RT Journal Article SR Electronic T1 ClockBase: a comprehensive platform for biological age profiling in human and mouse JF bioRxiv FD Cold Spring Harbor Laboratory SP 2023.02.28.530532 DO 10.1101/2023.02.28.530532 A1 Kejun Ying A1 Alexander Tyshkovskiy A1 Alexandre Trapp A1 Hanna Liu A1 Mahdi Moqri A1 Csaba Kerepesi A1 Vadim N. Gladyshev YR 2023 UL http://biorxiv.org/content/early/2023/03/01/2023.02.28.530532.abstract AB Aging represents the greatest risk factor for chronic diseases and mortality, but to understand it we need the ability to measure biological age. In recent years, many machine learning algorithms based on omics data, termed aging clocks, have been developed that can accurately predict the age of biological samples. However, there is currently no resource for systematic profiling of biological age. Here, we describe ClockBase, a platform that features biological age estimates based on multiple aging clock models applied to more than 2,000 DNA methylation datasets and nearly 200,000 samples. We further provide an online interface for statistical analyses and visualization of the data. To show how this resource could facilitate the discovery of biological age-modifying factors, we describe a novel anti-aging drug candidate, zebularine, which reduces the biological age estimates based on all aging clock models tested. We also show that pulmonary fibrosis accelerates epigenetic age. Together, ClockBase provides a resource for the scientific community to quantify and explore biological ages of samples, thus facilitating discovery of new longevity interventions and age-accelerating conditions.Competing Interest StatementThe authors have declared no competing interest.