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

IF 4.4 2区 医学 Q1 GENETICS & HEREDITY
Ajmal Khan, Boseung Choi, Seungbae Kang, Daniel Y Weng, Kevin Ying, Joseph P McElroy, Sahar Kamel, Sarah A Reisinger, Mark D Wewers, Peter G Shields, Min-Ae Song
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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.

肺微生物组预测表观遗传衰老及其与吸烟和电子烟使用的潜在关联。
背景:肺部有多种微生物群落,可能通过肺老化影响肺部健康。虽然肺部加速老化会增加对肺部疾病的易感性,但尚未有研究将无疾病个体的肺部微生物组与生物衰老联系起来。材料和方法:我们评估了健康吸烟者(SM)、电子烟使用者(EC)和从不吸烟者(NS) (n = 26、21-30岁)肺部基于甲基化的生物衰老(mAge)标志物(Horvath、GrimAge、PhenoAge和端粒长度)。我们使用超转录组分析来检测活细菌。使用XGBoost,我们对1016种细菌进行特征选择,以预测更快或更慢的肺成像,并将选择的细菌种类用作逻辑回归模型的解释变量。线性回归分析检验了所鉴定的细菌种类与暴露于吸烟和使用EC的尿液代谢物之间的关系,包括挥发性有机化合物(VOCs)和多环芳烃(PAHs)。结果:逻辑回归模型确定了细菌种类,根据每个mAge估计(准确率77%-85%;AUC 0.78-0.91)对肺衰老更快或更慢的个体进行分类。对GrimAge有较强预测作用的Alistipes finegoldii和Arachidicoccus sp.BS20在SM中的含量显著低于NS。花生胶球菌sp.BS20与SM和EC使用者中几种挥发性有机化合物和多环芳烃的尼古丁摄入调节代谢物显著相关。结论:我们的研究首次提示了健康个体肺部微生物组与生物衰老的潜在关联。此外,研究结果表明,暴露于吸烟和EC可能与与肺部生物老化相关的特定微生物谱的变化有关。这些结果支持需要进行更大规模的研究,以更好地了解这些关系的方向和可能的机制,并进一步探索肺微生物组作为旨在减轻肺衰老和疾病风险的干预措施的潜在目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
5.30%
发文量
150
期刊介绍: Clinical Epigenetics, the official journal of the Clinical Epigenetics Society, is an open access, peer-reviewed journal that encompasses all aspects of epigenetic principles and mechanisms in relation to human disease, diagnosis and therapy. Clinical trials and research in disease model organisms are particularly welcome.
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