P-306 Systematic Analyses of Chromatin Interactions at IBD-associated Loci Identify IL10RA and ATG9A as Novel Candidate Genes

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Inflammatory bowel disease (IBD) is a multifactorial disease that develops in genetically susceptible hosts. In search for genes that are involved in IBD, genome wide association studies (GWAS) have identified numerous associated genomic loci. The current selection of IBD candidate genes is based on the location of genes in the vicinity of the associated locus. This valuable approach has revealed multiple candidate genes, but is often limited by prior knowledge on gene function. We have previously shown that over half of the IBD-associated variants overlap with DNA regulatory elements (DREs) in non-coding DNA.1 This suggests that these variants may contribute to the IBD pathogenesis by affecting the function of regulatory elements. Although a DRE can be localized up to 1 megabase from the gene it regulates, they interact in close physical proximity by forming DNA loops.


We used Circularized Chromosome Conformation Capture-sequencing (4C-seq) to study DRE-gene interactions at IBD susceptibility loci. Since the activity of regulatory elements is cell type specific, 4C-seq was performed in monocytes, lymphocytes and intestinal epithelial cells—the major cell types involved in the IBD pathogenesis.


By using 4C-seq we have identified genomic regions that physically interact with the 92 DRE that were found at IBD susceptibility loci. Altogether, we identified 902 novel IBD candidate genes including ATG9A and IL10RA. We show that the expression of many novel candidate genes is genotype dependent and that these genes are upregulated during intestinal inflammation in IBD. Pathway analyses further identified HNF4α as a potential key upstream regulator of IBD candidate genes.


This study is the first to systematically analyse chromatin interactions at IBD susceptibility loci. We reveal many novel and relevant IBD candidate genes, pathways and regulators. Our approach complements classical candidate gene identification, links novel genes to IBD and can be applied to any GWAS data.

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