Forensic Age Estimation From Blood Samples by Combining DNA Methylation and MicroRNA Markers Using Droplet Digital...

Area of Science:

• Forensic Science
• Molecular Biology
• Genetics

Background:

• Age estimation is crucial in forensic investigations.
• DNA methylation (DNAm) and miRNA markers are used for age determination.
• Combining omics data can enhance predictive model accuracy.

Purpose of the Study:

• To develop a multiplex ddPCR system for simultaneous detection of age-associated DNAm and miRNA markers.
• To establish and evaluate age prediction models using combined DNAm and miRNA data.
• To assess the accuracy of these models for forensic applications.

Main Methods:

• Development of a novel multiplex droplet digital PCR (ddPCR) system.
• Simultaneous detection of KLF14 (DNAm) and miR-106b-5p (miRNA) markers.
• Age prediction model establishment using random forest (RF) on 132 blood samples.

Main Results:

• The RF model achieved a mean absolute deviation (MAD) of 3.51 years and R² of 0.84 for validation sets.
• For bloodstain samples, the MAD was 5.66 years, with errors ranging from 3.16 to 10.54 years.
• A stable 4-plex ddPCR method for detecting KLF14, miR-106b-5p, C-LESS-C1, and RNU6B was established.

Conclusions:

• Combining DNAm and miRNA data improves age prediction accuracy.
• The developed ddPCR method is stable and suitable for detecting multiple age-associated markers.
• Further validation with larger datasets is needed to confirm findings for forensic applications.