Epigenetics of Aging in Mammals: Mechanistic Foundations and Intervention Effects on DNA Methylation–Based Aging Biomarkers

Background: Aging is shaped by interdependent molecular processes captured by the hallmarks framework, in which epigenetic alterations stand out as a potentially modifiable regulatory layer. DNA methylation (DNAm) patterns change with age and can be summarized by epigenetic clocks that estimate biological age, pace of aging, and risk-related phenotypes. Yet, the extent to which interventions reproducibly modulate DNAm-based biomarkers across tissues and species remains uncertain. Methods: A systematized review of longitudinal intervention studies (2010–2025; English/Spanish) was conducted in PubMed, Scopus, and Cochrane CENTRAL, with selection documented using PRISMA. Human eligibility included randomized controlled trials (RCTs), non-randomized controlled studies, and pre–post designs (n≥10; adults ≥18 years). Preclinical eligibility included longitudinal mammalian studies (n≥5 per group). Outcomes were changes in DNAm-based epigenetic age (years) and/or pace of aging (e.g., DunedinPACE). Data were extracted into a standardized matrix (clock, tissue, effect direction/magnitude, safety, RoB_overall) and synthesized narratively; meta-analysis was not performed due to heterogeneity. Results: Thirty-five longitudinal studies were included (29 human, 6 preclinical). Lifestyle interventions in humans generally showed modest effects, with more consistent signals when exposure was sustained and accompanied by plausible physiological changes (e.g., prolonged calorie restriction affecting DunedinPACE, with effect sizes up to d=−0.43 at 12 months and d=−0.40 at 24 months in higher-adherence participants). Exogenous compounds showed higher heterogeneity and mixed evidence, including robust null epigenetic findings in some trials (e.g., metformin adjusted ITT differences ranging from −0.91 to +0.82 years across clocks, all p≥0.18) alongside favorable signals in smaller analytic subsets or open-label settings (e.g., bezisterim sub-study with reductions of −3.68 years in SkinBloodAge, −5.00 in Hannum, and −4.77 in InflammAge). Blood/circulation-derived interventions produced some of the largest reported effect sizes but also raised interpretation challenges: therapeutic plasma exchange with a sham arm reported epigenetic age decreases of ~1.3–2.6 years depending on the clock and regimen, with pronounced shifts in immune/inflammation-sensitive clocks; the apparent benefits waned after treatment cessation. Unexpectedly, repeated plasmapheresis in donors was associated with increases in several clocks and DunedinPACE per procedure (~+0.16–0.26 years per session across GrimAge-family clocks and ~0.003±0.001 DunedinPACE units per session). In rodents, plasma fractions/exosome-rich preparations and heterochronic parabiosis reported large percentage reductions across tissues, with strong dependence on exposure duration and concerns about translational uncertainty (up to ~77.6% in liver and ~68.2% in blood in one plasma-fraction study). Evidence for partial reprogramming (OSKM) was limited to a single rat study with small, near-significant trends in hippocampus-based clocks (two-sided p=0.064–0.088 across three clocks). Conclusions: DNAm-based epigenetic biomarkers are modifiable by interventions in mammals, but effects are heterogeneous and depend on the intervention, clock construct (age vs pace/risk signatures), biological matrix, tissue, follow-up duration, and study design. A single notion of “epigenetic rejuvenation” is not supported; instead, intervention effects appear domain-specific and must be interpreted in relation to what each clock measures.