérose en Plaques, Hôpital Neurologique Pierre Wertheimer, Hospices Civils de Lyon, Lyon, France

    • Sandra Vukusic


  1. Search for Massimo Filippi in:

  2. Search for Amit Bar-Or in:

  3. Search for Fredrik Piehl in:

  4. Search for Paolo Preziosa in:

  5. Search for Alessandra Solari in:

  6. Search for Sandra Vukusic in:

  7. Search for Maria A. Rocca in:


Introduction (M.F.); Epidemiology (S.V.); Mechanisms/pathophysiology (P.P. and A.B.-O.); Diagnosis, screening and prevention (P.P. and M.A.R.); Management (F.P.); Quality of life (A.S.); Outlook (all authors); Overview of Primer (M.F.).

Competing interests

M.F. is Editor-in-Chief of the Journal of Neurology, has received compensation for consulting services and/or speaking activities from Biogen Idec, Merck-Serono, Novartis and Teva and receives research support from ARiSLA (Fondazione Italiana di Ricerca per la SLA), Biogen Idec, Fondazione Italiana Sclerosi Multipla, the Italian Ministry of Health, Novartis, Roche and Teva. A.B.-O. has participated as a speaker in meetings sponsored by and received consulting fees and/or grant support from Biogen Idec, Celgene/Receptos, GlaxoSmithKline, Medimmune, Merck/EMD Serono, Novartis, Roche/Genentech and Sanofi-Genzyme. F.P. has received unrestricted academic research grants from Biogen, Genzyme and Novartis, and on behalf of Frederik Piehl, his department has received travel support and/or compensation for lectures and/or participation in advisory boards from Biogen, Genzyme, Merck-Serono, Novartis, Roche and Teva, which have been exclusively used for the support of research activities. P.P. has received speakers honoraria from Biogen Idec, Excemed, Merck-Serono and Novartis. A.S. was a board member of Merck-Serono and Novartis and received speaker honoraria from Almirall, Excemed, Genzyme, Merck-Serono and Teva. S.V. has received consulting and lecturing fees, travel grants and research support from Biogen, Celgene, Genentech, Genzyme, MedDay, Merck-Serono, Novartis, Roche, Sanofi-Aventis and Teva. M.A.R. has received speakers honoraria from Biogen Idec, Genzyme, Merck-Serono, Novartis, Roche, Sanofi-Aventis and Teva and receives research support from the Fondazione Italiana Sclerosi Multipla and the Italian Ministry of Health.

Corresponding author

Correspondence to Massimo Filippi.

About this article

Publication history