Evidence map›Paper›PMID 31836022›Full record

ReviewJournal of translational medicine2019

Integrating omics for a better understanding of Inflammatory Bowel Disease: a step towards personalized medicine.

Manoj Kumar, Mathieu Garand, Souhaila Al Khodor

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Decoding the power of the microbiome in human health.Frontiers in cellular and infection microbiology · 2026
    Review
  8. From AI-AssistedPharmaceuticals (Basel, Switzerland) · 2025
    Review
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  15. Foods (Basel, Switzerland) · 2023
    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

3 authors.

Manoj KumarResearch Department, Sidra Medicine, Doha, Qatar.
Mathieu GarandResearch Department, Sidra Medicine, Doha, Qatar.
Souhaila Al KhodorResearch Department, Sidra Medicine, Doha, Qatar. salkhodor@sidra.org.ORCID 0000-0003-4858-7130

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammatory Bowel Disease (IBD) is a multifactorial chronic disease. Understanding only one aspect of IBD pathogenesis does not reflect the complex nature of IBD nor will it improve its clinical management. Therefore, it is vital to dissect the interactions between the different players in IBD pathogenesis in order to understand the biology of the disease and enhance its clinical outcomes.

aimsTo provide an overview of the available omics data used to assess the potential mechanisms through which various players are contributing to IBD pathogenesis and propose a precision medicine model to fill the current knowledge gap in IBD.

resultsSeveral studies have reported microbial dysbiosis, immune and metabolic dysregulation in IBD patients, however, this data is not sufficient to create signatures that can differentiate between the disease subtypes or between disease relapse and remission.

conclusionsWe summarized the current knowledge in the application of omics in IBD patients, and we showed that the current knowledge gap in IBD hinders the improvements of clinical decision for treatment as well as the prediction of disease relapse. We propose one way to fill this gap by implementing integrative analysis of various omics datasets generated from one patient at a single time point.

Indexed as

GenomicsPrecision MedicineHumansInflammatory Bowel DiseasesMicrobiotaModels, BiologicalMutationCrohn’s diseaseMulti-omicsSystems biologyUlcerative colitis

Identifiers

PMID31836022
PMCPMC6909475

What OpenQuestion holds

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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.