Evidence map›Paper›PMID 39501126›Full record

ArticleNature aging2024

Phenome-wide associations of human aging uncover sex-specific dynamics.

Lee Reicher, Noam Bar, Anastasia Godneva, Yotam Reisner, Liron Zahavi, Nir Shahaf, Raja Dhir, Adina Weinberger, Eran Segal

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 NCT07742917 (Application of a Precision Lifestyle Medicine Clinical Program for a Sample of IFHAS Screening Cohort), which is not on this map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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.

NCT07742917 narecruitingnot on this mapstarted 2026, after this paper: background citation

Application of a Precision Lifestyle Medicine Clinical Program for a Sample of IFHAS Screening Cohort

TypeinterventionalSponsorInstitute for Healthier Living Abu DhabiRan2026 to 2027Enrolled150ConditionsObese Adults, BMI/Body Composition, Cardiometabolic Risk, Cardiovascular Disease RiskArmsPrecision Lifestyle Medicine Program, Standard IFHAS Care
3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
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  5. Correlation Analysis of 24-h Minimum Heart Rate Levels and Deceleration Capacity of Heart Rate in Patients With Type 2 Diabetes Mellitus Complicated With Essential Hypertension.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2026
    Article
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  17. Longitudinal big biological data in the AI era.Molecular systems biology · 2025
    Review
  18. Article
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  20. 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

9 authors.

Lee Reicher *Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Noam Bar *Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Anastasia GodnevaDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Yotam ReisnerDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.ORCID 0000-0001-9192-7167
Liron ZahaviDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.ORCID 0000-0001-8867-1287
Nir ShahafDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Raja DhirSwiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland.
Adina WeinbergerDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.ORCID 0000-0003-2231-4687
Eran SegalDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. eran.segal@weizmann.ac.il.ORCID 0000-0002-6859-1164

Funding

Linking microbiome genetic variants with cardiovascular phenotypes in 50,000 individualsR01HL160862 · NHLBI · J. DAVID GLADSTONE INSTITUTES · PI POLLARD, KATHERINE S. · 2022 to 2025
$2.7M
NHLBI NIH HHS R01 HL160862
6 · The paper itself

Abstract

Aging varies significantly among individuals of the same chronological age, indicating that biological age (BA), estimated from molecular and physiological biomarkers, may better reflect aging. Prior research has often ignored sex-specific differences in aging patterns and mainly focused on aging biomarkers from a single data modality. Here we analyze a deeply phenotyped longitudinal cohort (10K project, Israel) of 10,000 healthy individuals aged 40-70 years that includes clinical, physiological, behavioral, environmental and multiomic parameters. Follow-up visits are scheduled every 2 years for a total of 25 years. We devised machine learning models of chronological age and computed biological aging scores that represented diverse physiological systems, revealing different aging patterns among sexes. Higher BA scores were associated with a higher prevalence of age-related medical conditions, highlighting the clinical relevance of these scores. Our analysis revealed system-specific aging dynamics and the potential of deeply phenotyped cohorts to accelerate improvements in our understanding of chronic diseases. Our findings present a more holistic view of the aging process, and lay the foundation for personalized medical prevention strategies.

Indexed as

AgingAdultAgedBiomarkersFemaleHumansIsraelLongitudinal StudiesMachine LearningMaleMiddle AgedPhenomicsPhenotypeSex CharacteristicsSex FactorsBiomarkers

Identifiers

PMID39501126
PMCPMC12288840

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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.