Cell-type-specific aging clocks to quantify aging and rejuvenation in neurogenic regions of the brain

The diversity of cell types is a challenge for quantifying aging and its reversal. Here we develop 'aging clocks' based on single-cell transcriptomics to characterize cell-type-specific aging and rejuvenation. We generated single-cell transcriptomes from the subventricular zone neurogenic region of 28 mice, tiling ages from young to old. We trained single-cell-based regression models to predict chronological age and biological age (neural stem cell proliferation capacity). These aging clocks are generalizable to independent cohorts of mice, other regions of the brains, and other species. To determine if these aging clocks could quantify transcriptomic rejuvenation, we generated single-cell transcriptomic datasets of neurogenic regions for two interventions-heterochronic parabiosis and exercise. Aging clocks revealed that heterochronic parabiosis and exercise reverse transcriptomic aging in neurogenic regions, but in different ways. This study represents the first development of high-resolution aging clocks from single-cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation. Single-cell transcriptomic data from a neurogenic region of the mouse brain were used to build aging clocks for specific neural cell types. These clocks showed that heterochronic parabiosis and exercise lead to distinct transcriptomic rejuvenation patterns across cell types.

Automated summary

This study develops aging clocks based on single-cell transcriptomics to quantify the diversity of cell types in aging and rejuvenation. The clocks are applicable to different species and can predict chronological and biological age. The study demonstrates that heterochronic parabiosis and exercise have distinct effects on transcriptomic rejuvenation in specific neural cell types.