TY - JOUR

T1 - Age Prediction Using DNA Methylation Heterogeneity Metrics

AU - Karetnikov, Dmitry I.

AU - Romanov, Stanislav E.

AU - Baklaushev, Vladimir P.

AU - Laktionov, Petr P.

N1 - The research was supported by the Russian Science Foundation (project No. 22-74-10123).

PY - 2024/5

Y1 - 2024/5

N2 - Dynamic changes in genomic DNA methylation patterns govern the epigenetic developmental programs and accompany the organism‘s aging. Epigenetic clock (eAge) algorithms utilize DNA methylation to estimate the age and risk factors for diseases as well as analyze the impact of various interventions. High-throughput bisulfite sequencing methods, such as reduced-representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS), provide an opportunity to identify the genomic regions of disordered or heterogeneous DNA methylation, which might be associated with cell-type heterogeneity, DNA methylation erosion, and allele-specific methylation. We systematically evaluated the applicability of five scores assessing the variability of methylation patterns by evaluating within-sample heterogeneity (WSH) to construct human blood epigenetic clock models using RRBS data. The best performance was demonstrated by the model based on a metric designed to assess DNA methylation erosion with an MAE of 3.686 years. We also trained a prediction model that uses the average methylation level over genomic regions. Although this region-based model was relatively more efficient than the WSH-based model, the latter required the analysis of just a few short genomic regions and, therefore, could be a useful tool to design a reduced epigenetic clock that is analyzed by targeted next-generation sequencing.

AB - Dynamic changes in genomic DNA methylation patterns govern the epigenetic developmental programs and accompany the organism‘s aging. Epigenetic clock (eAge) algorithms utilize DNA methylation to estimate the age and risk factors for diseases as well as analyze the impact of various interventions. High-throughput bisulfite sequencing methods, such as reduced-representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS), provide an opportunity to identify the genomic regions of disordered or heterogeneous DNA methylation, which might be associated with cell-type heterogeneity, DNA methylation erosion, and allele-specific methylation. We systematically evaluated the applicability of five scores assessing the variability of methylation patterns by evaluating within-sample heterogeneity (WSH) to construct human blood epigenetic clock models using RRBS data. The best performance was demonstrated by the model based on a metric designed to assess DNA methylation erosion with an MAE of 3.686 years. We also trained a prediction model that uses the average methylation level over genomic regions. Although this region-based model was relatively more efficient than the WSH-based model, the latter required the analysis of just a few short genomic regions and, therefore, could be a useful tool to design a reduced epigenetic clock that is analyzed by targeted next-generation sequencing.

KW - DNA methylation heterogeneity

KW - bisulfite sequencing

KW - eAge clocks

KW - epigenetic age

KW - DNA Methylation

KW - Humans

KW - Aging/genetics

KW - Epigenesis, Genetic

KW - High-Throughput Nucleotide Sequencing/methods

KW - Algorithms

KW - CpG Islands

KW - Female

KW - Male

KW - Epigenomics/methods

KW - Aged

KW - Adult

KW - Middle Aged

KW - Sequence Analysis, DNA/methods

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85192705343&origin=inward&txGid=76372b38498110512f3f96f1cba491a2

UR - https://www.mendeley.com/catalogue/f84b5d03-5ac6-3cd0-9eb0-3a98e73add4d/

U2 - 10.3390/ijms25094967

DO - 10.3390/ijms25094967

M3 - Article

C2 - 38732187

VL - 25

JO - International Journal of Molecular Sciences

JF - International Journal of Molecular Sciences

SN - 1661-6596

IS - 9

M1 - 4967

ER -