Evidence map›Paper›PMID 33313682›Full record

ArticleInflammatory bowel diseases2021

Understanding the Molecular Drivers of Disease Heterogeneity in Crohn's Disease Using Multi-omic Data Integration and Network Analysis.

Padhmanand Sudhakar, Bram Verstockt, Jonathan Cremer, Sare Verstockt, João Sabino, Marc Ferrante, Séverine Vermeire

Open access · bronzeAbstract read
In one paragraph

Article in Inflammatory bowel diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 45 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. AI-enabled 'endo-histo-omics': breaking down intestinal barriers in IBD.Nature reviews. Gastroenterology & hepatology · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Observational
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Omics and Multi-Omics in IBD: No Integration, No Breakthroughs.International journal of molecular sciences · 2023
    Review
  18. Article
  19. Article
  20. Big Data in Gastroenterology Research.International journal of molecular sciences · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Padhmanand SudhakarDepartment of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID).ORCID 0000-0003-1907-4491
Bram VerstocktDepartment of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID).
Jonathan CremerDepartment of Microbiology and Immunology, Laboratory of Clinical Immunology, Katholieke Universiteit Leuven, Leuven, Belgium.
Sare VerstocktDepartment of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID).
João SabinoDepartment of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID).
Marc FerranteDepartment of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID).
Séverine VermeireDepartment of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID).
KU Leuven · BE

Funding

European Research Council 694679
6 · The paper itself

Abstract

Crohn's disease (CD), a form of inflammatory bowel disease (IBD), is characterized by heterogeneity along multiple clinical axes, which in turn impacts disease progression and treatment modalities. Using advanced data integration approaches and systems biology tools, we studied the contribution of CD susceptibility variants and gene expression in distinct peripheral immune cell subsets (CD14+ monocytes and CD4+ T cells) to relevant clinical traits. Our analyses revealed that most clinical traits capturing CD heterogeneity could be associated with CD14+ and CD4+ gene expression rather than disease susceptibility variants. By disentangling the sources of variation, we identified molecular features that could potentially be driving the heterogeneity of various clinical traits of CD patients. Further downstream analyses identified contextual hub proteins such as genes encoding barrier functions, antimicrobial peptides, chemokines, and their receptors, which are either targeted by drugs used in CD or other inflammatory diseases or are relevant to the biological functions implicated in disease pathology. These hubs could be used as cell type-specific targets to treat specific subtypes of CD patients in a more individualized approach based on the underlying biology driving their disease subtypes. Our study highlights the importance of data integration and systems approaches to investigate complex and heterogeneous diseases such as IBD.

Indexed as

Crohn DiseaseAntimicrobial PeptidesCD4-Positive T-LymphocytesChemokinesHumansSystems BiologyAntimicrobial PeptidesChemokinesbloodCD4+ T cellsclinical phenotypesCrohn’s diseasedata integrationdrug repurposingdrug targetsgene expressiongeneticsheterogeneityhubsmonocytesnetworkssystems biology

Identifiers

PMID33313682
PMCPMC8128416
OpenAlexW3112595545

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.