Simulating DNAm drift in >22k blood samples shows stochastic change explains 66–75 % of Horvath clock accuracy, 90 % for Zhang, but 63 % for PhenoAge, implying true aging reflects non-stochastic biology. Male, severe COVID-19 and smoker accelerations stem from these non-random effects.
In an 8-week twin study, only the vegan diet cut epigenetic age: lower PC GrimAge, PC PhenoAge, DunedinPACE and reduced aging in inflammation, heart, hormone, liver and metabolic systems. Omnivores didn’t shift, underscoring plant-based diets’ anti-aging edge.
Simulating DNAm drift in >22k blood samples shows stochastic change explains 66–75 % of Horvath clock accuracy, 90 % for Zhang, but 63 % for PhenoAge, implying true aging reflects non-stochastic biology. Male, severe COVID-19 and smoker accelerations stem from these non-random effects.
Using blood DNA methylation with machine learning, we built 11 system-specific epigenetic clocks (Heart, Lung, Kidney, etc.) plus a unified Systems Age. These scores predict system-level aging, mortality and disease, revealing distinct aging subtypes for personalized care.
In an 8-week twin study, only the vegan diet cut epigenetic age: lower PC GrimAge, PC PhenoAge, DunedinPACE and reduced aging in inflammation, heart, hormone, liver and metabolic systems. Omnivores didn’t shift, underscoring plant-based diets’ anti-aging edge.
Simulating DNAm drift in >22k blood samples shows stochastic change explains 66–75 % of Horvath clock accuracy, 90 % for Zhang, but 63 % for PhenoAge, implying true aging reflects non-stochastic biology. Male, severe COVID-19 and smoker accelerations stem from these non-random effects.
