Cui Xian, Sun Shiqun, Zhang Hui, Gong Yulu, Hao Darong, Xu Yaqian, Ding Chongyu, Wang Jing, An Tongyan, Liu Jinlong, Du Jun, Li Xiangwei
Diagnostic Imaging Center, Shanghai Children's Medical Center School of Medicine, Shanghai Jiao Tong University Shanghai 200127 China.
Department of Cardiovascular Medicine, Ruijin Hospital School of Medicine, Shanghai Jiao Tong University Shanghai China.
J Am Heart Assoc. 2025 May 6;14(9):e040374. doi: 10.1161/JAHA.124.040374. Epub 2025 May 2.
Several DNA methylation (DNAm) algorithms have recently emerged as robust predictors of aging and adverse health outcomes in older adults, offering valuable insights into cardiovascular disease (CVD) risk stratification. However, their predictive performance for CVD varies significantly. This study aimed to systematically investigate the associations of 12 widely used DNAm algorithms with CVD and mortality risk.
Data from the NHANES (National Health and Nutrition Examination Survey) 1999 to 2002 were used to assess 12 DNAm algorithms (eg, HannumAgeacc, PhenoAgeacc, GrimAgeMortacc, GrimAge2Mortacc) in relation to CVD risk and mortality. Two cohorts were analyzed: one for CVD risk (n=1230) and another for CVD mortality risk (n=1606). DNAm was measured using the Infinium Methylation EPIC BeadChip kit (Illumina). Odds ratios (ORs) and hazard ratios (HRs), along with 95% CIs per SD increase of these DNAm algorithms, were calculated.
Significant associations were observed for GrimAgeMortacc and GrimAge2Mortacc with coronary heart disease and heart attack, with multivariable-adjusted ORs per SD increase ranging from 2.15 to 2.76. However, several algorithms exhibited no significant association with self-reported prevalent CVD. For mortality risk, HannumAgeacc, PhenoAgeacc, ZhangAgeacc, GrimAgeMortacc, and GrimAge2Mortacc were significantly associated with CVD mortality. The multivariable-adjusted HRs per SD increase were 1.19 (95% CIs, 1.05-1.34), 1.13 (95% CIs, 1.01-1.26), 1.63 (95% CI, 1.08-2.47), 1.90 (95% CIs, 1.51-2.40), and 1.87 (95% CIs, 1.51-2.32), respectively. These associations were consistent across biological sex, age (≥50 and <65 versus ≥65 years), and race and ethnicity groups.
DNAm algorithms, particularly GrimAgeMortacc and GrimAge2Mortacc, may serve as valuable tools for CVD risk stratification and mortality risk assessment.
最近出现了几种DNA甲基化(DNAm)算法,作为老年人衰老和不良健康结局的有力预测指标,为心血管疾病(CVD)风险分层提供了有价值的见解。然而,它们对CVD的预测性能差异很大。本研究旨在系统地调查12种广泛使用的DNAm算法与CVD和死亡风险之间的关联。
使用1999年至2002年美国国家健康与营养检查调查(NHANES)的数据,评估12种DNAm算法(如HannumAgeacc、PhenoAgeacc、GrimAgeMortacc、GrimAge2Mortacc)与CVD风险和死亡率的关系。分析了两个队列:一个用于CVD风险(n = 1230),另一个用于CVD死亡风险(n = 1606)。使用Infinium甲基化EPIC BeadChip试剂盒(Illumina)测量DNAm。计算了这些DNAm算法每增加一个标准差的优势比(OR)和风险比(HR)以及95%置信区间。
观察到GrimAgeMortacc和GrimAge2Mortacc与冠心病和心脏病发作之间存在显著关联,每增加一个标准差的多变量调整OR范围为2.15至2.76。然而,几种算法与自我报告的CVD患病率无显著关联。对于死亡风险,HannumAgeacc、PhenoAgeacc、ZhangAgeacc、GrimAgeMortacc和GrimAge2Mortacc与CVD死亡率显著相关。每增加一个标准差的多变量调整HR分别为1.19(95%置信区间,1.05 - 1.34)、1.13(95%置信区间,1.01 - 1.26)、1.63(95%置信区间,1.08 - 2.47)、1.90(95%置信区间,1.51 - 2.40)和1.87(95%置信区间,1.51 - 2.32)。这些关联在生物性别、年龄(≥50岁且<65岁与≥65岁)以及种族和族裔群体中是一致的。
DNAm算法,特别是GrimAgeMortacc和GrimAge2Mortacc,可能是CVD风险分层和死亡风险评估的有价值工具。