Evidence map›Paper›PMID 42016314›Full record

ArticleiScience2026

A comprehensive multi-omics and functional study of evolutionary adaptive responses to smoke.

Simon D Pouwels, Hao Chen, Senani N H Rathnayake, Andy Lan, Rashad M Mahbub, Anna Chi Ying Yeung, Corry-Anke Brandsma, Thamar J Lobo, Victor Guryev, Irene H Heijink and 2 more

Abstract read
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In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Simon D PouwelsUniversity of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, Groningen, the Netherlands.
Hao ChenCentre for Inflammation, Centenary Institute and University of Technology Sydney, School of Life Sciences, Sydney, NSW, Australia.
Senani N H RathnayakeUniversity of Technology Sydney, Respiratory Bioinformatics and Molecular Biology (RBMB), School of Life Sciences, Sydney, NSW, Australia.
Andy LanUniversity of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands.
Rashad M MahbubUniversity of Technology Sydney, Respiratory Bioinformatics and Molecular Biology (RBMB), School of Life Sciences, Sydney, NSW, Australia.
Anna Chi Ying YeungUniversity of Technology Sydney, Respiratory Bioinformatics and Molecular Biology (RBMB), School of Life Sciences, Sydney, NSW, Australia.
Corry-Anke BrandsmaUniversity of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands.
Thamar J LoboEuropean Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Victor GuryevEuropean Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Irene H HeijinkUniversity of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, Groningen, the Netherlands.
Maarten van den BergeUniversity of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD, Groningen, the Netherlands.
Alen FaizUniversity of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, Groningen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cigarette smoking remains one of the leading causes of preventable death worldwide. Upon inhalation, smoke induces damage to the lung epithelium, which can be the driving force for the development of chronic lung diseases. In the current study, we identified the "smoking signature" by assessing transcriptomic differences between current and non-smokers in multiple cohorts. By mapping the smoking signature onto single-cell and spatial transcriptomics data, we identified the surface layer of the airway epithelium as the part of the airways most affected by smoke. Next, by comparing the smoking signature between lungs of humans and non-human primates, we identified a cluster of human-specific smoke-response genes, suggesting an evolutionary adaptation to smoke exposure. Methylation and ChIP-seq analyses were used to identify

Indexed as

BioinformaticsComplex system biologyToxicology

Identifiers

PMID42016314
PMCPMC13092862

What OpenQuestion holds

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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.