Evidence map›Paper›PMID 23209423›Full record

ArticlePLoS genetics2012

Lung eQTLs to help reveal the molecular underpinnings of asthma.

Ke Hao, Yohan Bossé, David C Nickle, Peter D Paré, Dirkje S Postma, Michel Laviolette, Andrew Sandford, Tillie L Hackett, Denise Daley, James C Hogg and 19 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 182 papers, 23 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
182citing papers in PubMed, 23 pooled it
15.3field-weighted citation impact, top 1% 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

182 citing papers in PubMed, 23 syntheses or guidelines pooled it, 329 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pleiotropic Analysis of Lung Cancer and Blood Triglycerides.Journal of the National Cancer Institute · 2016
    Pooled it
  12. Pooled it
  13. Pooled it
  14. Pooled it
  15. Pooled it
  16. Pooled it
  17. Pooled it
  18. Pooled it
  19. Pooled it
  20. Pooled it

122 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

29 authors at 9 institutions in 3 countries.

Ke HaoMerck Research Laboratories, Boston, Massachusetts, United States of America.
Yohan Bossé
David C Nickle
Peter D Paré
Dirkje S Postma
Michel Laviolette
Andrew Sandford
Tillie L Hackett
Denise Daley
James C Hogg
W Mark Elliott
Christian Couture
Maxime Lamontagne
Corry-Anke Brandsma
Maarten van den Berge
Gerard Koppelman
Alise S Reicin
Donald W Nicholson
Vladislav Malkov
Jonathan M Derry
Christine Suver
Jeffrey A Tsou
Amit Kulkarni
Chunsheng Zhang
Rupert Vessey
Greg J Opiteck
Sean P Curtis
Wim Timens
Don D Sin
Merck & Co., Inc., Rahway, NJ, USA (United States) · USSt. Paul's Hospital · CAUniversity of Groningen · NLUniversité Laval · CAUniversity of British Columbia · CARosetta Stone (United States) · USSage Bionetworks · USInstitut universitaire de cardiologie et de pneumologie de Québec · CAUniversity Medical Center Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have identified loci reproducibly associated with pulmonary diseases; however, the molecular mechanism underlying these associations are largely unknown. The objectives of this study were to discover genetic variants affecting gene expression in human lung tissue, to refine susceptibility loci for asthma identified in GWAS studies, and to use the genetics of gene expression and network analyses to find key molecular drivers of asthma. We performed a genome-wide search for expression quantitative trait loci (eQTL) in 1,111 human lung samples. The lung eQTL dataset was then used to inform asthma genetic studies reported in the literature. The top ranked lung eQTLs were integrated with the GWAS on asthma reported by the GABRIEL consortium to generate a Bayesian gene expression network for discovery of novel molecular pathways underpinning asthma. We detected 17,178 cis- and 593 trans- lung eQTLs, which can be used to explore the functional consequences of loci associated with lung diseases and traits. Some strong eQTLs are also asthma susceptibility loci. For example, rs3859192 on chr17q21 is robustly associated with the mRNA levels of GSDMA (P = 3.55 × 10(-151)). The genetic-gene expression network identified the SOCS3 pathway as one of the key drivers of asthma. The eQTLs and gene networks identified in this study are powerful tools for elucidating the causal mechanisms underlying pulmonary disease. This data resource offers much-needed support to pinpoint the causal genes and characterize the molecular function of gene variants associated with lung diseases.

Indexed as

Genome-Wide Association StudyQuantitative Trait LociSuppressor of Cytokine Signaling ProteinsAsthmaBayes TheoremGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseHumansPolymorphism, Single NucleotideSuppressor of Cytokine Signaling 3 ProteinSOCS3 protein, humanSuppressor of Cytokine Signaling 3 ProteinSuppressor of Cytokine Signaling Proteins

Identifiers

PMID23209423
PMCPMC3510026
OpenAlexW2148351250

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.