Patterns of autoantibody expression in multiple sclerosis identified through development of an autoantigen discovery technology
Europe B. DiCillo, … , David Pisetsky, Thomas Tedder
Europe B. DiCillo, … , David Pisetsky, Thomas Tedder
Published March 3, 2025
Citation Information: J Clin Invest. 2025;135(5):e171948. https://doi.org/10.1172/JCI171948.
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Research Article Autoimmunity Neuroscience

Patterns of autoantibody expression in multiple sclerosis identified through development of an autoantigen discovery technology

Abstract

Multiple sclerosis (MS) is a debilitating autoimmune disease of the CNS, which is characterized by demyelination and axonal injury and frequently preceded by a demyelinating event called clinically isolated syndrome (CIS). Despite the importance of B cells and autoantibodies in MS pathology, their target specificities remain largely unknown. For an agnostic and comprehensive evaluation of autoantibodies in MS, we developed and employed what we believe to be a novel autoantigen discovery technology, the Antigenome Platform. This Platform is a high-throughput assay comprising large-fragment (approximately 100 amino acids) cDNA libraries, phage display, serum antibody screening technology, and robust bioinformatics analysis pipelines. For autoantibody discovery, we assayed serum samples from CIS patients who received either placebo or treatment who were enrolled in the REFLEX clinical trial, which assessed the effects of IFN-β-1a (Rebif) clinical and MRI activity in patients with CIS. Serum autoantibodies from patients with CIS were significantly and reproducibly enriched for known and previously unreported protein targets; 166 targets were selected by over 10% of patients’ sera. Further, 10 autoantibody biomarkers associated with disease activity and 17 associated with patient response to IFN-β-1a therapy. These findings indicate widespread autoantibody production in MS and provide biomarkers for continued study and prediction of disease progression.

Authors

Europe B. DiCillo, Evgueni Kountikov, Minghua Zhu, Stefan Lanker, Danielle E. Harlow, Elizabeth R. Piette, Weiguo Zhang, Brooke Hayward, Joshua Heuler, Julie Korich, Jeffrey L. Bennett, David Pisetsky, Thomas Tedder

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Figure 3

Autoantigen specificities selected by sera from patients with CIS.

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Autoantigen specificities selected by sera from patients with CIS. (A an...
(A and B) Individual autoantigens (dots) are statistically compared between the HC group (n = 43) and (A) The test group of patients with CIS (CIS-Set-1; n = 51; month 0), (B) The validation group of patients with CIS (CIS-Set-2; n = 51; month 0). The x-axis represents the difference in sequencing count means between cohorts taken from log2-transformed sequencing counts. The y-axis represents the –log10 of q values (higher values indicate greater significance). Autoantigens above the horizontal line (q = 0.2) are considered significant. (C) Venn diagram shows the overlap of autoantigens selected by CIS-Set-1 and CIS-Set-2. The autoantigens reproducibly selected were extracted and filtered for autoantigens selected by at least 10% of all patients with CIS; 166 autoantigens remained. Kruskal-Wallis rank test was used for all statistical comparisons. (D) A protein-protein interaction network of the 166 reproducibly selected CIS-associated autoantigens selected by at least 10% of patients. Only interactions derived from STRING “experimental” and “database” data sources are shown. Proteins without shared connections are omitted. Circles represent antigens and the connecting lines represent interactions between antigens. MCL clustering was applied to help distinguish stronger interactions, where each cluster is uniquely colored. Solid lines between connections indicate stronger interactions than dotted lines. (E) Subcellular locations of the 166 CIS-associated autoantigens. Charts detail the percent of antigens that are predominately located in each subcellular compartment and subcompartment. Asterisks indicate locations that are significantly enriched (P value < 0.05) over what would be expected from a random set of proteins of the same size. Derived from SubCell Barcode (www.subcellbarcode.org). (F–I) Protein structure properties as labeled. Values are sorted in descending order; the gray curve indicates the values for all proteins included, and the black vertical lines indicate the placement of the 166 CIS-enriched autoantigens in the ranked list. The green curve indicates the enrichment score. The red and blue color gradient represents positive (red) to negative (blue) values.