Causality-enriched epigenetic age uncouples damage and adaptation.
Causality-enriched epigenetic age uncouples damage and adaptation.
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因果关系丰富的表观遗传年龄将损伤和适应分开。
DOI：
10.1038/s43587-023-00557-0
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发表时间：
2024
期刊：
影响因子：
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通讯作者：
Gladyshev,VadimN
中科院分区：
文献类型：
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作者：
Ying,Kejun;Liu,Hanna;Tarkhov,AndreiE;Sadler,MarieC;Lu,AkeT;Moqri,Mahdi;Horvath,Steve;Kutalik,Zoltán;Shen,Xia;Gladyshev,VadimN
基于DNA甲基化数据的机器学习模型可以预测生物年龄，但往往缺乏因果关系。通过利用表观基因组范围的孟德尔随机化的大规模遗传数据，我们确定了可能导致衰老相关性状的CpG位点。无论是现有的表观遗传时钟，还是与年龄相关的差异DNA甲基化都没有在这些位置丰富。这些CPGS包括促进衰老和防止衰老的位点，但它们的共同作用对年龄相关特征产生了负面影响。我们建立了一个新的框架，将因果信息引入表观遗传时钟，导致损伤和适应性年龄时钟，分别跟踪有害和适应性甲基化变化。损害与包括死亡率在内的不良后果相关，而适应年龄与有益的适应有关。这些因果关系丰富的时钟对短期干预表现出敏感性。我们的发现提供了CpG部位的详细图景，这些部位与寿命和健康寿命之间存在假定的因果联系，促进了衰老生物标记物的发展，评估了干预措施，并研究了与年龄相关的变化的可逆性。
Machine learning models based on DNA methylation data can predict biological age but often lack causal insights. By harnessing large-scale genetic data through epigenome-wide Mendelian randomization, we identified CpG sites potentially causal for aging-related traits. Neither the existing epigenetic clocks nor age-related differential DNA methylation are enriched in these sites. These CpGs include sites that contribute to aging and protect against it, yet their combined contribution negatively affects age-related traits. We established a new framework to introduce causal information into epigenetic clocks, resulting in DamAge and AdaptAge—clocks that track detrimental and adaptive methylation changes, respectively. DamAge correlates with adverse outcomes, including mortality, while AdaptAge is associated with beneficial adaptations. These causality-enriched clocks exhibit sensitivity to short-term interventions. Our findings provide a detailed landscape of CpG sites with putative causal links to lifespan and healthspan, facilitating the development of aging biomarkers, assessing interventions, and studying reversibility of age-associated changes.