Decoding autoimmune diseases through the adaptive immune receptor repertoires

The adaptive immune receptor repertoire (AIRR), composed of T-cell receptors (TCRs) and B-cell receptors (BCRs), underpins antigen-specific immunity through extensive diversity generated by V(D)J recombination and junctional modification. Advances in high-throughput AIRR sequencing have enabled comprehensive characterization of clonal diversity, gene usage patterns, and antigen-driven selection at unprecedented resolution. In autoimmune diseases, breakdown of immune tolerance permits the persistence and expansion of autoreactive lymphocyte clones, and is associated with characteristic repertoire remodeling. Reported alterations include changes in repertoire diversity, oligoclonal expansion, biased V(D)J gene usage, and convergent CDR3 motifs. Notably, repertoire changes exhibit spatial and temporal heterogeneity across peripheral blood and target tissues, highlighting the compartmentalized nature of adaptive immune responses. This review synthesizes current evidence on TCR and BCR repertoire alterations across major autoimmune diseases, including rheumatoid arthritis, systemic lupus erythematosus, Sjögren's disease, type 1 diabetes, and ankylosing spondylitis. We summarize emerging computational frameworks for AIRR analysis and highlight machine learning approaches for clonotype classification and antigen specificity prediction. Furthermore, we discuss the diagnostic, prognostic, and therapeutic implications of AIRR profiling, particularly the potential for identifying disease-associated clonotypes and guiding antigen-specific immunotherapies. Despite ongoing technical and biological challenges, continued advances in sequencing technologies and computational modeling are strengthening the role of AIRR analysis as a valuable framework for elucidating autoimmune pathogenesis and advancing precision immunology.