Deep-Learning Biomarker for Cellular Senescence and Health Outcomes
A study explores a deep-learning derived SASP Score as a potential biomarker for systemic cellular senescence burden, predicting mortality and chronic health conditions.
A study explores a deep-learning derived SASP Score as a potential biomarker for systemic cellular senescence burden, predicting mortality and chronic health conditions.
This study explores how blood cell composition affects DNA methylation age and age acceleration, revealing distinct biological interpretations and modest associations with health outcomes.
This study explores a novel ensemble DNA methylation clock that identifies immune-metabolic aging signatures associated with mortality, highlighting its predictive power over traditional models.
This study investigates the associations between substance use, including alcohol, tobacco, and opioids, and biological aging in a population-based sample of adults.
This study explores a deep-learning derived SASP Score as a biomarker for systemic cellular senescence burden, predicting mortality and chronic health conditions.
This study explores the associations between substance use, including alcohol and opioids, and biological aging as measured by epigenetic clocks.
This study explores a new DNA methylation clock that identifies immune-metabolic aging signatures associated with mortality, using data from the Framingham Heart Study.
This study explores how blood cell composition influences DNA methylation age and age acceleration, revealing distinct biological interpretations.
This study explores how blood cell composition affects DNA methylation age and age acceleration, revealing distinct biological interpretations and their implications for health outcomes.
This study presents a novel ensemble DNA methylation clock that identifies immune-metabolic aging signatures associated with mortality, using data from the Framingham Heart Study.