Toward Precision Health in Autoimmunity and Immune-Related Adverse Events: The Autoantibody Reactome, Spatial Omics,...

Area of Science:

• Immunology
• Autoimmunity
• Precision Medicine

Background:

• Autoimmune diseases and immune-related adverse events (irAEs) share features of dysregulated immunity.
• Current tools for risk stratification, early detection, and treatment guidance are limited.
• Tissue pathology is informative but not always accessible, while serology captures limited immune heterogeneity.

Purpose of the Study:

• To propose the autoantibody reactome as a unifying framework linking immune history, tissue pathology, and clinical outcomes.
• To highlight the potential of autoantibody reactomes for precision immunology in autoimmunity and immune toxicity.
• To outline steps for clinical translation of autoantibody reactome profiling.

Main Methods:

• Utilizing rheumatoid arthritis as a prototype for interpreting reactome features against tissue biology.
• Employing immune checkpoint inhibitor-associated inflammatory arthritis as a model for treatment-induced immune dysregulation.
• Integrating spatial transcriptomics and proteomics to decode reactome-defined immune states within tissues.

Main Results:

• Autoantibody reactomes can link systemic immune history with tissue pathology and clinical trajectories.
• Rheumatoid arthritis and ICI-associated arthritis serve as models for understanding reactome dynamics.
• Spatial omics can decode immune states within accessible tissue microenvironments.

Conclusions:

• A global autoantibody reactome framework can unify understanding across autoimmune disorders and irAEs.
• Clinical translation requires integrating autoantibody reactomes with multimodal data using transparent AI models.
• This approach can lead to clinically actionable decision support for risk prediction and treatment guidance.