Evidence map›Paper›PMID 27524493›Full record

ArticleGenomics2016

Diet-induced weight loss leads to a switch in gene regulatory network control in the rectal mucosa.

Ashley J Vargas, John Quackenbush, Kimberly Glass

Open access · hybridAbstract read
In one paragraph

Article in Genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Review
  3. Constructing gene regulatory networks using epigenetic data.NPJ systems biology and applications · 2021
    Article
  4. Gene Targeting in Disease Networks.Frontiers in genetics · 2021
    Article
  5. Article
  6. Molecular networks in Network Medicine: Development and applications.Wiley interdisciplinary reviews. Systems biology and medicine · 2020
    Review
  7. PUMA: PANDA Using MicroRNA Associations.Bioinformatics (Oxford, England) · 2020
    Article
  8. Review
  9. Article
  10. Estimating gene regulatory networks with pandaR.Bioinformatics (Oxford, England) · 2017
    Article
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 at 3 institutions in 1 country.

Ashley J VargasHarvard School of Public Health, Harvard University, Boston, MA, USA; Cancer Prevention Fellowship Program, National Cancer Institute, Rockville, MD, USA.
John QuackenbushHarvard School of Public Health, Harvard University, Boston, MA, USA; Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
Kimberly GlassDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA. Electronic address: rekrg@channing.harvard.edu.
Dana-Farber Cancer Institute · USHarvard University · USNational Cancer Institute · US

Funding

Statistical MethodsP01CA087969 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI TWOROGER, SHELLEY S · 2000 to 2019
$77.8M
Systems Biology, Bioinformatics, and BiostatisticsP01HL105339 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2011 to 2015
$12.2M
Using Networks to Assign Gene Function in Lung DiseaseR01HL111759 · NHLBI · DANA-FARBER CANCER INST · PI QUACKENBUSH, JOHN, SILVERMAN, EDWIN K · 2012 to 2015
$3.4M
NCI NIH HHS P01 CA087969NHLBI NIH HHS P01 HL105339NHLBI NIH HHS R01 HL111759
6 · The paper itself

Abstract

backgroundWeight loss may decrease risk of colorectal cancer in obese individuals, yet its effect in the colorectum is not well understood. We used integrative network modeling, Passing Attributes between Networks for Data Assimilation, to estimate transcriptional regulatory network models from mRNA expression levels from rectal mucosa biopsies measured pre- and post-weight loss in 10 obese, pre-menopausal women.

resultsWe identified significantly greater regulatory targeting of glucose transport pathways in the post-weight loss regulatory network, including "regulation of glucose transport" (FDR=0.02), "hexose transport" (FDR=0.06), "glucose transport" (FDR=0.06) and "monosaccharide transport" (FDR=0.08). These findings were not evident by gene expression analysis alone. Network analysis also suggested a regulatory switch from NFΚB1 to MAX control of MYC post-weight loss.

conclusionsThese network-based results expand upon standard gene expression analysis by providing evidence for a potential mechanistic alteration caused by weight loss.

Indexed as

Gene Regulatory NetworksAdultBasic-Leucine Zipper Transcription FactorsCaloric RestrictionFemaleGlucoseHumansIntestinal MucosaMiddle AgedNF-kappa B p50 SubunitObesityProto-Oncogene Proteins c-mycRectumWeight LossBasic-Leucine Zipper Transcription FactorsGlucoseMyc associated factor XNF-kappa B p50 SubunitNFKB1 protein, humanProto-Oncogene Proteins c-mycColorectal cancerColorectumDietGene networkGene regulationWeight loss

Identifiers

PMID27524493
PMCPMC5121035
OpenAlexW2515639027

What OpenQuestion holds

Textmetadata
LicenceTDM
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.