Background: Immune-mediated inflammatory diseases (IMIDs) are a diverse group of chronic conditions driven by dysregulation in immune response and complex interactions between genetic, environmental, and molecular factors. Despite their clinical heterogeneity, IMIDs share substantial epidemiological overlap, frequent comorbidity, and convergent immune pathways, suggesting underlying biological commonalities. Understanding these shared mechanisms is essential for developing pathway centric therapeutic strategies and for the advancement of the concept of cluster medicine, where diseases are classified and treated based on shared molecular architecture rather than affected organ systems.

Objectives: To investigate and characterise shared genetic architecture for 16 IMIDs including rheumatic, respiratory and connective tissue disorders, using large scale genome wide association study (GWAS) summary statistics.

Methods: Summary level data were collected from the GWAS Catalog, the Common Metabolic Diseases Knowledge Portal, and deCODE Genetics. Datasets were harmonised using a MungeSumStats pipeline, incorporating allele alignment, and mapping to unified GRCh37 genomic build. SNP-based heritability and pairwise genetic correlations were estimated using linkage disequilibrium score regression. Cross-phenotype association analysis was performed using the ASSET framework, focusing on the rheumatic IMID cluster including rheumatoid arthritis (RA), juvenile idiopathic arthritis (JIA), and psoriatic arthritis (PsA). Utilising FUMA (Functional Mapping and Annotation), pathway analysis was applied to the results of the rheumatic ASSET framework.

Results: IMIDs exhibited highly polygenic architectures, with SNP-based heritability estimates varying across diseases. Higher heritability was observed among classical autoimmune conditions, such as RA, Inflammatory bowel disease, and type 1 diabetes. In contrast, lower estimates were seen for barrier and allergic diseases, reflecting differences in genetic architecture, phenotypic heterogeneity, and GWAS effective sample size. Genetic correlation analysis revealed biologically coherent disease clusters corresponding to systemic autoimmunity, barrier-driven disease, and inflammatory arthropathies. Strong genetic correlations were observed between related disease pairs, including inflammatory bowel diseases and psoriatic phenotypes. Using MAGMA in FUMA, strong enrichment of αβ T-cell activation and CD4-positive T-cell regulatory pathways in the rheumatic ASSET analysis, even after excluding the MHC, was found. This suggests that shared genetic risk across inflammatory arthropathies converge on adaptive immune activation beyond classical antigen presentation, consistent with known disease biology and the genetic correlation structure.

Conclusions: These findings demonstrate that IMIDs cluster according to shared genetic and biological pathways rather than clinical phenotype alone. This pathway-based framework provides a mechanistic foundation for improved disease stratification and supports translational strategies such as therapeutic repurposing and pathway-informed precision medicine in rheumatology.

REFERENCES: NIL.

Acknowledgments: NIL.

Disclosure of Interests: None declared.