A Five-Color Multiplex Droplet Digital PCR Assay With Support Vector Regression for Forensic Age Prediction.

Area of Science:

• Forensic science
• Epigenetics
• Molecular biology

Background:

• Traditional forensic methylation analysis methods like SNaPshot and massively parallel sequencing (MPS) have limitations.
• Existing droplet digital PCR (ddPCR) assays often lack multiplexing and are tissue-specific.

Purpose of the Study:

• To develop and validate a novel, high-multiplex, cross-tissue assay for forensic age estimation.
• To compare the performance of support vector regression (SVR) and multiple linear regression (MLR) for age prediction using methylation data.

Main Methods:

• Validated 98 age-associated CpGs in 1398 Chinese blood methylomes.
• Developed a 17-plex assay on a 5-color fluorescence ddPCR platform.
• Applied the assay to saliva, blood, and buccal swab samples, analyzing age correlations and using SVR and MLR for modeling.

Main Results:

• Strong age correlations observed across different tissues (Spearman's |r|: 0.554-0.956).
• SVR models significantly outperformed MLR, explaining >98% of age variation with low mean absolute deviations (MADs) across tissues.
• The 5-color multiplex ddPCR assay demonstrated robust performance across broad age groups.

Conclusions:

• The novel 17-plex ddPCR assay provides a rapid, cost-effective, and cross-tissue solution for forensic age estimation.
• This advanced method serves as a viable alternative to SNaPshot and MPS, improving forensic investigation and health-related age prediction.