Biomarker Trajectories in Progressive Multiple Sclerosis: A Longitudinal Cohort Analysis

Authors

DOI:

https://doi.org/10.5281/zenodo.22849449

Keywords:

progressive multiple sclerosis, neurofilament light chain, glial fibrillary acidic protein, progression independent of relapse activity, longitudinal biomarkers

Abstract

Progressive multiple sclerosis has traditionally been understood as a distinct clinical phase that follows relapsing disease, but longitudinal cohort and trial evidence over the past decade has reframed much of the disability patients accumulate, even during nominally relapsing disease, as progression independent of relapse activity (PIRA) -- a gradual process running beneath the clinically defined relapsing-progressive divide. This article synthesizes the literature on the biomarkers now used to track that process longitudinally. We review blood-based fluid markers, principally serum neurofilament light chain and glial fibrillary acidic protein, which index axonal injury and astrocytic reactivity respectively and show complementary, combinable prognostic value for relapse-independent worsening; MRI-based markers, including chronic active paramagnetic-rim lesions and brain-age-derived atrophy measures, which offer a spatially specific window onto smoldering, non-relapsing inflammation and diffuse neurodegeneration; optical coherence tomography, which detects subclinical retinal neuroaxonal thinning even in eyes without a history of optic neuritis; and the earlier-stage literature on digital and wearable monitoring, which addresses the sampling-frequency limitations of episodic clinical and imaging assessment. Read together, the evidence supports a coherent, multimodal biomarker strategy for tracking progressive MS, while leaving definitional standardization of PIRA, validation in real-world populations, and individual-patient reference ranges as open priorities for the field.

References

Lublin FD, Reingold SC, Cohen JA, et al. (2014) Defining the clinical course of multiple sclerosis: The 2013 revisions. Neurology, 83(3): 278-286. DOI: 10.1212/WNL.0000000000000560

Cree BAC, Hollenbach JA, Bove R, et al. (2019) Silent progression in disease activity-free relapsing multiple sclerosis. Annals of Neurology, 85(5): 653-666. DOI: 10.1002/ana.25463

Kappos L, Wolinsky JS, Giovannoni G, et al. (2020) Contribution of Relapse-Independent Progression vs Relapse-Associated Worsening to Overall Confirmed Disability Accumulation in Typical Relapsing Multiple Sclerosis in a Pooled Analysis of 2 Randomized Clinical Trials. JAMA Neurology, 77(9): 1132-1140. DOI: 10.1001/jamaneurol.2020.1568

Tur C, Carbonell-Mirabent P, Cobo-Calvo Á, et al. (2023) Association of Early Progression Independent of Relapse Activity With Long-term Disability After a First Demyelinating Event in Multiple Sclerosis. JAMA Neurology, 80(2): 151-160. DOI: 10.1001/jamaneurol.2022.4655

Müller J, Cagol A, Lorscheider J, et al. (2023) Harmonizing Definitions for Progression Independent of Relapse Activity in Multiple Sclerosis: A Systematic Review. JAMA Neurology, 80(11): 1232-1245. DOI: 10.1001/jamaneurol.2023.3331

Montalban X, Hauser SL, Kappos L, et al. (2017) Ocrelizumab versus Placebo in Primary Progressive Multiple Sclerosis. New England Journal of Medicine, 376(3): 209-220. DOI: 10.1056/NEJMoa1606468

Kappos L, Bar-Or A, Cree BAC, et al. (2018) Siponimod versus placebo in secondary progressive multiple sclerosis (EXPAND): a double-blind, randomised, phase 3 study. The Lancet, 391(10127): 1263-1273. DOI: 10.1016/S0140-6736(18)30475-6

Disanto G, Barro C, Benkert P, et al. (2017) Serum Neurofilament Light: A Biomarker of Neuronal Damage in Multiple Sclerosis. Annals of Neurology, 81(6): 857-870. DOI: 10.1002/ana.24954

Kuhle J, Kropshofer H, Haering DA, et al. (2019) Blood neurofilament light chain as a biomarker of MS disease activity and treatment response. Neurology, 92(10): e1007-e1015. DOI: 10.1212/WNL.0000000000007032

Jakimovski D, Zivadinov R, Ramanthan M, et al. (2019) Serum neurofilament light chain level associations with clinical and cognitive performance in multiple sclerosis: A longitudinal retrospective 5-year study. Multiple Sclerosis Journal, 26(13): 1670-1681. DOI: 10.1177/1352458519881428

Thebault S, et al. (2020) Serum neurofilament light chain predicts long term clinical outcomes in multiple sclerosis. Scientific Reports, 10: 10381. DOI: 10.1038/s41598-020-67504-6

Bar-Or A, Thanei GA, Harp C, et al. (2023) Blood neurofilament light levels predict non-relapsing progression following anti-CD20 therapy in relapsing and primary progressive multiple sclerosis. eBioMedicine, 93: 104662. DOI: 10.1016/j.ebiom.2023.104662

Abdelhak A, Foschi M, Abu-Rumeileh S, et al. (2022) Blood GFAP as an emerging biomarker in brain and spinal cord disorders. Nature Reviews Neurology, 18(3): 158-172. DOI: 10.1038/s41582-021-00616-3

Meier S, Willemse EAJ, Schaedelin S, et al. (2023) Serum Glial Fibrillary Acidic Protein Compared With Neurofilament Light Chain as a Biomarker for Disease Progression in Multiple Sclerosis. JAMA Neurology, 80(3): 287-297. DOI: 10.1001/jamaneurol.2022.5250

Senel M, Tumani H, Lauda F, et al. (2014) Cerebrospinal Fluid Immunoglobulin Kappa Light Chain in Clinically Isolated Syndrome and Multiple Sclerosis. PLoS ONE, 9: e88680. DOI: 10.1371/journal.pone.0088680

Barkhof F, Filippi M, Miller DH, et al. (1997) Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain, 120(11): 2059-2069. DOI: 10.1093/brain/120.11.2059

Absinta M, Sati P, Schindler M, et al. (2016) Persistent 7-tesla phase rim predicts poor outcome in new multiple sclerosis patient lesions. Journal of Clinical Investigation, 126(7): 2597-2609. DOI: 10.1172/JCI86198

Absinta M, Sati P, Masuzzo F, et al. (2019) Association of Chronic Active Multiple Sclerosis Lesions With Disability In Vivo. JAMA Neurology, 76(12): 1474-1483. DOI: 10.1001/jamaneurol.2019.2399

Cole JH, et al. (2020) Longitudinal Assessment of Multiple Sclerosis with the Brain-Age Paradigm. Annals of Neurology, 88(1): 93-105. DOI: 10.1002/ana.25746

Filippi M, Bar-Or A, Piehl F, et al. (2018) Multiple sclerosis. Nature Reviews Disease Primers, 4: 43. DOI: 10.1038/s41572-018-0041-4

Petzold A, Balcer LJ, Calabresi PA, et al. (2017) Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurology, 16(10): 797-812. DOI: 10.1016/S1474-4422(17)30278-8

Block VAJ, Pitsch E, Tahir P, Cree BAC, Allen DD, Gelfand JM. (2016) Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review. PLOS ONE, 11: e0154335. DOI: 10.1371/journal.pone.0154335

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Published

2026-07-31