Evidence map›Paper›PMID 31446181›Full record

ArticleClinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association2020

Expression Levels of 4 Genes in Colon Tissue Might Be Used to Predict Which Patients Will Enter Endoscopic Remission After Vedolizumab Therapy for Inflammatory Bowel Diseases.

Bram Verstockt, Sare Verstockt, Marisol Veny, Jonas Dehairs, Kaline Arnauts, Gert Van Assche, Gert De Hertogh, Séverine Vermeire, Azucena Salas, Marc Ferrante

Abstract read
In one paragraph

Article in Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. How Artificial Intelligence Will Transform Clinical Care, Research, and Trials for Inflammatory Bowel Disease.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2025
    Review
  10. Article
  11. Challenges in IBD Research 2024: Precision Medicine.Inflammatory bowel diseases · 2024
    Review
  12. Observational
  13. Review
  14. Article
  15. Article
  16. Article
  17. Biomarkers That Predict Crohn's Disease Outcomes.Journal of the Canadian Association of Gastroenterology · 2024
    Review
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  19. Article
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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

10 authors.

Bram VerstocktDepartment of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Leuven, Belgium; Translational Research Center for Gastrointestinal Disorders, Department of Chronic Disease, Metabolism and Ageing, KU Leuven, Leuven, Belgium.
Sare VerstocktLaboratory for Complex Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium.
Marisol VenyDepartment of Gastroenterology, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Hospital Clínic, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain.
Jonas DehairsLaboratory of Lipid Metabolism and Cancer, Department of Oncology, KU Leuven, Leuven, Belgium.
Kaline ArnautsTranslational Research Center for Gastrointestinal Disorders, Department of Chronic Disease, Metabolism and Ageing, KU Leuven, Leuven, Belgium; Stem Cell Institute Leuven, Department of Development and Regeneration, KU Leuven, Leuven, Belgium.
Gert Van AsscheDepartment of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Leuven, Belgium; Translational Research Center for Gastrointestinal Disorders, Department of Chronic Disease, Metabolism and Ageing, KU Leuven, Leuven, Belgium.
Gert De HertoghTranslational Cell & Tissue Research Unit, Department of Imaging & Pathology, KU Leuven, Leuven, Belgium.
Séverine VermeireDepartment of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Leuven, Belgium; Translational Research Center for Gastrointestinal Disorders, Department of Chronic Disease, Metabolism and Ageing, KU Leuven, Leuven, Belgium.
Azucena SalasDepartment of Gastroenterology, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Hospital Clínic, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain.
Marc FerranteDepartment of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Leuven, Belgium; Translational Research Center for Gastrointestinal Disorders, Department of Chronic Disease, Metabolism and Ageing, KU Leuven, Leuven, Belgium. Electronic address: marc.ferrante@uzleuven.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

aimsWe aimed to identify biomarkers that might be used to predict responses of patients with inflammatory bowel diseases (IBD) to vedolizumab therapy.

methodsWe obtained biopsies from inflamed colon of patients with IBD who began treatment with vedolizumab (n = 31) or tumor necrosis factor (TNF) antagonists (n = 20) and performed RNA-sequencing analyses. We compared gene expression patterns between patients who did and did not enter endoscopic remission (absence of ulcerations at month 6 for patients with Crohn's disease or Mayo endoscopic subscore ≤1 at week 14 for patients with ulcerative colitis) and performed pathway analysis and cell deconvolution for training (n = 20) and validation (n = 11) datasets. Colon biopsies were also analyzed by immunohistochemistry. We validated a baseline gene expression pattern associated with endoscopic remission after vedolizumab therapy using 3 independent datasets (n = 66).

resultsWe identified significant differences in expression levels of 44 genes between patients who entered remission after vedolizumab and those who did not; we found significant increases in leukocyte migration in colon tissues from patients who did not enter remission (P < .006). Deconvolution methods identified a significant enrichment of monocytes (P = .005), M1-macrophages (P = .05), and CD4+ T cells (P = .008) in colon tissues from patients who did not enter remission, whereas colon tissues from patients in remission had higher numbers of naïve B cells before treatment (P = .05). Baseline expression levels of PIWIL1, MAATS1, RGS13, and DCHS2 identified patients who did vs did not enter remission with 80% accuracy in the training set and 100% accuracy in validation dataset 1. We validated these findings in the 3 independent datasets by microarray, RNA sequencing and quantitative PCR analysis (P = .003). Expression levels of these 4 genes did not associate with response to anti-TNF agents. We confirmed the presence of proteins encoded by mRNAs using immunohistochemistry.

conclusionsWe identified 4 genes whose baseline expression levels in colon tissues of patients with IBD associate with endoscopic remission after vedolizumab, but not anti-TNF, treatment. We validated this signature in 4 independent datasets and also at the protein level. Studies of these genes might provide insights into the mechanisms of action of vedolizumab.

Indexed as

Colitis, UlcerativeInflammatory Bowel DiseasesRGS ProteinsAntibodies, Monoclonal, HumanizedArgonaute ProteinsColonGastrointestinal AgentsHumansRemission InductionTreatment OutcomeTumor Necrosis Factor InhibitorsAntibodies, Monoclonal, HumanizedArgonaute ProteinsGastrointestinal AgentsPIWIL1 protein, humanRGS13 protein, humanRGS ProteinsTumor Necrosis Factor InhibitorsvedolizumabEndoscopic RemisisonIBDPersonalised MedicinePrecision MedicineVedolizumab

Identifiers

PMID31446181
PMCPMC7196933

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Registered trials

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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.