Wu Yu-Ru, Lin Wan-Yu
Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Room 501, No. 17, Xu-Zhou Road, Taipei, 100, Taiwan.
Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Taipei, Taiwan.
Biogerontology. 2025 Feb 5;26(2):51. doi: 10.1007/s10522-025-10195-1.
Epigenetic clocks use DNA methylation (DNAm) levels to predict an individual's biological age. However, relationships between lifestyle/biomarkers and epigenetic age acceleration (EAA) in Asian populations remain unknown. We here explored associations between lifestyle factors, physiological conditions, and epigenetic markers, including HannumEAA, IEAA, PhenoEAA, GrimEAA, DunedinPACE, DNAm-based smoking pack-years (DNAmPACKYRS), and DNAm plasminogen activator inhibitor 1 level (DNAmPAI1). A total of 2474 Taiwan Biobank (TWB) individuals aged between 30 and 70 provided physical health examinations, lifestyle questionnaire surveys, and blood and urine samples. Partial correlation analysis (while adjusting for chronological age, smoking, and drinking status) demonstrated that 29 factors were significantly correlated with at least one epigenetic marker (Pearson's correlation coefficient |r|> 0.15). Subsequently, by exploring the model with the smallest Akaike information criterion (AIC), we identified the best model for each epigenetic marker. As a DNAm-based marker demonstrated to predict healthspan and lifespan with greater accuracy, GrimEAA was also found to be better explained by lifestyle factors and physiological conditions. Totally 15 factors explained 44.7% variability in GrimEAA, including sex, body mass index (BMI), waist-hip ratio (WHR), smoking, hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C), creatinine, uric acid, gamma-glutamyl transferase (GGT), hemoglobin, and five cell-type proportions. In summary, smoking, elevated HbA1c, BMI, WHR, GGT, and uric acid were associated with more than one kind of EAA. At the same time, higher HDL-C and hemoglobin were related to epigenetic age deceleration (EAD). These findings offer valuable insights into biological aging.
表观遗传时钟利用DNA甲基化（DNAm）水平来预测个体的生物学年龄。然而，亚洲人群中生活方式/生物标志物与表观遗传年龄加速（EAA）之间的关系仍不清楚。我们在此探讨了生活方式因素、生理状况与表观遗传标志物之间的关联，这些表观遗传标志物包括汉纳姆EAA、IEAA、PhenoEAA、格里姆EAA、达尼丁PACE、基于DNAm的吸烟包年数（DNAmPACKYRS）以及DNAm纤溶酶原激活物抑制剂1水平（DNAmPAI1）。共有2474名年龄在30至70岁之间的台湾生物银行（TWB）个体接受了身体健康检查、生活方式问卷调查，并提供了血液和尿液样本。偏相关分析（在调整了实际年龄、吸烟和饮酒状况后）表明，29个因素与至少一种表观遗传标志物显著相关（皮尔逊相关系数|r|> 0.15）。随后，通过探索具有最小赤池信息准则（AIC）的模型，我们确定了每个表观遗传标志物的最佳模型。作为一种经证明能更准确预测健康寿命和寿命的基于DNAm的标志物，格里姆EAA也被发现能更好地由生活方式因素和生理状况来解释。总共15个因素解释了格里姆EAA中44.7%的变异性，包括性别、体重指数（BMI）、腰臀比（WHR）、吸烟、糖化血红蛋白（HbA1c）、高密度脂蛋白胆固醇（HDL-C）、肌酐、尿酸、γ-谷氨酰转移酶（GGT）、血红蛋白以及五种细胞类型比例。总之，吸烟、升高的HbA1c、BMI、WHR、GGT和尿酸与不止一种EAA相关。同时，较高的HDL-C和血红蛋白与表观遗传年龄减速（EAD）有关。这些发现为生物衰老提供了有价值的见解。
