Evidence map›Paper›PMID 35379844›Full record

ArticleScientific reports2022

High miR203a-3p and miR-375 expression in the airways of smokers with and without COPD.

Jos van Nijnatten, Corry-Anke Brandsma, Katrina Steiling, Pieter S Hiemstra, Wim Timens, Maarten van den Berge, Alen Faiz

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 12 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

7 authors at 4 institutions in 3 countries.

Jos van NijnattenDepartment of Pathology and Medical Biology, University Medical Center Groningen, The University of Groningen, Groningen, The Netherlands.
Corry-Anke BrandsmaDepartment of Pathology and Medical Biology, University Medical Center Groningen, The University of Groningen, Groningen, The Netherlands.
Katrina SteilingBioinformatics Program, Boston University, Boston, MA, USA.
Pieter S HiemstraDepartment of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands.
Wim TimensDepartment of Pathology and Medical Biology, University Medical Center Groningen, The University of Groningen, Groningen, The Netherlands.
Maarten van den BergeDepartment of Pulmonary Diseases, University Medical Center Groningen, The University of Groningen, Groningen, The Netherlands. m.van.den.berge@umcg.nl.
Alen FaizDepartment of Pulmonary Diseases, University Medical Center Groningen, The University of Groningen, Groningen, The Netherlands.
University Medical Center Groningen · NLBoston University · USLeiden University Medical Center · NLUniversity of Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smoking is a leading cause of chronic obstructive pulmonary disease (COPD). It is known to have a significant impact on gene expression and (inflammatory) cell populations in the airways involved in COPD pathogenesis. In this study, we investigated the impact of smoking on the expression of miRNAs in healthy and COPD individuals. We aimed to elucidate the overall smoking-induced miRNA changes and those specific to COPD. In addition, we investigated the downstream effects on regulatory gene expression and the correlation to cellular composition. We performed a genome-wide miRNA expression analysis on a dataset of 40 current- and 22 ex-smoking COPD patients and a dataset of 35 current- and 38 non-smoking respiratory healthy controls and validated the results in an independent dataset. miRNA expression was then correlated with mRNA expression in the same patients to assess potential regulatory effects of the miRNAs. Finally, cellular deconvolution analysis was used to relate miRNAs changes to specific cell populations. Current smoking was associated with increased expression of three miRNAs in the COPD patients and 18 miRNAs in the asymptomatic smokers compared to respiratory healthy controls. In comparison, four miRNAs were lower expressed with current smoking in asymptomatic controls. Two of the three smoking-related miRNAs in COPD, miR-203a-3p and miR-375, were also higher expressed with current smoking in COPD patients and the asymptomatic controls. The other smoking-related miRNA in COPD patients, i.e. miR-31-3p, was not present in the respiratory healthy control dataset. miRNA-mRNA correlations demonstrated that miR-203a-3p, miR-375 and also miR-31-3p expression were negatively associated with genes involved in pro-inflammatory pathways and positively associated with genes involved in the xenobiotic pathway. Cellular deconvolution showed that higher levels of miR-203a-3p were associated with higher proportions of proliferating-basal cells and secretory (club and goblet) cells and lower levels of fibroblasts, luminal macrophages, endothelial cells, B-cells, amongst other cell types. MiR-375 expression was associated with lower levels of secretory cells, ionocytes and submucosal cells, but higher levels of endothelial cells, smooth muscle cells, and mast cells, amongst other cell types. In conclusion, we identified two smoking-induced miRNAs (miR-375 and miR-203a-3p) that play a role in regulating inflammation and detoxification pathways, regardless of the presence or absence of COPD. Additionally, in patients with COPD, we identified miR-31-3p as a miRNA induced by smoking. Our identified miRNAs should be studied further to unravel which smoking-induced inflammatory mechanisms are reactive and which are involved in COPD pathogenesis.

Indexed as

MicroRNAsPulmonary Disease, Chronic ObstructiveEndothelial CellsHumansLungSmokersMicroRNAsMIRN375 microRNA, human

Identifiers

PMID35379844
PMCPMC8980043
OpenAlexW4226049761

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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.