Presentation Schedule
Ethnicity-Specific Epigenetic Clocks Reveal Enhanced Chronological Age Prediction in Asian Populations (103218)
Session Chair: Ives Lim
Wednesday, 25 March 2026 18:00
Session: Session 5
Room: Room 706 (7F)
Presentation Type: Oral Presentation
Contemporary epigenetic clocks today have been developed in predominantly European-ancestry cohorts, limiting their accuracy in diverse populations. We constructed novel DNA methylation-based chronological age clocks for three major Asian ethnic groups, Chinese (N=3,574), Malay (N=917), and Indian (N=1,075), using elastic net regression on a harmonized multi-cohort dataset profiled using the Illumina EPIC array. Ethnicity-specific models significantly outperformed established first-generation clocks, with mean absolute errors (MAE) ranging from 1.8 to 3.0 years and R2 values averaging 0.95, compared to the best existing clocks’ MAE of ~4.5 years. A transethnic model trained across all groups performed comparably across homogeneous ancestry subcohorts (MAE = 2.2-2.7, R2 = 0.91-0.94), as well as non-Asian populations (MAE = 2.4-6.9, R2 = 0.85-0.97), highlighting both specificity and generalizability. Jaccard index analysis revealed partially overlapping CpG sets, suggesting ethnicity-associated aging signatures. These findings demonstrate that tailored clocks can yield more precise aging estimates in under-represented populations and underscore the importance of ancestry-aware modelling in epigenetic biomarker development. Our study provides a critical step toward more equitable, population-sensitive biomarkers in aging research and precision health.
Authors:
Ives Lim, Bioinformatics Institute, A*STAR, Singapore
Penny Chan, Bioinformatics Institute, A*STAR, Singapore
Raghav Sehgal, Yale University, United States
John Chambers, Nanyang Technological University, Singapore
Patrick Tan, Duke-NUS, Singapore
Neerja Karnani, Bioinformatics Institute, singapore
About the Presenter(s)
Ives Lim, systems biology bioinformatician, specializes in multi-omics sequencing and integrative analysis.
Connect on Linkedin
https://www.linkedin.com/in/ives-lim/
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