Methylation-Based Forensic Age Estimation Across Biogeographic Backgrounds: Central Europeans, East Asians & West Africans
Organized by: International Forensic Scientist Awards
Website: forensicscientist.org
17th Edition of Forensic Scientist Awards 29-30 December 2025 | Dubai, United Arab
Introduction
Forensic science is rapidly evolving, and epigenetics has emerged as a powerful tool for human identification. Among the most promising markers are DNA methylation patterns, which change predictably with age. This makes them valuable for estimating the chronological age of unknown individuals.
This study explores how methylation-based age estimation performs across three major biogeographic groups: Central Europeans, East Asians, and West Africans.
Understanding DNA Methylation
DNA methylation is an epigenetic modification where methyl groups are added to specific cytosine bases (CpG sites). These modifications influence gene expression and vary with age, lifestyle, and environmental exposure.
Because methylation patterns shift consistently as people grow older, they serve as reliable biomarkers for forensic age prediction.
Why Compare Biogeographic Populations?
Human populations differ genetically due to ancestry-specific variations. Since DNA methylation may be influenced by genetic background and environment, evaluating age-prediction accuracy across populations is essential.
This study investigates whether the same methylation markers can be universally applied or if specific populations require refined prediction models.
Study Overview
The research analyzed methylation profiles from individuals representing three populations:
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Central Europeans
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East Asians
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West Africans
Using advanced methylation-based models and forensic markers such as ELOVL2, KLF14, and FHL2, researchers evaluated:
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Prediction accuracy
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Model bias across populations
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Marker performance consistency
Key Findings
1. High Accuracy of Methylation Markers
Core CpG markers showed strong correlations with chronological age in all three groups.
2. Population-Specific Differences
Some markers displayed minor variations in prediction accuracy depending on ancestry, emphasizing the importance of diverse datasets.
3. Improved Multigroup Models
Models trained on combined multiethnic data performed better across all populations compared to single-population models.
4. Forensic Implications
Accurate age estimation supports investigations such as:
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Identifying unknown remains
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Supporting missing-person cases
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Narrowing suspect pools
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Enhancing human identification workflows
Conclusion
This study demonstrates the strong potential of methylation-based forensic age estimation across different biogeographic backgrounds. While core markers perform reliably, population-inclusive modeling significantly improves prediction accuracy.
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