Simpkin Andrew J, Howe Laura D, Tilling Kate, Gaunt Tom R, Lyttleton Oliver, McArdle Wendy L, Ring Susan M, Horvath Steve, Smith George Davey, Relton Caroline L
MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK.
School of Social and Community Medicine, University of Bristol, Bristol, UK.
Int J Epidemiol. 2017 Apr 1;46(2):549-558. doi: 10.1093/ije/dyw307.
Statistical models that use an individual's DNA methylation levels to estimate their age (known as epigenetic clocks) have recently been developed, with 96% correlation found between epigenetic and chronological age. We postulate that differences between estimated and actual age [age acceleration (AA)] can be used as a measure of developmental age in early life.
We obtained DNA methylation measures at three time points (birth, age 7 years and age 17 years) in 1018 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). Using an online calculator, we estimated epigenetic age, and thus AA, for each child at each time point. We then investigated whether AA was prospectively associated with repeated measures of height, weight, body mass index (BMI), bone mineral density, bone mass, fat mass, lean mass and Tanner stage.
Positive AA at birth was associated with higher average fat mass [1321 g per year of AA, 95% confidence interval (CI) 386, 2256 g] from birth to adolescence (i.e. from age 0-17 years) and AA at age 7 was associated with higher average height (0.23 cm per year of AA, 95% CI 0.04, 0.41 cm). Conflicting evidence for the role of AA (at birth and in childhood) on changes during development was also found, with higher AA being positively associated with changes in weight, BMI and Tanner stage, but negatively with changes in height and fat mass.
We found evidence that being ahead of one's epigenetic age acceleration is related to developmental characteristics during childhood and adolescence. This demonstrates the potential for using AA as a measure of development in future research.
最近已开发出利用个体DNA甲基化水平来估计其年龄的统计模型(称为表观遗传时钟),发现表观遗传年龄与实际年龄之间的相关性为96%。我们推测,估计年龄与实际年龄之间的差异[年龄加速(AA)]可作为生命早期发育年龄的一种衡量指标。
我们从埃文亲子纵向研究(ALSPAC)中获取了1018名儿童在三个时间点(出生、7岁和17岁)的DNA甲基化测量值。使用在线计算器,我们估计了每个儿童在每个时间点的表观遗传年龄,从而得出年龄加速值。然后,我们调查了年龄加速值是否与身高、体重、体重指数(BMI)、骨密度、骨量、脂肪量、瘦体重和坦纳分期的重复测量值存在前瞻性关联。
出生时的正向年龄加速与从出生到青春期(即0至17岁)较高的平均脂肪量相关[年龄加速每增加1年,脂肪量增加1321克,95%置信区间(CI)为386至2256克],7岁时的年龄加速与较高的平均身高相关(年龄加速每增加1年,身高增加0.23厘米,95%CI为0.04至0.41厘米)。我们还发现了关于年龄加速(出生时和儿童期)在发育过程中作用的相互矛盾的证据,较高的年龄加速与体重、BMI和坦纳分期的变化呈正相关,但与身高和脂肪量的变化呈负相关。
我们发现有证据表明,表观遗传年龄加速超前与儿童期和青春期的发育特征有关。这表明在未来研究中使用年龄加速作为发育衡量指标具有潜力。