Advertisement

Journal of Neurology

, Volume 265, Issue 11, pp 2540–2547 | Cite as

Delayed treatment of MS is associated with high CSF levels of IL-6 and IL-8 and worse future disease course

  • Mario Stampanoni Bassi
  • Ennio Iezzi
  • Doriana Landi
  • Fabrizia Monteleone
  • Luana Gilio
  • Ilaria Simonelli
  • Alessandra Musella
  • Georgia Mandolesi
  • Francesca De Vito
  • Roberto Furlan
  • Annamaria Finardi
  • Girolama A. Marfia
  • Diego Centonze
  • Fabio Buttari
Original Communication
  • 41 Downloads

Abstract

Background

Clinical deterioration of relapsing–remitting MS (RR-MS) patients reflects not only the number and severity of overt inflammatory and demyelinating episodes, but also subtle central damage caused by persistent exposure to inflammatory molecules.

Objective

To explore the correlation between levels of CSF inflammatory molecules at the time of diagnosis and both demographic and clinical characteristics of a large sample of RR-MS patients, as well as the predictive value of cytokine levels on their prospective disease course.

Methods

In 205 patients diagnosed with RR-MS, we measured at the time of diagnosis the CSF levels of inflammatory molecules. Clinical and MRI evaluation was collected at the time of CSF withdrawal and during a median follow-up of 3 years.

Results

The time interval between the first anamnestic episode of focal neurological dysfunction and RR-MS diagnosis was the main factor associated with high CSF levels of IL-6 and IL-8. Furthermore, elevated CSF levels of these cytokines correlated with enhanced risk of clinical and radiological disease reactivation, switch to second-line treatments, and with disability progression in the follow-up.

Conclusions

Delayed diagnosis and treatment initiation are associated with higher CSF levels of IL-6 and IL-8 in RR-MS, leading to worsening disease course and poor response to treatments.

Keywords

RR-MS CSF cytokines IL-6 IL-8 Neuroinflammation Disease activity 

Notes

Acknowledgements

The present study was supported by the Italian Ministry of Health (Ricerca Corrente), and by the 5 × 1000 grant to IRCCS Neuromed.

Author contributions

MSB: conception and design of the study, drafting a significant portion of the manuscript or figures. EI: conception and design of the study, drafting a significant portion of the manuscript or figures. DL: acquisition and analysis of data. FM: acquisition and analysis of data. LG: acquisition and analysis of data. IS: statistical analysis of data. AM: acquisition and analysis of data. GM: acquisition and analysis of data. FV: acquisition and analysis of data. RF: analysis of data. AF: analysis of data. GAM: acquisition and analysis of data. DC: conception and design of the study, drafting a significant portion of the manuscript or figures. FB: conception and design of the study, drafting a significant portion of the manuscript or figures.

Compliance with ethical standards

Conflicts of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

References

  1. 1.
    Zeis T, Graumann U, Reynolds R, Schaeren-Wiemers N (2008) Normal-appearing white matter in multiple sclerosis is in a subtle balance between inflammation and neuroprotection. Brain 131:288–303.  https://doi.org/10.1093/brain/awm291 CrossRefPubMedGoogle Scholar
  2. 2.
    Linker RA, Sendtner M, Gold R (2005) Mechanisms of axonal degeneration in EAE lessons from CNTF and MHC I knockout mice. J Neurol Sci 233:167–172.  https://doi.org/10.1016/j.jns.2005.03.021 CrossRefPubMedGoogle Scholar
  3. 3.
    Dihb-Jalbut S, Arnold DL, Cleveland DW et al (2006) Neurodegeneration and neuroprotection in multiple sclerosis and other neurodegenerative diseases. J Neuroimmunol 176:198–215CrossRefGoogle Scholar
  4. 4.
    Maimone D, Gregory S, Arnason BG, Reder AT (1991) Cytokine levels in the cerebrospinal fluid and serum of patients with multiple sclerosis. J Neuroimmunol 32:67–74CrossRefGoogle Scholar
  5. 5.
    Matejčíková Z, Mareš J, Sládková V et al (2017) Cerebrospinal fluid and serum levels of interleukin-8 in patients with multiple sclerosis and its correlation with Q-albumin. Mult Scler Relat Disord 14:12–15.  https://doi.org/10.1016/j.msard.2017.03.007 CrossRefPubMedGoogle Scholar
  6. 6.
    Kothur K, Wienholt L, Brilot F, Dale RC (2016) CSF cytokines/chemokines as biomarkers in neuroinflammatory CNS disorders: a systematic review. Cytokine 7:227–237.  https://doi.org/10.1016/j.cyto.2015.10.001 CrossRefGoogle Scholar
  7. 7.
    Magliozzi R, Howell O, Vora A et al (2007) Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain 130:1089–1104.  https://doi.org/10.1093/brain/awm038 CrossRefPubMedGoogle Scholar
  8. 8.
    Rossi S, Motta C, Studer V et al (2014) Tumor necrosis factor is elevated in progressive multiple sclerosis and causes excitotoxic neurodegeneration. Mult Scler 20:304–312.  https://doi.org/10.1177/1352458513498128 CrossRefPubMedGoogle Scholar
  9. 9.
    Rossi S, Studer V, Motta C et al (2014) Cerebrospinal fluid detection of interleukin-1β in phase of remission predicts disease progression in multiple sclerosis. J Neuroinflammation 11:32.  https://doi.org/10.1186/1742-2094-11-32 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Rossi S, Motta C, Studer V et al (2015) Subclinical central inflammation is risk for RIS and CIS conversion to MS. Mult Scler 21:1443–1452.  https://doi.org/10.1177/1352458514564482 CrossRefPubMedGoogle Scholar
  11. 11.
    Centonze D, Muzio L, Rossi S et al (2009) Inflammation triggers synaptic alteration and degeneration in experimental autoimmune encephalomyelitis. J Neurosci 29:3442–3452.  https://doi.org/10.1523/JNEUROSCI.5804-08.2009 CrossRefPubMedGoogle Scholar
  12. 12.
    Mandolesi G, Musella A, Gentile A et al (2013) Interleukin–1β alters glutamate transmission at purkinje cell synapses in a mouse model of multiple sclerosis. J Neurosci 33:12105–12121.  https://doi.org/10.1523/JNEUROSCI.5369-12.2013 CrossRefPubMedGoogle Scholar
  13. 13.
    Polman CH, Reingold SC, Banwell B et al (2011) Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria. Ann Neurol 69:292–302.  https://doi.org/10.1002/ana.22366 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33:1444–1452CrossRefGoogle Scholar
  15. 15.
    Gutcher I, Becher B (2007) APC-derived cytokines and T cell polarization in autoimmune inflammation. J Clin Investig 117:1119–1127.  https://doi.org/10.1172/JCI31720 CrossRefPubMedGoogle Scholar
  16. 16.
    Bielekova B, Komori M, Xu Q et al (2012) Cerebrospinal fluid IL-12p40, CXCL13 and IL-8 as a combinatorial biomarker of active intrathecal inflammation. PLoS One 7:e48370.  https://doi.org/10.1371/journal.pone.0048370 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Ishizu T, Osoegawa M, Mei FJ et al (2005) Intrathecal activation of the IL-17/IL-8 axis in opticospinal multiple sclerosis. Brain 128:988–1002.  https://doi.org/10.1093/brain/awh453 CrossRefPubMedGoogle Scholar
  18. 18.
    Maimone D, Guazzi GC, Annunziata P (1997) IL-6 detection in multiple sclerosis brain. J Neurol Sci 146:59–65CrossRefGoogle Scholar
  19. 19.
    Matsushita T, Tateishi T, Isobe N et al (2013) Characteristic cerebrospinal fluid cytokine/chemokine profiles in neuromyelitis optica, relapsing remitting or primary progressive multiple sclerosis. PLoS One 8:e61835.  https://doi.org/10.1371/journal.pone.0061835 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Kimura A, Takemura M, Saito K et al (2017) Increased cerebrospinal fluid progranulin correlates with interleukin-6 in the acute phase of neuromyelitis optica spectrum disorder. J Neuroimmunol 305:175–181.  https://doi.org/10.1016/j.jneuroim.2017.01.006 CrossRefPubMedGoogle Scholar
  21. 21.
    Stelmasiak Z, Kozioł-Montewka M, Dobosz B et al (2000) Interleukin-6 concentration in serum and cerebrospinal fluid in multiple sclerosis patients. Med Sci Monit 6:1104–1108PubMedGoogle Scholar
  22. 22.
    Jacobs LD, Beck RW, Simon JH et al (2000) Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. CHAMPS Study Group. N Engl J Med 343:898–904.  https://doi.org/10.1056/NEJM200009283431301 CrossRefPubMedGoogle Scholar
  23. 23.
    Comi G, Filippi M, Barkhof F et al (2001) Early Treatment of Multiple Sclerosis Study Group. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet 357:1576–1582CrossRefGoogle Scholar
  24. 24.
    Kappos L, Polman CH, Freedman MS et al (2006) Treatment with interferon beta-1b delays conversion to clinically definite and McDonald MS in patients with clinically isolated syndromes. Neurology 67:1242–1249.  https://doi.org/10.1212/01.wnl.0000237641.33768.8d CrossRefPubMedGoogle Scholar
  25. 25.
    Kappos L, Freedman MS, Polman CH et al (2009) Long-term effect of early treatment with interferon beta-1b after a first clinical event suggestive of multiple sclerosis: 5-year active treatment extension of the phase 3 BENEFIT trial. Lancet Neurol 8:987–997.  https://doi.org/10.1016/S1474-4422(09)70237-6 CrossRefPubMedGoogle Scholar
  26. 26.
    Kappos L, Edan G, Freedman MS et al (2016) The 11-year long-term follow-up study from the randomized BENEFIT CIS trial. Neurology 87:978–987.  https://doi.org/10.1212/WNL.0000000000003078 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Rossi S, Furlan R, De Chiara V et al (2012) Interleukin–1β causes synaptic hyperexcitability in multiple sclerosis. Ann Neurol 71:76–83.  https://doi.org/10.1002/ana.22512 CrossRefPubMedGoogle Scholar
  28. 28.
    Stampanoni Bassi M, Mori F, Buttari F et al (2017) Neurophysiology of synaptic functioning in multiple sclerosis. Clin Neurophysiol 128:1148–1157.  https://doi.org/10.1016/j.clinph.2017.04.006 CrossRefPubMedGoogle Scholar
  29. 29.
    Bermel RA, Bakshi R (2006) The measurement and clinical relevance of brain atrophy in multiple sclerosis. Lancet Neurol 5:158–170.  https://doi.org/10.1016/S1474-4422(06)70349-0 CrossRefPubMedGoogle Scholar
  30. 30.
    Fox NC, Jenkins R, Leary SM et al (2000) Progressive cerebral atrophy in MS: a serial study using registered, volumetric MRI. Neurology 54:807–812CrossRefGoogle Scholar
  31. 31.
    Simon HJ, Jacobs LD, Campion MK et al (1999) A longitudinal study of brain atrophy in relapsing multiple sclerosis. Neurology 53:139–148CrossRefGoogle Scholar
  32. 32.
    De Stefano N, Airas L, Grigoriadis N et al (2014) Clinical relevance of brain volume measures in multiple sclerosis. CNS Drugs 28:147–156.  https://doi.org/10.1007/s40263-014-0140-z CrossRefPubMedGoogle Scholar
  33. 33.
    Skrzipek S, Vogelgesang A, Bröker BM, Dressel A (2012) Differential effects of interferon-β1b on cytokine patterns of CD4 + and CD8 + T cells derived from RRMS and PPMS patients. Mult Scler 18:674–678.  https://doi.org/10.1177/1352458511427317 CrossRefPubMedGoogle Scholar
  34. 34.
    Gentile A, Musella A, Bullitta S et al (2016) Siponimod (BAF312) prevents synaptic neurodegeneration in experimental multiple sclerosis. J Neuroinflammation 13:207.  https://doi.org/10.1186/s12974-016-0686-4 CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Gentile A, Musella A, De Vito F et al (2018) Laquinimod ameliorates excitotoxic damage by regulating glutamate re-uptake. J Neuroinflammation 15:5.  https://doi.org/10.1186/s12974-017-1048-6 CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Thompson AJ, Banwell BL, Barkhof F et al (2017) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17:162–173.  https://doi.org/10.1016/S1474-4422(17)30470-2 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Unit of Neurology and NeurorehabilitationIRCCS NeuromedPozzilliItaly
  2. 2.Multiple Sclerosis Research Unit, Department of Systems MedicineTor Vergata UniversityRomeItaly
  3. 3.Service of Medical Statistics and Information TechnologyFatebenefratelli Foundation for Health Research and EducationRomeItaly
  4. 4.Laboratory of Neuroimmunology and Synaptic PlasticityIRCCS San Raffaele PisanaRomeItaly
  5. 5.Neuroimmunology Unit, Division of Neuroscience, Institute of Experimental Neurology (INSpe)San Raffaele Scientific InstituteMilanItaly

Personalised recommendations