Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
Department of Statistics, Northwestern University, Evanston, IL, USA.
Clin Epigenetics. 2022 Jul 7;14(1):85. doi: 10.1186/s13148-022-01304-9.
DNA methylation-based GrimAge acceleration (GrimAA) is associated with a wide range of age-related health outcomes including cardiovascular disease. Since DNA methylation is modifiable by external and behavioral exposures, it is important to identify which of these exposures may have the strongest contributions to differences in GrimAA, to help guide potential intervention strategies. Here, we assessed the relative contributions of lifestyle- and health-related components, as well as their collective association, to GrimAA.
We included 744 participants (391 men and 353 women) from the Coronary Artery Risk Development in Young Adults (CARDIA) study with blood DNA methylation information at CARDIA Exam Year (Y) 20 (2005-2006, mean age 45.9 years). Six cumulative exposures by Y20 were included in the analysis: total packs of cigarettes, total alcohol consumption, education years, healthy diet score, sleep hours, and physical activity. We used quantile-based g-computation (QGC) and Bayesian kernel machine regression (BKMR) methods to assess the relative contribution of each exposure to a single overall association with GrimAA. We also assessed the collective association of the six components combined with GrimAA. Smoking showed the greatest positive contribution to GrimAA, accounting for 83.5% of overall positive associations of the six exposures with GrimAA (QGC weight = 0.835). The posterior inclusion probability (PIP) of smoking also achieved the highest score of 1.0 from BKMR analysis. Healthy diet and education years showed inverse contributions to GrimAA. We observed a U-shaped pattern in the contribution of alcohol consumption to GrimAA. While smoking was the greatest contributor across sex and race subgroups, the relative contributions of other components varied by subgroups.
Smoking, alcohol consumption, and education showed the highest contributions to GrimAA in our study. Higher amounts of smoking and alcohol consumption were likely to contribute to greater GrimAA, whereas achieved education was likely to contribute to lower GrimAA. Identifying pertinent lifestyle- and health-related exposures in a context of collective components can provide direction for intervention strategies and suggests which components should be the primary focus for promoting younger GrimAA.
基于 DNA 甲基化的 GrimAge 加速(GrimAA)与广泛的与年龄相关的健康结果相关,包括心血管疾病。由于 DNA 甲基化可通过外部和行为暴露进行修饰,因此重要的是要确定这些暴露中哪些对 GrimAA 的差异有最强的贡献,以帮助指导潜在的干预策略。在这里,我们评估了生活方式和健康相关因素的相对贡献,以及它们的集体关联,以了解 GrimAA。
我们纳入了来自冠状动脉风险发展在年轻人(CARDIA)研究的 744 名参与者(391 名男性和 353 名女性),他们在 CARDIA 检查年度(Y)20 时具有血液 DNA 甲基化信息(2005-2006 年,平均年龄 45.9 岁)。分析中包括 20 岁时的六种累积暴露:总香烟包数、总饮酒量、受教育年限、健康饮食评分、睡眠时间和体力活动。我们使用基于分位数的 g 计算(QGC)和贝叶斯核机器回归(BKMR)方法来评估每种暴露对与 GrimAA 单一总体关联的相对贡献。我们还评估了六个组成部分与 GrimAA 相结合的集体关联。吸烟对 GrimAA 的贡献最大,占六种暴露与 GrimAA 总体正相关的 83.5%(QGC 权重=0.835)。BKMR 分析中,吸烟的后验纳入概率(PIP)也达到了 1.0 的最高分。健康饮食和受教育年限对 GrimAA 呈负向贡献。我们观察到饮酒对 GrimAA 的贡献呈 U 型模式。虽然吸烟在性别和种族亚组中是最大的贡献者,但其他组成部分的相对贡献因亚组而异。
在我们的研究中,吸烟、饮酒和教育对 GrimAA 的贡献最大。吸烟和饮酒量越高,可能导致更大的 GrimAA,而获得的教育可能导致更低的 GrimAA。在集体成分的背景下确定相关的生活方式和健康相关暴露,可以为干预策略提供方向,并表明哪些成分应该是促进更年轻的 GrimAA 的主要焦点。