Lu Yanfang, Chen Anqi, Liao Mengxiao, Tao Ruiyang, Wen Shubo, Zhang Suhua, Li Chengtao
School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi, 030009, China.
Institute of Forensic Science, Fudan University, Shanghai, 200032, China.
Noncoding RNA Res. 2025 Mar 3;12:81-91. doi: 10.1016/j.ncrna.2025.03.003. eCollection 2025 Jun.
Age estimation is a critical aspect of human identification. Traditional methods, reliant on morphological examinations, are often suitable for living subjects. However, there are relatively few studies on age estimation based on biological samples, such as blood. Recent advancements have concentrated on DNA methylation for forensic age prediction. However, to explore further possibilities, this study investigated microRNAs (miRNAs) as alternative molecular markers for age estimation. Peripheral blood samples from 127 healthy individuals were analyzed for miRNA expression using small RNA sequencing. Lasso regression selected 103 candidate miRNAs, and Shapley additive explanations (SHAP) analysis identified 38 key miRNAs significant for age prediction. Five machine learning models were developed, with the elastic net model achieving the best performance (MAE of 4.08 years) on the testing set, surpassing current miRNA age estimation results. Additionally, we observed significant changes in the expression levels of miRNAs in healthy individuals aged 48-52 years. This study demonstrated the potential of blood miRNA biomarkers in age prediction and provides a set of miRNA markers for developing more accurate age prediction methods.
年龄估计是人类身份识别的一个关键方面。依赖形态学检查的传统方法通常适用于活体对象。然而，基于血液等生物样本进行年龄估计的研究相对较少。最近的进展集中在利用DNA甲基化进行法医年龄预测。然而，为了探索更多可能性，本研究调查了微小RNA（miRNA）作为年龄估计的替代分子标记。使用小RNA测序分析了127名健康个体的外周血样本中的miRNA表达。套索回归选择了103个候选miRNA，而夏普利加性解释（SHAP）分析确定了38个对年龄预测有显著意义的关键miRNA。开发了五种机器学习模型，其中弹性网络模型在测试集上表现最佳（平均绝对误差为4.08岁），超过了当前的miRNA年龄估计结果。此外，我们观察到48至52岁健康个体中miRNA表达水平有显著变化。本研究证明了血液miRNA生物标志物在年龄预测中的潜力，并为开发更准确的年龄预测方法提供了一组miRNA标记。
