Yi So-Yun, Steffen Lyn M, Jacobs David R, Joyce Brian, Guan Weihua, Duprez Daniel, Lakshminarayan Kamakshi, Zheng Yinan, Hou Lifang
University of Minnesota School of Public Health Division of Epidemiology and Community Health, Minneapolis, MN, United States.
University of Minnesota School of Public Health Division of Epidemiology and Community Health, Minneapolis, MN, United States.
J Nutr. 2025 Apr;155(4):1210-1217. doi: 10.1016/j.tjnut.2025.01.022. Epub 2025 Jan 27.
Dietary intake is one lifestyle factor that is expected to impact gene expression by altering DNA methylation (DNAm), thus affecting epigenetic aging. Studies on the association between quality of carbohydrates and epigenetic age acceleration (EAA) are scarce despite the evidence that quality may be more important than amount of carbohydrates consumed.
We aimed to identify the cross-sectional associations of carbohydrate quality and fiber-rich food score with EAA in the Coronary Artery Risk Development in Young Adults (CARDIA) study.
Trained interviewers administered the CARDIA Diet History to obtain dietary intake at examination year 20. EAA measures, PhenoAge acceleration (PhenoAA) and GrimAge acceleration (GrimAA), were generated based on epigenetic age estimates calculated using DNAm profiling data from fasting blood samples at examination years 20, 25, and 30. Linear mixed-effects regression models were used to evaluate the association of carbohydrate quality, defined using carbohydrate:fiber ratio, and fiber-rich food score with EAA measures.
After adjusting for demographic and lifestyle factors, quartiles of carbohydrate quality (defined using carbohydrate:fiber ratio) were inversely associated with PhenoAA and GrimAA; the highest carbohydrate quality quartile showing a difference (standard error [SE]) of -1.19 (0.2) y for PhenoAA (P-trend < 0.001) and -1.20 (0.1) y for GrimAA (P-trend < 0.001) compared with the lowest carbohydrate quality quartile. Similarly, quartiles of fiber-rich food score (created based on daily intakes of whole grains, fruit, vegetables, nuts, and legumes) were inversely associated with PhenoAA and GrimAA; the highest quartile showing a difference (SE) of -1.06 (0.2) y for PhenoAA (P-trend = 0.002) and -1.31 (0.2) y for GrimAA (P-trend < 0.001) compared with the lowest quartile.
Our findings suggest that consuming a high carbohydrate quality diet and a dietary pattern composed of fiber-rich foods is cross-sectionally associated with slower biological aging.
饮食摄入是一种生活方式因素，预计会通过改变DNA甲基化（DNAm）来影响基因表达，从而影响表观遗传衰老。尽管有证据表明碳水化合物的质量可能比其摄入量更为重要，但关于碳水化合物质量与表观遗传年龄加速（EAA）之间关联的研究却很稀少。
在年轻人冠状动脉风险发展（CARDIA）研究中，我们旨在确定碳水化合物质量和富含纤维食物得分与EAA之间的横断面关联。
经过培训的访谈员采用CARDIA饮食史来获取第20年检查时的饮食摄入量。EAA指标，即表型年龄加速（PhenoAA）和 GrimAge加速（GrimAA），是根据使用第20、25和30年检查时空腹血样的DNAm谱数据计算出的表观遗传年龄估计值生成的。线性混合效应回归模型用于评估用碳水化合物：纤维比率定义的碳水化合物质量以及富含纤维食物得分与EAA指标之间的关联。
在对人口统计学和生活方式因素进行调整后，碳水化合物质量四分位数（用碳水化合物：纤维比率定义）与PhenoAA和GrimAA呈负相关；与碳水化合物质量最低的四分位数相比，碳水化合物质量最高的四分位数在PhenoAA方面显示出差异（标准误[SE]）为-1.19（0.2）岁（P趋势<0.001），在GrimAA方面为-1.20（0.1）岁（P趋势<0.001）。同样，富含纤维食物得分四分位数（根据全谷物、水果、蔬菜、坚果和豆类的每日摄入量得出）与PhenoAA和GrimAA呈负相关；与最低四分位数相比，最高四分位数在PhenoAA方面显示出差异（SE）为-1.06（0.2）岁（P趋势 = 0.002），在GrimAA方面为-1.31（0.2）岁（P趋势<0.001）。
我们的研究结果表明，摄入高碳水化合物质量的饮食以及由富含纤维食物组成的饮食模式与生物衰老减缓存在横断面关联。
