Evidence map›Paper›PMID 42850743›Full record

ArticleAging cell2026

When to Trust Epigenetic Clocks: Avoiding False Positives in Aging Interventions.

Daniel S Borrus, Raghav Sehgal, Jenel Fraij Armstrong, Jessica Kasamoto, John Gonzalez, Albert Higgins-Chen

Abstract read
PubMed Publisher
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

6 authors.

Daniel S BorrusDepartment of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0002-1493-0896
Raghav SehgalDepartment of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0002-9387-1758
Jenel Fraij ArmstrongProgram in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA.
Jessica KasamotoProgram in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0002-4604-6093
John GonzalezDepartment of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0002-1020-8783
Albert Higgins-ChenDepartment of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0003-2904-2741

Funding

Yale Training Program in Geriatric Clinical Epidemiology and Aging-Related ResearchT32AG019134 · NIA · YALE UNIVERSITY · PI Terri R. Fried · 2001 to 2026
$7.5M
QUANTITATIVE ASSESSMENT OF BIOLOGICAL AGE AND ITS APPLICATIONSR01AG065403 · NIA · YALE UNIVERSITY · PI Vadim N. Gladyshev, Albert Tzongyang Higgins-Chen · 2020 to 2026
$4.2M
Biological Underpinnings of Socioeconomic Differentials in Health and MortalityR01AG060110 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRIMMINS, EILEEN M · 2018 to 2022
$2.6M
Gruber Science Fellowship at Yale UniversityImpetus GrantNIA NIH HHS R01AG060110NIA NIH HHS R01AG065403NIA NIH HHS T32AG019134Thomas P. Detre Fellowship Award in Translational Neuroscience Research from Yale University
6 · The paper itself

Abstract

Epigenetic clocks have emerged as potential biomarkers of aging due to their association with morbidity and mortality. They have recently gained traction as outcome measurements for anti-aging interventions. However, as the number of new epigenetic clocks continues to grow, different clocks may not agree on the effect of an intervention. This raises the question of when researchers can trust epigenetic clock results. In this study, we find that when extending previously published single-clock intervention studies to include additional clock models, no additional clocks reach statistical significance. We then analyze clock behavior across positive control datasets (age-accelerating events) to propose three criteria that increase confidence in a result: (1) reliable PC-based clocks respond, (2) mortality-trained or pace-of-aging clocks respond, and (3) multiple clocks respond in the same direction. To explain why genuine effects would appear across multiple clocks, we perform a simulation study to demonstrate how reliable clocks are more sensitive to true effects, and use longitudinal control datasets to show that reliable clock changes are correlated with each other. We then show examples of interventions that do satisfy these criteria. These findings provide a framework for interpreting epigenetic clock results in anti-aging intervention studies, and suggest that some previously published single-clock findings may warrant reexamination.

Indexed as

AgingEpigenesis, GeneticAnimalsFalse Positive ReactionsHumansanti‐agingbiomarkersepigenetic clocksinterventionslongevity

Identifiers

PMID42850743

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.