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Validation of CSF free light chain in diagnosis and prognosis of multiple sclerosis and clinically isolated syndrome: prospective cohort study in Buenos Aires

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Abstract

Background

The objective was to evaluate the precision of kappa and lambda free light chains (KFLC and LFLC) in CSF for the diagnosis of multiple sclerosis (MS) and prognosis of clinically isolated syndrome (CIS).

Methods

CSF and serum samples from CIS, MS and other neurological non-MS disease were collected between 2015 and 2017. FLC concentrations were measured using immunoassay Freelite™. Results were correlated with the patients’ diagnoses and ROC curve analysis was used to determine accuracy. In CIS patients, analysis of FLC were compared in CIS converters vs. non-converter during follow-up.

Results

In the MS group (n = 41), the optimal cut-off for KFLC determined was 7 mg/L, with a diagnostic sensitivity and specificity of 95% and 97%, respectively. The optimal cut-off for LFLC was 0.7 mg/L, with a diagnostic sensitivity and specificity of 71% and 81%, respectively. 36 CIS patients were included; mean follow-up time was 28 ± 9 months, and 22 (61.1%) patients converted to MS. The median concentration of CSF K and LFLCs at CIS diagnosis was slightly higher in CIS-converters compared to non-converters, but this did not reach statistical significance (KFLC: median 7 ± 5.3 mg/L vs. 5 ± 2.3 mg/L, p = 0.11; LFLC 0.7 ± 0.33 mg/L vs. 0.5 ± 0.23 mg/L p = 0.16). A strong correlation was observed between the concentration of K and L FLCs at diagnosis and the change in PBVC during follow-up (r = 0.72 and r = 0.65, respectively).

Conclusion

KFLCs have a high sensitivity and specificity for the diagnosis of MS. FLC concentrations at CIS diagnosis were not significantly higher in CIS-converters.

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References

  1. Ebers GC (2008) Environmental factors and multiple sclerosis. Lancet Neurol 7(3):268–277

    Article  PubMed  Google Scholar 

  2. Lublin FD, Reingold SC, Cohen JA, Cutter GR, Sorensen PS, Thompson AJ, Wolinsky JS, Balcer LJ, Banwell B, Barkhof F et al (2014) Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology 83(3):278–286

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hassan-Smith G, Durant L, Tsentemeidou A, Assi LK, Faint JM, Kalra S, Douglas MR, Curnow SJ (2014) High sensitivity and specificity of elevated cerebrospinal fluid kappa free light chains in suspected multiple sclerosis. J Neuroimmunol 276(1–2):175–179

    Article  CAS  PubMed  Google Scholar 

  4. Voortman MM, Stojakovic T, Pirpamer L, Jehna M, Langkammer C, Scharnagl H, Reindl M, Ropele S, Seifert-Held T, Archelos JJ et al (2017) Prognostic value of free light chains lambda and kappa in early multiple sclerosis. Mult Scler 23(11):1496–1505

    Article  CAS  PubMed  Google Scholar 

  5. Corona T, Roman GC (2006) Multiple sclerosis in Latin America. Neuroepidemiology 26(1):1–3

    Article  PubMed  Google Scholar 

  6. Cristiano E, Rojas J, Romano M, Frider N, Machnicki G, Giunta D, Calegaro D, Corona T, Flores J, Gracia F et al (2013) The epidemiology of multiple sclerosis in Latin America and the Caribbean: a systematic review. Mult Scler 19(7):844–854

    Article  CAS  PubMed  Google Scholar 

  7. Presslauer S, Milosavljevic D, Brucke T, Bayer P, Hubl W (2008) Elevated levels of kappa free light chains in CSF support the diagnosis of multiple sclerosis. J Neurol 255(10):1508–1514

    Article  CAS  PubMed  Google Scholar 

  8. Presslauer S, Milosavljevic D, Huebl W, Parigger S, Schneider-Koch G, Bruecke T (2014) Kappa free light chains: diagnostic and prognostic relevance in MS and CIS. PLoS One 9(2):e89945

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, Fujihara K, Havrdova E, Hutchinson M, Kappos L et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302

    Article  PubMed  PubMed Central  Google Scholar 

  10. Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, Correale J, Fazekas F, Filippi M, Freedman MS et al (2018) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17(2):162–173

    Article  PubMed  Google Scholar 

  11. Rovira A, Wattjes MP, Tintore M, Tur C, Yousry TA, Sormani MP, De Stefano N, Filippi M, Auger C, Rocca MA et al (2015) Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process. Nat Rev Neurol 11(8):471–482

    Article  PubMed  Google Scholar 

  12. Smith SM, De Stefano N, Jenkinson M, Matthews PM (2001) Normalized accurate measurement of longitudinal brain change. J Comput Assist Tomogr 25(3):466–475

    Article  CAS  PubMed  Google Scholar 

  13. Smith SM, Zhang Y, Jenkinson M, Chen J, Matthews PM, Federico A, De Stefano N (2002) Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 17(1):479–489

    Article  PubMed  Google Scholar 

  14. De Stefano N, Stromillo ML, Rossi F, Battaglini M, Giorgio A, Portaccio E, Hakiki B, Malentacchi G, Gasperini C, Santangelo M et al (2011) Improving the characterization of radiologically isolated syndrome suggestive of multiple sclerosis. PLoS One 6(4):e19452

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Vrenken H, Jenkinson M, Horsfield MA, Battaglini M, van Schijndel RA, Rostrup E, Geurts JJ, Fisher E, Zijdenbos A, Ashburner J et al (2013) Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis. J Neurol 260(10):2458–2471

    Article  CAS  PubMed  Google Scholar 

  16. Chard DT, Jackson JS, Miller DH, Wheeler-Kingshott CA (2010) Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes. J Magn Reson Imaging 32(1):223–228

    Article  PubMed  Google Scholar 

  17. Puthenparampil M, Altinier S, Stropparo E, Zywicki S, Poggiali D, Cazzola C, Toffanin E, Ruggero S, Grassivaro F, Zaninotto M et al (2018) Intrathecal K free light chain synthesis in multiple sclerosis at clinical onset associates with local IgG production and improves the diagnostic value of cerebrospinal fluid examination. Mult Scler Relat Disord 25:241–245

    Article  CAS  PubMed  Google Scholar 

  18. Ganelin-Cohen E, Golderman S, Yeskaraev R, Rozenberg A, Livneh A, Kaplan B (2018) Search for new biomarkers of pediatric multiple sclerosis: application of immunoglobulin free light chain analysis. Clin Chem Lab Med 56(7):1081–1089

    Article  CAS  PubMed  Google Scholar 

  19. Presslauer S, Milosavljevic D, Huebl W, Aboulenein-Djamshidian F, Krugluger W, Deisenhammer F, Senel M, Tumani H, Hegen H (2016) Validation of kappa free light chains as a diagnostic biomarker in multiple sclerosis and clinically isolated syndrome: a multicenter study. Mult Scler 22(4):502–510

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Central Laboratory, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina

    María Soledad Sáez, María Victoria Lorenzón & Patricia Sorroche

  2. Multiple Sclerosis Center of Buenos Aires, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina

    Juan Ignacio Rojas, Francisco Sánchez, Liliana Patrucco, Jimena Míguez & Edgardo Cristiano

  3. Neurology Department, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina

    Carolina Azcona

  4. Servicio de Neurología (Neurology Department), Hospital Italiano de Buenos Aires, Gascón 450, 1181, Buenos Aires, Argentina

    Juan Ignacio Rojas

Authors
  1. María Soledad Sáez
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  2. Juan Ignacio Rojas
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  3. María Victoria Lorenzón
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  4. Francisco Sánchez
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  5. Liliana Patrucco
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  6. Jimena Míguez
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  7. Carolina Azcona
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  8. Patricia Sorroche
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  9. Edgardo Cristiano
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Corresponding author

Correspondence to Juan Ignacio Rojas.

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Sáez, M.S., Rojas, J.I., Lorenzón, M.V. et al. Validation of CSF free light chain in diagnosis and prognosis of multiple sclerosis and clinically isolated syndrome: prospective cohort study in Buenos Aires. J Neurol 266, 112–118 (2019). https://doi.org/10.1007/s00415-018-9106-2

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  • DOI: https://doi.org/10.1007/s00415-018-9106-2

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