five

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

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE291605
下载链接
链接失效反馈
官方服务:
资源简介:
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. To develop cell-type specific transcriptomic aging clocks for the human prefrontal cortex, we perfomed single-nuclei RNA sequencing on frozen post mortem brain tissue derived from 31 subjects between 18 and 94 years of age at the time of death with median post mortem interval (PMI) of 4.5 (2-12) hours, across three age groups of human adulthood. The frozen samples were collected from the lateral surface of the prefrontal cortex, namely, the ventrolateral prefrontal cortex, the dorsolateral prefrontal cortex and the middle frontal gyrus, followed by nuclei isolation using ultracentrifugation and FACS sorting, before performing snRNAseq using 10X genomics (see Methods section for further details).
创建时间:
2025-09-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作