A pan-tissue DNA-methylation epigenetic clock based on deep learning

ABSTRACT: Several age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years, with the vast majority based on regularized linear regression. This study explores the improvement in the performance and interpretation of epigenetic clocks using deep learning. First, we gathered 142 publicly available data sets from several human tissues to develop AltumAge, a neural network framework that is a highly accurate and precise age predictor. Compared to ElasticNet, AltumAge performs better for within-data set and cross-data set age prediction, being particularly more generalizable in older ages and new tissue types. We then used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observe that while most

SUBMITTER: de Lima Camillo L 

PROVIDER: S-EPMC9158789 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature