Development of a microRNA-Based age estimation model using whole-blood microRNA expression profiling.

Journal: Non-coding RNA research
Published Date: Mar 3, 2025

Abstract

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.

Authors

  • Yanfang Lu
    School of Forensic Medicine, Shanxi Medical University, Taiyuan, Shanxi, 030009, China.
  • Anqi Chen
    School of Information Engineering, Wuhan University of Technology, 430070 Wuhan, Hubei, China.
  • Mengxiao Liao
    Institute of Forensic Science, Fudan University, Shanghai, 200032, China.
  • Ruiyang Tao
    Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Sciences, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai, China.
  • Shubo Wen
    Institute of Forensic Science, Fudan University, Shanghai, 200032, China.
  • Suhua Zhang
    Institute of Forensic Science, Fudan University, Shanghai, China.
  • Chengtao Li
    School of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi'an 170021, China.

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