Systematic analysis of chromatin interactions at disease associated loci links novel candidate genes to inflammatory bowel disease

Claartje A. Meddens, Magdalena Harakalova, Noortje A. M. van den Dungen, Hassan Foroughi Asl, Hemme J. Hijma, Edwin P. J. G. Cuppen, Johan L. M. Björkegren, Folkert W. Asselbergs, Edward E. S. Nieuwenhuis, Michal Mokry

Genome-wide association studies (GWAS) have revealed many susceptibility loci for complex genetic diseases. For most loci, the causal genes have not been identified. Currently, the identification of candidate genes is predominantly based on genes that localize close to or within identified loci. We have recently shown that 92 of the 163 inflammatory bowel disease (IBD)-loci co-localize with non-coding DNA regulatory elements (DREs). Mutations in DREs can contribute to IBD pathogenesis through dysregulation of gene expression. Consequently, genes that are regulated by these 92 DREs are to be considered as candidate genes. This study uses circular chromosome conformation capture-sequencing (4C-seq) to systematically analyze chromatin-interactions at IBD susceptibility loci that localize to regulatory DNA. Using 4C-seq, we identify genomic regions that physically interact with the 92 DRE that were found 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. Altogether, we identified 902 novel IBD candidate genes. These include genes specific for IBD-subtypes and many noteworthy genes including ATG9A and IL10RA. We show that expression of many novel candidate genes is genotype-dependent and that these genes are upregulated during intestinal inflammation in IBD. Furthermore, we identify HNF4α as a potential key upstream regulator of IBD candidate genes. 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 existing GWAS data.