Evidence map›Paper›PMID 22189154›Full record

SynthesisBMC systems biology2011

A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections.

Stewart T Chang, Nicolas Tchitchek, Debashis Ghosh, Arndt Benecke, Michael G Katze

Abstract readMeta-Analysis
In one paragraph

Synthesis in BMC systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Bugs in the system.Immunological reviews · 2013
    Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Critical dynamics in host-pathogen systems.Current topics in microbiology and immunology · 2013
    Review
  14. Article
  15. 6th International Conference on Emerging Zoonoses.Zoonoses and public health · 2012
    Article
  16. Systems biology from virus to humans.Journal of analytical science and technology
    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.

Stewart T ChangDepartment of Microbiology, University of Washington, Seattle WA, USA.
Nicolas Tchitchek
Debashis Ghosh
Arndt Benecke
Michael G Katze

Funding

NIAID NIH HHS HHSN272200800060C
6 · The paper itself

Abstract

backgroundDuring respiratory viral infections host injury occurs due in part to inappropriate host responses. In this study we sought to uncover the host transcriptional responses underlying differences between high- and low-pathogenic infections.

resultsFrom a compendium of 12 studies that included responses to influenza A subtype H5N1, reconstructed 1918 influenza A virus, and SARS coronavirus, we used meta-analysis to derive multiple gene expression signatures. We compared these signatures by their capacity to segregate biological conditions by pathogenicity and predict pathogenicity in a test data set. The highest-performing signature was expressed as a continuum in low-, medium-, and high-pathogenicity samples, suggesting a direct, analog relationship between expression and pathogenicity. This signature comprised 57 genes including a subnetwork of chemokines, implicating dysregulated cell recruitment in injury.

conclusionsHighly pathogenic viruses elicit expression of many of the same key genes as lower pathogenic viruses but to a higher degree. This increased degree of expression may result in the uncontrolled co-localization of inflammatory cell types and lead to irreversible host damage.

Indexed as

ChemokinesCluster AnalysisGene Expression ProfilingGene Expression Regulation, ViralHumansInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H5N1 SubtypeRespiratory Tract InfectionsSevere acute respiratory syndrome-related coronavirusVirulenceChemokines

Identifiers

PMID22189154
PMCPMC3297540

What OpenQuestion holds

Textmetadata
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.