Evidence map›Paper›PMID 27585741›Full record

ArticleScientific reports2016

Distinct metabolic network states manifest in the gene expression profiles of pediatric inflammatory bowel disease patients and controls.

Carolin Knecht, Christoph Fretter, Philip Rosenstiel, Michael Krawczak, Marc-Thorsten Hütt

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. 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

5 authors.

Carolin KnechtInstitute of Medical Informatics and Statistics, Christian-Albrechts University Kiel, Kiel, Germany.
Christoph FretterDepartment of Life Sciences and Chemistry, Jacobs University, Bremen, Germany.
Philip RosenstielInstitute of Clinical Molecular Biology, Center for Molecular Biosciences, Christian-Albrechts University Kiel, Kiel, Germany.
Michael KrawczakInstitute of Medical Informatics and Statistics, Christian-Albrechts University Kiel, Kiel, Germany.
Marc-Thorsten HüttDepartment of Life Sciences and Chemistry, Jacobs University, Bremen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Information on biological networks can greatly facilitate the function-orientated interpretation of high-throughput molecular data. Genome-wide metabolic network models of human cells, in particular, can be employed to contextualize gene expression profiles of patients with the goal of both, a better understanding of individual etiologies and an educated reclassification of (clinically defined) phenotypes. We analyzed publicly available expression profiles of intestinal tissues from treatment-naive pediatric inflammatory bowel disease (IBD) patients and age-matched control individuals, using a reaction-centric metabolic network derived from the Recon2 model. By way of defining a measure of 'coherence', we quantified how well individual patterns of expression changes matched the metabolic network. We observed a bimodal distribution of metabolic network coherence in both patients and controls, albeit at notably different mixture probabilities. Multidimensional scaling analysis revealed a bisectional pattern as well that overlapped widely with the metabolic network-based results. Expression differences driving the observed bimodality were related to cellular transport of thiamine and bile acid metabolism, thereby highlighting the crosstalk between metabolism and other vital pathways. We demonstrated how classical data mining and network analysis can jointly identify biologically meaningful patterns in gene expression data.

Indexed as

Gene Expression ProfilingAdolescentCase-Control StudiesChildChild, PreschoolData MiningFemaleGene Expression RegulationHumansInflammatory Bowel DiseasesIntestinal MucosaIntestinesMaleMetabolic Networks and PathwaysPhenotype

Identifiers

PMID27585741
PMCPMC5009330

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.