Evidence map›Paper›PMID 26102239›Full record

ArticleAmerican journal of respiratory cell and molecular biology2016

Airway Epithelial Expression Quantitative Trait Loci Reveal Genes Underlying Asthma and Other Airway Diseases.

Wei Luo, Ma'en Obeidat, Antonio Fabio Di Narzo, Rong Chen, Don D Sin, Peter D Paré, Ke Hao

Abstract read
In one paragraph

Article in American journal of respiratory cell and molecular biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  15. Lessons Learned From GWAS of Asthma.Allergy, asthma & immunology research · 2019
    Review
  16. Article
  17. Article
  18. Multitissue Transcriptomics Delineates the Diversity of Airway T Cell Functions in Asthma.American journal of respiratory cell and molecular biology · 2018
    Article
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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.

Wei Luo1 College of Computer Science and Technology, Huaqiao University, Xiamen, China.
Ma'en Obeidat3 The University of British Columbia Center for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada.
Antonio Fabio Di Narzo2 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.
Rong Chen2 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.
Don D Sin3 The University of British Columbia Center for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada.
Peter D Paré3 The University of British Columbia Center for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada.
Ke Hao2 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.

Funding

Integrative Omics to Discover Molecular Determinants of COPDR01HL118542 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI HACKETT, TILLIE-LOUISE, LENBURG, MARC ELLIOTT · 2013 to 2016
$2.7M
Canadian Institutes of Health ResearchNHLBI NIH HHS R01 HL118542NHLBI NIH HHS R01HL118542
6 · The paper itself

Abstract

Genome-wide association studies (GWASs) have identified loci that are robustly associated with asthma and related phenotypes; however, the molecular mechanisms underlying these associations need to be explored. The most relevant tissues to study the functional consequences of asthma are the airways. We used publically available data to derive expression quantitative trait loci (eQTLs) for human epithelial cells from small and large airways and applied the eQTLs in the interpretation of GWAS results of asthma and related phenotypes. For the small airways (n = 105), we discovered 660 eQTLs at a 10% false discovery rate (FDR), among which 315 eQTLs were not previously reported in a large-scale eQTL study of whole lung tissue. A large fraction of the identified eQTLs is supported by data from Encyclopedia of DNA Elements (ENCODE) showing that the eQTLs reside in regulatory elements (57.5 and 67.6% of cis- and trans-eQTLs, respectively). Published pulmonary GWAS hits were enriched as airway epithelial eQTLs (9.2-fold). Further, genes regulated by asthma GWAS loci in epithelium are significantly enriched in immune response pathways, such as IL-4 signaling (FDR, 5.2 × 10(-4)). The airway epithelial eQTLs described in this study are complementary to previously reported lung eQTLs and represent a powerful resource to link GWAS-associated variants to their regulatory function and thus elucidate the molecular mechanisms underlying asthma and airway-related conditions.

Indexed as

Polymorphism, Single NucleotideQuantitative Trait LociAsthmaComputational BiologyDatabases, GeneticEpithelial CellsFemaleGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksGenetic MarkersGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMalePhenotypeGenetic Markersairway diseasesairway epitheliumasthmaexpression quantitative trait loci

Identifiers

PMID26102239
PMCPMC4821039

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Registered trials

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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.