Forensic age estimation from human blood using age-related microRNAs and circular RNAs markers - Wang, Junyan; Zhang, Haixia; Wang, Chunyan; Fu, Lihong; Wang, Qian; Li, Shujin; Cong, Bin (Frontiers in Genetics, 2022)
Aging is a complicated process characterized by progressive and extensive changes in physiological homeostasis at the organismal, tissue, and cellular levels. In modern society, age estimation is essential in a large variety of legal rights and duties. Accumulating evidence suggests roles for microRNAs (miRNAs) and circular RNAs (circRNAs) in regulating numerous processes during aging. Here, we performed circRNA sequencing in two age groups and analyzed microarray data of 171 healthy subjects (17-104 years old) downloaded from Gene Expression Omnibus (GEO) and ArrayExpress databases with integrated bioinformatics methods. A total of 1403 circRNAs were differentially expressed between young and old groups, and 141 circRNAs were expressed exclusively in elderly samples while 10 circRNAs were expressed only in young subjects. Based on their expression pattern in these two groups, the circRNAs were categorized into three classes: age-related expression between young and old, age-limited expression-young only, and age-limited expression-old only. The top 5 expressed circRNAs among 3 classes and 18 differentially expressed miRNAs screened from online databases were selected to validate using RT-qPCR tests. An independent set of 200 blood samples (20-80 years old) was used to develop age prediction models based on 15 age-related noncoding RNAs (11 miRNAs and 4 circRNAs). Different machine learning algorithms for age prediction were applied, including regression tree, bagging, support vector regression (SVR), random forest regression (RFR), and XGBoost. Among them, RFR model performed best in both training set (MAE = 3.68 years, r = 0.96) and testing set (MAE = 6.840 years, r = 0.77). Models using one single type of predictors, circRNAs-only or miRNAs-only, result in bigger errors. Smaller prediction errors were shown in males than females when constructing models according to different-sex separately. Putative miRNA targets (430 genes) were enriched in the cellular senescence pathway and cell homeostasis and cell differentiation regulation, indirectly indicating that the miRNAs screened in our study were correlated with development and aging. This study implicates that the noncoding RNA aging clock demonstrates good performance in predicting chronological age and will be an available biological marker in routine forensic investigation to predict the age of biological samples.