Evidence map›Paper›PMID 40954326›Full record

ArticleNature aging2025

Systems Age: a single blood methylation test to quantify aging heterogeneity across 11 physiological systems.

Raghav Sehgal, Yaroslav Markov, Chenxi Qin, Margarita Meer, Courtney Hadley, Aladdin H Shadyab, Ramon Casanova, JoAnn E Manson, Parveen Bhatti, Ann Z Moore and 6 more

Abstract read
In one paragraph

Article in Nature aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
–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

62 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Relative impact of multidomain lifestyle interventions on deficit accumulation frailty over 24 months in the U.S. POINTER trial.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Review
  10. Article
  11. Observational
  12. Article
  13. Exploring Epigenetic Aging and Cognitive Change in Middle Adulthood.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Article
  14. System-Specific Epigenetic Aging Signatures in Autistic Adults.bioRxiv : the preprint server for biology · 2026
    Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Epigenetic aging and blood based neurodegeneration markers in LASI-DAD.The journal of prevention of Alzheimer's disease · 2026
    Article
  20. Review

2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Raghav SehgalProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-9387-1758
Yaroslav MarkovProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
Chenxi QinDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.
Margarita MeerAltos Labs, San Diego Institute of Sciences, San Diego, CA, USA.
Courtney HadleyHarvey Cushing/John Hay Whitney Medical Library at Yale University, New Haven, CT, USA.
Aladdin H ShadyabHerbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA.
Ramon CasanovaDepartment of Biostatistics and Data Science, School of Medicine, Wake Forest University, Winston-Salem, NC, USA.
JoAnn E MansonDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-9426-7595
Parveen BhattiCancer Control Research, BC Cancer, Vancouver, BC, Canada.
Ann Z MooreLongitudinal Studies Section, Translational Gerontology Branch, National Institutes of Health, National Institute on Aging, Baltimore, MD, USA.
Eileen M CrimminsLeonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0001-5459-5239
Sara HaggDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.ORCID http://orcid.org/0000-0002-2452-1500
Themistocles L AssimesDepartment of Medicine (Division of Cardiovascular Medicine) and Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-2349-0009
Eric A WhitselDepartment of Epidemiology, Gillings School of Public Health and Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.ORCID http://orcid.org/0000-0003-4843-3641
Albert T Higgins-ChenDepartment of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.ORCID http://orcid.org/0000-0003-2904-2741
Morgan LevineAltos Labs, San Diego Institute of Sciences, San Diego, CA, USA. mlevine@altoslabs.com.ORCID http://orcid.org/0000-0001-9890-9324

Funding

USC/UCLA Center on Biodemography &Population HealthP30AG017265 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JENNIFER A AILSHIRE · 1999 to 2026
$17.9M
Molecular Networks Underlying Resilience to Alzheimer's Disease Among APOE E4 CarriersR01AG057912 · NIA · YALE UNIVERSITY · PI GAITERI, CHRISTOPHER A., HIGGINS-CHEN, ALBERT TZONGYANG · 2017 to 2021
$4.5M
QUANTITATIVE ASSESSMENT OF BIOLOGICAL AGE AND ITS APPLICATIONSR01AG065403 · NIA · YALE UNIVERSITY · PI Vadim N. Gladyshev, Albert Tzongyang Higgins-Chen · 2020 to 2026
$4.2M
Social Circumstances and Epigenomics Promoting Health in Three CountriesR01AG068937 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRIMMINS, EILEEN M, FAUL, JESSICA · 2020 to 2025
$2.9M
Biological Underpinnings of Socioeconomic Differentials in Health and MortalityR01AG060110 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRIMMINS, EILEEN M · 2018 to 2022
$2.6M
Gruber FoundationNIA NIH HHS P30 AG017265NIA NIH HHS R01 AG057912NIA NIH HHS R01 AG060110NIA NIH HHS R01 AG065403NIA NIH HHS R01 AG068937
6 · The paper itself

Abstract

Aging occurs at different rates across individuals and physiological systems, but most epigenetic clocks provide a single age estimate, overlooking within-person variation. Here we developed systems-based DNA methylation clocks that measure aging in 11 distinct physiological systems-Heart, Lung, Kidney, Liver, Brain, Immune, Inflammatory, Blood, Musculoskeletal, Hormone and Metabolic-using data from a single blood draw. By integrating supervised and unsupervised machine learning with clinical biomarkers, functional assessments and mortality risk, we derived system-specific scores that outperformed existing global clocks in predicting relevant diseases and aging phenotypes. We also created a composite Systems Age score to capture overall multisystem aging. Clustering individuals based on these scores revealed distinct biological aging subtypes, each associated with unique patterns of health decline and disease risk. This framework enables a more granular and clinically relevant assessment of biological aging and may support personalized approaches to monitor and target system-specific aging processes.

Indexed as

AgingDNA MethylationAdultAgedAged, 80 and overBiomarkersEpigenesis, GeneticFemaleHumansMachine LearningMaleMiddle AgedBiomarkers

Identifiers

PMID40954326
PMCPMC13222069

What OpenQuestion holds

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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.