Title: Evaluation of 7 age-related CpGs for forensic purpose in blood from Chinese Han population

Biography:

Pan Chao is a doctoral candidate from Huazhong University of Science and Technology

Abstract

Age prediction is an important part of forensic fields, age-related CpG sites have been regarded as the most promising biomarker in this fields. Latest developments have shown that the methylation levels of DNA molecular genetic markers is linearly related to the chronological age. In this study, we developed a SNaPshot multiplex assay to measure DNA methylation simultaneously at the 7 CpGs (cg02228185 in ASPA gene, cg09809672 in EDARADD gene, cg19283806 in CCDC102B gene, cg04208403 in ZNF423 gene, chr17: 44390358 of GRCh38 in ITGA2B gene, cg14361627 in KLF14 gene and cg06639320 in FHL2 gene), then we investigated DNA methylation changes and assessed their relevance to age based on different gender at these CpGs in 230 samples collected from 140 males and 90 females aged from 0 to 86 years, cg19283806 in the CCDC102B gene demonstrated strong correlation between DNA methylation and age in all gender sample types. We built age prediction models separately for each gender type using the DNA methylation values at the 7 CpGs by stepwise linear regression. The training sample model including 6 CpGs explained 85.12 % of variation in 230 individuals. The developed model was validated in an independent testing set of 80 blood samples. In training set and testing set, compare with the other age group, the number of correct predictions ±5 years both acquired the highest level of 73.2% and 74.1% in the aged 20–40 years old. The age prediction models in our study would be reliable and effective in forensic age prediction.