Mapping the genetic landscape of immune-mediated disorders: potential implications for classification and therapeutic strategies

Vera Fominykh ^1* Alexey A. Shadrin ¹ Piotr Jaholkowski ¹ Julian Fuhrer ¹ Nadine Parker ¹ Erik D. Wiström ² Oleksandr Frei ¹ Olav B Smeland ² Helga Sanner ² Srdjan Djurovic ² Ole A Andreassen ¹

• ¹ University of Oslo, Oslo, Norway
• ² Oslo University Hospital, Oslo, Nordland, Norway

Objectives: Based on clinical, biomarker and genetic data, McGonagle and McDermott suggested autoimmune and autoinflammatory disorders can be classified as a disease continuum from purely autoimmune to autoinflammatory with mixed diseases in between.However, the genetic architecture of this spectrum has not been systematically described. Here we investigate the continuum of polygenic immune-mediated disorders using genome-wide association studies (GWAS) and statistical genetics methods.We mapped the genetic landscape of 15 immune-mediated disorders using GWAS summary statistics and methods including genomic structural equation modelling (genomic SEM), linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and Gaussian causal mixture modelling (MiXeR). We performed enrichment analyses of tissues and biological gene-sets using MAGMA.Results: Genomic SEM suggested a continuum structure with four underlying latent factors from autoimmune diseases at one end to autoinflammatory on the opposite end. Across disorders we observed a balanced mixture of negative and positive local genetic correlations within the major histocompatibility complex, while outside this region, local genetic correlations were predominantly positive. MiXeR analysis showed large genetic overlap in accordance with the continuum landscape. MAGMA analysis implicated genes associated with known monogenic immune diseases for prominent autoimmune and autoinflammatory component.Conclusions Our findings support a polygenic continuum across immune-mediated disorders, with four genetic clusters. The "polygenic autoimmune" and "polygenic autoinflammatory" clusters reside on margins of this continuum. These findings provide insights and lead us to hypothesize that the identified clusters could inform future therapeutical strategies, with patients in the same clusters potentially responding similarly to specific therapies.