Evidence map›Paper›PMID 41746138›Full record

ArticleAging cell2026

DNA Methylation Signatures of Cellular Senescence Are Not Reversed by Senolytic Treatment.

Jessica Kasamoto, John González, Yaroslav Markov, Raghav Sehgal, Edwin Lee, Varun B Dwaraka, Ryan Smith, Albert T Higgins-Chen

Abstract read
In one paragraph

Article in Aging cell, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jessica KasamotoProgram in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA.ORCID 0000-0002-4604-6093
John GonzálezDepartment of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID 0000-0002-1020-8783
Yaroslav MarkovProgram in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA.ORCID 0000-0001-8778-4909
Raghav SehgalDepartment of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID 0000-0002-9387-1758
Edwin LeeInstitute for Hormonal Balance, Orlando, Florida, USA.
Varun B DwarakaTruDiagnostic, Lexington, Kentucky, USA.
Ryan SmithTruDiagnostic, Lexington, Kentucky, USA.
Albert T Higgins-ChenDepartment of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA.

Funding

QUANTITATIVE ASSESSMENT OF BIOLOGICAL AGE AND ITS APPLICATIONSR01AG065403 · NIA · YALE UNIVERSITY · PI Vadim N. Gladyshev, Albert Tzongyang Higgins-Chen · 2020 to 2026
$4.2M
NIA NIH HHS NIA:1R01AG065403NIA NIH HHS R01 AG065403NIH HHS NIH 5T15LM007056-38
6 · The paper itself

Abstract

Epigenetic clocks are commonly used aging biomarkers based on DNA methylation that predict long-term morbidity and mortality risk. Increased cellular senescence with age is also posited to contribute to age-related disease and mortality. However, prior studies have found that existing epigenetic clocks show inconsistent associations with cellular senescence and no reductions after senolytic treatment. We hypothesize this reflects that senescence-related CpGs are a small proportion of age-related CpGs, and that an epigenetic clock focused on a core senescence signal conserved across different cell types and different senescence inducers would be a better tool for monitoring senescence and senolytic treatment compared to traditional epigenetic clocks. In our study, we find that senescence, age and mortality risk intersect at a small subset of the DNA methylome (9363 CpGs out of 396,333 analyzed; 2.4%). Utilizing these CpGs, we generated three different epigenetic clocks trained to predict in vitro senescence, age, and mortality, respectively. Surprisingly, all three of these predictors stayed the same or even accelerated after senolytic treatment in both in vivo and in vitro data. Our findings not only call into question whether cellular senescence can be captured by DNA methylation but also challenge the assumption that aging biomarkers decrease after geroscience interventions.

Indexed as

Cellular SenescenceDNA MethylationSenotherapeuticsAgingAnimalsCpG IslandsEpigenesis, GeneticHumansSenotherapeuticsagingbiomarkerepigenetic clocksenescencesenolytics

Identifiers

PMID41746138
PMCPMC12938503

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.