Artificial neural network, predictor variables and sensitivity threshold for DNA methylation-based age prediction using blood samples.

ABSTRACT: Regression models are often used to predict age of an individual based on methylation patterns. Artificial neural network (ANN) however was recently shown to be more accurate for age prediction. Additionally, the impact of ethnicity and sex on our previous regression model have not been studied. Furthermore, there is currently no age prediction study investigating the lower limit of input DNA at the bisulfite treatment stage prior to pyrosequencing. Herein, we evaluated both regression and ANN models, and the impact of ethnicity and sex on age prediction for 333 local blood samples using three loci on the pyrosequencing platform. Subsequently, we trained a one locus-based ANN model to reduce the amount of DNA used. We demonstrated that the ANN model has a higher accuracy of age prediction

SUBMITTER: Thong Z 

PROVIDER: S-EPMC7814006 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature