sNfL May Predict Multiple Sclerosis Disease Activity in Individual Patients

Tilburg, Netherlands. Living room portrait of a mature adult woman suffering from Multiple Sclerosis sitting besides her wheelchair.
Researchers sought to assess the applicability of sNfL to identify people at risk for future disease activity at the group level and in individuals with multiple sclerosis.

Serum neurofilament light chain (sNfL) can be used as a biomarker for monitoring treatment efficacy and predicting disease course in individuals with multiple sclerosis (MS), according to study findings published in Lancet Neurology.

sNfL is an established marker of acute disease activity, treatment response, and predictor of long-term course of disability in MS. However, sNfL as a biomarker is limited to group-level analyses, and in personalized medicine, its routine use has not been possible, the researchers explained. Furthermore, the protein naturally varies with age and weight, which makes it difficult to establish cut-offs where “normal” values for one patient may be considered as “high” for another patient.

The objective of the current study was to evaluate whether sNfL measures could predict the risk for future disease activity at the group level and in individuals in 2 large and independent cohorts of patients with MS.

A control group of participants in 4 European and US population-based studies was included for derivation of a reference database of sNfL values. To test the reference database, the researchers prospectively collected data from participants in the Swiss MS Cohort (SMSC). Validation of the findings was conducted in data from patients with MS from the Swedish MS registry.

A total of 10,133 serum samples (samples available per control person: median 1 [interquartile range [IQR], 1-2]) from 5390 participants without evidence of CNS disease were available for developing the reference database of sNfL percentiles and Z score values. The age-related increase of sNfL percentiles and Z scores in the control group was nonlinear. The increase was exponential but had an inflection point at about age 50 years and a steeper increase afterward.

The researchers also obtained 7769 serum samples from 1313 patients in the SMSC (median number of samples per person, 6.0; IQR, 3.0-8.0). Clinical and MRI measures of disease worsening or progression were strongly and independently associated with higher sNfL Z scores in the multivariable mixed-effects model with sNfL Z scores as a dependent variable.

Compared with untreated participants, a treatment effectiveness hierarchy was observed for high-efficacy monoclonal antibody therapies vs oral therapies and of oral therapies vs platform compounds. These findings were supported in the validation cohort. The estimated additive effects on sNfL Z score were –0.14 (95% CI, –0.23 to 0.05; P =.0018) for high-efficacy monoclonal antibody treatment vs oral therapy, and –0.23 (–0.36 to 0.10; P <.0001) for oral vs platform therapy.

An sNfL Z score >1.5 was associated with an increased risk of future clinical or magnetic resonance imaging disease activity in all patients with MS (odds ratio [OR] 3.15; 95% CI, 2.35-4.23; P <.0001) and in those who were considered stable with no evidence of disease activity (2.66; 1.08-6.55; P =.034).

Changes in sNfL Z scores over time were evaluated in the mixed-effects model of disease activity and long-term treatment effects. In the first year of therapy, sNfL concentrations were reduced rapidly in treated patients and decreased only marginally in untreated participants. The reduction of the sNfL Z score was more rapid with high-efficacy monoclonal antibody therapy use vs oral therapies and platform compounds (P <.0001 for the interaction term between treatment category and treatment duration).

High-efficacy monoclonal antibody treatment, and oral therapies to a lesser extent, had sNfL concentrations that overlapped with those of the control group (ie, sNfL Z score 0), and for platform compounds the sNfL concentrations remained increased in the following 4 years.

The researchers noted that the reference database is based on a cohort of patients without clinical manifestation of somatic disease and many subclinical disease conditions could be associated with an increase in sNfL concentration.

“sNfL percentiles and Z scores could be used as a clinical method to identify subclinical disease activity in individual people with multiple sclerosis and to monitor drug response,” stated the researchers. “It is now available for clinicians by use of an Internet-based app.”

Disclosure: This research was supported in part by Biogen, Celgene, Novartis, and Roche. Some of the study authors declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of disclosures.


Benkert P, Meier S, Schaedelin S, et al. Serum neurofilament light chain for individual prognostication of disease activity in people with multiple sclerosis: a retrospective modelling and validation study. Lancet Neurol. Published online March 1, 2022. doi: 10.1016/S1474-4422(22)00009-6