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

Blood-based biomarkers can be economic and easily accessible tools for monitoring and predicting disease activity in multiple sclerosis. The objective of this study was to determine the predictive value of a multivariate proteomic assay for concurrent and future microstructural/axonal brain pathology in a longitudinal study of a heterogeneous group of people with multiple sclerosis. A proteomic analysis was obtained on serum samples from 202 people with multiple sclerosis (148 relapsing-remitting and 54 progressive) at baseline and 5-year follow-up. The concentration of 21 proteins related to multiple pathways of multiple sclerosis pathophysiology was derived using Proximity Extension Assay on the Olink platform. Patients were imaged on the same 3T MRI scanner at both timepoints. The rate of whole brain, white matter and grey matter atrophy over the 5-year follow-up was determined using the multi-timepoint Structural Image Evaluation, using Normalisation, of Atrophy algorithms. Lesion burden measures were also assessed. The severity of microstructural axonal brain pathology was quantified using diffusion tensor imaging. Fractional anisotropy and mean diffusivity of normal-appearing brain tissue, normal-appearing white matter, grey matter, T2 and T1 lesions were calculated. Age, sex and body mass index-adjusted step-wise regression models were used. Glial fibrillary acidic protein was the most common and highest-ranked proteomic biomarker associated with greater concurrent microstructural central nervous system alterations (P < 0.001). The rate of whole brain atrophy was associated with baseline levels of glial fibrillary acidic protein, protogenin precursor, neurofilament light chain and myelin oligodendrocyte (P < 0.009), whereas grey matter atrophy was associated with higher baseline neurofilament light chain, higher osteopontin and lower protogenin precursor levels (P < 0.016). Higher baseline glial fibrillary acidic protein level was a significant predictor of future severity of the microstructural CNS alterations as measured by normal-appearing brain tissue fractional anisotropy and mean diffusivity (standardized & beta; = -0.397/0.327, P < 0.001), normal-appearing white matter fractional anisotropy (standardized & beta; = -0.466, P < 0.0012), grey matter mean diffusivity (standardized & beta; = 0.346, P < 0.011) and T2 lesion mean diffusivity (standardized & beta; = 0.416, P < 0.001) at the 5-year follow-up. Serum levels of myelin-oligodendrocyte glycoprotein, neurofilament light chain, contactin-2 and osteopontin proteins were additionally and independently associated with worse concomitant and future axonal pathology. Higher glial fibrillary acidic protein levels were associated with future disability progression (Exp(B) = 8.65, P = 0.004). Multiple proteomic biomarkers are independently associated with greater severity of axonal brain pathology as measured by diffusion tensor imaging in multiple sclerosis. Baseline serum glial fibrillary acidic protein levels can predict future disability progression. Jakimovski et al. utilized serum proteomic data consisting of 21 biomarkers related to multiple sclerosis pathophysiological processes in predicting concurrent and future microstructural MRI pathology. Higher glial fibrillary acidic protein and lower myelin-oligodendrocyte levels were predictive of more severe axonal damage.

Automated summary

Blood-based biomarkers can be used as economic and easily accessible tools for monitoring and predicting disease activity in multiple sclerosis. This study found that a multivariate proteomic assay can predict concurrent and future microstructural brain pathology in people with multiple sclerosis. Glial fibrillary acidic protein was the most common and highest-ranked biomarker associated with central nervous system alterations. Higher levels of glial fibrillary acidic protein were also predictive of more severe axonal damage and disability progression.