ObjectivePatients with IBD display substantial heterogeneity in clinical characteristics. We hypothesise that individual differences in the complex interaction of the host genome and the gut microbiota can explain the onset and the heterogeneous presentation of IBD. Therefore, we performed a case–control analysis of the gut microbiota, the host genome and the clinical phenotypes of IBD.DesignStool samples, peripheral blood and extensive phenotype data were collected from 313 patients with IBD and 582 truly healthy controls, selected from a population cohort. The gut microbiota composition was assessed by tag-sequencing the 16S rRNA gene. All participants were genotyped. We composed genetic risk scores from 11 functional genetic variants proven to be associated with IBD in genes that are directly involved in the bacterial handling in the gut: NOD2, CARD9, ATG16L1, IRGM and FUT2.ResultsStrikingly, we observed significant alterations of the gut microbiota of healthy individuals with a high genetic risk for IBD: the IBD genetic risk score was significantly associated with a decrease in the genus Roseburia in healthy controls (false discovery rate 0.017). Moreover, disease location was a major determinant of the gut microbiota: the gut microbiota of patients with colonic Crohn's disease (CD) is different from that of patients with ileal CD, with a decrease in alpha diversity associated to ileal disease (p=3.28×10−13).ConclusionsWe show for the first time that genetic risk variants associated with IBD influence the gut microbiota in healthy individuals. Roseburia spp are acetate-to-butyrate converters, and a decrease has already been observed in patients with IBD.

BackgroundInflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data generated from the same IBD patients.Construction and contentWe initiated the 1000IBD project (https://1000ibd.org) to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1215 participants have been enrolled in the project and enrolment is on-going. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.Utility and discussionAll molecular data generated within the 1000IBD project will be shared on the European Genome-Phenome Archive (https://ega-archive.org, accession no: EGAS00001002702). The first data release, detailed in this announcement and released simultaneously with this publication, will contain basic phenotypes for 1215 participants, genotypes of 314 participants and gut microbiome data from stool samples (315 participants) and biopsies (107 participants) generated by tag sequencing the 16S gene. Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.ConclusionsWe report on the establishment and future development of the 1000IBD project: the first comprehensive multi-omics dataset aimed at discovering IBD biomarker profiles and treatment targets.Electronic supplementary materialThe online version of this article (10.1186/s12876-018-0917-5) contains supplementary material, which is available to authorized users.

Sex differences in patients with IBD include age of onset, disease location, and EIM prevalence. No large differences in therapeutic management of IBD were observed between men and women with IBD. 10.1093/ibd/izy004_video1izy004_Video_15786481854001.