| Literature DB >> 35967312 |
Rodolfo A Kölliker Frers1,2, Matilde Otero-Losada1, Tamara Kobiec1,3, Lucas D Udovin1, María Laura Aon Bertolino1, María I Herrera1,3, Francisco Capani1,4.
Abstract
Multiple sclerosis (MS) is an inflammatory neurodegenerative disease characterized by demyelination, progressive axonal loss, and varying clinical presentations. Axonal damage associated with the inflammatory process causes neurofilaments, the major neuron structural proteins, to be released into the extracellular space, reaching the cerebrospinal fluid (CSF) and the peripheral blood. Methodological advances in neurofilaments' serological detection and imaging technology, along with many clinical and therapeutic studies in the last years, have deepened our understanding of MS immunopathogenesis. This review examines the use of light chain neurofilaments (NFLs) as peripheral MS biomarkers in light of the current clinical and therapeutic evidence, MS immunopathology, and technological advances in diagnostic tools. It aims to highlight NFL multidimensional value as a reliable MS biomarker with a diagnostic-prognostic profile while improving our comprehension of inflammatory neurodegenerative processes, mainly RRMS, the most frequent clinical presentation of MS.Entities:
Keywords: axonal damage; diagnosis; monitoring; multiple sclerosis; neurofilaments (NFs); serum detection
Mesh:
Substances:
Year: 2022 PMID: 35967312 PMCID: PMC9368191 DOI: 10.3389/fimmu.2022.912005
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 8.786
Figure 1Immunopathogenesis of MS in brief.
Figure 2Schematic representation of axonal damage generation, the release of constitutive neurofilaments, anti-NFL antibodies generation, and their diagnostic potential.
Findings supporting the biomarker value of circulating NFL concentration in MS.
| Reference # | Results | Value |
|---|---|---|
| ( | NFL level was higher in patients with either RRMS (16.9 ng/L) or PPMS or SPMS (23 ng/L) than in controls (10.5 ng/L). | diagnostic |
| ( | NFL level was associated with gadolinium-binding T1 lesions up to 2 months back and 1 month forth. | prognostic |
| ( | NFL fluctuation correlated with EDSS score and neuropsychological outcome variation over 24 months. Brain volume decreased faster in patients with higher baseline NFL levels. The increase in NFL levels predicted the increase in brain lesions. | prognostic |
| ( | Baseline NFL levels were associated with the number of gadolinium-binding lesions and the accumulation of new lesions in T2. Patients with a high rate of cerebral atrophy progression had high NFL levels. | disease activity biomarker |
| ( | NFL level at the initial stages of the disease correlated with brain lesions detected ten years later, including cerebral parenchymal fraction and volume of hyperintense lesions in T2 sequences. | prognostic |
| ( | Over 6.5 years’ follow-up, NFL level above the 90th percentile of control values was an independent predictor of the following year worsening EDSS in MS patients. Lesions were independently associated with increased NFL level. The higher the NFL percentile, the more pronounced were brain and spinal volume losses. | prognostic |
Decrease in NFL level in response to disease-modifying therapies.
| Reference # | DMT | QR-NFL |
|---|---|---|
| ( | Natalizumab | 37% |
| ( | IFN or glatiramer acetate switch to rituximab | 21% |
| ( | Natalizumab | 20% |
| ( | Fingolimod | 33% |
| ( | Natalizumab | <16 pg/mL |
| ( | Fingolimod vs IFNβ1α | 38% |
| ( | Ibudilast | ND |
ND, No difference; QR-NFL, quantitative reduction in NFL.
Figure 3Clinicopathological evolutionary profile of RRMS.
Figure 4Inflammation in MS periventricular lesions with paramagnetic rims on 3T MRI. Lesion edge shows paramagnetic substances related to inflammation. (A) Schematic view of the lesion (pink color) in the periventricular area; (B) Active chronic lesion with peripheral gadolinium leak (centripetal pattern) and paramagnetic border (clear zone); (C) Active chronic lesion with paramagnetic border (delimited by dark gray border), observed without contrast. Images (B, C) show periventricular RRMS lesions with paramagnetic edges (postcontrast and precontrast, respectively, in T1 images); L, Lesion; V, Ventricle.
Figure 5Schematic representation of white matter active acute and chronic lesions and inflammatory infiltrate in periventricular lesions with paramagnetic borders.
Figure 6Schematic representation of an algorithm potentially applicable to clinical practice. Longitudinal sNFL measurement is considered for guiding clinical decision-making in RRMS treatment. Yellow fields mark four areas using sNFL as a guidance for decision-making in (1) initial diagnosis, (2) choice of initial treatment, (3) subclinical disease activity assessment, and (4) treatment optimization in clinically active patients.