Identifying genetic and cellular connections and distinctions among 15 autoimmune diseases using an in-silico approach

利用计算机模拟方法识别15种自身免疫性疾病之间的遗传和细胞联系及区别

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Abstract

BACKGROUND: Despite the identification of numerous genetic loci associated with autoimmune diseases (ADs) through genome-wide association studies (GWAS), elucidating the mechanisms underlying these associations remains challenging. METHODS: We integrated GWAS results with multi-omics data across diverse immune cell types to investigate both the shared and disease-specific association signals across 15 common ADs. RESULTS: Our analyses reveal a high prevalence of locus-sharing (50.8%) across these diseases when defined by physical proximity, but a substantially lower proportion of shared association signals (14.7%) when defined by linkage disequilibrium. This suggests that loci shared across diseases often harbor distinct association signals and mechanisms. We demonstrate that within individual loci, association signals frequently exhibit regulatory activity in different cell types and, less commonly, target different genes. Notably, for several loci, disease-specific associations appear to be mediated through regulatory activity in distinct cell types. Overall, we identify 1,554 genes associated with ADs. Further pathway enrichment and protein-protein interaction network analyses unveil both shared functions and disease-specific pathways among these genes. CONCLUSIONS: By integrating GWAS and multi-omics data, our study delineates the genetic and regulatory architecture underlying autoimmunity, suggesting potential therapeutic targets and opportunities for drug repurposing.

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