Modeling Methods and Influencing Factors for Age Estimation Based on DNA Methylation

doi:10.12116/j.issn.1004-5619.2023.530106

Abstract

Abstract:

Age estimation based on tissues or body fluids is an important task in forensic science. The changes of DNA methylation status with age have certain rules, which can be used to estimate the age of the individuals. Therefore, it is of great significance to discover specific DNA methylation sites and develop new age estimation models. At present, statistical models for age estimation have been developed based on the rule that DNA methylation status changes with age. The commonly used models include multiple linear regression model, multiple quantile regression model, support vector machine model, artificial neural network model, random forest model, etc. In addition, there are many factors that affect the level of DNA methylation, such as the tissue specificity of methylation. This paper reviews these modeling methods and influencing factors for age estimation based on DNA methylation, with a view to provide reference for the establishment of age estimation models.

Key words: forensic genetics, DNA methylation, age estimation, statistical model, review

CLC Number:

Yi-hang HUANG, Wei-bo LIANG, Hui JIAN, Sheng-qiu QU. Modeling Methods and Influencing Factors for Age Estimation Based on DNA Methylation[J]. Journal of Forensic Medicine, 2023, 39(6): 601-607.

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