Biomarkers and Bioinformatics Oral Presentation

PS09.05 - Value of serum neurofilament light chain levels as a biomarker of suboptimal treatment response in MS clinical practice

  • Ö. Yaldizli
  • Ö. Yaldizli
  • P. Benkert
  • A. Maceski
  • M. Barakovic
  • R. Todea
  • A. Cagol
  • S. Schaedelin
  • G. Disanto
  • J. Oechtering
  • A. Orleth
  • D. Rey
  • T. Sinnecker
  • R. Rahmanzadeh
  • S. Zadic
  • R. Galbusera
  • L. Achtnichts
  • S. Aeschbacher
  • A. Chan
  • D. Conen
  • T. Derfuss
  • O. Findling
  • B. Fischer-Barnicol
  • K. Hrusovsky
  • H. Kropshofer
  • P. Lalive
  • J. Lieb
  • J. Lorscheider
  • P. Maggi
  • C. Müller
  • S. Müller
  • Y. Naegelin
  • J. Müller
  • J. Oksenberg
  • C. Pot
  • R. Du Pasquier
  • E. Radue
  • A. Salmen
  • J. Vehoff
  • E. Waubant
  • S. Wellmann
  • H. Wiendl
  • J. Wuerfel
  • C. Zecca
  • K. Berger
  • C. Gobbi
  • L. Kappos
  • D. Leppert
  • C. Granziera
  • J. Kuhle
Presentation Number
Presentation Topic
Biomarkers and Bioinformatics
Lecture Time
10:09 - 10:21



Serum neurofilament light chain (sNfL) reflects neuro-axonal damage and may qualify as a biomarker of suboptimal response to disease modifying therapy (DMT).


To investigate the predictive value of sNfL in clinically isolated syndrome (CIS) and relapsing-remitting (RR) MS patients with established DMT for future MS disease activity in the Swiss MS Cohort Study.


All patients were on DMT for at least 3 months. sNfL was measured 6 or 12-monthly with the NF-light®assay. The association between sNfL and age was modeled using a generalized additive model for location scale and shape. Z-scores (sNfLz) were derived thereof, reflecting the deviation of a patient sNfL value from the mean value of same age healthy controls (n=8865 samples). We used univariable mixed logistic regression models to investigate the association between sNfLz and the occurrence of clinical events (relapses, EDSS worsening [≥1.5 steps if EDSS 0; ≥1.0 if 1.0-5.5 or ≥0.5 if >5.5] in the following year in all patients, and in those fulfilling NEDA-3 criteria (no relapses, EDSS worsening, contrast enhancing or new/enlarging T2 lesions in brain MRI, based on previous year). We combined sNfLz with clinical and MRI measures of MS disease activity in the previous year (EDA-3) in a multivariable mixed logistic regression model for predicting clinical events in the following year.


sNfL was measured in 1062 patients with 5192 longitudinal samples (median age 39.7 yrs; EDSS 2.0; 4.1% CIS, 95.9% RRMS; median follow-up 5 yrs). sNfLz predicted clinical events in the following year (OR 1.21 [95%CI 1.11-1.36], p<0.001, n=4624). This effect increased in magnitude with increasing sNfLz (sNfLz >1: OR 1.41 [95%CI 1.15-1.73], p=0.001; >1.5: OR 1.80 [95%CI 1.43-2.28], p<0.001; >2: OR 2.33 [95%CI 1.74-3.14], p<0.001). Similar results were found for the prediction of future new/enlarging T2 lesions and brain volume loss. In the multivariable model, new/enlarging T2 lesions (OR 1.88 [95%CI 1.13-3.12], p=0.016) and sNfLz>1.5 (OR 2.18 [95%CI 1.21-3.90], p=0.009) predicted future clinical events (n=853), while previous EDSS worsening, previous relapses and current contrast enhancement did not. In NEDA-3 patients, change of sNfLz (per standard deviation) was associated with a 37% increased risk of clinical events in the subsequent year (OR 1.37 [95%CI 1.04-1.78], p=0.025, n=587).


Our data support the value of sNfL levels, beyond the NEDA3 concept, for treatment monitoring in MS clinical practice.