What question did this study set out to answer?

To identify a universal epigenetic aging signature based on DNA methylation across diverse tissue types for predicting donor chronological age.

October 26, 2011AgingOpen Access

Epigenetic-aging-signature to determine age in different tissues

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To identify a universal epigenetic aging signature based on DNA methylation across diverse tissue types for predicting donor chronological age.
Screened 27,578 CpG sites from public HumanMethylation27 BeadChip data across dermis, epidermis, cervical smear, T-cells, and monocytes.
Applied Pavlidis Template Matching to identify hypermethylated age-associated sites and constructed a predictive model using five specific CpG loci.
Validated the multi-tissue predictive model against eight independent datasets comprising varied cell and tissue types.
Identified 19 CpG sites that consistently hypermethylate with age across multiple cell types (R > 0.6; p < 10^-13).
Constructed a predictive signature using five CpG sites (associated with NPTX2, TRIM58, GRIA2, KCNQ1DN, and BIRC4BP) that tracked age in all tested tissues.
Achieved an average absolute difference of approximately 11 years between predicted age and true chronological age in validation sets.

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Implication

Cross-tissue computational study reveals an epigenetic aging signature for donor age across human cell types, highlighting utility in forensic analysis.

Cite This Study

Koch et al. (2011) studied this question.

synapsesocial.com/papers/69d83af252654bb436d18bd4 https://doi.org/10.18632/aging.100395

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Implication

Cross-tissue computational study reveals an epigenetic aging signature for donor age across human cell types, highlighting utility in forensic analysis.

Epigenetic-aging-signature to determine age in different tissues

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Epigenetic-aging-signature to determine age in different tissues

Key Points

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Implication

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