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Predicting human age with bloodstains by sjTREC quantification.

Xue-ling Ou1, Jun Gao, Huan Wang

  • 1Department of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangzhou, People's Republic of China.

Plos One
|August 11, 2012
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Summary

Age-related decline of signal joint T-cell receptor rearrangement excision circles (sjTRECs) in bloodstains allows for age prediction. sjTREC quantification is reliable for fresh and short-term stored samples, with potential accuracy loss in very old samples.

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Area of Science:

  • Forensic Science
  • Immunology
  • Molecular Biology

Background:

  • Signal joint T-cell receptor rearrangement excision circles (sjTRECs) decline with age in peripheral blood.
  • Few studies have assessed sjTREC detection in bloodstains, limiting forensic age prediction capabilities.
  • Bloodstains are common in forensic investigations, making sjTREC analysis a potentially valuable tool.

Purpose of the Study:

  • To quantify sjTRECs in human bloodstains across a wide age range (0-86 years).
  • To establish a formula for age estimation based on sjTREC levels in bloodstains.
  • To evaluate the impact of storage time on sjTREC quantification and age prediction accuracy.

Main Methods:

  • Sensitive Taqman real-time quantitative polymerase chain reaction (qPCR) for sjTREC quantification.
  • Analysis of 264 bloodstain samples from individuals aged 0-86 years.
  • Comparison of sjTREC content in fresh versus stored bloodstains (up to 1.5 years and 20 years).

Main Results:

  • sjTREC content in bloodstains showed a significant age-dependent decline (r = -0.8712).
  • A formula for age estimation was derived: Age = -7.1815Y-42.458 ± 9.42.
  • No significant sjTREC loss was observed after 4 weeks of storage, but losses occurred after 1.5 years.
  • sjTREC detection in 20-year-old bloodstains correlated with age, but accuracy decreased over time.

Conclusions:

  • sjTREC quantification in bloodstains is a viable method for age prediction in forensic contexts.
  • The method shows good reliability for fresh and short-term stored samples.
  • Further research is needed to address time-dependent effects on accuracy for aged samples.