Identification of the shared genetic architecture underlying seven autoimmune diseases with GWAS summary statistics

Abstract

Background: The common clinical symptoms and immunopathological mechanisms have been observed among multiple autoimmune diseases (ADs), but the shared genetic etiology remains unclear.

Methods: GWAS summary statistics of seven ADs were downloaded from Open Targets Genetics and Dryad. Linkage disequilibrium score regression (LDSC) was applied to estimate overall genetic correlations, bivariate causal mixture model (MiXeR) was used to qualify the polygenic overlap, and stratified-LDSC partitioned heritability to reveal tissue and cell type specific enrichments. Ultimately, we conducted a novel adaptive association test called MTaSPUsSet for identifying pleiotropic genes.

Results: The high heritability of seven ADs ranged from 0.1228 to 0.5972, and strong genetic correlations among certain phenotypes varied between 0.185 and 0.721. There was substantial polygenic overlap, with the number of shared SNPs approximately 0.03K to 0.21K. The specificity of SNP heritability was enriched in the immune/hematopoietic related tissue and cells. Furthermore, we identified 32 pleiotropic genes associated with seven ADs, 23 genes were considered as novel genes. These genes were involved in several cell regulation pathways and immunologic signatures.

Conclusion: We comprehensively explored the shared genetic architecture across seven ADs. The findings progress the exploration of common molecular mechanisms and biological processes involved, and facilitate understanding of disease etiology.

Keywords: autoimmune diseases; genetic architecture; genome-wide association studies; multiple adaptive association tests; pleiotropic.