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Background <p>Accurate estimation of the time since the deposition of biological samples is a critical aspect of forensic investigations, as it can provide important temporal information about crime scenes. Saliva stains, frequently encountered in forensic casework, degrade over time, and their analysis can offer clues about the timing of events. Recent advances in molecular techniques have focused on using RNA degradation rates as a time-dependent biomarker due to the instability of RNA molecules post-deposition. This study explores the degradation rates of specific mRNA markers, SPRR1A and GAPDH, in dried saliva stains using Quantitative Real-Time PCR (RT-qPCR) and constructs a predictive model for aging such stains.</p> Results <p>The degradation rates profiles of the two mRNA markers revealed distinct patterns. GAPDH exhibited rapid degradation rates compared to SPRR1A, which degraded more gradually, consistent with previous observations of RNA stability differences in biological samples. A multiple regression model was developed using the fold changes of SPRR1A and GAPDH expression normalized to the housekeeping gene B2M. The resulting formula, T =  − 3.40⋅log (FC<sup>SPRR1A</sup>) − 12.43⋅log (FC<sup>GAPDH</sup>) + 7.07, demonstrated a strong predictive capability, explaining 77.3% of the variance in the time since deposition (R<sup>2</sup> = 0.773). The model performed accurately for samples up to 45&#xa0;days old, showing a low mean absolute error. GAPDH played a dominant role in the prediction due to its rapid degradation rates, while the inclusion of SPRR1A enhanced the accuracy, especially for older samples.</p> Conclusions <p>This study underscores the potential of using mRNA degradation rates patterns for forensic time estimation of saliva stains. The combination of qPCR analysis with a multidimensional predictive model offers a reliable tool for determining the age of biological samples, aiding forensic investigations. The method provides a non-invasive and precise approach for estimating the time since deposition, particularly in the crucial early days after a crime scene is established.</p>

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Forensic saliva stains aging, using reverse transcription real-time PCR combined with a multidimensional prediction model of specific mRNA markers

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月2日

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  • Emad Ahmad Mostafa,
  • Eman Abd Elhakim Attia,
  • Nashwa El-Khazragy,
  • Hanan E. Salem

摘要

Background

Accurate estimation of the time since the deposition of biological samples is a critical aspect of forensic investigations, as it can provide important temporal information about crime scenes. Saliva stains, frequently encountered in forensic casework, degrade over time, and their analysis can offer clues about the timing of events. Recent advances in molecular techniques have focused on using RNA degradation rates as a time-dependent biomarker due to the instability of RNA molecules post-deposition. This study explores the degradation rates of specific mRNA markers, SPRR1A and GAPDH, in dried saliva stains using Quantitative Real-Time PCR (RT-qPCR) and constructs a predictive model for aging such stains.

Results

The degradation rates profiles of the two mRNA markers revealed distinct patterns. GAPDH exhibited rapid degradation rates compared to SPRR1A, which degraded more gradually, consistent with previous observations of RNA stability differences in biological samples. A multiple regression model was developed using the fold changes of SPRR1A and GAPDH expression normalized to the housekeeping gene B2M. The resulting formula, T =  − 3.40⋅log (FCSPRR1A) − 12.43⋅log (FCGAPDH) + 7.07, demonstrated a strong predictive capability, explaining 77.3% of the variance in the time since deposition (R2 = 0.773). The model performed accurately for samples up to 45 days old, showing a low mean absolute error. GAPDH played a dominant role in the prediction due to its rapid degradation rates, while the inclusion of SPRR1A enhanced the accuracy, especially for older samples.

Conclusions

This study underscores the potential of using mRNA degradation rates patterns for forensic time estimation of saliva stains. The combination of qPCR analysis with a multidimensional predictive model offers a reliable tool for determining the age of biological samples, aiding forensic investigations. The method provides a non-invasive and precise approach for estimating the time since deposition, particularly in the crucial early days after a crime scene is established.