表观遗传时钟是根据特定 CpG 位点的 DNA 甲基化来估计表观遗传年龄的数学模型。随着新的甲基化微阵列的开发和旧模型的停产，现有的表观遗传时钟可能会过时。在这里，我们探讨了新的 EPICv2 DNA 甲基化阵列中引入的变化对现有表观遗传时钟的影响。我们使用 10,835 个样本的数据集测试了 EPICv2 阵列探针组上四个表观遗传时钟的性能。我们开发了一种新的表观遗传年龄预测模型，兼容 450 k、EPICv1 和 EPICv2 微阵列，并在 2095 个样本上进行了验证。我们使用两个重复采样的数据集来估计技术噪音和受试者内部变异。我们使用来自（i）接受过不同治疗的癌症幸存者，（ii）乳腺癌患者和对照，以及（iii）基于运动的干预研究的数据，来测试我们的模型检测表观遗传年龄加速变化的能力。对理论上的抗衰老干预措施的反应。EPICv2 探针组测试的四个时钟的结果明显失真，导致平均差异长达 25 年。我们的新模型产生了高度准确的实足年龄预测，可与最先进的震钟相媲美。该模型报告了正常人群中最低的表观遗传年龄加速，以及同一受试者的技术重复和重复样本之间的最低变异。最后，我们的模型重现了癌症患者和接受放射治疗的幸存者的表观遗传年龄加速增加的先前结果，并且基于运动的干预措施没有变化。现有的表观遗传时钟需要更新才能完全兼容 EPICv2。我们的新模型将最先进的表观遗传时钟的功能转化为 EPICv2 平台，并与旧的微阵列交叉兼容。表观遗传年龄预测变异的表征提供了有用的指标来了解表观遗传年龄变化的相关性。对受辐射、癌症和基于运动的干预措施影响的受试者的数据进行的分析表明，尽管乳腺癌等病理状态、危险的环境因素（辐射）和运动（有益的干预措施）都不是实际年龄的良好预测因素，导致这些第一代模型确定的“表观遗传年龄”值发生显着变化。© 2024。作者。

Epigenetic clocks are mathematical models used to estimate epigenetic age based on DNA methylation at specific CpG sites. As new methylation microarrays are developed and older models discontinued, existing epigenetic clocks might become obsolete. Here, we explored the effects of the changes introduced in the new EPICv2 DNA methylation array on existing epigenetic clocks.We tested the performance of four epigenetic clocks on the probeset of the EPICv2 array using a dataset of 10,835 samples. We developed a new epigenetic age prediction model compatible across the 450 k, EPICv1, and EPICv2 microarrays and validated it on 2095 samples. We estimated technical noise and intra-subject variation using two datasets with repeated sampling. We used data from (i) cancer survivors who had undergone different therapies, (ii) breast cancer patients and controls, and (iii) an exercise-based interventional study, to test the ability of our model to detect alterations in epigenetic age acceleration in response to theoretically antiaging interventions.The results of the four epiclocks tested are significantly distorted by the EPICv2 probeset, causing an average difference of up to 25 years. Our new model produced highly accurate chronological age predictions, comparable to a state-of-the-art epiclock. The model reported the lowest epigenetic age acceleration in normal populations, as well as the lowest variation across technical replicates and repeated samples from the same subjects. Finally, our model reproduced previous results of increased epigenetic age acceleration in cancer patients and in survivors treated with radiation therapy, and no changes from exercise-based interventions.Existing epigenetic clocks require updates for full EPICv2 compatibility. Our new model translates the capabilities of state-of-the-art epigenetic clocks to the EPICv2 platform and is cross-compatible with older microarrays. The characterization of epigenetic age prediction variation provides useful metrics to contextualize the relevance of epigenetic age alterations. The analysis of data from subjects influenced by radiation, cancer, and exercise-based interventions shows that despite being good predictors of chronological age, neither a pathological state like breast cancer, a hazardous environmental factor (radiation), nor exercise (a beneficial intervention) caused significant changes in the values of the "epigenetic age" determined by these first-generation models.© 2024. The Author(s).