Evidence map›Paper›PMID 40301976›Full record

ArticleJournal of translational medicine2025

Early-life smoking, cardiovascular disease risk, and the mediating role of DNA methylation biomarkers of aging.

Chang Sheng, Rui Zhou, Hongcai Wang, Guoqiang Lin, Zhou Cai, Wei Wang

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Observational
  5. Article
  6. Immunosenescence: signaling pathways, diseases and therapeutic targets.Signal transduction and targeted therapy · 2025
    Review
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.

Chang Sheng *Department of Vascular Surgery, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Rui Zhou *Department of Endocrinology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Hongcai WangDepartment of Cardiovascular Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Guoqiang LinDepartment of Cardiovascular Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Zhou CaiDepartment of Vascular Surgery, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. jinjians@csu.edu.cn.
Wei WangDepartment of Vascular Surgery, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. weiwangcsu@csu.edu.cn.ORCID http://orcid.org/0000-0002-0957-5762

Funding

National Natural Science Foundation of China 82070491National Natural Science Foundation of China 82470507
6 · The paper itself

Abstract

backgroundEarly-life smoking is linked to biological aging and chronic diseases, yet its specific relationship with cardiovascular disease (CVD) risk and the role of DNA methylation biomarkers of aging as potential mediators of that relationship remain underexplored.

methodsIn this study, we analyzed data from 2345 participants in the National Health and Nutrition Examination Survey (NHANES; 1999-2002). Early-life smoking status was assessed on the basis of the age of smoking initiation (ASI) and categorized into three smoking initiation periods (SIPs): childhood (5-14 years), adolescence/adulthood (> 14 years), and never smoked. DNA methylation biomarkers of aging (DNAm PhenoAge, DunedinPoAm, HorvathTelo) were measured, and CVD outcomes were determined via self-reported, physician-confirmed diagnoses. Multivariate logistic regression and causal mediation analyses were performed to assess the associations between SIP and CVD outcomes and explore the mediating effects of DNA methylation biomarkers on those associations.

resultsEarlier smoking initiation was more strongly associated with an increased risk of developing CVD, with childhood smoking showing the highest risk (OR = 1.95, 95% CI: 1.15-3.29; P = 0.013). Furthermore, DNA methylation biomarkers of aging were independently associated with increased CVD risk (1-year increase in DNAm PhenoAge: OR = 1.03, 95% CI: 1.01-1.05, P < 0.001; 0.1-unit increase in DunedinPoAm: OR = 1.19, 95% CI: 1.00-1.40, P < 0.05; 1-kb increase in HorvathTelo: OR = 0.57, 95% CI: 0.34-0.96, P < 0.05). Subgroup analysis revealed that the association between early-life smoking status and the risk of developing CVD was stronger among individuals without household smoking exposure (P for interaction = 0.035). Moreover, compared with early-life smoking status, later smoking initiation status was correlated with delayed epigenetic aging, as indicated by lower DNAm PhenoAge (β=-0.02, 95% CI: -0.03--0.01, P < 0.01), slower DunedinPoAm (β=-0.01, 95% CI: -0.01--0.01, P < 0.001), and longer HorvathTelo (β = 0.01, 95% CI: 0.01-0.01, P < 0.001). Mediation analysis revealed that DNAm PhenoAge significantly mediated the relationship between early-life smoking status and CVD risk, accounting for 6% of the total effect (ASI: ACME=-0.000100, P = 0.010; SIP: ACME = 0.004796, P = 0.022).

conclusionEarly-life smoking status is associated with significantly increased CVD risk. DNAm PhenoAge partially mediates this relationship, suggesting its potential as a target for prevention. Moreover, these findings highlight the need for early smoking prevention to reduce CVD risk.

Indexed as

AgingBiomarkersCardiovascular DiseasesDNA MethylationSmokingAdolescentAdultAgedChildChild, PreschoolFemaleHumansMaleMiddle AgedRisk FactorsBiomarkersCardiovascular diseaseDNA methylation biomarkersEarly-life smokingEpigenetic aging

Identifiers

PMID40301976
PMCPMC12038996

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.