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Epigenetic age prediction in semen - marker selection and model development.

Aleksandra Pisarek1, Ewelina Pośpiech1, Antonia Heidegger2

  • 1Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.

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|August 10, 2021
PubMed
Summary

Epigenetic age prediction from semen DNA is now possible using novel DNA methylation markers. This research identifies new age-correlated sites, improving forensic age estimation accuracy from semen samples.

Keywords:
DNA methylationamplicon bisulfite sequencingepigenetic ageepigenetic age estimationsemen

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Area of Science:

  • Forensic Science
  • Epigenetics
  • Molecular Biology

Background:

  • DNA methylation analysis is crucial for biomedical research and forensic science.
  • Epigenetic age estimation using differentially methylated sites (DMSs) has advanced molecular age prediction.
  • Previous epigenetic age studies primarily utilized somatic cell types, leaving semen-derived DNA under-explored.

Purpose of the Study:

  • To identify novel DNA methylation markers for age prediction in semen-derived DNA.
  • To validate these markers and develop an accurate epigenetic age prediction model for semen.
  • To assess the potential and limitations of current epigenetic methods for forensic semen analysis.

Main Methods:

  • Infinium MethylationEPIC BeadChip arrays were used to analyze DNA methylation in semen samples.
  • Targeted bisulfite massively parallel sequencing validated age-correlated novel DMSs and previously known sites.
  • Prediction modeling was performed using identified CpG sites to estimate age.

Main Results:

  • Numerous novel DMSs moderately correlated with age were identified in semen DNA.
  • Nine new and three previously known age-correlated markers were validated in an independent dataset.
  • A predictive model using 6 CpGs from genes SH2B2, EXOC3, IFITM2, GALR2, and FOLH1B achieved a 5.1-year mean absolute error for age prediction in semen.

Conclusions:

  • Novel DNA methylation markers can accurately predict age from semen-derived DNA.
  • The developed model shows promise for forensic applications, though further technological advancements are needed.
  • Sensitive analysis of more age-correlated DMSs from compromised forensic DNA is essential for enhanced accuracy.