GWAS have linked SNPs to risk of inflammatory bowel disease (IBD), but a systematic characterization of disease-associated genes has been lacking. Prior studies utilized microarrays that did not capture many genes encoded within risk loci or defined expression quantitative trait loci (eQTLs) using peripheral blood, which is not the target tissue in IBD. To address these gaps, we sought to characterize the expression of IBD-associated risk genes in disease-relevant tissues and in the setting of active IBD. Terminal ileal (TI) and colonic mucosal tissues were obtained from patients with Crohn’s disease or ulcerative colitis and from healthy controls. We developed a NanoString code set to profile 678 genes within IBD risk loci. A subset of patients and controls were genotyped for IBD-associated risk SNPs. Analyses included differential expression and variance analysis, weighted gene coexpression network analysis, and eQTL analysis. We identified 116 genes that discriminate between healthy TI and colon samples and uncovered patterns in variance of gene expression that highlight heterogeneity of disease. We identified 107 coexpressed gene pairs for which transcriptional regulation is either conserved or reversed in an inflammation-independent or -dependent manner. We demonstrate that on average approximately 60% of disease-associated genes are differentially expressed in inflamed tissue. Last, we identified eQTLs with either genotype-only effects on expression or an interaction effect between genotype and inflammation. Our data reinforce tissue specificity of expression in disease-associated candidate genes, highlight genes and gene pairs that are regulated in disease-relevant tissue and inflammation, and provide a foundation to advance the understanding of IBD pathogenesis.

Although numerous polymorphisms have been associated with inflammatory bowel disease (IBD), identifying the function of these genetic factors has proved challenging. Here we identified a role for nine genes in IBD susceptibility loci in antibacterial autophagy and characterized a role for one of these genes, GPR65, in maintaining lysosome function. Mice lacking Gpr65, a proton-sensing G protein-coupled receptor, showed increased susceptibly to bacteria-induced colitis. Epithelial cells and macrophages lacking GPR65 exhibited impaired clearance of intracellular bacteria and accumulation of aberrant lysosomes. Similarly, IBD patient cells and epithelial cells expressing an IBD-associated missense variant, GPR65 I231L, displayed aberrant lysosomal pH resulting in lysosomal dysfunction, impaired bacterial restriction, and altered lipid droplet formation. The GPR65 I231L polymorphism was sufficient to confer decreased GPR65 signaling. Collectively, these data establish a role for GPR65 in IBD susceptibility and identify lysosomal dysfunction as a potentially causative element in IBD pathogenesis with effects on cellular homeostasis and defense.

BACKGROUND: Crohn’s disease and ulcerative colitis are the two major forms of inflammatory bowel disease; treatment strategies have historically been determined by this binary categorisation. Genetic studies have identified 163 susceptibility loci for inflammatory bowel disease, mostly shared between Crohn’s disease and ulcerative colitis. We undertook the largest genotype association study, to date, in widely used clinical subphenotypes of inflammatory bowel disease with the goal of further understanding the biological relations between diseases. METHODS: This study included patients from 49 centres in 16 countries in Europe, North America, and Australasia. We applied the Montreal classification system of inflammatory bowel disease subphenotypes to 34,819 patients (19,713 with Crohn’s disease, 14,683 with ulcerative colitis) genotyped on the Immunochip array. We tested for genotype-phenotype associations across 156,154 genetic variants. We generated genetic risk scores by combining information from all known inflammatory bowel disease associations to summarise the total load of genetic risk for a particular phenotype. We used these risk scores to test the hypothesis that colonic Crohn’s disease, ileal Crohn’s disease, and ulcerative colitis are all genetically distinct from each other, and to attempt to identify patients with a mismatch between clinical diagnosis and genetic risk profile. FINDINGS: After quality control, the primary analysis included 29,838 patients (16,902 with Crohn’s disease, 12,597 with ulcerative colitis). Three loci (NOD2, MHC, and MST1 3p21) were associated with subphenotypes of inflammatory bowel disease, mainly disease location (essentially fixed over time; median follow-up of 10·5 years). Little or no genetic association with disease behaviour (which changed dramatically over time) remained after conditioning on disease location and age at onset. The genetic risk score representing all known risk alleles for inflammatory bowel disease showed strong association with disease subphenotype (p=1·65 × 10(-78)), even after exclusion of NOD2, MHC, and 3p21 (p=9·23 × 10(-18)). Predictive models based on the genetic risk score strongly distinguished colonic from ileal Crohn’s disease. Our genetic risk score could also identify a small number of patients with discrepant genetic risk profiles who were significantly more likely to have a revised diagnosis after follow-up (p=6·8 × 10(-4)). INTERPRETATION: Our data support a continuum of disorders within inflammatory bowel disease, much better explained by three groups (ileal Crohn’s disease, colonic Crohn’s disease, and ulcerative colitis) than by Crohn’s disease and ulcerative colitis as currently defined. Disease location is an intrinsic aspect of a patient’s disease, in part genetically determined, and the major driver to changes in disease behaviour over time. FUNDING: International Inflammatory Bowel Disease Genetics Consortium members funding sources (see Acknowledgments for full list).

Ribosome profiling is widely used to study translation in vivo, but not all sequence reads correspond to ribosome-protected RNA. Here we describe Rfoot, a computational pipeline that analyzes ribosomal profiling data and identifies native, nonribosomal RNA-protein complexes. We use Rfoot to precisely map RNase-protected regions within small nucleolar RNAs, spliceosomal RNAs, microRNAs, tRNAs, long noncoding (lnc)RNAs and 3′ untranslated regions of mRNAs in human cells. We show that RNAs of the same class can show differential complex association. Although only a subset of lncRNAs show RNase footprints, many of these have multiple footprints, and the protected regions are evolutionarily conserved, suggestive of biological functions.