Evidence map›Paper›PMID 41302568›Full record

ReviewInternational journal of environmental research and public health2025

Epigenetic Alterations Induced by Smoking and Their Intersection with Artificial Intelligence: A Narrative Review.

Edith Simona Ianosi, Daria Maria Tomoroga, Anca Meda Văsieșiu, Bianca Liana Grigorescu, Mara Vultur, Maria Beatrice Ianosi

Abstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2025. 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

6 authors.

Edith Simona IanosiDepartment of Pulmonology, University of Medicine, Pharmacy, Science and Technology "George Emil Palade" of Târgu Mureș, 540139 Târgu Mureș, Romania.ORCID 0009-0003-3558-2856
Daria Maria TomorogaUniversity of Medicine, Pharmacy, Science and Technology "George Emil Palade" of Târgu Mureș, 540139 Târgu Mureș, Romania.ORCID 0009-0002-5101-3437
Anca Meda VăsieșiuDepartment of Infectious Disease, University of Medicine, Pharmacy, Science and Technology "George Emil Palade" of Târgu Mureș, 540139 Târgu Mureș, Romania.ORCID 0000-0003-2880-4337
Bianca Liana GrigorescuDepartment of Anaesthesiology and Intensive Care, University of Medicine, Pharmacy, Science and Technology "George Emil Palade" of Târgu Mureș, 540139 Târgu Mureș, Romania.
Mara VulturDepartment of Pulmonology, University of Medicine, Pharmacy, Science and Technology "George Emil Palade" of Târgu Mureș, 540139 Târgu Mureș, Romania.ORCID 0009-0002-1695-6990
Maria Beatrice IanosiClinic of Pulmonology, County Hospital Mures, 540011 Târgu Mures, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCigarette smoking is unquestionably associated with an increase in morbidity and mortality worldwide, exerting significant adverse effects on respiratory health. The impact of tobacco persists in the epigenome long after smoking cessation. Furthermore, the offspring of smokers may also be affected by the detrimental effects of smoking. MATERIAL AND

methodsThe modifications made to the body, such as DNA methylation, histone modification, and regulation by non-coding RNAs, do not change the DNA sequence but can influence gene expression. In respiratory disease, multigenerational effects have been reported in humans, with an increased risk of asthma or COPD and decreased lung function in offspring, despite them not being exposed to smoke. Prenatal nicotine exposure leads to pulmonary pathology that persists across three consecutive generations, supported by animal studies conducted by Rehan et al. Significant advances in high-throughput genomic and epigenomic technologies have enabled the discovery of molecular phenotypes. These either reflect or are influenced by them. Due to the hidden environmental effects and the rise of artificial intelligence (AI) in biomedical research, new predictive models are emerging that not only explain complex data but also enable earlier detection and prevention of smoking-related diseases. In this narrative review, we synthesise the latest research on how smoking affects gene regulation and chromatin structure, emphasising how tobacco can increase vulnerability to multiple diseases. DISCUSSION: For many years, it was widely believed that diseases are solely inherited through genetics. However, recent research in epigenetics has led to a significant realisation: environmental factors play a crucial role in an individual's life. External influences leave a mark on DNA that can influence future health and offer insights into potential illnesses. In this context, it is possible that in the future, doctors might treat people not as a whole but as individual beings, with personalised medication, tests, and other approaches.

conclusionsThe accumulated evidence suggests that exposure to various environmental factors is associated with multigenerational changes in gene expression patterns, which may contribute to increased disease risk. The application of artificial intelligence in this domain is currently a crucial tool for researching potential future health issues in individuals, and it holds a powerful prospect that could transform current medical and scientific practice.

Indexed as

Artificial IntelligenceCigarette SmokingEpigenesis, GeneticGene Expression RegulationPrenatal Exposure Delayed EffectsHumansNicotinePredictive Learning ModelsNicotineartificial intelligenceDNA methylationepigenetic inheritancehistone modificationmultigenerational respiratory diseasenon-coding RNAtransgenerational respiratory disease

Identifiers

PMID41302568
PMCPMC12652836

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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.