ePoster

COMPUTATIONAL PREDICTION OF CANDIDATE AUTOANTIGENS IN RASMUSSEN ENCEPHALITIS THROUGH T-CELL RECEPTOR REPERTOIRE ANALYSIS

Mar Fandiño Ciuranaand 4 co-authors

Hospital del Mar Research Institute

FENS Forum 2026 (2026)
Barcelona, Spain
Board PS04-08PM-001

Presentation

Date TBA

Board: PS04-08PM-001

Poster preview

COMPUTATIONAL PREDICTION OF CANDIDATE AUTOANTIGENS IN RASMUSSEN ENCEPHALITIS THROUGH T-CELL RECEPTOR REPERTOIRE ANALYSIS poster preview

Event Information

Poster Board

PS04-08PM-001

Abstract

Rasmussen encephalitis (RE) is a rare, severe neurological disorder characterised by chronic inflammation, progressive hemispheric atrophy and drug-resistant epilepsy. Evidence suggests that resting memory CD8+ T-cell infiltration and clonal expansion in the central nervous system (CNS) drive the pathogenesis, pointing towards an antigen-specific autoimmune mechanism. However, the identity of the target autoantigen(s) remains elusive. Here, we developed a computational pipeline to predict candidate autoantigens through T-cell receptor (TCR) repertoire analysis and molecular mimicry investigation. We analysed publicly available TCR sequencing data from RE patients, focusing on clonotypes expanded in both brain tissue and peripheral blood. Using the Immunarch package, we identified the top expanded clonotypes and analysed their complementarity-determining region 3 (CDR3) sequences. TCRMatch was employed to identify known epitope specificities, revealing matches to viral peptides from betacoronavirus ORF7b protein. Structural modelling using TCRmodel and OpenFold3 confirmed stable interactions between the dominant TCR clonotype (CASSGYEQYF), the viral peptide and the most prevalent human leukocyte antigen in RE patients (HLA-C*07:01). BLAST analysis against the human proteome identified significant sequence similarity (70.59% identity) between the viral epitope and TMEM63B, a mechanosensitive cation channel expressed in cortical neurons and glia. Pathogenic variants in TMEM63B cause developmental and epileptic encephalopathies, supporting its biological plausibility as an RE autoantigen. This computational framework establishes TMEM63B as a candidate autoantigen warranting experimental validation. Ongoing work includes single-cell TCR sequencing of a multicentric RE patient cohort to characterise encephalitogenic T-cell profiles and validate predicted antigenic targets, which will provide critical insights into RE pathogenesis and potential therapeutic interventions.

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