Metabolic regulation of human DNA methylation clocks

生物衰老轨迹存在显著的个体间差异，但这些差异的根源 分歧尚不清楚。维持生命和促进压力适应的一个特殊细胞成分是 线粒体，它包含自己的基因组，并产生表观遗传所需的代谢中间产物 修改。结果，线粒体的遗传缺陷缩短了动物模型和患者的寿命。 线粒体DNA缺陷，可能是通过线粒体信号对基因表达的影响和 表观遗传机制，包括DNA甲基化(DNaM)。DNaM中的可靠更改发生在 特定基因组位置的年龄增长，已被捕获并整合到预测算法中 被称为表观遗传时钟。这些时钟可以预测DNAmAge，并且已经过大量验证和荟萃分析 人类队列证明DNAmAge可以预测死亡率和与年龄相关的疾病。但鲜为人知的是 关于时钟实际测量的是什么(即，是什么使它们滴答作响)，以及它们是否可以通过新陈代谢进行修改 影响寿命的因素。绘制表观遗传时钟的终生行为及其对两者的反应 应激介质和线粒体功能障碍，我们已经建立了原代人成纤维细胞细胞 寿命模型，其中：i)dNaM老化签名是保守的，ii)dNaM老化速度加快 约为人体的70倍，iii)代谢和线粒体功能障碍减少寿命(即， Hayflick限制)减少25%-50%，以及iv)其他老化生物标志物，包括CCF-mtDNA和促炎性 细胞因子IL6也在细胞的整个生命周期内逐渐被诱导。在目标1中，我们将描述dNaM 在雌性和雄性细胞中，使用四种不同的全局 DNAmAge算法，一种基于基因的方法，并通过对单一CpG轨迹进行建模。总会有结果的 经过验证并扩展到可用的人类老龄化队列中。在目标2中，我们将检查 具有两个可靠降低Hayflick限制的干预的dNaM时钟：i)我们将使用聚合 诱导特定线粒体呼吸缺陷的药理学和遗传学方法，以及ii)暴露 细胞对慢性糖皮质激素的刺激作用概括了已知的慢性心理应激的影响 加速人类的生物衰老。在最终目标中，我们将进行研究，以了解基于时钟的 DNAmAge与其他有效的衰老生物标志物相关，包括年龄相关基因的表达(Elov12， P16INK4a)、端粒长度、循环中无细胞线粒体DNA(CCF-mtDNA)和炎症细胞因子IL-6。 此外，还将进行其他实验，以确定细胞分裂对表观遗传学的贡献。 年龄加速，环境氧的作用，并测试DNA去甲基化试剂对其他 老化的生物标志物和寿命。总体而言，这些研究将揭示新的纵向联系 表观遗传时钟和人类衰老生物标志物，并建立线粒体信号作为驱动因素的作用 人体系统中的细胞老化。

There are substantial inter-individual differences in biological aging trajectories, but the origin of these differences is unclear. One specific cellular component that sustains life and fuels stress adaptation are mitochondria, which contain their own genome and generate metabolic intermediates necessary for epigenetic modifications. As a result, genetic defects in mitochondria shorten lifespan in both animal models and patients with mtDNA defects, possibly via the influence of mitochondrial signaling on gene expression and the epigenetic machinery, which includes DNA methylation (DNAm). Reliable changes in DNAm occur with advancing age at specific genomic locations, which have been captured and integrated in predictive algorithms called epigenetic clocks. These clocks predict DNAmAge and have been validated and meta-analyzed in large human cohorts demonstrating that DNAmAge predicts mortality and age-related diseases. But little is known about what clocks actually measure (i.e., what makes them tick), and about their modifiability by metabolic factors across the lifespan. To map the life-long behavior of epigenetic clocks and their responses to both stress mediators and mitochondrial dysfunction, we have developed a primary human fibroblasts cellular lifespan model where: i) DNAm signatures of aging are conserved, ii) the rate of DNAm aging is accelerated about 70 times relative to the human body, iii) metabolic and mitochondrial dysfunction reduces lifespan (i.e., the Hayflick limit) by 25-50%, and iv) other aging biomarkers including ccf-mtDNA and the pro-inflammatory cytokine IL6 are also progressively induced across the cellular lifespan. In Aim 1, we will characterize DNAm aging trajectories across the entire cellular lifespan in both female and male cells using four different global DNAmAge algorithms, a gene-based approach, and by modeling single-CpG trajectories. There results will be validated and extended into available human aging cohorts. In Aim 2, we will examine the modifiability of DNAm clocks with two interventions that reliably decrease the Hayflick limit: i) we will use converging pharmacological and genetic approaches to induce specific mitochondrial respiratory defects, and ii) expose cells to chronic glucocorticoid stimulation to recapitulate the effects of chronic psychosocial stress known to accelerate biological aging in humans. In the final aim, we will perform studies to understand how clock-based DNAmAge relate to other validated aging biomarkers including the expression of age-related genes (Elovl2, p16INK4a), telomere length, circulating cell-free mtDNA (ccf-mtDNA), and the inflammatory cytokine IL-6. Moreover, additional experiments will be performed to establish the contribution of cell division to epigenetic age acceleration, the role of ambient oxygen, and to test the effect of a DNA demethylation agent on other aging biomarkers and on lifespan. Overall, these studies will uncover novel longitudinal associations between epigenetic clocks and human aging biomarkers, and establish the role of mitochondrial signaling as a driver of cellular aging in a human system.