The 1000IBD project: multi-omics data of 1000 inflammatory bowel disease patients; data release 1.
Crohn’s disease
Dataset
Genome
Inflammatory bowel disease
Microbiome
Transcriptome
Ulcerative colitis
Journal
BMC gastroenterology
ISSN: 1471-230X
Titre abrégé: BMC Gastroenterol
Pays: England
ID NLM: 100968547
Informations de publication
Date de publication:
08 Jan 2019
08 Jan 2019
Historique:
received:
06
06
2018
accepted:
06
12
2018
entrez:
10
1
2019
pubmed:
10
1
2019
medline:
1
2
2019
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
BACKGROUND
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
UNASSIGNED
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
CONCLUSIONS
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
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.
Identifiants
pubmed: 30621600
doi: 10.1186/s12876-018-0917-5
pii: 10.1186/s12876-018-0917-5
pmc: PMC6325838
doi:
Substances chimiques
Biomarkers
0
RNA, Ribosomal, 16S
0
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
5Subventions
Organisme : Nederlandse Organisatie voor Wetenschappelijk Onderzoek
ID : 016.136.308
Organisme : Nederlandse Organisatie voor Wetenschappelijk Onderzoek
ID : 92.003.577
Organisme : Maag Lever Darm Stichting
ID : MLDS D16-14
Organisme : Maag Lever Darm Stichting (NL)
ID : CD14-04
Commentaires et corrections
Type : ErratumIn
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