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Proteomics and relationship with axonal pathology in multiple sclerosis: 5-year diffusion tensor imaging study.

Dejan Jakimovski1, Ferhan Qureshi2, Murali Ramanathan3

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Blood biomarkers can predict multiple sclerosis (MS) brain changes. Higher glial fibrillary acidic protein levels in serum indicate greater future disability progression in MS patients.

Keywords:
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Area of Science:

  • Neuroscience
  • Biomarker Discovery
  • Neuroimmunology

Background:

  • Blood-based biomarkers offer accessible monitoring for multiple sclerosis (MS).
  • Predicting MS progression requires understanding concurrent and future brain pathology.
  • Proteomic assays provide a multivariate approach to biomarker identification.

Purpose of the Study:

  • To assess the predictive value of a proteomic assay for MS brain pathology.
  • To correlate serum protein levels with microstructural and axonal damage over 5 years.
  • To identify biomarkers predicting future disability progression in MS.

Main Methods:

  • Serum samples from 202 MS patients were analyzed using the Olink Proximity Extension Assay for 21 proteins.
  • MRI scans at baseline and 5-year follow-up assessed brain atrophy and lesion burden.
  • Diffusion tensor imaging quantified microstructural axonal pathology (FA, MD) in various brain tissues and lesions.

Main Results:

  • Glial fibrillary acidic protein (GFAP) was strongly associated with concurrent CNS alterations (P < 0.001).
  • Baseline GFAP, protogenin precursor, neurofilament light chain, and myelin oligodendrocyte predicted whole brain atrophy (P < 0.009).
  • Higher baseline GFAP predicted future microstructural damage and disability progression (standardized β = -0.397/0.327, P < 0.001; Exp(B) = 8.65, P = 0.004).

Conclusions:

  • Multiple proteomic biomarkers, including GFAP, are independently linked to axonal pathology severity in MS.
  • Baseline serum GFAP levels are significant predictors of future disability progression in multiple sclerosis.
  • Proteomic profiling holds promise for non-invasive monitoring and prediction of MS outcomes.