Evidence map›Paper›PMID 41683864›Full record

ArticleInternational journal of molecular sciences2026

Serum Neurofilament Light Chain and Glial Fibrillary Acidic Protein as Differential Biomarkers of Response to Dimethyl Fumarate and Ocrelizumab in Multiple Sclerosis.

Alessandra Mingione, Andrea Corona, Corinne Monzani, Alen Zollo, Carola Cirocco, Tiziana Zaccone, Mariangela Scavone, Gian Marco Podda, Paola Signorelli, Monica Miozzo and 2 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Alessandra MingioneLaboratory of Precision Medicine of Neurological Diseases, Department of Health Science, University of Milan, 20142 Milan, Italy.ORCID 0000-0001-8008-0191
Andrea CoronaLaboratory of Precision Medicine of Neurological Diseases, Department of Health Science, University of Milan, 20142 Milan, Italy.
Corinne MonzaniLaboratory of Precision Medicine of Neurological Diseases, Department of Health Science, University of Milan, 20142 Milan, Italy.
Alen ZolloLaboratory of Precision Medicine of Neurological Diseases, Department of Health Science, University of Milan, 20142 Milan, Italy.ORCID 0009-0005-0908-7469
Carola CiroccoLaboratory of Precision Medicine of Neurological Diseases, Department of Health Science, University of Milan, 20142 Milan, Italy.
Tiziana ZacconeClinical Neurology Unit, ASST Santi Paolo e Carlo, 20142 Milan, Italy.ORCID 0009-0008-2371-9591
Mariangela ScavoneLaboratory of Haemostasis and Thrombosis, Dipartimento di Scienze della Salute, Università degli Studi di Milano, 20142 Milan, Italy.ORCID 0000-0002-8421-0210
Gian Marco PoddaLaboratory of Haemostasis and Thrombosis, Dipartimento di Scienze della Salute, Università degli Studi di Milano, 20142 Milan, Italy.
Paola SignorelliAldo Ravelli Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Sciences, Università degli Studi di Milano, 20142 Milan, Italy.ORCID 0000-0003-2368-2393
Monica MiozzoMedical Genetics, Department of Health Sciences, Università degli Studi di Milano, 20142 Milan, Italy.
Alberto PrioriAldo Ravelli Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Sciences, Università degli Studi di Milano, 20142 Milan, Italy.ORCID 0000-0002-1549-3851
Filippo Martinelli-BoneschiLaboratory of Precision Medicine of Neurological Diseases, Department of Health Science, University of Milan, 20142 Milan, Italy.ORCID 0000-0002-9955-1368

Funding

European Union-NextGenerationEU. Project PNC 0000001 D3 4 Health,-CUP [B53C22006080001], the National Plan for Complementary Investments to the NRRP
6 · The paper itself

Abstract

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease. Quantifying neuronal damage is a critical step for patient care. Neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) are the most promising serum biomarkers reflecting neuronal damage and astroglial activation, respectively. This study analyzed sNfL and sGFAP in 177 MS patients and 71 healthy controls (HCs) using SIMOA technology, classifying patients as responders (Rs) or non-responders (NRs) based on "No Evidence of Disease Activity 3" (NEDA-3) status during two years of treatment. Longitudinal analyses were performed for Dimethyl fumarate (DMF) and Ocrelizumab (OCRE) treatment. Biomarker-age correlation analysis in HCs confirmed correlation between both NfL and GFAP, with age and cut-off values specific for age decades being calculated. Both biomarkers were higher in MS patients compared to HCs. sNfL showed a significant increase in NR patients overall. In contrast, sGFAP was elevated in the low-to-moderate-efficacy treatment agents (LETAs) NR group and also in the DMF NR subgroup, suggesting that it monitors persistent astrogliosis. Longitudinal analysis showed that both biomarkers decreased during DMF treatment after one year. During OCRE treatment, sNfL rapidly reduced to HC levels within one year, while sGFAP decreased only after two years. This highlights that OCRE acts differently on the pathological processes linked to the two biomarkers.

Indexed as

Antibodies, Monoclonal, HumanizedDimethyl FumarateGlial Fibrillary Acidic ProteinMultiple SclerosisNeurofilament ProteinsAdultBiomarkersFemaleHumansMaleMiddle AgedAntibodies, Monoclonal, HumanizedBiomarkersDimethyl FumarateGFAP protein, humanGlial Fibrillary Acidic Proteinneurofilament protein LNeurofilament ProteinsDimethyl fumaratemultiple sclerosisOcrelizumabsGFAPSIMOAsNfL

Identifiers

PMID41683864
PMCPMC12897660

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.