GWAS of stool frequency provides insights into gastrointestinal motility and irritable bowel syndrome.

Gut dysmotility is associated with constipation, diarrhea, and functional gastrointestinal disorders like irritable bowel syndrome (IBS), although its molecular underpinnings are poorly characterized. We studied stool frequency (defined by the number of bowel movements per day, based on questionnaire data) as a proxy for gut motility in a GWAS meta-analysis including 167,875 individuals from UK Biobank and four smaller population-based cohorts. We identify 14 loci associated with stool frequency (p ≤ 5.0 × 10-8). Gene set and pathway analyses detected enrichment for genes involved in neurotransmitter/neuropeptide signaling and preferentially expressed in enteric motor neurons controlling peristalsis. PheWAS identified pleiotropic associations with dysmotility syndromes and the response to their pharmacological treatment. The genetic architecture of stool frequency correlates with that of IBS, and UK Biobank participants from the top 1% of stool frequency polygenic score distribution were associated with 5× higher risk of IBS with diarrhea. These findings pave the way for the identification of actionable pathological mechanisms in IBS and the dysmotility syndromes.

Genome-wide analysis of 53,400 people with irritable bowel syndrome highlights shared genetic pathways with mood and anxiety disorders.

Irritable bowel syndrome (IBS) results from disordered brain-gut interactions. Identifying susceptibility genes could highlight the underlying pathophysiological mechanisms. We designed a digestive health questionnaire for UK Biobank and combined identified cases with IBS with independent cohorts. We conducted a genome-wide association study with 53,400 cases and 433,201 controls and replicated significant associations in a 23andMe panel (205,252 cases and 1,384,055 controls). Our study identified and confirmed six genetic susceptibility loci for IBS. Implicated genes included NCAM1, CADM2, PHF2/FAM120A, DOCK9, CKAP2/TPTE2P3 and BAG6. The first four are associated with mood and anxiety disorders, expressed in the nervous system, or both. Mirroring this, we also found strong genome-wide correlation between the risk of IBS and anxiety, neuroticism and depression (rg > 0.5). Additional analyses suggested this arises due to shared pathogenic pathways rather than, for example, anxiety causing abdominal symptoms. Implicated mechanisms require further exploration to help understand the altered brain-gut interactions underlying IBS.

Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools.

Capture Hi-C is widely used to obtain high-resolution profiles of chromosomal interactions involving, at least on one end, regions of interest such as gene promoters. Signal detection in Capture Hi-C data is challenging and cannot be adequately accomplished with tools developed for other chromosome conformation capture methods, including standard Hi-C. Capture Hi-C Analysis of Genomic Organization (CHiCAGO) is a computational pipeline developed specifically for Capture Hi-C analysis. It implements a statistical model accounting for biological and technical background components, as well as bespoke normalization and multiple testing procedures for this data type. Here we provide a step-by-step guide to the CHiCAGO workflow that is aimed at users with basic experience of the command line and R. We also describe more advanced strategies for tuning the key parameters for custom experiments and provide guidance on data preprocessing and downstream analysis using companion tools. In a typical experiment, CHiCAGO takes ~2-3 h to run, although pre- and postprocessing steps may take much longer.

High-resolution targeted 3C interrogation of cis-regulatory element organization at genome-wide scale.

Chromosome conformation capture (3C) provides an adaptable tool for studying diverse biological questions. Current 3C methods generally provide either low-resolution interaction profiles across the entire genome, or high-resolution interaction profiles at limited numbers of loci. Due to technical limitations, generation of reproducible high-resolution interaction profiles has not been achieved at genome-wide scale. Here, to overcome this barrier, we systematically test each step of 3C and report two improvements over current methods. We show that up to 30% of reporter events generated using the popular in situ 3C method arise from ligations between two individual nuclei, but this noise can be almost entirely eliminated by isolating intact nuclei after ligation. Using Nuclear-Titrated Capture-C, we generate reproducible high-resolution genome-wide 3C interaction profiles by targeting 8055 gene promoters in erythroid cells. By pairing high-resolution 3C interaction calls with nascent gene expression we interrogate the role of promoter hubs and super-enhancers in gene regulation.