Causal aging biomarker empowers systemic antiaging therapy screening Kejun Albert Ying

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In this episode of TimePie Lecture, Kejun Ying, a PhD student in Vadim Gladyshev's lab at Harvard Medical School, introduced how causal aging biomarker empowers systemic anti-aging therapy screening. • ‪@kejunalbertying6632‬ • Ying's research focuses on understanding the causes of aging and developing machine learning-based aging biomarkers to facilitate the discovery of new anti-aging interventions. • #longevity #aging #antiaging #lifespan #biomarkers #healthspan #research • 00:00 Introduction • 00:30 Anti-aging therapies are not new • 01:23 What stops us from a systematic screening • 02:21 DNA methylation profile predicts biological age • 02:41 Causality matters for model applications • 03:41 Epigenome-wide Mendelian Randomization • 05:30 Damaging vs protective age-related changes • 05:49 Causality-enriched clock models • 07:12 Clockbase, an online platform for exploring and analyzing biological age • 08:30 Biolearn, an open-source library for biomarkers of aging • 09:02 Moving toward the consensus on aging biomarkers • 10:11 Standardizing metadata annotation with LLMs • 10:41 Systemic anti-aging treatment screening • 12:18 Q A

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