Establishing the relationship between brain cellular senescence and brain structure
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Cellular senescence and brain atrophy are both associated with brain aging, suggesting these processes may share underlying biological mechanisms. This study investigated these mechanisms by integrating structural neuroimaging with gene and protein expression data from prefrontal cortex tissue collected from individuals who underwent neurosurgery. Cell-type-specific gene expression signatures associated with neuroimaging features and cellular senescence were identified and replicated in several independent datasets. Significant correlations between these signatures were observed in excitatory neurons and microglia, especially for volume-related features. These associations were also observed for excitatory neurons in an independent brain gene expression dataset from individuals below 5 years of age, implying a role for senescence during brain development. Together, this study provides a deep characterization of molecular signatures linking brain structure and cellular senescence across different life stages and suggests mechanisms supporting brain development may also contribute to volume reduction observed during aging.
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SenCat adds value beyond earlier computational and ML methods through its broad atlas, its in-house generation under tightly controlled and consistent conditions, its combination of RNA and protein data, and its capacity to derive both shared and context-limited senescence programs within one framework.
“the added value of SenCat lies in the breadth of the underlying atlas, the fact that it was entirely generated under strictly controlled and consistent settings in-house, the integration of transcriptomic and proteomic modalities, and the ability to derive both shared and context-restricted senescence-associated programs from a common framework.”
From SenCat: Cataloging human cell senescence through multi-omic profiling of multiple senescent primary cell types (2026) · cites this paper as [27]
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Sorted by citations
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- Authors
- Lund, A. N., Kopell, B. H., Golestani, N., Vornholt, E., Thompson, R. C., Liharska, L. E., Luo, Y., Cheng, E., Park, Y. J., Fennessy, B., Wilkins, L., Kaji, D. A., Silk, H., Ziafat, K., Hashemi, A., Moya, E., Feng, C., Linares, L. M., Grice, A. B., Xie, S., Rieder, M.-K., Scarpa, J., Kota, P., Cohen, V., Sullivan, B., Shah, P., Ma, W., Johnson, J. S., Miller, G. M., Searfoss, R., Chand, N. M., Wang, P., Nadkarni, G. N., Narain, N. R., Nestler, E. J., Kiebish, M. A., Schadt, E. E., Charney, A. W., & Beckmann, N. D.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- BPGbio, Inc. (United States) (US)
- Corresponding author
- Charney, Alexander W.
- Beckmann, Noam D.
- ORCID
- Lund, Anina N.
- Kopell, Brian H.
- Golestani, Negar
- Vornholt, Eric
- Thompson, Ryan C.
- Liharska, Lora E.
- Cheng, Esther
- Park, You Jeong
- Fennessy, Brian
- Kaji, Deepak A.
- Ziafat, Kimia
- Hashemi, Alice
- Moya, Emily
- Feng, Claudia
- Miller, Gregory M.
- Searfoss, Richard
- Wang, Pei
- Nadkarni, Girish N.
- Narain, Niven R.
- Nestler, Eric J.
- Kiebish, Michael A.
- Charney, Alexander W.
- Beckmann, Noam D.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2026-01
- Volume
- 189
- Issue
- 2
- Pages
- 511-527.e17
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC13202612
- OpenAlex
- W7125427132
- Cited by
- 6
- References
- 115
- Citations by year
- 2026: 6
- FWCI
- 27.43
- Type
- journal article
- Language
- en
- Open access
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 386 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- Funders
- National Institute on Aging
- Michael J Fox Foundation for Parkinson's Research
- Topics
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Keywords
- cellular senescence, brain atrophy, brain aging, brain structure, prefrontal cortex, cell type-specific gene expression, excitatory neurons, microglia, brain volume, brain development
- MeSH terms
- Adolescent, Adult, Aged, Aging, Atrophy, Brain, Child, Preschool, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neurons, Cellular Senescence, Prefrontal Cortex, Microglia, Young Adult, Transcriptome, Neuroimaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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