Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites
Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites
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DOI：
10.1093/hmg/ddt531
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发表时间：
2014-03-01
影响因子：
3.5
通讯作者：
Brenner, Hermann
中科院分区：
文献类型：
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作者：
Florath, Ines;Butterbach, Katja;Brenner, Hermann
了解表观遗传修饰的作用，e。G.衰老过程中的DNA甲基化需要在大型队列中表征甲基化模式。我们使用Infinium HumanMethylation 450 BeadChip（Illumina）分析了965名年龄在50至75岁之间的基于人群的队列研究参与者全血DNA中的> 480 000个CpG位点。在对400名个体的探索性分析中，鉴定了甲基化与年龄之间关联的具有最高斯皮尔曼相关系数的200个CpG位点。在这200个CpG中，162个与年龄显著相关，这在498个个体的独立队列中使用混合线性回归模型进行了验证，该模型针对性别，吸烟行为，年龄相关疾病和随机批次效应进行了调整，并通过Bonferroni进行了多次测试。在另一个由67名没有重大年龄相关疾病史的个体组成的独立队列中，随访8年，我们观察到96%（52%，显着）的年龄正相关CpG的甲基化增加，而每个个体在年龄增长8岁时，年龄负相关CpG的甲基化完全丧失（89%，显着）。基于17个CpG作为预测变量的年龄预测回归模型解释了71%的年龄方差，平均准确度为2.6岁。与从乌尔姆出生队列研究中获得的脐带血样本相比，我们观察到从出生到老年，86个CpG的平均甲基化水平变化超过2倍。我们能够鉴定出65个甲基化与年龄显著相关的新CpG位点。
Understanding the role of epigenetic modifications, e. g. DNA methylation, in the process of aging requires the characterization of methylation patterns in large cohorts. We analysed > 480 000 CpG sites using Infinium HumanMethylation450 BeadChip (Illumina) in whole blood DNA of 965 participants of a population-based cohort study aged between 50 and 75 years. In an exploratory analysis in 400 individuals, 200 CpG sites with the highest Spearman correlation coefficients for the association between methylation and age were identified. Of these 200 CpGs, 162 were significantly associated with age, which was verified in an independent cohort of 498 individuals using mixed linear regression models adjusted for gender, smoking behaviour, age-related diseases and random batch effect and corrected for multiple testing by Bonferroni. In another independent cohort of 67 individuals without history of major age-related diseases and with a follow-up of 8 years, we observed a gain in methylation at 96% (52%, significant) of the positively age-associated CpGs and a loss at all (89%, significant) of the negatively age-associated CpGs in each individual while getting 8 years older. A regression model for age prediction based on 17 CpGs as predicting variables explained 71% of the variance in age with an average accuracy of 2.6 years. In comparison with cord blood samples obtained from the Ulm Birth Cohort Study, we observed a more than 2-fold change in mean methylation levels from birth to older age at 86 CpGs. We were able to identify 65 novel CpG sites with significant association of methylation with age.