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

Chandramouli Muralidharan1,2,3, Enikő Zakar-Polyák4,5,6, Anita Adami1

  • 1Laboratory of Molecular Neurogenetics, Department of Experimental Medical Science, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund University, Lund, 221 84, Sweden.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|August 29, 2025
PubMed
Summary

Scientists developed cell-type-specific transcriptomic aging clocks using human brain data. These clocks accurately measure biological aging across different brain cells, revealing altered aging in neurodegenerative diseases.

Keywords:
aging clocksbiological clockshuman brain agingsingle nuclei sequencingtranscriptomic clocks

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Area of Science:

  • Neuroscience
  • Genomics
  • Aging Research

Background:

  • Aging is the main risk factor for neurodegenerative diseases.
  • Understanding cell-type-specific brain aging is crucial but poorly understood.

Purpose of the Study:

  • To develop and validate human cell-type-specific transcriptomic aging clocks.
  • To investigate cell-type-specific aging patterns in the human brain.
  • To explore altered aging trajectories in neurodegenerative conditions.

Main Methods:

  • Utilized single-nucleus RNA sequencing data from post mortem human prefrontal cortex (31 donors, 18-94 years).
  • Developed transcriptomic aging clocks trained on major brain cell types.
  • Validated clock performance on independent datasets.

Main Results:

  • Identified distinct transcriptomic changes associated with aging in different cell types, including inflammatory gene upregulation in microglia.
  • Aging clocks accurately predicted chronological age and captured biologically relevant pathways.
  • Demonstrated robustness of clocks across independent datasets.
  • Observed cell-type-specific age acceleration in individuals with Alzheimer's disease and schizophrenia.

Conclusions:

  • Cell-type-specific transcriptomic clocks are feasible tools for measuring biological aging in the human brain.
  • These clocks can identify altered aging trajectories in neurodegenerative diseases.
  • Findings highlight potential mechanisms for selective vulnerability in neurological disorders.