Evidence map›Paper›PMID 38898237›Full record

ArticleNature aging2024

Principal component-based clinical aging clocks identify signatures of healthy aging and targets for clinical intervention.

Sheng Fong, Kamil Pabis, Djakim Latumalea, Nomuundari Dugersuren, Maximilian Unfried, Nicholas Tolwinski, Brian Kennedy, Jan Gruber

Registry-linked trialAbstract read
In one paragraph

Article in Nature aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07444073 (Assessing Biological Aging in a Real-World Medical Weight Loss Program Using the LinAge2 Clinical Clock), which is not on this map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing 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.

NCT07444073 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Assessing Biological Aging in a Real-World Medical Weight Loss Program Using the LinAge2 Clinical Clock

TypeobservationalSponsorNational University of SingaporeRan2026 to 2027Enrolled440ConditionsAging, Obesity & OverweightArmsNot applicable. This is an observational study.
3 · Its place in the literature

Who cites it

59 citing papers in PubMed.

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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.

Sheng FongDepartment of Geriatric Medicine, Singapore General Hospital, Singapore, Singapore.ORCID http://orcid.org/0000-0002-5834-512X
Kamil PabisHealthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Djakim LatumaleaHealthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0009-0007-4786-4745
Nomuundari DugersurenScience Division, Yale-NUS College, Singapore, Singapore.
Maximilian UnfriedHealthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0001-8660-1576
Nicholas TolwinskiScience Division, Yale-NUS College, Singapore, Singapore.ORCID http://orcid.org/0000-0002-8507-2737
Brian KennedyHealthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0002-5754-1874
Jan GruberHealthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. bchjg@nus.edu.sg.ORCID http://orcid.org/0000-0003-3329-3789

Funding

Ministry of Education - Singapore (MOE) A-0007215-00-00Ministry of Education - Singapore (MOE) IG21-SG007Ministry of Education - Singapore (MOE) IG21-SG103Ministry of Health -Singapore (MOH) MOH-001294-00
6 · The paper itself

Abstract

Clocks that measure biological age should predict all-cause mortality and give rise to actionable insights to promote healthy aging. Here we applied dimensionality reduction by principal component analysis to clinical data to generate a clinical aging clock (PCAge) identifying signatures (principal components) separating healthy and unhealthy aging trajectories. We found signatures of metabolic dysregulation, cardiac and renal dysfunction and inflammation that predict unsuccessful aging, and we demonstrate that these processes can be impacted using well-established drug interventions. Furthermore, we generated a streamlined aging clock (LinAge), based directly on PCAge, which maintains equivalent predictive power but relies on substantially fewer features. Finally, we demonstrate that our approach can be tailored to individual datasets, by re-training a custom clinical clock (CALinAge), for use in the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) study of caloric restriction. Our analysis of CALERIE participants suggests that 2 years of mild caloric restriction significantly reduces biological age. Altogether, we demonstrate that this dimensionality reduction approach, through integrating different biological markers, can provide targets for preventative medicine and the promotion of healthy aging.

Indexed as

Caloric RestrictionHealthy AgingPrincipal Component AnalysisAdultAgedAgingBiological ClocksFemaleHumansMaleMiddle Aged

Identifiers

PMID38898237
PMCPMC11333290

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Registered trials

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.