The Integrated Cellular and Molecular Landscape of Autoimmunity

Area of Science:

• Immunogenomics
• Autoimmune Diseases
• Computational Biology

Background:

• Autoimmune diseases involve complex immune dysregulation.
• Understanding shared and distinct immune mechanisms is crucial for effective treatment.
• Large-scale data integration is needed to identify common immunopathologic patterns.

Purpose of the Study:

• To perform a large-scale immunogenomic analysis of 10 autoimmune diseases.
• To identify core immune mechanisms and disease-specific signatures underlying autoimmunity.
• To develop a modular framework for understanding immune dysregulation and advancing precision medicine.

Main Methods:

• Meta-analysis of ~13,000 transcriptomic profiles from blood and tissue.
• Derivation of higher-order immune features including cell type proportions, cytokine levels, pathway activity, transcription factor regulation, and miRNA activity.
• Organization of features into 15 coherent immune modules for cross-disease comparison.

Main Results:

• Identified core immune mechanisms: interferon responses, inflammation, and adaptive immune suppression.
• Revealed shared and distinct immunopathological patterns across 10 autoimmune diseases.
• The inflammation module correlated with disease severity and predicted treatment response.

Conclusions:

• A modular framework enhances biological interpretability of complex immune dysregulation in autoimmunity.
• This approach facilitates systematic cross-disease comparisons and identifies key immunopathologic patterns.
• The developed interactive app supports reproducibility and further research in autoimmune disease precision medicine.