Framingham Heart Study, Massachusetts.
Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Massachusetts.
J Gerontol A Biol Sci Med Sci. 2018 May 9;73(6):757-762. doi: 10.1093/gerona/glx144.
We tested the association of biologic age (BA) measures constructed from different types of biomarkers with mortality and disease in a community-based sample.
In Framingham Offspring participants at Exams 7 (1998-2001, mean age 62 ± 10) and 8 (2005-2008, mean age 67 ± 9), we used the Klemera-Doubal method to estimate clinical BA and inflammatory BA and computed the difference (∆age) between BA and CA. Clinical ∆age was computed at Exam 2 (1979-1983, mean age 45 ± 10). At Exam 8, we computed measures of intrinsic and extrinsic epigenetic age. Participants were followed through 2014 for outcomes. Cox proportional hazards models tested the association of each BA estimate with each outcome adjusting for covariates.
Sample sizes ranged from 2532 to 3417 participants. In multivariable models, each 1-year increase in clinical ∆age at Exam 2 (hazard ratio [HR] = 1.04-1.06, p < 2 × 10-16) and clinical ∆age and inflammatory ∆age at Exam 7 significantly increased the hazards of mortality and incident cardiovascular disease (HR = 1.01-1.05, p < 2 × 10-7), whereas inflammatory ∆age increased the hazards of cancer (HR = 1.01, p < .05). At Exam 8, increased clinical ∆age, inflammatory ∆age, and extrinsic epigenetic age all significantly increased the hazard of mortality (HR = 1.03-1.05, all p < .05); clinical ∆age and inflammatory ∆age increased cardiovascular disease risk (HR = 1.04-1.05, all p < .01); and clinical ∆age increased cancer risk (HR = 1.03, p < .01) when all three BA measures were included in the model. Intrinsic epigenetic age was not significantly associated with any outcome.
Our findings suggest BA measures may be complementary in predicting risk for mortality and age-related disease.
我们在一个基于社区的样本中测试了由不同类型生物标志物构建的生物年龄（BA）测量值与死亡率和疾病的相关性。
在弗雷明汉后代参与者的第七次检查（1998-2001 年，平均年龄 62±10 岁）和第八次检查（2005-2008 年，平均年龄 67±9 岁）中，我们使用 Klemera-Doubal 方法估计临床 BA 和炎症 BA，并计算 BA 与 CA 之间的差异（∆age）。临床 ∆age 是在第二次检查（1979-1983 年，平均年龄 45±10 岁）时计算的。在第八次检查中，我们计算了内在和外在表观遗传年龄的指标。通过 2014 年的结果对参与者进行随访。Cox 比例风险模型调整协变量后，测试了每个 BA 估计值与每个结果的相关性。
样本量范围为 2532 至 3417 名参与者。在多变量模型中，第二次检查时临床 ∆age 每年增加 1 年（危险比 [HR] = 1.04-1.06，p < 2×10-16）和临床 ∆age 和炎症 ∆age 在第七次检查时显著增加了死亡率和心血管疾病事件的风险（HR = 1.01-1.05，p < 2×10-7），而炎症 ∆age 增加了癌症的风险（HR = 1.01，p <.05）。在第八次检查中，临床 ∆age、炎症 ∆age 和外在表观遗传年龄的增加均显著增加了死亡率的风险（HR = 1.03-1.05，所有 p <.05）；临床 ∆age 和炎症 ∆age 增加了心血管疾病的风险（HR = 1.04-1.05，所有 p <.01）；当模型中包含所有三种 BA 测量值时，临床 ∆age 增加了癌症的风险（HR = 1.03，p <.01）。内在表观遗传年龄与任何结果均无显著相关性。
我们的研究结果表明，BA 测量值可能在预测死亡率和与年龄相关疾病的风险方面具有互补性。
