Development of a microRNA-Based age estimation model using whole-blood microRNA expression profiling
Yanfang Lu1,2, Anqi Chen2, Mengxiao Liao2
1School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi, 030009, China.
Non-Coding RNA Research
|March 27, 2025
Summary
This study explored microRNAs (miRNAs) in blood for predicting human age, offering a novel forensic identification method. The developed elastic net model achieved high accuracy, identifying key miRNA biomarkers for more precise age estimation.
Area of Science:
- Forensic Science
- Molecular Biology
- Genetics
Background:
- Accurate age estimation is vital for human identification.
- Traditional methods have limitations, especially with biological samples.
- DNA methylation is a recent focus for forensic age prediction.
Purpose of the Study:
- Investigate microRNAs (miRNAs) as novel molecular markers for age estimation.
- Explore alternative biomarkers beyond DNA methylation for forensic applications.
- Identify specific miRNA signatures associated with chronological age.
Main Methods:
- Analyzed miRNA expression in 127 peripheral blood samples using small RNA sequencing.
- Employed Lasso regression to select candidate miRNAs and SHAP analysis for significance.
- Developed and evaluated five machine learning models for age prediction.
Main Results:
- Identified 103 candidate and 38 key significant miRNAs for age prediction.
- The elastic net model achieved the best performance with a Mean Absolute Error (MAE) of 4.08 years.
- Observed significant miRNA expression changes in individuals aged 48-52 years.
Conclusions:
- Blood-based miRNA biomarkers show significant potential for accurate age prediction.
- This study provides a validated set of miRNA markers for future age estimation methods.
- Findings contribute to advancing forensic identification techniques using molecular markers.
