Bormann Felix, Rodríguez-Paredes Manuel, Hagemann Sabine, Manchanda Himanshu, Kristof Boris, Gutekunst Julian, Raddatz Günter, Haas Rainer, Terstegen Lara, Wenck Horst, Kaderali Lars, Winnefeld Marc, Lyko Frank
Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany.
University Tumor Center Düsseldorf, University of Düsseldorf, Düsseldorf, Germany.
Aging Cell. 2016 Jun;15(3):563-71. doi: 10.1111/acel.12470. Epub 2016 Mar 23.
Epigenetic changes represent an attractive mechanism for understanding the phenotypic changes associated with human aging. Age-related changes in DNA methylation at the genome scale have been termed 'epigenetic drift', but the defining features of this phenomenon remain to be established. Human epidermis represents an excellent model for understanding age-related epigenetic changes because of its substantial cell-type homogeneity and its well-known age-related phenotype. We have now generated and analyzed the currently largest set of human epidermis methylomes (N = 108) using array-based profiling of 450 000 methylation marks in various age groups. Data analysis confirmed that age-related methylation differences are locally restricted and characterized by relatively small effect sizes. Nevertheless, methylation data could be used to predict the chronological age of sample donors with high accuracy. We also identified discontinuous methylation changes as a novel feature of the aging methylome. Finally, our analysis uncovered an age-related erosion of DNA methylation patterns that is characterized by a reduced dynamic range and increased heterogeneity of global methylation patterns. These changes in methylation variability were accompanied by a reduced connectivity of transcriptional networks. Our findings thus define the loss of epigenetic regulatory fidelity as a key feature of the aging epigenome.
表观遗传变化是理解与人类衰老相关的表型变化的一种有吸引力的机制。基因组规模上与年龄相关的DNA甲基化变化被称为“表观遗传漂变”,但这一现象的定义特征仍有待确定。人类表皮因其细胞类型的高度同质性和众所周知的与年龄相关的表型,是理解与年龄相关的表观遗传变化的绝佳模型。我们现在使用基于阵列的方法对不同年龄组的45万个甲基化标记进行分析,生成并分析了目前最大规模的人类表皮甲基化组数据集(N = 108)。数据分析证实,与年龄相关的甲基化差异在局部受到限制,且效应大小相对较小。尽管如此,甲基化数据可用于高精度预测样本供体的实际年龄。我们还将不连续的甲基化变化确定为衰老甲基化组的一个新特征。最后,我们的分析揭示了与年龄相关的DNA甲基化模式侵蚀,其特征是整体甲基化模式的动态范围减小和异质性增加。甲基化变异性的这些变化伴随着转录网络连通性的降低。因此,我们的研究结果将表观遗传调控保真度的丧失定义为衰老表观基因组的一个关键特征。