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Human Brain Cell-Type-Specific Aging Clocks Based on Single-Nuclei Transcriptomics

ABSTRACT: Aging is the primary risk factor for most neurodegenerative diseases, yet the cell-type-specific progression of brain aging remains poorly understood. Here, human cell-type-specific transcriptomic aging clocks are developed using high-quality single-nucleus RNA sequencing data from post mortem human prefrontal cortex tissue of 31 donors aged 18–94 years, encompassing 73,941 high-quality nuclei. Distinct transcriptomic changes are observed across major cell types, including upregulation of inflammatory response genes in microglia from older samples. Aging clocks trained on each major cell type accurately predict chronological age, capture biologically relevant pathways, and remain robust in independent single-nucleus RNA-sequencing datasets, underscoring their broad applicability. Notably, cell-type-specific age acceleration is identified in individuals with Alzheimer's disease and schizophrenia, suggesting altered aging trajectories in these conditions. These findings demonstrate the feasibility of cell-type-specific transcriptomic clocks to measure biological aging in the human brain and highlight potential mechanisms of selective vulnerability in neurodegenerative diseases.

ORGANISM(S): Homo sapiens

PROVIDER: GSE291605 | GEO | 2025/08/29

REPOSITORIES: GEO

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Project description:Epigenetic clocks are a common group of tools used to measure biological aging – the progressive deterioration of cells, tissues and organs. Epigenetic clocks have been trained almost exclusively using blood-based tissues but there is growing interest in estimating epigenetic age using less-invasive oral-based tissues (i.e., buccal or saliva) in both research and commercial settings. However, differentiated cell types across body tissues exhibit unique DNA methylation landscapes and age-related alterations to the DNA methylome. Applying epigenetic clocks derived from blood-based tissues to estimate epigenetic age of oral-based tissues may introduce biases. We tested the within-person comparability of common epigenetic clocks across four tissue types: buccal epithelial, saliva, dry blood spots, and peripheral blood mononuclear cells. We tested 163 distinct tissue samples from 47 individuals aged 19-70 years. Overall, there were significant within-person differences in epigenetic clock estimates from oral-based versus blood-based tissues, with average differences of almost 30 years observed in some age clocks. In addition, most epigenetic clock estimates of blood-based tissues exhibited low correlation with estimates from oral-based tissues despite controlling for cellular proportions and other technical factors. Notably, the Skin and Blood clock exhibited the lowest age acceleration values of any clock across all tissue types, indicating its unique ability to accurately estimate chronological age in both oral- and blood-based tissues. Our findings indicate that application of blood-derived epigenetic clocks in oral-based tissues may not yield comparable estimates of epigenetic age, highlighting the need for careful consideration of tissue type when estimating epigenetic age. NOTE: The full study included children and adult samples, however, the current data only includes the adult samples (sample sizes and age range have been adjusted to reflect the adult data only).

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Human Brain Cell-Type-Specific Aging Clocks Based on Single-Nuclei Transcriptomics

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