A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures.

ABSTRACT: Accurately measuring biological age is crucial for improving healthcare for the elderly population. However, the complexity of aging biology poses challenges in how to robustly estimate aging and interpret the biological significance of the traits used for estimation. Here we present SCALE, a statistical pipeline that quantifies biological aging in different tissues using explainable features learned from literature and single-cell transcriptomic data. Applying SCALE to the "Mouse Aging Cell Atlas" (Tabula Muris Senis) data, we identified tissue-level transcriptomic aging programs for more than 20 murine tissues and created a multitissue resource of mouse quantitative aging-associated genes. We observe that SCALE correlates well with other age indicators, such as the accumulation of

SUBMITTER: Mao S 

PROVIDER: S-EPMC10547252 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature