Age Prediction Using DNA Methylation Heterogeneity Metrics.
Int J Mol Sci
; 25(9)2024 May 02.
Article
en En
| MEDLINE
| ID: mdl-38732187
ABSTRACT
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.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Envejecimiento
/
Metilación de ADN
/
Epigénesis Genética
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Secuenciación de Nucleótidos de Alto Rendimiento
Límite:
Adult
/
Aged
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Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
Int J Mol Sci
Año:
2024
Tipo del documento:
Article
País de afiliación:
Rusia
Pais de publicación:
Suiza