Evidence map›Paper›PMID 25431000›Full record

ArticleBMC systems biology2014

Sexually-dimorphic targeting of functionally-related genes in COPD.

Kimberly Glass, John Quackenbush, Edwin K Silverman, Bartolome Celli, Stephen I Rennard, Guo-Cheng Yuan, Dawn L DeMeo

Abstract read
In one paragraph

Article in BMC systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Trial
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  10. New role for cardiomyocytebioRxiv : the preprint server for biology · 2024
    Article
  11. Article
  12. Gene regulatory Networks Reveal Sex Difference in Lung Adenocarcinoma.bioRxiv : the preprint server for biology · 2023
    Article
  13. Network-based approaches for modeling disease regulation and progression.Computational and structural biotechnology journal · 2023
    Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Constructing gene regulatory networks using epigenetic data.NPJ systems biology and applications · 2021
    Article
  19. Review
  20. 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

7 authors.

Kimberly GlassDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA. rekrg@channing.harvard.edu.
John QuackenbushDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA. johnq@jimmy.harvard.edu.
Edwin K SilvermanChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. reeks@channing.harvard.edu.
Bartolome CelliDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA. bcelli@partners.org.
Stephen I RennardDivision of Pulmonary, Critical Care, Sleep and Allergy, University of Nebraska Medical Center, Omaha, NE, USA. srennard@unmc.edu.
Guo-Cheng YuanDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA. gcyuan@jimmy.harvard.edu.
Dawn L DeMeoChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. redld@channing.harvard.edu.

Funding

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
Genetic Features of Gender Differences in COPDR01HL089438 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI DEMEO, DAWN L · 2008 to 2011
$3.3M
NHLBI NIH HHS P01 HL105339NHLBI NIH HHS R01 HL089438NHLBI NIH HHS R01 HL111759NHLBI NIH HHS R01 HL111759-01A1NHLBI NIH HHS R01 HL111759-02S1
6 · The paper itself

Abstract

backgroundThere is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism.

resultsHere we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways.

conclusionsNetwork analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts.

Indexed as

Models, BiologicalSex CharacteristicsSoftwareFemaleGene Regulatory NetworksHumansMalePrincipal Component AnalysisPulmonary Disease, Chronic ObstructiveRegulatory Elements, TranscriptionalSputum

Identifiers

PMID25431000
PMCPMC4269917

What OpenQuestion holds

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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.