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DNA methylation-based age prediction using massively parallel sequencing data and multiple machine learning models.

Anastasia Aliferi1, David Ballard1, Matteo D Gallidabino2

  • 1King's Forensics, Department of Analytical, Environmental and Forensic Sciences, Faculty of Life Sciences and Medicine, King's College London, 150 Stamford Street, London SE1 9NH, United Kingdom.

Forensic Science International. Genetics
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Summary
This summary is machine-generated.

This study introduces a DNA methylation method to estimate chronological age, achieving high accuracy for forensic DNA intelligence. The developed algorithm predicts age within approximately 4 years, aiding in narrowing suspect pools.

Keywords:
Age predictionArtificial neural networksDNA methylationMachine learningSalivaSpermWhole blood

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Area of Science:

  • Forensic genetics
  • Epigenetics
  • Bioinformatics

Background:

  • DNA intelligence aims to extract actionable information from DNA evidence.
  • Estimating geographical ancestry and physical appearance are established DNA intelligence applications.
  • Chronological age estimation using DNA methylation complements existing forensic DNA profiling capabilities.

Purpose of the Study:

  • To develop and validate a DNA methylation-based method for estimating chronological age.
  • To assess the accuracy and sensitivity of the age estimation method using various statistical models.
  • To evaluate the method's performance on different DNA sample types (blood and saliva).

Main Methods:

  • Analysis of 110 whole blood samples (ages 11-93) using DNA methylation quantification assay.
  • Bisulphite conversion and massively parallel sequencing of 12 CpG sites.
  • Comparison of 17 statistical modeling approaches, selecting a Support Vector Machine with polynomial function (SVMp) model.

Main Results:

  • The selected SVMp model achieved a root mean square error (RMSE) of 4.9 years and a mean average error (MAE) of 4.1 years in blind testing.
  • 52% of samples were predicted within 4 years of error, and 86% within 7 years.
  • The method maintained accuracy with low DNA input (down to 10 ng) and showed promising results on saliva samples (50% within 4 years error).

Conclusions:

  • DNA methylation analysis provides a reliable method for estimating chronological age.
  • The developed method is robust, accurate, and sensitive to DNA input quantity.
  • This age estimation technique has significant potential for enhancing forensic DNA intelligence applications.