Estimation of the human postmortem interval using an established rat mathematical model and multi-RNA markers

Area of Science:

• Forensic Science
• Molecular Biology
• Biochemistry

Background:

• Previous RNA degradation models for postmortem interval (PMI) determination were primarily based on rat brain tissue.
• Translating animal data to human cases presents challenges due to complex postmortem RNA changes.
• A need exists for validated RNA biomarkers and models applicable to human tissues for accurate PMI estimation.

Purpose of the Study:

• To screen for valid RNA biomarkers in human tissues (myocardium and liver) for PMI determination.
• To establish and validate mathematical models based on selected RNA markers.
• To improve the accuracy of PMI prediction in forensic investigations.

Main Methods:

• Quantitative real-time PCR (qPCR) was used to detect multi-RNA markers in human myocardium and liver tissues.
• Ct values of ten biomarkers were analyzed for correlation with prolonged postmortem intervals (PMI).
• Mathematical models were developed using R software, with beta-actin (ΔCt) as a key predictive marker.

Main Results:

• Specific RNA markers (5S, miR-1, miR-133a) showed stability for PMI estimation up to 5 days.
• Liver-specific miR-122 degraded under higher temperatures; 5S was confirmed as a reliable endogenous control for liver.
• Beta-actin (ΔCt) demonstrated the strongest correlation with PMI, enabling accurate model development.

Conclusions:

• Validated RNA biomarkers and mathematical models significantly improve PMI prediction accuracy in human cases.
• Comprehensive consideration of tissue-specific biomarkers and environmental factors enhances forensic analysis.
• This research provides a robust framework for PMI determination using molecular markers in forensic science.