Profiling senescent cells in human brains reveals neurons with CDKN2D/p19 and tau neuropathology
Open accessAbstract
Senescent cells contribute to pathology and dysfunction in animal models 1. Their sparse distribution and heterogenous phenotype have presented challenges for detecting them in human tissues. We developed a senescence eigengene approach to identify these rare cells within large, diverse populations of postmortem human brain cells. Eigengenes are useful when no single gene reliably captures a phenotype, like senescence; they also help to reduce noise, which is important in large transcriptomic datasets where subtle signals from low-expressing genes can be lost. Each of our eigengenes detected ~2% senescent cells from a population of ~140,000 single nuclei derived from 76 postmortem human brains with various levels of Alzheimer's disease (AD) pathology. More than 97% of the senescent cells were excitatory neurons and overlapped with tau-containing neurofibrillary tangles (NFTs). Cyclin dependent kinase inhibitor 2D (CDKN2D/p19) was predicted as the most significant contributor to the primary senescence eigengene. RNAscope and immunofluorescence confirmed its elevated expression in AD brain tissue whereby p19-expressing neurons had 1.8-fold larger nuclei and significantly more cells with lipofuscin than p19-negative neurons. These hallmark senescence phenotypes were further elevated in the presence of NFTs. Collectively, CDKN2D/p19-expressing neurons with NFTs represent a unique cellular population in human AD with a senescence phenotype. The eigengenes developed may be useful in future senescence profiling studies as they accurately identified senescent cells in snRNASeq datasets and predicted biomarkers for histological investigation.
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Only microglia showed full expression of the full canonical senescence pathway (CSP).
“Microglia, oligodendrocytes and astrocytes transcriptomes all showed enrichment for genes upregulated in an early senescence (“senescence initiators”) pathway, but only microglia showed full expression of the full canonical senescence pathway (CSP) [16].”
From Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics (2024) · cites this paper as [16]
The paper’s results (section labeled Abstract; page unavailable) say excitatory neurons were the predominant CSP-positive cells, accounting for 97% and 92% of CSP cells in the two adult brain cohorts. They also report CSP enrichment in endothelial cells in cohort 2. This contradicts the claim that only microglia showed the canonical senescence phenotype. (LLM, conf=0.94)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredCellular senescence is involved in the pathogenesis of Alzheimer's disease.
“Cellular senescence contributes to Alzheimer’s disease (AD) pathogenesis.”
From Senolytic therapy in mild Alzheimer's disease: a phase 1 feasibility trial (2023) · cites this paper as [7]
The Abstract (page not provided) reports senescence-phenotype neurons overlapping with tau-containing tangles in human AD brains and says rodent-model data indicate that senescent brain cells contribute to neurodegeneration and cognitive dysfunction. The human findings show an association, not that cellular senescence contributes causally to AD pathogenesis as the citing sentence states. (LLM, conf=0.85)
Experimental — accuracy not yet measuredTranscriptomic data from postmortem Alzheimer's disease brain tissue and mouse models show senescent cell signatures responsive to dasatinib plus quercetin, associated with neurofibrillary tangle-bearing neurons.
“Transcriptomic data from postmortem human AD brain tissue and AD mouse models revealed senescent cell signatures predicted to be responsive to D + Q therapy (that is, SCAPs), which were specifically associated with neurofibrillary tangle (NFT)-bearing neurons6,7.”
From Senolytic therapy in mild Alzheimer's disease: a phase 1 feasibility trial (2023) · cites this paper as [7]
The Abstract (page unavailable) reports senescence signatures in transcriptomic data from postmortem human brains and their overlap with neurofibrillary tangle-bearing excitatory neurons. The Methods, “Eigengene analysis” (page unavailable), describes analysis of human RNA-sequencing data; the gene sets included findings from mouse models, but this paper does not report analyzing transcriptomic data from AD mouse models or predicting responsiveness to dasatinib plus quercetin. (LLM, conf=0.88)
Experimental — accuracy not yet measuredFeatures of premature senescence associated with DSBs and p16 expression have been described in post-mitotic cells such as neurons.
“However, features of premature senescence associated particularly with DNA double-strand breaks (DSBs) and p16 expression also have been described in post-mitotic cells such as neurons[16, 18, 29].”
From Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics (2024) · cites this paper as [16]
The paper’s Abstract reports a senescence phenotype in neurons, supporting the general point that post-mitotic cells can show senescence features. But it identifies CDKN2D/p19, not p16, as the prominent marker, cautions that p16 expression can occur independently of senescence, and does not describe DNA double-strand breaks as a feature of these neurons. (LLM, conf=0.87)
Experimental — accuracy not yet measuredDehkordi et al. previously concluded that excitatory neurons uniquely expressed a senescence signature based on relative enrichment of nuclear genes expressed with an eigengene reflecting a canonical senescence response.
“Dehkordi et al. previously concluded that excitatory neurons uniquely expressed a senescence signature based on relative enrichment of nuclear genes expressed with an eigengene reflecting a canonical senescence response [16].”
From Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics (2024) · cites this paper as [16]
The paper’s copy (section labeled Abstract; page unavailable) describes a canonical senescence phenotype eigengene derived from gene expression in single brain nuclei and identifies excitatory neurons as the predominant senescent cell type. It reports that excitatory neurons accounted for 97% and 92% of CSP-identified senescent cells in two adult cohorts, so “uniquely expressed” overstates the finding: expression was not exclusive to them. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Senescent cell accumulation contributes to the progression of age-related disorders including Alzheimer's disease.
“Senescent cell accumulation contributes to the progression of age-related disorders including Alzheimer’s disease (AD).”
From Evaluation of exploratory fluid biomarkers from a phase 1 senolytic trial in mild Alzheimer's disease (2025) · cites this paper as [3]
The Abstract (page not provided) says senescent cells contribute to pathology in animal models and reports a senescence phenotype in neurons from human AD brains. It does not establish that senescent-cell accumulation causes AD to progress; its analysis found no significant association between senescent-cell counts and AD stage across most measures. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSenescent cells accumulate in multiple central nervous system cell types in aging and neurodegenerative disease.
“In the context of aging and neurodegenerative disease, senescent cell accumulation has been identified in multiple cell types within the central nervous system (CNS), including neurons6,7,14,15, astrocytes16,17, microglia8,18, oligodendrocyte precursor cells19 and endothelial cells20.”
From Senolytic therapy in mild Alzheimer's disease: a phase 1 feasibility trial (2023) · cites this paper as [7]
Experimental — accuracy not yet measuredProportion of senescent nuclei increased with AD only for microglia in MTG, and also in SSC.
“We then calculated the proportions of nuclei expressing CSP (senescent nuclei) as described in [16] and found an increase in the proportion of senescent nuclei with AD only for microglia in the MTG an observation consistent with our imaging mass cytometry observations (Fig. 2f, Supplementary Fig. 4b). Additionally, increased proportion of senescent nuclei was also observed in SSC (Fig. 2f).”
From Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics (2024) · cites this paper as [16]
Previous studies have highlighted senescence in multiple brain cell types in AD.
“Previous studies have highlighted senescence in multiple brain cell types in AD [3, 16, 32, 52, 80].”
From Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics (2024) · cites this paper as [16]
AstMet is not enriched in senescence genes (P ≥ 0.4).
“AstMet was not enriched in senescence genes34 (P ≥ 0.4)”
From Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease (2024) · cites this paper as [34]
Senescence markers beyond p16 include p21, p19, uPAR, and GPNMB.
“Studies have begun to reveal the remarkable heterogeneity of cellular senescence in different tissues, highlighting the importance of cellular senescence markers beyond p16 – including Cdkn1a (p21) [7–10], Cdkn2d (p19) [11], uPAR [12], and glycoprotein non-metastatic melanoma protein B (GPNMB) [13] – and emphasizing the urgent need for a better understanding of senescent cell heterogeneity.”
From The heterogeneity of cellular senescence: insights at the single-cell level (2023) · cites this paper as [11]
The senescent cells found in the human Alzheimer's disease brain dataset were mostly excitatory neurons with tau pathology commonly seen with Alzheimer's disease.
“The senescent cells found in this dataset were mostly excitatory neurons with tau pathology commonly seen with AD.”
From The heterogeneity of cellular senescence: insights at the single-cell level (2023) · cites this paper as [11]
In human Alzheimer's disease brains, p19/CDKN2D was the most significant marker of senescent cells in postmortem brains and defined a unique group of senescent cells.
“In human brains, a single-nucleus RNA sequencing study using an eigengene approach found that p19/CDKN2D was the most significant marker of senescent cells in postmortem brains from patients with Alzheimer’s disease (AD), and also defined a unique group of senescent cells in human AD brains [11].”
From The heterogeneity of cellular senescence: insights at the single-cell level (2023) · cites this paper as [11]
p19 upregulation was validated by mFISH and mABI in human Alzheimer's disease brains, and p19-expressing cells had larger nuclei and more lipofuscin-positive cells than non-p19-expressing cells.
“p19 upregulation was further validated by mFISH and mABI in human AD brains and additional experiments confirmed that p19-expressing cells had several key features, including larger nuclei and more lipofuscin-positive cells than non-p19-expressing cells.”
From The heterogeneity of cellular senescence: insights at the single-cell level (2023) · cites this paper as [11]
Some SASP genes used to identify senescent cells had expression levels also upregulated in cells showing no common senescent hallmarks.
“For example, some SASP genes were used to identify senescent cells, but their expression levels were also upregulated in cells showing no common senescent hallmarks.”
From The heterogeneity of cellular senescence: insights at the single-cell level (2023) · cites this paper as [11]
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Senolytic therapy in mild Alzheimer's disease: a phase 1 feasibility trial
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Self-citationHerdy, J. R., Traxler, L., Agarwal, R. K., Karbacher, L., Schlachetzki, J. C. M., Boehnke, L., Zangwill, D., Galasko, D., Glass, C. K., Mertens, J., et al. (2022) · Cell Stem Cell · doi:10.1016/j.stem.2022.11.010 · Cited by 208 · see citing works
Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease
Serrano-Pozo, A., Li, H., Li, Z., Muñoz-Castro, C., Jaisa-aad, M., Healey, M. A., Welikovitch, L. A., Jayakumar, R., Bryant, A. G., Noori, A., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01791-4 · Cited by 140 · see citing works
Self-citationMatsudaira, T., Nakano, S., Konishi, Y., Kawamoto, S., Uemura, K., Kondo, T., Sakurai, K., Ozawa, T., Hikida, T., Komine, O., et al. (2023) · Communications Biology · doi:10.1038/s42003-023-05027-2 · Cited by 98 · see citing works
Microglia: Friend and foe in tauopathy
Odfalk, K. F., Bieniek, K. F., & Hopp, S. C. (2022) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2022.102306 · Cited by 60 · see citing works
Fancy, N. N., Smith, A. M., Caramello, A., Tsartsalis, S., Davey, K., Muirhead, R. C. J., McGarry, A., Jenkyns, M. H., Schneegans, E., Chau, V., et al. (2024) · Acta Neuropathologica · doi:10.1007/s00401-024-02727-9 · Cited by 48 · see citing works
“Microglia, oligodendrocytes and astrocytes transcriptomes all showed enrichment for genes upregulated in an early senescence (“senescence initiators”) pathway, but only microglia showed full expression of the full canonical senescence pathway (CSP) [16].”
BackgroundMethodResultInfluentialDistinct senotypes in p16- and p21-positive cells across human and mouse aging tissues
Saul, D., Jurk, D., Doolittle, M. L., Kosinsky, R. L., Han, Y., Zhang, X., Franco, A. C., Kim, S. Y., Wyles, S. P., Prakash, Y. S., et al. (2025) · The EMBO Journal · doi:10.1038/s44318-025-00601-2 · Cited by 45 · see citing works
A p21-GFP zebrafish model of senescence for rapid testing of senolytics in vivo
Morsli, S., Henriques, C. M., Ellis, P. S., Mortiboys, H., Baxendale, S., Loynes, C. A., Renshaw, S. A., & Bellantuono, I. (2023) · Aging Cell · doi:10.1111/acel.13835 · Cited by 21 · see citing works
Garbarino, V. R., Palavicini, J. P., Melendez, J., Barthelemy, N. R., He, Y., Kautz, T. F., Lopez-Cruzan, M., Mathews, J. J., Xu, P., Zhang, B., et al. (2025) · Neurotherapeutics · doi:10.1016/j.neurot.2025.e00591 · Cited by 19 · see citing works
Self-citation
- Authors
- Dehkordi, S. K., Walker, J., Sah, E., Bennett, E., Atrian, F., Frost, B., Woost, B., Bennett, R. E., Orr, T. C., Zhou, Y., Andhey, P. S., Colonna, M., Sudmant, P. H., Xu, P., Wang, M., Zhang, B., Zare, H., & Orr, M. E.
- Affiliations
- The University of Texas at San Antonio Health Science Center (US)
- Wake Forest University Health Sciences (US)
- Harvard University (US)
- Washington University in St. Louis (US)
- University of California, Berkeley (US)
- Icahn School of Medicine at Mount Sinai (US)
- W. G. (Bill) Hefner VA Medical Center (US)
- Corresponding author
- Zare, Habil
- Orr, Miranda E.
- ORCID
- Venue
- Nature Aging
- Published
- 2021-12-10
- Volume
- 1
- Issue
- 12
- Pages
- 1107-1116
- ISSN
- 2662-8465 (ISSN-L)
- PMC
- PMC9075501
- OpenAlex
- W4200534156
- Cited by
- 169
- References
- 55
- Citations by year
- 2026: 30 · 2025: 63 · 2024: 39 · 2023: 21 · 2022: 15 · 2021: 1
- FWCI
- 11.94
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature Aging (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute on Aging (T32AG021890, R01AG057896, K99AG061259, P30AG062421, R21AG059176, RF1AG059082, RF1AG057440, U01AG046170, R01AG057907, R01AG068293)
- Cure Alzheimer’s Fund
- U.S. Department of Veterans Affairs (K2BX003804)
- Topics
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- cellular senescence, senescent cells, human brain, Alzheimer's disease, tau pathology, neurofibrillary tangles, excitatory neurons, single-nucleus RNA sequencing, lipofuscin, postmortem brain, senescence biomarkers
- MeSH terms
- Alzheimer Disease, Animals, Brain, Humans, Neurons, Cellular Senescence, Cyclin-Dependent Kinase Inhibitor p19
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