The abundance of the biological data and the rapid evolution of the newer machine learning technologies have increased the epigenetics research in the last decade. This has enhanced the ability to measure the biological age of humans and different organisms via their omics data. DNA methylation array data are commonly used in the prediction of methylation age. Horvath clock has been adopted in various aging studies as a DNA methylation age predicting clock due to its higher accuracy and multi tissue prediction potential. In the current study, we have developed a pan tissue methylation-aging clock by using the publicly available illumina 450k and EPIC array methylation datasets. In doing that, we developed a highly accurate epigenetic clock, which predicts the age of multiple tissues with higher accuracy. We have also analyzed the selected probes for their biological relevance. Upon analyzing the selected features further, we found out evidences, which support the Antagonistic pleiotropy theory of aging.

生物数据的丰富性和新机器学习技术的快速发展在过去十年中增加了表观遗传学研究。这增强了通过组学数据测量人类和不同生物体生物学年龄的能力。DNA甲基化阵列数据常用于甲基化年龄的预测。由于其更高的准确性和多组织预测潜力，Horvath 时钟已在各种衰老研究中用作 DNA 甲基化年龄预测时钟。在目前的研究中，我们使用公开可用的 illumina 450k 和 EPIC 阵列甲基化数据集开发了泛组织甲基化老化时钟。为此，我们开发了一种高度准确的表观遗传时钟，可以更准确地预测多个组织的年龄。我们还分析了所选探针的生物学相关性。在进一步分析所选特征后，我们发现了支持衰老拮抗多效性理论的证据。