SkeletAge: Transcriptomics-based Aging Clock Identifies 26 New Targets in Skeletal Muscle Aging.

ABSTRACT: Identifying the set of genes that regulate baseline healthy aging - aging that is not confounded by illness - is critical to understating aging biology. Machine learning-based age-estimators (such as epigenetic clocks) offer a robust method for capturing biomarkers that strongly correlate with age. In principle, we can use these estimators to find novel targets for aging research, which can then be used for developing drugs that can extend the healthspan. However, methylation-based clocks do not provide direct mechanistic insight into aging, limiting their utility for drug discovery. Here, we describe a method for building tissue-specific bulk RNA-seq-based age-estimators that can be used to identify the ageprint. The ageprint is a set of genes that drive baseline healthy aging in a

SUBMITTER: Ali M 

PROVIDER: S-EPMC12324255 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature