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An autoantibody signature predictive for multiple sclerosis.

Colin R Zamecnik¹, Gavin M Sowa^2,3, Ahmed Abdelhak¹

¹Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.

Nature Medicine

|April 19, 2024

Summary

A unique autoantibody signature identifies a subset of multiple sclerosis (MS) patients years before symptom onset. This discovery offers potential for early diagnosis and targeted therapies in MS.

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Area of Science:

Immunology
Neurology
Biomarker Discovery

Background:

B cells play a role in multiple sclerosis (MS) pathophysiology, but a reliable predictive or diagnostic autoantibody is still needed.
Existing research has not identified a specific autoantibody for early MS detection.

Purpose of the Study:

To identify autoantibody profiles in patients with MS (PwMS) using a large repository.
To investigate the potential of autoantibodies as early diagnostic or predictive biomarkers for MS.

Main Methods:

Utilized the Department of Defense Serum Repository (DoDSR) for whole-proteome autoantibody profiling of PwMS.
Analyzed autoantibody signatures years before and after MS onset.
Validated findings in a separate incident MS cohort using cerebrospinal fluid and serum samples.

Main Results:

Identified a unique autoantibody signature in approximately 10% of PwMS, targeting a motif similar to human pathogens.
This signature was present years before MS symptoms and associated with higher serum neurofilament light (sNfL) levels.
The autoantibody profile demonstrated high specificity for MS in both serum and cerebrospinal fluid, persisting over time.

Conclusions:

The identified autoantibody signature provides molecular evidence of an immunologically active preclinical period in MS.
This signature may serve as an antigen-specific biomarker for identifying high-risk individuals with early neuroinflammatory syndromes.
Further research can characterize this MS patient subset and refine biomarker utility.