Mapping the genetic landscape of disorders on the autoimmune-autoinflammatory continuum: potential implications for classification and treatment
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Objectives
Based on clinical, biomarker and genetic data, autoimmune and autoinflammatory disorders (AIDs) can be classified as a disease continuum from pure autoinflammatory to pure autoimmune with mixed diseases in between. However, the genetic architecture of AIDs has not been systematically described. Here we investigate the polygenic continuum of AIDs using genome-wide association studies (GWAS) and statistical genetics methods.
Methods
We mapped the genetic landscape of 15 AIDs 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 AIDs, we observed a balanced mixture of negative and positive local correlations within the major histocompatibility complex, while outside this region they were predominantly positive. MiXeR analysis showed large genetic overlap in accordance with the continuum landscape. MAGMA analysis implicated genes associated with monogenic immune diseases in autoimmune (factor 1) and autoinflammatory diseases (factor 4).
Conclusions
Our findings support a polygenic continuum across AIDs, with four genetic clusters. The “polygenic autoimmune” and “polygenic autoinflammatory” clusters reside on margins of this continuum. The identified genetic patterns across different AIDs can potentially guide drug selection, as patients within the same clusters may benefit from the same therapies.
