EnsembleAge Clock: Reliable, Robust Epigenetic Age Clock Service Reveals Epigenetic Age Acceleration
Wednesday, November 5, 2025
2:30 PM-4:00 PM
BIOMED Seminar
Title:
EnsembleAge Clock: A Reliable and Robust Epigenetic Age Clock Service Reveals Epigenetic Age Acceleration in Opioid-overdosed Brains
Speaker:
Hayan Lee, PhD
Assistant Professor
Cancer Epigenetics Institute
Nuclear Dynamics and Cancer Program
Fox Chase Cancer Center
Temple Health
Adjunct Assistant Professor
Department of Cancer and Cellular Biology
Department of Medical Genetics and Molecular Biochemistry
Lewis Katz School of Medicine (LKSOM)
Temple University
Details:
Age is a major risk factor for various diseases, such as cancer, cardiovascular conditions, and neurodegenerative diseases. However, chronological age, the simple number of years one has lived, does not capture individual health differences, prompting the development of methods to accurately estimate biological age instead of relying on chronological age. One of the major molecular approaches exploits DNA methylation (DNAm), which is an essential epigenetic modifier for regulating gene expression, cell differentiation, and aging. DNAm-based aging clocks have been developed to predict biological age, but the prediction is highly dependent on training data, including organs and assay technologies. To address these clocks’ high variance, we present two EnsembleAge Clocks, leveraging eight previously developed DNAm clocks, harnessing the strengths of each methylome age clock, smoothing out individual variances, and providing a more robust estimation of biological age.
We validated our EnsembleAge Clock models using DNA methylation data from nine organs in the GTEx dataset. Our EnsembleNaive age clock model achieved the lowest median absolute error (MeAE) of 4.04 years in whole blood. The EnsembleLR model demonstrated the lowest MeAE of 6.35 years across multiple tissues, including breast, lung, muscle, ovary, prostate, testis, and colon. The significant reduction in MeAE underscores its high practical value in clinical and forensic applications, especially in contexts where epigenetic changes are subtle. We further applied our models to four public datasets representing diverse biological applications, including administered short-term medical opioid use (GSE151485) and long-term opioid overdose (GSE164822).
Our model reveals over 10 years of age acceleration in opioid-overdosed brains but no significant epigenetic age acceleration when opioid usage was well administered. Our EnsembleAge clock models are also implemented as a web service, allowing users to conveniently upload their DNA methylation data and receive predictions of their biological age. This empowers individuals to track their biological/epigenetic age over time, mitigating the effect of variance and promoting healthy aging and a beneficial lifestyle. Our Ensemble Age Clock service is available at https://ensemble.epiclock.app/.
Biosketch:
Hayan Lee, PhD, is an Assistant Professor at Fox Chase Cancer Center, Temple Health, leading a lab focused on computational epigenetics, including multiomics data analysis, machine learning model development, and data visualization in cancer and aging. Previously, Dr. Lee was a computational postdoctoral scholar in the Snyder Lab at Stanford University, with prior training as a Simons Postdoctoral Fellow at the Joint Genome Institute (JGI). He holds a PhD in Computer Science from Stony Brook University, where he worked on genome assembly using long-read sequencing under the guidance of Professor Michael Schatz. Dr. Lee also earned his MS from Carnegie Mellon University and a BS (cum laude) from Seoul National University, with industry experience developing Windows kernel-level drivers at AhnLab, Inc., in South Korea.
Dr. Lee's research interests include developing machine learning algorithms, AI-based tools, and computational pipelines for epigenetic biomarker discovery through integrative multiomics analysis in aging and cancer.
Contact Information
Carolyn Riley
cr63@drexel.edu