A Comprehensive Assessment of Methylation-Based Age Prediction Methods

Wang, H., Qu, J., Zong, Z. X., Cai, R. R., Li, K. Y., Zhao, L. S., Hai, Q. B., Tian, T. R., Kuang, J. Z., Zhang, L., Zhao, J., Liu, X. G., Zhang, C.

Boston University · biorxiv

Paper

Abstract

DNA methylation (DNAm) clock is widely used to measure biological age, helping to identify key biomarkers associated with aging, infer the progression of aging, and have promise for elucidating, delaying, or even reversing aging. During the past decade, a large number of epigenetic clocks have been developed. However, they are decentralized, with applicable scopes overlapping. We benchmark 15 of these methods on 142 Illumina DNAm array datasets in five criteria and analyze the biological significance of CPGs about aging and overlapping. There are many exciting commons in models performance. We found the optimal model closely related to the numbers and characteristics of the training data. We provided a comprehensive assessment process to guide DNAm clock research at (https://dnamclock.com), the corresponding data and evaluation pipeline are freely available (https://github.comyNENUBioCompute/MethylationEvaluation), this study will aid in the development of improved tools designed to analyze increasingly large DNAm datasets.

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper is relevant to longevity research as it focuses on DNA methylation clocks, which are tools for measuring biological age and understanding the aging process. By benchmarking various methods and providing a comprehensive assessment, it contributes to the development of better tools for analyzing aging-related data. However, while it presents solid research, the findings appear to be incremental rather than groundbreaking, limiting its overall impact on the field.

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