Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Jan 8;19(1):5.
doi: 10.1186/s12876-018-0917-5.

The 1000IBD Project: Multi-Omics Data of 1000 Inflammatory Bowel Disease Patients; Data Release 1

Affiliations
Free PMC article

The 1000IBD Project: Multi-Omics Data of 1000 Inflammatory Bowel Disease Patients; Data Release 1

Floris Imhann et al. BMC Gastroenterol. .
Free PMC article

Erratum in

Abstract

Background: Inflammatory 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 content: We 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 discussion: All 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.

Conclusions: We 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.

Keywords: Crohn’s disease; Dataset; Genome; Inflammatory bowel disease; Microbiome; Transcriptome; Ulcerative colitis.

Conflict of interest statement

Ethics approval and consent to participate

The 1000IBD project was approved by the Institutional Review Board of the UMCG (official name in Dutch: Medisch Ethische Toetsingscommissie (METc) of the University Medical Center Groningen in Groningen, the Netherlands; IRB number 2008.338). All participants signed a written informed consent form.

Consent for publication

Not applicable.

Competing interests

FI received a speaker fee from AbbVie, KJvdV: none, RB: none, RA: none, MDV: none, AVV: none, CV: none, LMS: none; KWJvdS: none, VP: none, HMvD: none, MCV: none, EAMF: none, MAS: none, GD: none, RKW: none.These activities did not conflict with the work described in this article.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
1000IBD Project Logo. This logo depicts the intestine and the multifaceted character of the project
Fig. 2
Fig. 2
Simplified 1000IBD data model. 1000IBD-ID is the 1000IBD identifier used in every data-layer, also referred to as primary key (PK) and foreign key 1 (FK1). RNAseq: RNA-sequencing, 16S: Sequencing data of the microbial 16S rRNA gene; WGS: whole genome shotgun sequencing
Fig. 3
Fig. 3
Flow of research data from the 1000IBD project. In Stage 1, data that has been generated or will be generated is announced. In Stage 2, summary statistics will be made available. In Stage 3, the data itself will be publicly released

Similar articles

See all similar articles

Cited by 2 articles

References

    1. Abraham C, Cho JH. Inflammatory bowel disease. N Engl J Med. 2009;361:2066–2078. doi: 10.1056/NEJMra0804647. - DOI - PMC - PubMed
    1. Cleynen I, et al. Inherited determinants of Crohn’s disease and ulcerative colitis phenotypes: a genetic association study. Lancet. 2016;387:156–167. doi: 10.1016/S0140-6736(15)00465-1. - DOI - PMC - PubMed
    1. Jostins L, et al. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature. 2012;491:119–124. doi: 10.1038/nature11582. - DOI - PMC - PubMed
    1. Huang H, et al. Fine-mapping inflammatory bowel disease loci to single-variant resolution. Nature. 2017;547:173–178. doi: 10.1038/nature22969. - DOI - PMC - PubMed
    1. Goyette P, et al. High-density mapping of the MHC identifies a shared role for HLA-DRB1∗01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis. Nat. Genet. 2015;47:172–179. - PMC - PubMed

MeSH terms

Feedback