Abstract
GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach.
Highlights
Genome Wide Association Studies (GWAS) have identified >200 risk loci for Inflammatory Bowel Disease (IBD)
Using standard methods based on linear regression and two megabase windows centered on the position of the interrogating probe (Methods), we identified significant cis-eQTL (FDR < 0.05) for 8804 of 18,580 tested probes in at least one tissue, amounting to a total of 23,650 cis-eQTL effects (Supplementary Data 1)
We use this “Correlated Expression and Disease Association Research” data set (CEDAR) to identify 23,650 significant cis-eQTL, which fall into 9720 regulatory modules of which at least ∼889 affect more than one gene in more than one tissue
Summary
GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. For the majority of risk loci, the GWAS signals are not driven by coding variants They must be driven by common regulatory variants, i.e., variants that perturb the expression levels of one (or more) target genes in one (or more) disease relevant cell types[4]. Some of these trans-eQTL may participate in the disease process
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
