Evidence map›Paper›PMID 31233743›Full record

ArticleChest2019

Gene Expression Alterations in the Bronchial Epithelium of e-Cigarette Users.

Sean E Corbett, Matthew Nitzberg, Elizabeth Moses, Eric Kleerup, Teresa Wang, Catalina Perdomo, Claudia Perdomo, Gang Liu, Xiaohui Xiao, Hanqiao Liu and 6 more

Abstract readComparative Study
In one paragraph

Article in Chest, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

13 citing papers in PubMed, 21 citations in OpenAlex.

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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

16 authors at 2 institutions in 1 country.

Sean E CorbettBioinformatics Program, Boston University, Boston, MA; Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
Matthew NitzbergSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA; Pulmonary Center, Boston University School of Medicine, Boston, MA.
Elizabeth MosesSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
Eric KleerupDivision of Pulmonary and Critical Care Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA.
Teresa WangBioinformatics Program, Boston University, Boston, MA; Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
Catalina PerdomoSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
Claudia PerdomoDivision of Pulmonary and Critical Care Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA.
Gang LiuSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
Xiaohui XiaoSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
Hanqiao LiuSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
David A ElashoffDepartment of Biostatistics, University of California, Los Angeles, CA.
Daniel R BrooksSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA; Department of Epidemiology, Boston University School of Public Health, Boston, MA.
George T O'ConnorSection of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA; Pulmonary Center, Boston University School of Medicine, Boston, MA.
Steven M DubinettDivision of Pulmonary and Critical Care Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA.
Avrum SpiraBioinformatics Program, Boston University, Boston, MA; Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA; Pulmonary Center, Boston University School of Medicine, Boston, MA; Johnson & Johnson, Cambridge, MA. Electronic address: aspira@bu.edu.
Marc E LenburgBioinformatics Program, Boston University, Boston, MA; Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA.
Boston University · USUniversity of California, Los Angeles · US

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
BIOLOGY OF THE LUNG--MULTIDISCIPLINARY PROGRAMT32HL007035 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Darrell N. Kotton, JOSEPH P MIZGERD · 1985 to 2026
$24.3M
The UCLA - Boston University Lung Cancer Biomarker Development LaboratoryU01CA152751 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M., ELASHOFF, DAVID · 2010 to 2015
$5.0M
NCI NIH HHS P30 CA016042NCI NIH HHS U01 CA152751NHLBI NIH HHS T32 HL007035
6 · The paper itself

Abstract

backgroundAlthough e-cigarette (ECIG) use has increased in the United States, their potential health effects remain uncertain. Understanding the effects of tobacco cigarette (TCIG) smoke on bronchial airway epithelial gene expression have previously provided insights into tobacco-related disease pathogenesis. Identifying the impact of ECIGs on airway gene expression could provide insights into their potential long-term health effects. We sought to compare the bronchial airway gene-expression profiles of former TCIG smokers now using ECIGs with the profiles of former and current TCIG smokers.

methodsWe performed gene-expression profiling of bronchial epithelial cells collected from current TCIG smokers (n = 9), current ECIG users who are former TCIG smokers (n = 15), and former TCIG smokers (n = 21). We then compared our findings with previous studies of the effects of TCIG use on bronchial epithelium, as well an in vitro model of ECIG exposure.

resultsAmong 3,165 genes whose expression varied between the three study groups (q < 0.05), we identified 468 genes altered in ECIG users relative to former smokers (P < .05). Seventy-nine of these genes were up- or down-regulated concordantly among ECIG and TCIG users. We did not detect ECIG-associated gene-expression changes in known pathways associated with TCIG usage. Genes downregulated in ECIG users are enriched among the genes most downregulated by exposure of airway epithelium to ECIG vapor in vitro.

conclusionsECIGs induce both distinct and shared patterns of gene expression relative to TCIGs in the bronchial airway epithelium. The concordance of the genes altered in ECIG users and in the in vitro study suggests that genes altered in ECIG users are likely to be changed as the direct effect of ECIG exposure.

Indexed as

Electronic Nicotine Delivery SystemsEpithelial CellsGene Expression RegulationAdultBronchiCigarette SmokingFemaleGene Expression ProfilingHumansMaleMiddle AgedSmokingbiostatisticsgeneresearch-clinicalsmoking

Identifiers

PMID31233743
PMCPMC6859252
OpenAlexW2950298946

What OpenQuestion holds

Textmetadata
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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.