Novel methods for the discovery of disease-associated T cell epitopes in autoimmunity
Abstract
A detailed understanding of the pathology of autoimmune diseases hinges on the identification of self-antigens and epitopes targeted by the immune system. While the characterization of autoantibodies is now well-established, facilitating both mechanistic insights and clinical biomarker applications, the identification of autoreactive T cell epitopes remains considerably more challenging. This complexity is amplified by the presence of autoreactive T cells in healthy individuals, necessitating highly sensitive and specific methods to allow for the detection of subtle differences between the autoreactive T cell population in healthy controls and in patients. Fortunately, T cell epitope discovery is a rapidly advancing field, with new methods continually emerging to improve sensitivity, throughput, and resolution. In this review, we will provide a structured overview of the key methods used to identify T cell epitopes, spanning both foundational techniques thathave been instrumental in the early discovery of self-epitopes involved in autoimmunity as well as recent high throughput approaches that offer enhanced precision and scalability. In the second part, we give an overview of the techniques used in the validation of the role of self-peptides in the autoimmune disorder. We conclude by discussing future directions in the field, emphasizing the critical role of T cell epitope discovery in driving the development of targeted, antigen-specific therapies for autoimmune disorders. This review aims to provide a practical and conceptual framework for T cell epitope discovery in autoimmune diseases, integrating established experimental approaches with emerging computational and high-throughput methodologies to guide informed method selection in contemporary research.
Fields of Study & Subjects
vaccines and immunoinformatics approaches
Monoclonal and Polyclonal Antibodies Research
Systemic Lupus Erythematosus Research
Publication details
- Journal / source
- Methods
- Publisher
- Elsevier BV
- Volume
- 248
- Pages
- 64–82
- Publication date
- 11 February 2026
- Language
- EN