Chen Brian H, Marioni Riccardo E, Colicino Elena, Peters Marjolein J, Ward-Caviness Cavin K, Tsai Pei-Chien, Roetker Nicholas S, Just Allan C, Demerath Ellen W, Guan Weihua, Bressler Jan, Fornage Myriam, Studenski Stephanie, Vandiver Amy R, Moore Ann Zenobia, Tanaka Toshiko, Kiel Douglas P, Liang Liming, Vokonas Pantel, Schwartz Joel, Lunetta Kathryn L, Murabito Joanne M, Bandinelli Stefania, Hernandez Dena G, Melzer David, Nalls Michael, Pilling Luke C, Price Timothy R, Singleton Andrew B, Gieger Christian, Holle Rolf, Kretschmer Anja, Kronenberg Florian, Kunze Sonja, Linseisen Jakob, Meisinger Christine, Rathmann Wolfgang, Waldenberger Melanie, Visscher Peter M, Shah Sonia, Wray Naomi R, McRae Allan F, Franco Oscar H, Hofman Albert, Uitterlinden André G, Absher Devin, Assimes Themistocles, Levine Morgan E, Lu Ake T, Tsao Philip S, Hou Lifang, Manson JoAnn E, Carty Cara L, LaCroix Andrea Z, Reiner Alexander P, Spector Tim D, Feinberg Andrew P, Levy Daniel, Baccarelli Andrea, van Meurs Joyce, Bell Jordana T, Peters Annette, Deary Ian J, Pankow James S, Ferrucci Luigi, Horvath Steve
Longitudinal Studies Section, Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
The NHLBI's Framingham Heart Study, Framingham, MA 01702, USA.
Aging (Albany NY). 2016 Sep 28;8(9):1844-1865. doi: 10.18632/aging.101020.
Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10, independent of chronological age, even after adjusting for additional risk factors (p<5.4x10, and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.
基于DNA甲基化模式的生物学年龄估计，通常被称为“表观遗传年龄”“DNAm年龄”，已被证明是人类年龄的可靠生物标志物。我们之前证明，不考虑实际年龄，血液中评估的表观遗传年龄可预测四个人类队列中的全因死亡率。在此，我们将最初的观察扩展到13个不同队列，样本总量达13089人，包括三个种族/族裔群体。此外，我们研究了将血细胞组成信息纳入表观遗传年龄指标是否能提高其对死亡率的预测能力。所有考虑的表观遗传年龄加速指标均能预测死亡率（p≤8.2×10，不考虑实际年龄，即使在调整其他风险因素后（p<5.4×10）以及在我们研究的种族/族裔群体（非西班牙裔白人、西班牙裔、非裔美国人）中也是如此。纳入血细胞组成信息的表观遗传年龄估计得出的死亡时间p值最小（p=7.5×10）。总体而言，本研究a）强化了表观遗传年龄能预测超出实际年龄和传统风险因素的全因死亡率的证据，b）表明纳入血细胞计数信息的表观遗传年龄估计与全因死亡率存在高度显著关联。
