The potential of serum neurofilament as biomarker for multiple sclerosis.
Stefan BittnerJiwon OhEva Kubala HavrdováMar TintoréFrauke ZippPublished in: Brain : a journal of neurology (2021)
Multiple sclerosis is a highly heterogeneous disease, and the detection of neuroaxonal damage as well as its quantification is a critical step for patients. Blood-based serum neurofilament light chain (sNfL) is currently under close investigation as an easily accessible biomarker of prognosis and treatment response in patients with multiple sclerosis. There is abundant evidence that sNfL levels reflect ongoing inflammatory-driven neuroaxonal damage (e.g. relapses or MRI disease activity) and that sNfL levels predict disease activity over the next few years. In contrast, the association of sNfL with long-term clinical outcomes or its ability to reflect slow, diffuse neurodegenerative damage in multiple sclerosis is less clear. However, early results from real-world cohorts and clinical trials using sNfL as a marker of treatment response in multiple sclerosis are encouraging. Importantly, clinical algorithms should now be developed that incorporate the routine use of sNfL to guide individualized clinical decision-making in people with multiple sclerosis, together with additional fluid biomarkers and clinical and MRI measures. Here, we propose specific clinical scenarios where implementing sNfL measures may be of utility, including, among others: initial diagnosis, first treatment choice, surveillance of subclinical disease activity and guidance of therapy selection.
Keyphrases
- multiple sclerosis
- disease activity
- rheumatoid arthritis
- systemic lupus erythematosus
- rheumatoid arthritis patients
- ankylosing spondylitis
- oxidative stress
- juvenile idiopathic arthritis
- clinical trial
- white matter
- magnetic resonance imaging
- contrast enhanced
- end stage renal disease
- public health
- magnetic resonance
- chronic kidney disease
- machine learning
- ejection fraction
- stem cells
- risk assessment
- computed tomography
- randomized controlled trial
- quality improvement
- prognostic factors
- deep learning
- mesenchymal stem cells
- cerebrospinal fluid
- climate change
- peritoneal dialysis
- study protocol
- double blind
- combination therapy
- patient reported outcomes
- label free