The study, led by Valerio Nicolella and Marcello Moccia of Federico II University of Naples, included 792 people with multiple sclerosis and 302 healthy controls, for a total of 1,094 participants. Crucially, the researchers deliberately selected a clinically stable population: every person with multiple sclerosis included in the analysis had shown no evidence of disease activity in the previous year, with no clinical relapses, no new MRI lesions, and no progression on the Expanded Disability Status Scale, and none went on to develop relapses or radiological activity during follow-up. This design choice matters, because neurofilament light chain levels are known to spike during acute inflammatory attacks. By excluding anyone with recent or subsequent disease activity, the team could focus on what the biomarker says about chronic, slowly accumulating neuroaxonal damage rather than transient inflammatory flares.

Neurofilament light chain is a structural protein of nerve fibres that leaks into the blood when axons are injured. Its concentration rises steadily with age in healthy people, following a non-linear trajectory with a steeper climb after around age fifty, and it also rises in neurological diseases that destroy nerve tissue. Because of this dual sensitivity, the protein must always be interpreted in the context of a person’s age. The Italian team turned that necessity into an opportunity. Using age-specific reference cut-offs derived from large cohorts of healthy individuals, they assigned each participant a so-called NfL-derived age: if the protein level exceeded the threshold for the person’s chronological age band, the individual was classified as biologically older than their birth certificate suggested. The gap between this NfL-derived age and chronological age became the study’s central metric.

The results were striking. Even though absolute neurofilament levels were, on average, higher in the older control group than in the multiple sclerosis group, the relationship between chronological age and NfL-derived age was markedly weaker in the patients. In controls, chronological age strongly predicted the NfL-derived age category, with an odds ratio of 7.23, whereas in people with multiple sclerosis the association was much looser, with an odds ratio of 2.67. When the two groups were compared directly, individuals with multiple sclerosis had a 45 percent higher likelihood of having an NfL-derived age above their chronological age than controls, with an odds ratio of 1.44 and a p-value of 0.007. In other words, disease-related neuroaxonal injury appears to inject variability into what is otherwise a predictable, age-driven trajectory, shifting the biological profile of many patients toward an older brain.

The clinical correlates of this NfL age gap were equally informative. Each one-point increase on the Expanded Disability Status Scale was associated with a higher gap, with a coefficient of 0.147, and patients with a progressive disease course showed a significantly larger gap than those with relapsing disease, with a coefficient of 0.34. Notably, the gap was not associated with disease duration or with the class of disease-modifying treatment a patient was taking, although each additional previous therapy was linked to a slightly larger gap. This pattern suggests that accelerated neuroaxonal ageing in multiple sclerosis tracks disease severity and progression rather than simply the passage of time since diagnosis, echoing earlier MRI-based studies in which the brain age gap estimated from structural scans was higher in patients with more severe disease.

The researchers were careful to position their metric within the broader landscape of biological ageing research. Epigenetic clocks, telomere length, and plasma proteomic signatures capture systemic ageing across the whole organism, whereas neurofilament light chain reflects a brain-specific dimension of biological age. Recent work on plasma proteomics has shown that brain-derived proteins, most prominently neurofilament light chain, trace a distinct ageing trajectory that correlates only weakly with organism-wide ageing markers and with MRI-derived estimates of brain ageing. The Naples team argues that this is a feature rather than a flaw: a blood-based neuroaxonal marker offers a scalable, inexpensive approximation of brain ageing that can be measured in routine clinical practice, without the cost and complexity of brain imaging pipelines or genome-wide methylation assays.

Methodologically, the study was rigorous in its handling of the biomarker’s quirks. Plasma samples were drawn fasting, processed within three hours, and quantified with the Fujirebio Lumipulse immunoassay, with values then converted to SIMOA equivalents using published algorithms so that the age-specific reference cut-offs of Simrén and colleagues could be applied. Because the resulting age categories are ordinal, the researchers converted them into numerical ranks and defined the NfL age gap as the difference between the NfL-derived rank and the chronological rank, a bounded variable ranging from minus three to plus four. Statistical models, including ordered and generalized ordered logistic regression and linear regression adjusted for age and sex, were used to test the associations, and sensitivity analyses restricted to patients without confirmed disability progression yielded consistent results.

The study also has honest limitations that temper the enthusiasm. Controls were older than the patients on average, 50.6 versus 47.4 years, which explains their higher absolute neurofilament levels, although the analysis focused on within-person age gaps rather than raw group comparisons. Information on comorbidities and body mass index was lacking, and both are known to influence circulating neurofilament levels, partly through effects on blood volume and the distribution of the protein outside the nervous system. The broad 18-to-50-year reference band also limits precision, particularly for individuals near its edges, and the reference cut-offs themselves represent high-percentile red-flag thresholds rather than normative ageing curves. Perhaps most importantly, the NfL age gap did not predict the risk of future EDSS progression in Cox models, a null result consistent with emerging evidence that disability accumulation may be tracked more closely by glial markers such as glial fibrillary acidic protein than by neurofilament light chain alone.

Those caveats aside, the implications are considerable. If neurofilament light chain can flag patients whose brains are biologically older than their years, clinicians may gain a tool for risk stratification that goes beyond what chronological age or disability scores alone can offer, potentially informing decisions about when to escalate therapy or when to consider neuroprotective and reparative strategies in clinical trials. The authors emphasize that the metric should be viewed as a dynamic marker of neuroaxonal injury relative to age rather than a definitive brain age clock, and that validation in more diverse populations, including patients with active inflammatory disease, is still needed. Future studies combining neurofilament light chain with GFAP and other emerging biomarkers may refine these ageing models further. For now, the message is provocative and simple: multiple sclerosis leaves a measurable fingerprint of accelerated brain ageing in the blood, and that fingerprint is visible even in patients whose disease appears, by every conventional measure, to be quiet.

Subject of Research: Neurofilament light chain-derived biological brain age and its clinical correlates in multiple sclerosis

Article Title: Evaluating the neurofilament light chain-derived gap between biological and chronological age in multiple sclerosis and controls

Article References: Nicolella, V., Polito, C., Criscuolo, V., Varelli, M., Fasano, S., Fiorenza, M., Pascarella, G., Carotenuto, A., Petracca, M., Lanzillo, R., Castaldo, G., Morra, V. B., Salvatore, F., Terracciano, D., & Moccia, M. (2026). Evaluating the neurofilament light chain-derived gap between biological and chronological age in multiple sclerosis and controls. Journal of Neurology, 273(10), Article 625. https://doi.org/10.1007/s00415-026-14157-6

Image Credits: AI Generated

DOI: 10.1007/s00415-026-14157-6

Keywords: multiple sclerosis, neurofilament light chain, biological age, brain ageing, biomarkers, neuroaxonal injury, disability, progressive disease, plasma biomarkers, neurodegeneration, Journal of Neurology, Evaluating