SPAID: a comprehensive database for disease-specific autoantigens in autoimmune disorders

Area of Science:

• Immunology
• Genomics
• Bioinformatics

Background:

• Autoimmune diseases (ADs) are chronic inflammatory conditions with complex causes and difficult diagnoses.
• Identifying autoantigens is crucial for precise diagnosis and therapy, but the immunogenic landscape is largely unexplored.
• Previous research focused mainly on canonical proteins, overlooking potential non-canonical autoantigens.

Purpose of the Study:

• To develop SPAID, a comprehensive resource for candidate autoantigen discovery across 14 autoimmune diseases.
• To integrate both canonical and non-canonical proteins using a two-level evidence framework.
• To facilitate mechanistic investigations into antigen origins and pathogenic recognition in autoimmunity.

Main Methods:

• Developed SPAID, a web-based resource integrating diverse protein data.
• Implemented a two-level evidence framework: validated level (experimental epitopes) and proteomics-based level (mass spectrometry data).
• Annotated proteomics data with differential expression, immunogenicity scores, and functional features.

Main Results:

• SPAID provides a comprehensive catalog of candidate autoantigens across 14 ADs.
• The resource integrates experimentally validated epitopes with mass spectrometry-identified proteins.
• SPAID enables detailed characterization of autoantigen repertoires and supports further validation.

Conclusions:

• SPAID offers a foundational resource for advancing antigen-centered research in autoimmunity.
• The integrated approach facilitates the discovery of novel diagnostic and therapeutic targets.
• This resource aids in understanding the origins and recognition of pathogenic antigens.