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

Muralidharan, Chandramouli LU orcid ; Zakar-Polyák, Enikő ; Adami, Anita LU orcid ; Abbas, Anna A. ; Sharma, Yogita LU ; Garza, Raquel LU orcid ; Johansson, Jenny G. LU ; Atacho, Diahann A.M. LU orcid ; Renner, Éva and Palkovits, Miklós , et al. (2025) In Advanced Science
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... (More)

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.

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organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
aging clocks, biological clocks, human brain aging, single nuclei sequencing, transcriptomic clocks
in
Advanced Science
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:40878446
  • scopus:105014629209
ISSN
2198-3844
DOI
10.1002/advs.202506109
language
English
LU publication?
yes
id
fb413215-3659-4316-9c65-732156b92d7c
date added to LUP
2025-11-17 09:43:21
date last changed
2025-11-18 03:40:56
@article{fb413215-3659-4316-9c65-732156b92d7c,
  abstract     = {{<p>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.</p>}},
  author       = {{Muralidharan, Chandramouli and Zakar-Polyák, Enikő and Adami, Anita and Abbas, Anna A. and Sharma, Yogita and Garza, Raquel and Johansson, Jenny G. and Atacho, Diahann A.M. and Renner, Éva and Palkovits, Miklós and Kerepesi, Csaba and Jakobsson, Johan and Pircs, Karolina}},
  issn         = {{2198-3844}},
  keywords     = {{aging clocks; biological clocks; human brain aging; single nuclei sequencing; transcriptomic clocks}},
  language     = {{eng}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Advanced Science}},
  title        = {{Human Brain Cell-Type-Specific Aging Clocks Based on Single-Nuclei Transcriptomics}},
  url          = {{http://dx.doi.org/10.1002/advs.202506109}},
  doi          = {{10.1002/advs.202506109}},
  year         = {{2025}},
}