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.
Epigenetic clocks are widely used in geroscience but little known about their modifiability and behavior across the lifespan. Here we use a human cellular lifespan system that recapitulates key hallmarks of human aging (DNA methylation signatures, ccf-mtDNA, inflammation) to map individualized trajectories in the rate of epigenetic aging among cells from healthy women and men, in response to glucocorticoid stress, and to targeted mitochondrial dysfunction. These high-resolution longitudinal multi-system data will provide new insights into inter-individual differences in aging trajectories, the modifiability of epigenetic clocks, and provide causal evidence for the of mitochondrial dysfunction as a potential biological determinant of epigenetic aging.