The 1000IBD project: multi-omics data of 1000 inflammatory bowel disease patients; data release 1

Abstract

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.

Impact of commonly used drugs on the composition and metabolic function of the gut microbiota

“…Cohort description. For this study we used three independent Dutch cohorts: (1) a general population cohort, LifeLines-DEEP, consisting of 1539 individuals; (2) 544 patients with IBD from the 1000 IBD cohort of the University Medical Center of Groningen (UMCG); and (3) an IBS case-control cohort with 313 participants from Maastricht University Medical Center + (MUMC + ) [37][38][39] . The LifeLines-DEEP cohort consists of volunteers from the general population from whom faecal samples have been collected.…”

Gut microbial co-abundance networks show specificity in inflammatory bowel disease and obesity

“…The 1000 Inflammatory Bowel Disease (1000IBD) cohort consists of patients with IBD recruited at the specialized IBD outpatient clinic of the University Medical Center Groningen in the Netherlands 14 , 74 . IBD diagnosis was made based on accepted radiological, endoscopic and histopathological evaluation.…”

Enteric Viruses and Inflammatory Bowel Disease

“…Real-time integrated studies are needed to decipher the mechanisms underlying IBD pathogenesis. Such studies would then contribute to the development of personalized therapeutic approaches to IBD [ 97 , 98 , 99 ]. With the advent of artificial intelligence and big data, analysis of the “integratome” (from the so-called “integrated omics”) should also open new avenues of research for enteric virus infections in IBD [ 100 ].…”