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Investigating Target Gene Function in a CD40 Agonistic Antibody-induced Colitis Model using CRISPR/Cas9-based Technologies
Published on: June 2, 2021
Stratified shared genetic architecture of IBD and RA: an integrated analysis from polygenic overlap to directional
Yiwen Jia1, Yuntian Xia2, Siyuan Chen1
1Department of Gastroenterology, The Third Affiliated Hospital of Anhui Medical University, Hefei, China.
Background:
Inflammatory bowel disease (IBD) and rheumatoid arthritis (RA) are chronic immune-mediated disorders with overlapping clinical and immunological features, yet genome-wide genetic correlation (rg) between them has remained modest.
Methods:
We integrated multiple complementary approaches to dissect their genetic relationship, including MiXeR, LAVA, conditional/conjunctional FDR (cond/conjFDR), PLACO, and FUMA, using large-scale GWAS datasets of European ancestry.
Results:
MiXeR revealed extensive polygenic overlap between IBD and RA (Dice coefficient ≈ 0.46), encompassing hundreds of shared causal variants, while the global rg remained low (≈0.06). The weakened rg was attributable to directional heterogeneity, as many shared variants exhibited opposite effect directions across the two diseases. LAVA identified specific loci with significant positive local correlations, such as TNFAIP3 (6q23), COG6/TNFSF11 (13q14), and JAK2 (7q36). Cond/conjFDR and PLACO uncovered thousands of pleiotropic SNPs, with high consistency across methods, confirming extensive genetic sharing. FUMA functional annotation highlighted enrichment of shared genes in T-cell activation, cytokine signaling, and Th1/Th17 differentiation pathways, with tissue enrichment observed in blood, spleen, intestine, and lung.
Conclusions:
Despite modest genome-wide correlation, IBD and RA share a high degree of polygenic risk, and the apparent paradox is explained by mixed effect directions of shared variants. These results provide a stratified view of their shared genetic architecture and offer new insights into common immunological pathways contributing to comorbidity. As the GWAS datasets were predominantly of European ancestry, the generalizability of these findings to non-European populations remains uncertain, validation in ancestrally diverse cohorts is needed.
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