Lung microbiome predictors of epigenetic aging and potential associations with smoking and electronic cigarette use

BACKGROUND: The lungs harbor diverse microbial communities that may influence pulmonary health, potentially through lung aging. While accelerated lung aging can increase susceptibility to pulmonary diseases, no studies have yet linked the lung microbiome to biological aging in disease-free individuals. MATERIALS AND METHODS: We assessed well-studied methylation-based biological aging (mAge) markers (Horvath, GrimAge, PhenoAge, and telomere-length) in the lungs of healthy smokers (SM), electronic cigarette (EC) users, and never-smokers (NS) (n = 26, 21-30 years). We used metatranscriptome profiling to detect live bacteria. Using XGBoost, we performed feature selection on 1016 bacterial species to predict faster or slower lung mAge, and the selected bacterial species were used as explanatory variables in a logistic regression model. Linear regression analyses examined the associations between identified bacterial species and urinary metabolites of exposure to smoking and EC use, including volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs). RESULTS: The logistic regression models identified bacterial species that classified individuals with faster or slower lung aging based on each mAge estimate (accuracy 77%-85%; AUC 0.78-0.91). Two species strongly predictive of GrimAge, Alistipes finegoldii and Arachidicoccus sp.BS20 were significantly less present in SM compared to NS. Arachidicoccus sp.BS20 was significantly associated with nicotine-intake-adjusted metabolites of several VOCs and PAHs in SM and EC users. CONCLUSION: For the first time, our study suggests potential associations of the microbiome with biological aging in the lungs of healthy individuals. In addition, the findings indicate that exposure to smoking and EC may be linked to shifts in particular microbial profiles associated with biological aging of the lungs. These results support the need for larger studies to better understand the direction and possible mechanisms of these relationships, and to further explore the lung microbiome as a potential target for interventions aimed at mitigating pulmonary aging and disease risk.

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Publication Details

Journal
Clinical Epigenetics
Published
2026-04-11
DOI
https://doi.org/10.1186/s13148-026-02126-9
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.00

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article

Lung microbiome predictors of epigenetic aging and potential associations with smoking and electronic cigarette use

Daniel Weng, Min‐Ae Song, M D Wewers, P. Shields et al.
Clinical Epigenetics
Gut microbiota and health
article

Lung microbiome predictors of epigenetic aging and potential associations with smoking and electronic cigarette use

Daniel Weng, Min‐Ae Song, M D Wewers, P. Shields, Boseung Choi, Sahar Kamel, Sarah A. Reisinger, Kevin L. Ying, A.R. Khan, Joseph P. McElroy, Seungbae Kang
article en

Abstract

BACKGROUND: The lungs harbor diverse microbial communities that may influence pulmonary health, potentially through lung aging. While accelerated lung aging can increase susceptibility to pulmonary diseases, no studies have yet linked the lung microbiome to biological aging in disease-free individuals. MATERIALS AND METHODS: We assessed well-studied methylation-based biological aging (mAge) markers (Horvath, GrimAge, PhenoAge, and telomere-length) in the lungs of healthy smokers (SM), electronic cigarette (EC) users, and never-smokers (NS) (n = 26, 21-30 years). We used metatranscriptome profiling to detect live bacteria. Using XGBoost, we performed feature selection on 1016 bacterial species to predict faster or slower lung mAge, and the selected bacterial species were used as explanatory variables in a logistic regression model. Linear regression analyses examined the associations between identified bacterial species and urinary metabolites of exposure to smoking and EC use, including volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs). RESULTS: The logistic regression models identified bacterial species that classified individuals with faster or slower lung aging based on each mAge estimate (accuracy 77%-85%; AUC 0.78-0.91). Two species strongly predictive of GrimAge, Alistipes finegoldii and Arachidicoccus sp.BS20 were significantly less present in SM compared to NS. Arachidicoccus sp.BS20 was significantly associated with nicotine-intake-adjusted metabolites of several VOCs and PAHs in SM and EC users. CONCLUSION: For the first time, our study suggests potential associations of the microbiome with biological aging in the lungs of healthy individuals. In addition, the findings indicate that exposure to smoking and EC may be linked to shifts in particular microbial profiles associated with biological aging of the lungs. These results support the need for larger studies to better understand the direction and possible mechanisms of these relationships, and to further explore the lung microbiome as a potential target for interventions aimed at mitigating pulmonary aging and disease risk.

Clinical Epigenetics
Korea University (KR), The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute (US), Ohio Department of Health (US), The Ohio State University Wexner Medical Center (US), Institute for Basic Science (KR), The Ohio State University (US)
Prevent Cancer Foundation, Ministry of Education, National Center for Advancing Translational Sciences
Good health and well-being
Openalex Percentile: Top 24%
Gut microbiota and health
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