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Updated: Jul 1, 2025

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
DNA methylation marker identification and poly-methylation risk score in prediction of healthspan termination
Meiqi Yang1, Mei Wang1, Xiaoyu Zhao2
1Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Abstract:
Aim: To elucidate the epigenetic consequences of DNA methylation in healthspan termination (HST), considering the current limited understanding. Materials & methods: Genetically predicted DNA methylation models were established (n = 2478). These models were applied to genome-wide association study data on HST. Then, a poly-methylation risk score (PMRS) was established in 241,008 individuals from the UK Biobank. Results: Of the 63,046 CpGs from the prediction models, 13 novel CpGs were associated with HST. Furthermore, people with high PMRSs showed higher HST risk (hazard ratio: 1.18; 95% CI: 1.13-1.25). Conclusion: The study indicates that DNA methylation may influence HST by regulating the expression of genes (e.g., PRMT6, CTSK). PMRSs have a promising application in discriminating subpopulations to facilitate early prevention.

