The evaluation of seven age-related CpGs for forensic purpose in blood from Chinese Han population. (May 2020)

• Record Type: Journal Article
• Authors: Pan, Chao; Yi, Shaohua; Xiao, Chao; Huang, Yujie; Chen, Xiaoying; Huang, Daixin
• Is Part Of: Forensic science international. Volume 46(2020)
• Publication Date: 2020-05
• Subjects: DNA methylation -- Age prediction -- Forensic science -- Human blood; Forensic genetics -- Periodicals; Génétique légale -- Périodiques; Forensic genetics; Electronic journals; Periodicals; 614.1
• DOI: 10.1016/j.fsigen.2020.102251
• Languages: English
• ISSNs: 1872-4973

Abstract

Highlights: DNA methylation of seven known age-related CpGs was measured using a multiplex methylation SNaPshot assay. DNA methylation of the seven CpGs showed strong or moderate age-correlation in blood from the Chinese Han population. Two age prediction models, stepwise regression and support vector regression, were established based on our study data. The support vector regression (MAD = 4.01) was superior to the stepwise regression (MAD = 4.22) in age prediction. These DNA methylation markers would be useful for age prediction in blood samples from the Chinese Han populations. Abstract: Age prediction of biological samples is one of the important tasks in forensic DNA phenotyping, and DNA methylation is regarded as the most promising biomarker for forensic age prediction. To date, numerous CpG sites have been reported to be age-related based on the changes in methylation. In this study, seven age-related CpG (AR-CpG) sites, cg02228185 ( ASPA ), cg09809672 ( EDARADD ), cg19283806 ( CCDC102B ), cg04208403 ( ZNF423 ), chr17: 44, 390, 358 of GRCh38/hg38 ( ITGA2B ), cg14361627 ( KLF14 ), and cg06639320 ( FHL2 ), were selected and analyzed in 310 blood samples using a multiplex methylation SNaPshot assay to evaluate the value of selected AR-CpGs in age prediction in blood from Chinese Han population. The study confirmed the correlation of all the investigated markers with human age, and the correlation of cg19283806 with age is the highest while cg04208403 is the lowest in the Chinese Han population. Two different age prediction models, stepwise regression and support vector regression (SVR), were established based on the methylation SNaPshot data using 230 blood samples from donors aged 2–86 years old. The stepwise regression model included six AR-CpGs (except cg09809672) and enabled age prediction with R 2 = 0.85, mean absolute deviation (MAD) = 4.22, while the SVR model enabled age prediction with R 2 = 0.86, MAD = 4.01. An independent set of 80 samples was used to test the two models′ performance and the prediction MAD for the validation set was 4.71 and 4.56 for the stepwise regression and SVR models, respectively. The number of correct predictions for ±5 years achieved a high level of 67.50 % and 73.75 %, respectively for the stepwise regression and SVR models. In general, the SVR model was superior to the linear regression model in age prediction. These results suggest that these seven CpG sites would be useful for age prediction in blood samples from the Chinese Han population.