Cell type-resolved chromatin accessibility clocks for brain aging

Abstract

Aging is a progressive decline in biological function that is proposed to be driven by the accumulation of epigenetic noise and the loss of epigenetic information. Among epigenetic readouts, DNA methylation has been extensively used to develop aging clocks, machine learning models that predict age from molecular data. However, DNA methylation clocks are relatively difficult to interpret and remain distant from gene regulatory networks, a gap that can be complemented by clocks built from another epigenetic layer: chromatin accessibility profiled by ATAC-seq. Existing chromatin accessibility clocks predict age from bulk ATAC-seq data, thereby averaging over the epigenetic heterogeneity across cells that drives aging. We hypothesized that a chromatin accessibility clock trained at the level of individual cell types, using pseudobulk profiles derived from single-nucleus ATAC-seq (snATAC-seq) data, would be particularly useful for characterizing cell type-specific aging. We focused on the brain, a highly heterogeneous tissue whose diverse cell types age asynchronously, and assessed how well cell type-specific accessibility clocks can predict chronological age, capture rejuvenation from genetic perturbation, and detect age acceleration in age-associated neurodegenerative disease. To this end, we introduce a set of cell type-specific and all-cell aging clocks built from snATAC-seq profiles of the prefrontal cortex (PFC) of 357 human donors (15 to 100 years), which generalize to accurately predict age across brain regions and species. Beyond healthy aging, these PFC clocks captured the rejuvenating effects of SIRT6 overexpression in mouse liver and cell type-specific age acceleration in Alzheimer’s disease (AD) and Parkinson’s disease, with microglial age acceleration correlating most strongly with pathology among major cell types, and with female oligodendrocytes and OPCs showing the largest sex differences in age acceleration. Interpreting the clocks further revealed the regulatory elements, genes, pathways, and motifs underlying these signals across species, disease, and perturbation, including repression of the NF-κB pathway in SIRT6 transgenic mice, upregulation of immune and inflammatory pathways in severe AD, and conserved age-predictive peaks related to histone regulation, metabolism, and neuronal survival across brain regions and species. Together, these results establish PFC snATAC-seq aging clocks as a generalizable tool that accurately predicts age and captures cell type-specific perturbation effects of rejuvenation and disease on the epigenetic landscape, providing both a means to evaluate perturbations and insight into the epigenetic mechanisms of aging and disease.