Background: Epigenetic mechanisms may contribute to the biological processes linking lifestyle factors with aging and noncommunicable diseases (NCDs). DNA methylation and DNA methylation-based aging markers have attracted particular attention as possible (bio)markers of environmentally responsive biological processes and aging-related health risks.Objective: This review aimed to summarize current evidence on epigenetic mechanisms linking lifestyle factors with noncommunicable diseases and biological aging, with emphasis on DNA methylation, epigenetic clocks, and their possible implications for personalized prevention.Methods: Literature searches were conducted via Medline/PubMed, Scopus, and Web of Science to retrieve English publications on lifestyle-related epigenetic mechanisms, biological aging, and NCDs. Original human research studies, systematic reviews, narrative reviews, and relevant consensus or expert opinion publications were analyzed. The evidence was synthesized narratively across major thematic domains, including smoking, nutrition, physical activity, obesity, epigenetic aging, and NCDs.Results: Tobacco smoking showed the most consistent and reproducible associations with DNA methylation, including well-characterized smoking-related loci such as AHRR and F2RL3. Nutrition, physical activity, and obesity were also associated with variation in DNA methylation and DNA methylation-based aging mechanisms, although findings were heterogeneous across retrieved studies. Epigenetic aging measures, including the Horvath clock, PhenoAge, GrimAge, and DunedinPACE, capture different aspects of aging and point to varying associations with health-related outcomes. Heterogeneity in study populations, tissues, exposure assessment, laboratory methods, and epigenetic measures in analysed studies have limited comparisons and causal interpretation.Conclusion: Current evidence supports epigenetic regulation as a biologically plausible interface linking lifestyle factors with aging-related processes and NCD risk. Most evidence-based data are based on observational research studies, and causal relationships are not fully established. Epigenetic (bio)markers may be relevant for individualized prevention. Further longitudinal and interventional research studies, validation among varied populations, methodological standardization, and evaluation of clinical utility are required before their implementation.
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Seiil et al. (2026) studied this question.
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