TY - JOUR

T1 - A Novel Framework for the Design of Minimized Epigenetic Clocks Using the Analysis of DNA Methylation Heterogeneity

AU - Romanov, Stanislav E.

AU - Karetnikov, Dmitry I.

AU - Kalashnikova, Darya A.

AU - Polivcev, Denis E.

AU - Osipov, Yakov A.

AU - Maksimov, Daniil A.

AU - Antoshina, Polina A.

AU - Shloma, Viktor V.

AU - Samoilova, Ekaterina M.

AU - Ivanova, Alina A.

AU - Karimov, Rustam F.

AU - Tkalin, Artem N.

AU - Shevchenko, Alexander A.

AU - Kalsin, Vladimir A.

AU - Baklaushev, Vladimir P.

AU - Laktionov, Petr P.

N1 - This study was conducted in accordance with the Declaration of Helsinki and approved by the local ethics committee of the Federal Center for Medical Sciences of the Federal Medical and Biological Agency of Russia (protocol No. 7-5-22 dated 6 September 2022).

PY - 2025

Y1 - 2025

N2 - Despite the significant progress made in the development of epigenetic age (eAge) clocks designed to estimate the various aspects of aging, currently available models, generated using large DNA methylation microarray datasets, still cannot fully address the issues of batch effects and technical variation. This hinders the use of the publicly available eAge clocks in routine laboratory practice, and it motivates the development of cost-effective, custom epigenetic clocks that are tailored to the given biological subjects and research methods. In this study, we analyzed the local DNA methylation of mesenchymal stem cell samples during culture expansion using high-throughput targeted bisulfite sequencing (BS-seq). Using the obtained data, we trained a minimized eAge model based on a Random Forest Regression with Leave-One-Out Cross-Validation, which determines cell passage with good performance (MAE 1.094 and R2 0.897) and which is comparable to previous solutions. Using the advantage of BS-seq to analyze consecutive CpGs methylation patterns, we demonstrated that combining the analysis of average DNA methylation levels with local methylation heterogeneity scores—thereby reflecting stochastic DNA methylation dynamics—can improve the quality of the epigenetic clock models. Therefore, we propose a research strategy for creating customized epigenetic clocks using targeted BS-seq and provide a mechanistic conceptualization of how information on longitudinal changes in DNA methylation patterns can potentially be used for the assessment of specific aging aspects.

AB - Despite the significant progress made in the development of epigenetic age (eAge) clocks designed to estimate the various aspects of aging, currently available models, generated using large DNA methylation microarray datasets, still cannot fully address the issues of batch effects and technical variation. This hinders the use of the publicly available eAge clocks in routine laboratory practice, and it motivates the development of cost-effective, custom epigenetic clocks that are tailored to the given biological subjects and research methods. In this study, we analyzed the local DNA methylation of mesenchymal stem cell samples during culture expansion using high-throughput targeted bisulfite sequencing (BS-seq). Using the obtained data, we trained a minimized eAge model based on a Random Forest Regression with Leave-One-Out Cross-Validation, which determines cell passage with good performance (MAE 1.094 and R2 0.897) and which is comparable to previous solutions. Using the advantage of BS-seq to analyze consecutive CpGs methylation patterns, we demonstrated that combining the analysis of average DNA methylation levels with local methylation heterogeneity scores—thereby reflecting stochastic DNA methylation dynamics—can improve the quality of the epigenetic clock models. Therefore, we propose a research strategy for creating customized epigenetic clocks using targeted BS-seq and provide a mechanistic conceptualization of how information on longitudinal changes in DNA methylation patterns can potentially be used for the assessment of specific aging aspects.

KW - DNA methylation heterogeneity

KW - bisulfite sequencing

KW - eAge clocks

KW - epigenetic age

KW - mesenchymal stem cells

UR - https://www.mendeley.com/catalogue/9b3d39c6-daef-36a6-bf6e-4f2d69b4d16b/

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-105007853026&origin=inward&txGid=3a79f06e1ebb8ccd83167e217b0af7b4

U2 - 10.3390/ijms26115051

DO - 10.3390/ijms26115051

M3 - Article

C2 - 40507860

VL - 26

JO - International Journal of Molecular Sciences

JF - International Journal of Molecular Sciences

SN - 1661-6596

IS - 11

M1 - 5051

ER -