Evidence map›Paper›PMID 40889076›Full record

ArticleGeroScience2026

Physiological health Age (PhysAge): a novel multi-system molecular timepiece predicts health and mortality in older adults.

Thalida Em Arpawong, Belinda Hernandez, Claire Potter, Robert J Leigh, Eric T Klopack, Claire Hill, Giovanni Fiorito, Laura J Smyth, Aisling M O'Halloran, Bernadette McGuinness and 5 more

Abstract read
In one paragraph

Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Epigenetic aging and blood based neurodegeneration markers in LASI-DAD.The journal of prevention of Alzheimer's disease · 2026
    Article
  2. Review
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

15 authors.

Thalida Em ArpawongLeonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, 90089, USA. arpawong@usc.edu.ORCID 0000-0001-9671-9535
Belinda HernandezThe Irish Longitudinal Study On Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Claire PotterCentre for Public Health, Queens University, Belfast, Northern Ireland.
Robert J LeighThe Irish Longitudinal Study On Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Eric T KlopackLeonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, 90089, USA.
Claire HillCentre for Public Health, Queens University, Belfast, Northern Ireland.
Giovanni FioritoClinical Bioinformatics Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
Laura J SmythCentre for Public Health, Queens University, Belfast, Northern Ireland.
Aisling M O'HalloranSchool of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland.
Bernadette McGuinnessCentre for Public Health, Queens University, Belfast, Northern Ireland.
Jessica D FaulSurvey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48106, USA.
Rose Anne KennyThe Irish Longitudinal Study On Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Amy Jayne McKnightCentre for Public Health, Queens University, Belfast, Northern Ireland.
Eileen M CrimminsLeonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, 90089, USA.
Cathal McCroryThe Irish Longitudinal Study On Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
USC/UCLA Center on Biodemography &Population HealthP30AG017265 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JENNIFER A AILSHIRE · 1999 to 2026
$17.9M
RESEARCH TRAINING IN GERONTOLOGYT32AG000037 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JENNIFER A AILSHIRE, EILEEN M CRIMMINS · 1985 to 2026
$13.2M
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
NIA NIH HHS P30 AG017265NIA NIH HHS R01 AG060110NIA NIH HHS R01 AG068937NIA NIH HHS T32 AG000037NIA NIH HHS U01 AG009740Wellcome Trust 203930/B/16/Z
6 · The paper itself

Abstract

The complexity of epigenetic changes that accompany aging has been distilled into a number of molecular timepieces-termed epigenetic clocks-that characterize the pace of biological aging to differing degrees. Here, we develop and validate a DNA methylation-based Physiological health Age (PhysAge) score, comprised of eight DNA methylation surrogates to represent multi-system physiology and developed from commonly measured clinical biomarkers: CRP, peak flow, pulse pressure, HDL-cholesterol, Hba1c, waist-to-height ratio (WHR), cystatin C, and dehydroepianrosterone sulphate (DHEAS). We use data from the population-representative US Health and Retirement Study (HRS), split into a training (n = 1589) and test sample (n = 1588) and corroborate findings in two independent cohorts: The Irish Longitudinal Study of Aging (TILDA; n = 488) and the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA; n = 1830). PhysAge and the predominant second-generation epigenetic clocks, PhenoAge, GrimAge2, and DunedinPACE, were tested for their prediction of mortality and multiple age-related clinical measures (i.e., grip strength, gait speed, cognitive function, disability, frailty). PhysAge was comparable to extant clocks in predicting health measures and was indistinguishable from GrimAge2 in predicting mortality, despite not being trained on mortality. Moreover, the eight individual surrogates comprising PhysAge predicted health outcomes better than the measured values in many instances. The established clinical relevance of the biomarkers from which surrogates were derived opens up new opportunities for cross-study and cross-country comparisons of population health. Findings suggest that the DNA methylation PhysAge can be leveraged as a single biomarker to represent multiple physiological systems and offers utility in the context of clinical monitoring.

Indexed as

AgingDNA MethylationHealthy AgingMortalityAgedAged, 80 and overBiomarkersEpigenesis, GeneticFemaleGeriatric AssessmentHealth StatusHumansLongitudinal StudiesMaleMiddle AgedUnited StatesBiomarkersAccelerated agingBiological agingEpigeneticsFunctional healthMortality

Identifiers

PMID40889076
PMCPMC12972485

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.