Evidence map›Paper›PMID 28324666›Full record

SynthesisAmerican journal of respiratory cell and molecular biology2017

Gene Expression Analysis to Assess the Relevance of Rodent Models to Human Lung Injury.

Timothy E Sweeney, Shane Lofgren, Purvesh Khatri, Angela J Rogers

Open access · greenAbstract readComparative StudyMeta-Analysis
In one paragraph

Synthesis in American journal of respiratory cell and molecular biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Transcriptomic congruence analysis for evaluating model organisms.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Rare Variants in Inborn Errors of Immunity Genes Associated With Covid-19 Severity.Frontiers in cellular and infection microbiology · 2022
    Article
  7. YAP expression in endothelial cells prevents ventilator-induced lung injury.American journal of physiology. Lung cellular and molecular physiology · 2021
    Article
  8. Article
  9. Transcriptional Profiling of the Murine Airway Response to Acute Ozone Exposure.Toxicological sciences : an official journal of the Society of Toxicology · 2020
    Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. 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

4 authors at 2 institutions in 3 countries.

Timothy E Sweeney1 Stanford Institute for Immunity, Transplantation and Infection.ORCID 0000-0002-3596-1093
Shane Lofgren1 Stanford Institute for Immunity, Transplantation and Infection.
Purvesh Khatri1 Stanford Institute for Immunity, Transplantation and Infection.
Angela J Rogers3 Department of Medicine, Division of Pulmonary and Critical Care Medicine, Stanford University School of Medicine, Stanford, California.
Translational Research Informatics Center (Japan) · JPStanford University · US

Funding

Using a tonsil organoid system to probe conditions for the induction of protective antibody and T cell responses to influenza.U19AI057229 · NIAID · STANFORD UNIVERSITY · PI Mark Morris Davis · 2003 to 2026
$88.5M
Bioinformatics Approach to Influenza A/H1N1 Vaccine Immune ProfilingU01AI089859 · NIAID · MAYO CLINIC ROCHESTER · PI POLAND, GREGORY A. · 2010 to 2015
$33.8M
Translational Incubator CoreU19AI109662 · NIAID · STANFORD UNIVERSITY · PI GLENN, JEFFREY S · 2014 to 2019
$28.6M
Metabolic derangements in ARDSK23HL125663 · NHLBI · STANFORD UNIVERSITY · PI ROGERS, ANGELA J · 2015 to 2018
$744k
NHLBI NIH HHS K23 HL125663NIAID NIH HHS U01 AI089859NIAID NIH HHS U19 AI057229NIAID NIH HHS U19 AI109662
6 · The paper itself

Abstract

The relevance of animal models to human diseases is an area of intense scientific debate. The degree to which mouse models of lung injury recapitulate human lung injury has never been assessed. Integrating data from both human and animal expression studies allows for increased statistical power and identification of conserved differential gene expression across organisms and conditions. We sought comprehensive integration of gene expression data in experimental acute lung injury (ALI) in rodents compared with humans. We performed two separate gene expression multicohort analyses to determine differential gene expression in experimental animal and human lung injury. We used correlational and pathway analyses combined with external in vitro gene expression data to identify both potential drivers of underlying inflammation and therapeutic drug candidates. We identified 21 animal lung tissue datasets and three human lung injury bronchoalveolar lavage datasets. We show that the metasignatures of animal and human experimental ALI are significantly correlated despite these widely varying experimental conditions. The gene expression changes among mice and rats across diverse injury models (ozone, ventilator-induced lung injury, LPS) are significantly correlated with human models of lung injury (Pearson r = 0.33-0.45, P < 1E

Indexed as

Disease Models, AnimalTranscriptomeAcute Lung InjuryAlveolar Epithelial CellsAnimalsBronchoalveolar Lavage FluidDatasets as TopicDrug DiscoveryDrugs, InvestigationalGene Regulatory NetworksHumansLigandsLipopolysaccharidesMacrophages, AlveolarMiceNeutrophilsDrugs, InvestigationalLigandsLipopolysaccharidesOzoneacute lung injuryacute respiratory distress syndromeanimal modelgene expressionhuman

Identifiers

PMID28324666
PMCPMC5576585
OpenAlexW2601450563

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.